cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20188754
title: Meta data_Zhang et al., 2022

description: Enhanced nitrogen deposition has altered forest nitrogen cycling across China, which also affect soil greenhouse gas emissions. This dataset demonstrated the responses of methane uptake and nitrous oxide emission to nitrogen enhanced deposition in forest soils in China and outside of China..
DOI: 10.6084/m9.figshare.20188754.v2
title: Meta data_Zhang et al., 2022

description: Enhanced nitrogen deposition has altered forest nitrogen cycling across China, which also affect soil greenhouse gas emissions. This dataset demonstrated the responses of methane uptake and nitrous oxide emission to nitrogen enhanced deposition in forest soils in China and outside of China..
DOI: 10.6084/m9.figshare.20188754.v1
title: Meta data_Zhang et al., 2022

description: Enhanced nitrogen deposition has altered forest nitrogen cycling across China, which also affect soil greenhouse gas emissions. This dataset demonstrated the responses of methane uptake and nitrous oxide emission to nitrogen enhanced deposition in forest soils in China and outside of China..
DOI: 10.6084/m9.figshare.20188763
title: Additional file 2 of Bookend: precise transcript reconstruction with end-guided assembly

description: Additional file 2: Dataset 1. Bookend Floral Bud, hybrid assembly of Arabidopsis stage 12 inflorescence. Dataset 2. Classification of Bookend Floral Bud transcripts against TAIR10 and Araport11. Dataset 3. Tissue-specific quantification of TSSs from TAIR10, Araport11 and Bookend Floral Bud annotations. Dataset 4. Bookend mESC, hybrid assembly of mouse embryonic stem cells. Dataset 5. Classification of Bookend mESC transcripts against RefSeq and Gencode.
DOI: 10.6084/m9.figshare.20188763.v1
title: Additional file 2 of Bookend: precise transcript reconstruction with end-guided assembly

description: Additional file 2: Dataset 1. Bookend Floral Bud, hybrid assembly of Arabidopsis stage 12 inflorescence. Dataset 2. Classification of Bookend Floral Bud transcripts against TAIR10 and Araport11. Dataset 3. Tissue-specific quantification of TSSs from TAIR10, Araport11 and Bookend Floral Bud annotations. Dataset 4. Bookend mESC, hybrid assembly of mouse embryonic stem cells. Dataset 5. Classification of Bookend mESC transcripts against RefSeq and Gencode.
DOI: 10.5517/ccdc.csd.cc29x94p
title: CCDC 2142352: Experimental Crystal Structure Determination

description: Related Article: Heng Zhang, Lu-Yu Cai, Kuo Wang, Hong-Wu Zhao|2022|Org.Biomol.Chem.|20|5115|doi:10.1039/D2OB00791F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29zr68
title: CCDC 2144710: Experimental Crystal Structure Determination

description: Related Article: Rémi Andres, Qian Wang, Jieping Zhu|2022|Angew.Chem.,Int.Ed.|61|e202201788|doi:10.1002/anie.202201788
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b1xht
title: CCDC 2146796: Experimental Crystal Structure Determination

description: Related Article: Rémi Andres, Qian Wang, Jieping Zhu|2022|Angew.Chem.,Int.Ed.|61|e202201788|doi:10.1002/anie.202201788
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b6h13
title: CCDC 2151184: Experimental Crystal Structure Determination

description: Related Article: Masahiro Ikeshita, Takato Suzuki, Kana Matsudaira, Maho Kitahara, Yoshitane Imai, Takashi Tsuno|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15502|doi:10.1039/D2CP01861F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b6h24
title: CCDC 2151185: Experimental Crystal Structure Determination

description: Related Article: Masahiro Ikeshita, Takato Suzuki, Kana Matsudaira, Maho Kitahara, Yoshitane Imai, Takashi Tsuno|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15502|doi:10.1039/D2CP01861F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b6h35
title: CCDC 2151186: Experimental Crystal Structure Determination

description: Related Article: Masahiro Ikeshita, Takato Suzuki, Kana Matsudaira, Maho Kitahara, Yoshitane Imai, Takashi Tsuno|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15502|doi:10.1039/D2CP01861F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.6781394
title: Single-Cell Autism data stored as sce object

description: The raw autism dataset is from UCSC Cell Browser Dataset, Autism section (https://cells.ucsc.edu). It is stored as SingleCellExperiment object for further usage.
description: {"references": ["Velmeshev D, Schirmer L, Jung D, Haeussler M, Perez Y, Mayer S, Bhaduri A, Goyal N, Rowitch DH, Kriegstein AR. Single-cell genomics identifies cell type-specific molecular changes in autism. Science. 2019 May 17;364(6441):685-689. doi: 10.1126/science.aav8130. PMID: 31097668; PMCID: PMC7678724."]}
DOI: 10.5281/zenodo.6781393
title: Single-Cell Autism data stored as sce object

description: The raw autism dataset is from UCSC Cell Browser Dataset, Autism section (https://cells.ucsc.edu). It is stored as SingleCellExperiment object for further usage.
description: {"references": ["Velmeshev D, Schirmer L, Jung D, Haeussler M, Perez Y, Mayer S, Bhaduri A, Goyal N, Rowitch DH, Kriegstein AR. Single-cell genomics identifies cell type-specific molecular changes in autism. Science. 2019 May 17;364(6441):685-689. doi: 10.1126/science.aav8130. PMID: 31097668; PMCID: PMC7678724."]}
DOI: 10.5281/zenodo.6781463
title: Analyzing Polyethylene Terephthalate Bottle Waste Technology Using Analytic Hierarchy Process for Developing Countries: A case Study from Indonesia

description: PET bottle waste is easy to recycle because it is easy to separate, abundant, and competitively priced. Technologies for the treatment of PET bottle waste have been evaluated to date using life cycle assessment (LCA), but this does not take into account all the aspects that policy makers consider necessary to select an acceptable technology. Aspects such as society, economics, policies, and technical applicability need to be considered along with environment and resources consumption to complement the LCA results for PET bottle waste. These aspects were selected as criteria for the Analytical Hierarchy Process (AHP), and stakeholders were invited to make a comparison evaluation of the criteria and sub criteria. Academics were involved to compare the technology option. The results show that society is the highest priority because it is the main actor that ensures the application of the technology, and job creation is the most important indicator for the selection of the technology. After comparing open landfill, sanitary landfill, incineration with energy recovery, pelletizing, glycolysis, and hydrolysis for utilization of PET bottle waste, this study suggests pelletizing as the acceptable technology for Indonesia because pelletizing is supported by social aspects and creates more jobs. This is the first time that a single plastic fraction that is easy to collect and recycle has been studied with AHP. The results show that this type of plastic could also be reused in developing countries through mechanical recycling.
DOI: 10.5281/zenodo.6571189
title: Analyzing Polyethylene Terephthalate Bottle Waste Technology Using Analytic Hierarchy Process for Developing Countries: A case Study from Indonesia

description: PET bottle waste is easy to recycle because it is easy to separate, abundant, and competitively priced. Technologies for the treatment of PET bottle waste have been evaluated to date using life cycle assessment (LCA), but this does not take into account all the aspects that policy makers consider necessary to select an acceptable technology. Aspects such as society, economics, policies, and technical applicability need to be considered along with environment and resources consumption to complement the LCA results for PET bottle waste. These aspects were selected as criteria for the Analytical Hierarchy Process (AHP), and stakeholders were invited to make a comparison evaluation of the criteria and sub criteria. Academics were involved to compare the technology option. The results show that society is the highest priority because it is the main actor that ensures the application of the technology, and job creation is the most important indicator for the selection of the technology. After comparing open landfill, sanitary landfill, incineration with energy recovery, pelletizing, glycolysis, and hydrolysis for utilization of PET bottle waste, this study suggests pelletizing as the acceptable technology for Indonesia because pelletizing is supported by social aspects and creates more jobs. This is the first time that a single plastic fraction that is easy to collect and recycle has been studied with AHP. The results show that this type of plastic could also be reused in developing countries through mechanical recycling.
DOI: 10.26188/20189006.v1
title: Vitamin D Gene analysis.txt

description: Gene array
DOI: 10.26188/20189006
title: Vitamin D Gene analysis.txt

description: Gene array
DOI: 10.5281/zenodo.6781435
title: An atlas of seabed biodiversity for Aotearoa New Zealand_supplementary materials2

description: Database of model evaluation and expert appraisal scores for spatial layers derived from 'An atlas of seabed biodiversity for Aotearoa New Zealand'. The atlas provides predicted distribution and associated uncertainty from species distribution models for seafloor associated taxa in the NZ marine environment. Spatial datasets are accessible via a geoportal hosted by the NZ Department of Conservation Portal (https://doc-marine-data-deptconservation.hub.arcgis.com). Abstract to a manuscript supporting the publication of the atlas is given below. The waters of Aotearoa New Zealand span over 4.2 million km<sup>2</sup> of the South Pacific Ocean and harbour a rich diversity of seafloor associated taxa. Due to the immensity and remoteness of the area, there are significant gaps in the availability of data to quantify and map the distribution of seafloor and demersal biodiversity, limiting effective management. In this study, we describe the development and accessibility of an online atlas of seabed biodiversity that aims to fill these gaps. Species distribution models were developed for 579 taxa across four taxonomic groups: demersal fish, reef fish, subtidal invertebrates and macroalgae. Spatial layers for taxa distribution based on habitat suitability were statistically validated and then, as a further check, evaluated by taxonomic experts to provide measures of confidence to guide the future use of these layers. Spatially explicit uncertainty (SD) layers were also developed for each taxon distribution. We generated layer-specific metadata, including statistical and expert evaluation scores, which were uploaded alongside the accompanying spatial layers to an online open access marine data portal hosted by the New Zealand Department of Conservation. The online atlas is fully interactive, with search and plotting functions, and allows the export of single or multiple spatial layers on seafloor biodiversity. The atlas provides the most comprehensive database on the distribution of seafloor taxa for Aotearoa New Zealand and is thus an invaluable resource for managers, researchers and the general public that will guide the management and conservation of seafloor communities.
DOI: 10.5281/zenodo.6781434
title: An atlas of seabed biodiversity for Aotearoa New Zealand_supplementary materials2

description: Database of model evaluation and expert appraisal scores for spatial layers derived from 'An atlas of seabed biodiversity for Aotearoa New Zealand'. The atlas provides predicted distribution and associated uncertainty from species distribution models for seafloor associated taxa in the NZ marine environment. Spatial datasets are accessible via a geoportal hosted by the NZ Department of Conservation Portal (https://doc-marine-data-deptconservation.hub.arcgis.com). Abstract to a manuscript supporting the publication of the atlas is given below. The waters of Aotearoa New Zealand span over 4.2 million km<sup>2</sup> of the South Pacific Ocean and harbour a rich diversity of seafloor associated taxa. Due to the immensity and remoteness of the area, there are significant gaps in the availability of data to quantify and map the distribution of seafloor and demersal biodiversity, limiting effective management. In this study, we describe the development and accessibility of an online atlas of seabed biodiversity that aims to fill these gaps. Species distribution models were developed for 579 taxa across four taxonomic groups: demersal fish, reef fish, subtidal invertebrates and macroalgae. Spatial layers for taxa distribution based on habitat suitability were statistically validated and then, as a further check, evaluated by taxonomic experts to provide measures of confidence to guide the future use of these layers. Spatially explicit uncertainty (SD) layers were also developed for each taxon distribution. We generated layer-specific metadata, including statistical and expert evaluation scores, which were uploaded alongside the accompanying spatial layers to an online open access marine data portal hosted by the New Zealand Department of Conservation. The online atlas is fully interactive, with search and plotting functions, and allows the export of single or multiple spatial layers on seafloor biodiversity. The atlas provides the most comprehensive database on the distribution of seafloor taxa for Aotearoa New Zealand and is thus an invaluable resource for managers, researchers and the general public that will guide the management and conservation of seafloor communities.
DOI: 10.5281/zenodo.6781446
title: Datasets for SPNet

description: The datasets are used in paper <em>Deep learning for locating contaminated sites from self-potential signals: a laboratory perspective</em>. SPtest.mat: This mat file includes 100,000 SP source models and associated forward modeling SP signals. Note that the SP signals in this file have been added to different types of noise and have been normalized to [0,1]. Therefore, the datasets can be fed into SPNet training directly. If you want to have the actual forward modeling SP response, you can use the 3D forward modeling codes at Github https://github.com/geohang/SPNet. longlabdata.mat: This is the laboratory-measured SP signal, which has been interpolated to have the same size as the input of the SPNet.
DOI: 10.5281/zenodo.5808276
title: Datasets for SPNet

description: The datasets are used in paper <em>Deep learning for locating contaminated sites from self-potential signals: a laboratory perspective</em>. SPtest.mat: This mat file includes 100,000 SP source models and associated forward modeling SP signals. Note that the SP signals in this file have been added to different types of noise and have been normalized to [0,1]. Therefore, the datasets can be fed into SPNet training directly. If you want to have the actual forward modeling SP response, you can use the 3D forward modeling codes at Github https://github.com/geohang/SPNet. longlabdata.mat: This is the laboratory-measured SP signal, which has been interpolated to have the same size as the input of the SPNet.
DOI: 10.26188/17031389
title: Too hot to hunt: mechanistic predictions of thermal refuge from cat predation risk - data files

description: Data and code to support publication: <strong>Briscoe, N.J. McGregor, H. Roshier, D. Carter, A. Wintle, B.A. Kearney, M. R. (2022), Too hot to hunt: mechanistic predictions of thermal refuge from feral cat predation, Conservation Letters, </strong> doi:10.1111/conl.12906 <strong> </strong> <br> This data set includes data used to parameterise and test biophysical models of feral cats in Australia. It includes observed microclimate and feral cat activity/behaviour data and biophysical model predictions for two study sites (Arid Recovery, South Australia and Scotia Wildlife Sanctuary, managed by Australian Wildlife Conservancy in NSW), as well as examples of continent-wide predictions of feral cat heat stress. Data and code are arranged in three zipped folders: Site_tests.zip = tests of model predictions of microclimate conditions and feral cat activity/behaviour at Arid Recovery and Scotia Landscape_predictions.zip = example code and output for plotting yearly heat stress and the number of consecutive years of lethal conditions, and comparing this with the distirbuiton of several cat-sensitive species. Cat_model.zip = fortran and R files used to compile and run biophysical model of feral cats. The most recent NicheMapR files can be found at https://github.com/mrke/NicheMapR along with licensing information. Citations for NicheMapR model: Kearney, M. R., and W. P. Porter. 2017. NicheMapR - an R package for biophysical modelling: the microclimate model. Ecography 40:664–674. Kearney, M.R., Briscoe, N.J., Mathewson, P.D. and Porter, W.P. (2021), NicheMapR – an R package for biophysical modelling: the endotherm model. Ecography, 44: 1595-1605. <br> Additional details of files and variables in each dataset are provided in the README file. <br> Predictions of heat stress for all simulations and sites modelled can be found at: http://bioforecasts.science.unimelb.edu.au/app_direct/cat_oz/ Feral cat GPS data collected at Scotia are available via Movebank (doi:10.5441/001/1.6m6h9s33), with details outlined in: Roshier DA, Carter A. 2021. Space use and interactions of two introduced mesopredators, European red fox and feral cat, in an arid landscape. <em>Ecosphere</em>. 12(7): e03628. doi:10.1002/ecs2.3628
DOI: 10.26188/17031389.v1
title: Too hot to hunt: mechanistic predictions of thermal refuge from cat predation risk - data files

description: Data and code to support publication: <strong>Briscoe, N.J. McGregor, H. Roshier, D. Carter, A. Wintle, B.A. Kearney, M. R. (2022), Too hot to hunt: mechanistic predictions of thermal refuge from feral cat predation, Conservation Letters, </strong> doi:10.1111/conl.12906 <strong> </strong> <br> This data set includes data used to parameterise and test biophysical models of feral cats in Australia. It includes observed microclimate and feral cat activity/behaviour data and biophysical model predictions for two study sites (Arid Recovery, South Australia and Scotia Wildlife Sanctuary, managed by Australian Wildlife Conservancy in NSW), as well as examples of continent-wide predictions of feral cat heat stress. Data and code are arranged in three zipped folders: Site_tests.zip = tests of model predictions of microclimate conditions and feral cat activity/behaviour at Arid Recovery and Scotia Landscape_predictions.zip = example code and output for plotting yearly heat stress and the number of consecutive years of lethal conditions, and comparing this with the distirbuiton of several cat-sensitive species. Cat_model.zip = fortran and R files used to compile and run biophysical model of feral cats. The most recent NicheMapR files can be found at https://github.com/mrke/NicheMapR along with licensing information. Citations for NicheMapR model: Kearney, M. R., and W. P. Porter. 2017. NicheMapR - an R package for biophysical modelling: the microclimate model. Ecography 40:664–674. Kearney, M.R., Briscoe, N.J., Mathewson, P.D. and Porter, W.P. (2021), NicheMapR – an R package for biophysical modelling: the endotherm model. Ecography, 44: 1595-1605. <br> Additional details of files and variables in each dataset are provided in the README file. <br> Predictions of heat stress for all simulations and sites modelled can be found at: http://bioforecasts.science.unimelb.edu.au/app_direct/cat_oz/ Feral cat GPS data collected at Scotia are available via Movebank (doi:10.5441/001/1.6m6h9s33), with details outlined in: Roshier DA, Carter A. 2021. Space use and interactions of two introduced mesopredators, European red fox and feral cat, in an arid landscape. <em>Ecosphere</em>. 12(7): e03628. doi:10.1002/ecs2.3628
DOI: 10.5517/ccdc.csd.cc2b6h46
title: CCDC 2151187: Experimental Crystal Structure Determination

description: Related Article: Masahiro Ikeshita, Takato Suzuki, Kana Matsudaira, Maho Kitahara, Yoshitane Imai, Takashi Tsuno|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15502|doi:10.1039/D2CP01861F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27f4nh
title: CCDC 2068216: Experimental Crystal Structure Determination

description: Related Article: Aaron D. Nicholas, Leah C. Garman, Nicolina Albano, Christopher L. Cahill|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15305|doi:10.1039/D2CP01996E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25814/txp0-vs96
title: Land tenure of Australia 2010–11 to 2015–16, 250 m
DOI: 10.5517/ccdc.csd.cc2bbxh3
title: CCDC 2155445: Experimental Crystal Structure Determination

description: Related Article: Oliver P. E. Townrow, Simon B. Duckett, Andrew S. Weller, Jose M. Goicoechea|2022|Chemical Science|13|7626|doi:10.1039/D2SC02552C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.