cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/p728-ye68
title: Dissecting the major genetic components underlying cotton lint development

description: Numerous genetic loci and several genes have been associated with lint percentage (lint%), one of the most important cotton yield components, but we still know little about the major genetic components underlying lint%. Here, we first identified MYB25-like_At and HD1_At as being the genetic loci underlying the fibreless trait of SL1-7-1. Consistently, the two genes were very lowly expressed in SL1-7-1 ovules during fibre initiation. We then dissected the genetic components involved in determining lint% using segregating populations derived from the crossing of fuzzless mutants and intermediate segregants with different lint%, which not only confirmed HD1_At but identified HD1_Dt as being one of the major genetic components contributing to lint%. The segregating populations also allowed us to evaluate the relative contributions of MYB25-like_At, MYB25-like_Dt, HD1_At, and HD1_Dt to lint%, and this was further confirmed by using an Upland cotton (Gossypium hirsutum) population with 723 accessions (including 81 fuzzless accessions). Haplotype analysis of the G. hirsutum accessions showed that the lint% of the accessions with the LP allele (higher lint%) at MYB25-like_At, MYB25-like_Dt, or HD1_At was significantly higher than that with the lp allele (lower lint%). Furthermore, the lint% of the accessions with three or four LP alleles at MYB25-like and HD1 was significantly higher than that with two LP alleles. The results prompted us to propose a new strategy for breeding high yielding cotton varieties, i.e., pyramiding new lint% LP alleles without any negative impact on seed size and fibre quality with the known LP alleles of MYB25-like and HD1. The collection contains all raw sequencing data and the phenotype data (lint%) as well as qPCR results of the 4 genes.
DOI: 10.5281/zenodo.8115309
title: NRSurCat-1

description: Posterior samples from the NRSurCat-1. Refer to the paper for more details. Website hosting plots for this work can be found here.
DOI: 10.5281/zenodo.8115310
title: NRSurCat-1

description: Posterior samples from the NRSurCat-1. Refer to the paper for more details. Website hosting plots for this work can be found here.
DOI: 10.5281/zenodo.8380709
title: Seismic data and receiver functions from two linear dense nodal array in the southern Chinese Altai region

description: Seismic data and receiver functions from two linear dense nodal array in the southern Chinese Altai region. All data are arranged by seismic events, and the number before the first dot of each file name represents the station number.
DOI: 10.5281/zenodo.8380710
title: Seismic data and receiver functions from two linear dense nodal array in the southern Chinese Altai region

description: Seismic data and receiver functions from two linear dense nodal array in the southern Chinese Altai region. All data are arranged by seismic events, and the number before the first dot of each file name represents the station number.
DOI: 10.5281/zenodo.8381786
title: Seismic data and receiver functions from two linear dense nodal array in the southern Chinese Altai region

description: Seismic data and receiver functions from two linear dense nodal array in the southern Chinese Altai region. All data are arranged by seismic events, and the number before the first dot of each file name represents the station number.
DOI: 10.6084/m9.figshare.23828172
title: Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard

description: This Description of data in Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard.txt file was generated on 2023-07-12 by Qiong Zhang<br>GENERAL INFORMATION<br>1. Title of Dataset: Description of data in Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard2. Author InformationPrincipal Investigator Contact InformationName: Qiong ZhangInstitution: Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, ChinaAddress: Beichen West Road, Chaoyang District, Beijing, ChinaEmail: zhangqiong@ioz.ac.cn3. Date of data collection: From 2021-07 to 2021-08<br>4. Geographic location of data collection: Our data was collected in Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (25.1N, 102.7E; elevation 1036 m).<br><br>SHARING/ACCESS INFORMATION<br>Licenses/restrictions placed on the data: If you make extensive use of data from this data set, please credit the authors.<br>DATA & FILE OVERVIEW<br>File List:growth data.xls Growth data of all individuals.survival.xls Survival information of all individuals.OS data.xls Oxidative stress data of 38 individuals.white blood cells count.xls White blood cells counts of 38 individuals.
DOI: 10.6084/m9.figshare.23828172.v4
title: Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard

description: This Description of data in Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard.txt file was generated on 2023-07-12 by Qiong Zhang<br>GENERAL INFORMATION<br>1. Title of Dataset: Description of data in Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard2. Author InformationPrincipal Investigator Contact InformationName: Qiong ZhangInstitution: Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, ChinaAddress: Beichen West Road, Chaoyang District, Beijing, ChinaEmail: zhangqiong@ioz.ac.cn3. Date of data collection: From 2021-07 to 2021-08<br>4. Geographic location of data collection: Our data was collected in Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (25.1N, 102.7E; elevation 1036 m).<br><br>SHARING/ACCESS INFORMATION<br>Licenses/restrictions placed on the data: If you make extensive use of data from this data set, please credit the authors.<br>DATA & FILE OVERVIEW<br>File List:growth data.xls Growth data of all individuals.survival.xls Survival information of all individuals.OS data.xls Oxidative stress data of 38 individuals.white blood cells count.xls White blood cells counts of 38 individuals.
DOI: 10.6084/m9.figshare.23828172.v3
title: Oxidative stress mediates the impact of heat waves on survival, growth and immune status in a lizard

description: This Description of data in Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard.txt file was generated on 2023-07-12 by Qiong Zhang<br>GENERAL INFORMATION<br>1. Title of Dataset: Description of data in Oxidative stress mediates the impact of heat waves on survival, growth, and immune status in a lizard2. Author InformationPrincipal Investigator Contact InformationName: Qiong ZhangInstitution: Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, ChinaAddress: Beichen West Road, Chaoyang District, Beijing, ChinaEmail: zhangqiong@ioz.ac.cn3. Date of data collection: From 2021-07 to 2021-08<br>4. Geographic location of data collection: Our data was collected in Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (25.1N, 102.7E; elevation 1036 m).<br><br>SHARING/ACCESS INFORMATION<br>Licenses/restrictions placed on the data: If you make extensive use of data from this data set, please credit the authors.<br>DATA & FILE OVERVIEW<br>File List:growth data.xls Growth data of all individuals.survival.xls Survival information of all individuals.OS data.xls Oxidative stress data of 38 individuals.white blood cells count.xls White blood cells counts of 38 individuals.
DOI: 10.34740/kaggle/dsv/6550641
title: Our World in Data - COVID-19
DOI: 10.5281/zenodo.8381740
title: hg38 genome data

description: hg38_ctgmin500k.fa.gz:Raw Hg38 genome fasta. hg38_ctgmin500k_simulated1.fa.gz : Simulated heterozygous hg38 genome. hg38_ctgmin500k_simulated2.fa.gz : Simulated error-included hg38 genome.
DOI: 10.5281/zenodo.8381739
title: hg38 genome data

description: hg38_ctgmin500k.fa.gz:Raw Hg38 genome fasta. hg38_ctgmin500k_simulated1.fa.gz : Simulated heterozygous hg38 genome. hg38_ctgmin500k_simulated2.fa.gz : Simulated error-included hg38 genome.
DOI: 10.6084/m9.figshare.23659653
title: Anxiety-Disorders-plink.meta_P_Sorted.gz

description: GWAS summary statistics from anxiety disorders meta-analysis (combining genome-wide associations from UK Biobank, iPSYCH, ANGST, MVP, and FINNGEN)
DOI: 10.57841/casdc.0002562
title: TiSiN/Ag纳米多层涂层海水环境磨蚀性能研究
DOI: 10.5281/zenodo.3539350
title: ChinaHighPM2.5 (Version 1)

description: The high-resolution (1 km) and high-quality PM<sub>2.5</sub> data set in China (i.e., ChinaHighPM<sub>2.5</sub> data set) from 2000 to 2018 are generated for the first time. This data set is generated using a newly developed space-time extremely randomized trees (STET) model based on the newly released MODIS Collection 6 MAIAC 1-km AOD products, meteorological variables, emissions, and auxiliary data. The ChinaHighPM<sub>2.5</sub> data set can be greatly useful for air pollution studies in medium- or small-scale areas. <strong>Note that this dataset is closed since a new version is published at </strong>10.5281/zenodo.3539349.
description: If you have any questions about the data set, please contact me (weijing_rs@163.com).
description: {"references": ["Wei, J., Li, Z., Cribb, M., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustin, A., Liu, L., Wu, H., and Song, Y. Improved 1 km resolution PM2.5 estimates across China using enhanced space-time extremely randomized trees, Atmospheric Chemistry and Physics, 2020, 20(6), 3273-3289. https://doi.org/10.5194/acp-20-3273-2020", "Wei, J., Huang, W., Li, Z., Xue, W., Peng, Y., Sun, L., and Cribb, M. Estimating 1-km-resolution PM2.5 concentrations across China using the space-time random forest approach, Remote Sensing of Environment, 2019, 231, 111221. https://doi.org/10.1016/j.rse.2019.111221"]}
DOI: 10.13011/m3-2x20-6q21
title: Temperature-Dependent Material Database: HY-80
DOI: 10.6084/m9.figshare.21184203.v2
title: Additional file 2 of Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

description: Additional file 2.
DOI: 10.6084/m9.figshare.21184206.v2
title: Additional file 3 of Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

description: Additional file 3.
DOI: 10.25625/gmdddy/1k7lab
title: forest-indonesia-district.tab

description: :unav
DOI: 10.6084/m9.figshare.21184203
title: Additional file 2 of Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

description: Additional file 2.
DOI: 10.6084/m9.figshare.21184206
title: Additional file 3 of Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

description: Additional file 3.
DOI: 10.6084/m9.figshare.21184203.v1
title: Additional file 2 of Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

description: Additional file 2.
DOI: 10.6084/m9.figshare.21184206.v1
title: Additional file 3 of Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer

description: Additional file 3.
DOI: 10.57841/casdc.0002563
title: 7055铝合金在3.5%NaCl溶液中腐蚀磨损性能的研究
DOI: 10.5281/zenodo.3538556
title: ChinaHighPM1 (Version 1)

description: The high-resolution (1 km) and high-quality PM<sub>1</sub> data set in China (i.e., ChinaHighPM<sub>1</sub> data set) from 2014 to 2018 are generated for the first time. This data set is generated using a newly developed space-time extremely randomized trees (STET) model based on the newly released MODIS Collection 6 MAIAC 1-km AOD products, meteorological variables, emissions, and auxiliary data. The STET model can derive daily PM<sub>1</sub> concentrations with an average across-validation coefficient of determination of 0.77, a low root-mean-square error of 14.6 μg/m<sup>3</sup>, and a mean absolute error of 8.9 μg/m<sup>3</sup>. The STET model, incorporating the spatiotemporal information, shows superior performance in PM<sub>1</sub> estimates relative to previous studies. The ChinaHighPM<sub>1</sub> data set can be greatly useful for air pollution studies in medium- or small-scale areas. <strong>Note that this dataset is closed since a new version is published at </strong>10.5281/zenodo.3538555<strong>.</strong>
description: If you have any questions about the data set or need higher temporal-resolution, i.e., daily or monthly PM1 data), please contact me (weijing_rs@163.com; weijing.rs@gmail.com).
description: {"references": ["Wei, J., Li, Z., Guo, J., Sun, L., Huang, W., Xue, W., Fan, T, and Cribb, M. Satellite-derived 1-km-resolution PM1 concentrations from 2014 to 2018 across China, Environmental Science & Technology, 2019, 53(22), 13265-13274. https://doi.org/10.1021/acs.est.9b03258"]}
DOI: 10.5281/zenodo.8381779
title: Ray-tracing data for "Propagation of very oblique chorus waves near a plasmaspheric plume boundary"

description: The dataset consists of ray-tracing results, background density models, and the figure codes for the manuscript "Propagation of very oblique chorus waves near a plasmaspheric plume boundary". The dataset and codes are in Matlab.
DOI: 10.5281/zenodo.8381778
title: Ray-tracing data for "Propagation of very oblique chorus waves near a plasmaspheric plume boundary"

description: The dataset consists of ray-tracing results, background density models, and the figure codes for the manuscript "Propagation of very oblique chorus waves near a plasmaspheric plume boundary". The dataset and codes are in Matlab.
DOI: 10.6084/m9.figshare.24202461
title: AT-rich trinucleotides

description: Here we performed a whole-genome analysis of all combinations of AT-rich trinucleotide two-repeats in human.
DOI: 10.6084/m9.figshare.24202461.v1
title: AT-rich trinucleotides

description: Here we performed a whole-genome analysis of all combinations of AT-rich trinucleotide two-repeats in human.
DOI: 10.57841/casdc.0002564
title: 液氮激冷对含氢非晶碳膜性能的影响
DOI: 10.57841/casdc.0002565
title: α-ZrP层状纳米片的修饰改性及其摩擦学性能
DOI: 10.6084/m9.figshare.24202605
title: <b>Ships and Offshore Structures</b>

description: The files include experimental data, underwater photos and videos.
DOI: 10.57841/casdc.0002566
title: 基于极限学习机和优化算法的润滑油添加剂种类识别与含量预测
DOI: 10.57841/casdc.0002567
title: 电流作用对铜镁合金弯曲微动疲劳损伤特性的影响
DOI: 10.25625/gzrpih/ajwelw
title: indofrag.data.frag.cai_am_3.2016.tif

description: :unav
DOI: 10.25625/gzrpih/q0eekf
title: indofrag.data.frag.cai_am_3.2015.tif

description: :unav
DOI: 10.25625/gzrpih/jkkkus
title: indofrag.data.frag.cai_am_3.2013.tif

description: :unav
DOI: 10.25625/gzrpih/t0qkfq
title: indofrag.data.frag.cai_am_3.2017.tif

description: :unav
DOI: 10.25625/gzrpih/em1jnr
title: indofrag.data.frag.cai_am_3.2018.tif

description: :unav
DOI: 10.25625/gzrpih/8xuobg
title: indofrag.data.frag.cai_am_3.2014.tif

description: :unav
DOI: 10.25625/gzrpih/a0hxfz
title: indofrag.data.frag.cai_am_3.2012.tif

description: :unav
DOI: 10.25625/gzrpih/stmd98
title: indofrag.data.frag.cai_am_3.2019.tif

description: :unav
DOI: 10.25625/gzrpih/sx0via
title: indofrag.data.frag.cai_am_3.2011.tif

description: :unav
DOI: 10.25625/gzrpih/vkaip0
title: indofrag.data.frag.cai_am_3.2003.tif

description: :unav
DOI: 10.25625/gzrpih/x07ivc
title: indofrag.data.frag.cai_am_3.2008.tif

description: :unav
DOI: 10.25625/gzrpih/cqakpi
title: indofrag.data.frag.cai_am_3.2010.tif

description: :unav
DOI: 10.25625/gzrpih/havb2t
title: indofrag.data.frag.cai_mn_3.2013.tif

description: :unav
DOI: 10.25625/gzrpih/tpiv14
title: indofrag.data.frag.cai_mn_3.2008.tif

description: :unav
DOI: 10.25625/gzrpih/vwchok
title: indofrag.data.frag.pafrac.2011.tif

description: :unav
DOI: 10.25625/gzrpih/jqcqn9
title: indofrag.data.frag.clumpy.2007.tif

description: :unav
DOI: 10.25625/gzrpih/mnazvo
title: indofrag.data.frag.pafrac.2016.tif

description: :unav
DOI: 10.25625/gzrpih/zolab7
title: indofrag.data.frag.pafrac.2015.tif

description: :unav
DOI: 10.25625/gzrpih/wkzyjc
title: indofrag.data.frag.cai_mn_3.2019.tif

description: :unav
DOI: 10.25625/gzrpih/3xq0od
title: indofrag.data.frag.nlsi.2017.tif

description: :unav
DOI: 10.25625/gzrpih/jq6dwr
title: indofrag.data.frag.cai_mn_3.2006.tif

description: :unav
DOI: 10.25625/gzrpih/klzggf
title: indofrag.data.frag.cai_mn_3.2017.tif

description: :unav
DOI: 10.25625/gzrpih/ywb80s
title: indofrag.data.frag.cai_am_3.2000.tif

description: :unav
DOI: 10.25625/gzrpih/pn5pua
title: indofrag.data.frag.nlsi.2005.tif

description: :unav
DOI: 10.25625/gzrpih/a0inqu
title: indofrag.data.frag.pafrac.2001.tif

description: :unav
DOI: 10.25625/gzrpih/ryjqzi
title: indofrag.data.frag.cai_cv_3.2010.tif

description: :unav
DOI: 10.25625/gzrpih/bg3gkg
title: indofrag.data.frag.clumpy.2000.tif

description: :unav
DOI: 10.25625/gzrpih/w2mtuw
title: indofrag.data.frag.pafrac.2004.tif

description: :unav
DOI: 10.25625/gzrpih/dzjqiv
title: indofrag.data.frag.nlsi.2011.tif

description: :unav
DOI: 10.25625/gzrpih/n8u3zt
title: indofrag.data.frag.clumpy.2002.tif

description: :unav
DOI: 10.25625/gzrpih/8l583j
title: indofrag.data.frag.clumpy.2005.tif

description: :unav
DOI: 10.25625/gzrpih/thyozw
title: indofrag.data.frag.pafrac.2012.tif

description: :unav
DOI: 10.25625/gzrpih/qzxkl5
title: indofrag.data.frag.clumpy.2011.tif

description: :unav
DOI: 10.25625/gzrpih/sammcx
title: indofrag.data.frag.nlsi.2013.tif

description: :unav
DOI: 10.25625/gzrpih/gwiyuk
title: indofrag.data.frag.cai_mn_3.2005.tif

description: :unav
DOI: 10.25625/gzrpih/ysgh00
title: indofrag.data.frag.cai_cv_3.2005.tif

description: :unav
DOI: 10.25625/gzrpih/cwzzes
title: indofrag.data.frag.clumpy.2015.tif

description: :unav
DOI: 10.25625/gzrpih/haf0rc
title: indofrag.data.frag.cai_cv_3.2008.tif

description: :unav
DOI: 10.25625/gzrpih/nbjifk
title: indofrag.data.frag.pafrac.2000.tif

description: :unav
DOI: 10.25625/gzrpih/gzoz1v
title: indofrag.data.frag.nlsi.2000.tif

description: :unav
DOI: 10.25625/gzrpih/lixmb4
title: indofrag.data.frag.cai_cv_3.2015.tif

description: :unav
DOI: 10.25625/gzrpih/yjwwgb
title: indofrag.data.frag.cai_cv_3.2014.tif

description: :unav
DOI: 10.25625/gzrpih/z7r9vs
title: indofrag.data.frag.cai_cv_3.2018.tif

description: :unav
DOI: 10.25625/gzrpih/c114t9
title: indofrag.data.frag.cai_cv_3.2009.tif

description: :unav
DOI: 10.25625/gzrpih/yutezr
title: indofrag.data.frag.clumpy.2017.tif

description: :unav
DOI: 10.25625/gzrpih/vvsshc
title: indofrag.data.frag.nlsi.2014.tif

description: :unav
DOI: 10.25625/gzrpih/a54pyf
title: indofrag.data.frag.cai_cv_3.2012.tif

description: :unav
DOI: 10.25625/gzrpih/mziggy
title: indofrag.data.frag.cai_cv_3.2019.tif

description: :unav
DOI: 10.25625/gzrpih/tujnwa
title: indofrag.data.frag.cai_mn_3.2007.tif

description: :unav
DOI: 10.25625/gzrpih/w3qcjs
title: indofrag.data.frag.clumpy.2010.tif

description: :unav
DOI: 10.25625/gzrpih/4hzhe3
title: indofrag.data.frag.pafrac.2010.tif

description: :unav
DOI: 10.25625/gzrpih/bicaeg
title: indofrag.data.frag.pafrac.2017.tif

description: :unav
DOI: 10.25625/gzrpih/bhl79o
title: indofrag.data.frag.clumpy.2006.tif

description: :unav
DOI: 10.25625/gzrpih/mdrcgq
title: indofrag.data.frag.cai_am_3.2005.tif

description: :unav
DOI: 10.25625/gzrpih/2vj6zy
title: indofrag.data.frag.nlsi.2004.tif

description: :unav
DOI: 10.25625/gzrpih/feg1b5
title: indofrag.data.frag.cai_am_3.2001.tif

description: :unav
DOI: 10.25625/gzrpih/svgbeb
title: indofrag.data.frag.nlsi.2012.tif

description: :unav
DOI: 10.25625/gzrpih/zdhsyv
title: indofrag.data.frag.cai_am_3.2006.tif

description: :unav
DOI: 10.25625/gzrpih/pusvio
title: indofrag.data.frag.pafrac.2008.tif

description: :unav
DOI: 10.25625/gzrpih/iv5nua
title: indofrag.data.frag.clumpy.2013.tif

description: :unav
DOI: 10.25625/gzrpih/7ipqio
title: indofrag.data.frag.clumpy.2012.tif

description: :unav
DOI: 10.25625/gzrpih/rd2kyk
title: indofrag.data.frag.clumpy.2008.tif

description: :unav
DOI: 10.25625/gzrpih/fedagb
title: indofrag.data.frag.cai_am_3.2007.tif

description: :unav
DOI: 10.25625/gzrpih/sm2z5n
title: indofrag.data.frag.nlsi.2007.tif

description: :unav
DOI: 10.25625/gzrpih/lwxvyz
title: indofrag.data.frag.cai_mn_3.2003.tif

description: :unav
DOI: 10.25625/gzrpih/jy2qf0
title: indofrag.data.frag.pafrac.2002.tif

description: :unav
DOI: 10.25625/gzrpih/trvout
title: indofrag.data.frag.nlsi.2008.tif

description: :unav
DOI: 10.25625/gzrpih/ipullp
title: indofrag.data.frag.nlsi.2010.tif

description: :unav
DOI: 10.25625/gzrpih/m8bilm
title: indofrag.data.frag.cai_cv_3.2016.tif

description: :unav
DOI: 10.25625/gzrpih/df3e8a
title: indofrag.data.frag.cai_cv_3.2007.tif

description: :unav
DOI: 10.25625/gzrpih/xwz7nd
title: indofrag.data.frag.nlsi.2019.tif

description: :unav
DOI: 10.25625/gzrpih/gaidmq
title: indofrag.data.frag.cai_mn_3.2018.tif

description: :unav
DOI: 10.25625/gzrpih/n4xx1u
title: indofrag.data.frag.clumpy.2001.tif

description: :unav
DOI: 10.25625/gzrpih/srgr90
title: indofrag.data.frag.cai_mn_3.2012.tif

description: :unav
DOI: 10.25625/gzrpih/g8aj8k
title: indofrag.data.frag.cai_mn_3.2004.tif

description: :unav
DOI: 10.25625/gzrpih/wtlwcg
title: indofrag.data.frag.clumpy.2018.tif

description: :unav
DOI: 10.25625/gzrpih/bt9qnh
title: indofrag.data.frag.cai_cv_3.2004.tif

description: :unav
DOI: 10.25625/gzrpih/fgvggo
title: indofrag.data.frag.nlsi.2015.tif

description: :unav
DOI: 10.25625/gzrpih/uzl0zm
title: indofrag.data.frag.cai_cv_3.2013.tif

description: :unav
DOI: 10.25625/gzrpih/1es1vi
title: indofrag.data.frag.cai_mn_3.2011.tif

description: :unav
DOI: 10.25625/gzrpih/fwbktv
title: indofrag.data.frag.pafrac.2009.tif

description: :unav
DOI: 10.25625/gzrpih/da0ksx
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