cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14291/tccon.ggg2020.lauder01.r0
title: TCCON data from Lauder (NZ), 120HR, Release GGG2020.R0

description: The Total Carbon Column Observing Network (TCCON) is
    a network of ground-based Fourier Transform Spectrometers that record direct
    solar absorption spectra of the atmosphere in the near-infrared. From these
    spectra, accurate and precise column-averaged abundances of atmospheric
    constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
    is the GGG2020 data release of observations from the TCCON station at
    Lauder, New Zealand, 120HR
DOI: 10.14291/tccon.ggg2020.saga01.r0
title: TCCON data from Saga (JP), Release GGG2020.R0

description: The Total Carbon Column Observing Network (TCCON) is
    a network of ground-based Fourier Transform Spectrometers that record direct
    solar absorption spectra of the atmosphere in the near-infrared. From these
    spectra, accurate and precise column-averaged abundances of atmospheric
    constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
    is the GGG2020 data release of observations from the TCCON station at
    Saga, Japan
DOI: 10.14291/tccon.ggg2020.izana01.r1
title: TCCON data from Izana (ES), Release GGG2020.R1

description: The Total Carbon Column Observing Network (TCCON) is
    a network of ground-based Fourier Transform Spectrometers that record direct
    solar absorption spectra of the atmosphere in the near-infrared. From these
    spectra, accurate and precise column-averaged abundances of atmospheric
    constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
    is the GGG2020 data release of observations from the TCCON station at
    Izana, Tenerife, Spain
DOI: 10.14291/tccon.ggg2020.burgos01.r0
title: TCCON data from Burgos, Ilocos Norte (PH), Release GGG2020.R0

description: The Total Carbon Column Observing Network (TCCON) is
    a network of ground-based Fourier Transform Spectrometers that record direct
    solar absorption spectra of the atmosphere in the near-infrared. From these
    spectra, accurate and precise column-averaged abundances of atmospheric
    constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
    is the GGG2020 data release of observations from the TCCON station at
    Burgos, Ilocos Norte, Philippines
DOI: 10.14291/tccon.ggg2020.easttroutlake01.r0
title: TCCON data from East Trout Lake, SK (CA), Release GGG2020.R0

description: The Total Carbon Column Observing Network (TCCON) is
    a network of ground-based Fourier Transform Spectrometers that record direct
    solar absorption spectra of the atmosphere in the near-infrared. From these
    spectra, accurate and precise column-averaged abundances of atmospheric
    constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
    is the GGG2020 data release of observations from the TCCON station at
    East Trout Lake, Canada
DOI: 10.14291/tccon.ggg2020.indianapolis01.r1
title: TCCON data from Indianapolis (US), Release GGG2020.R1

description: The Total Carbon Column Observing Network (TCCON) is
    a network of ground-based Fourier Transform Spectrometers that record direct
    solar absorption spectra of the atmosphere in the near-infrared. From these
    spectra, accurate and precise column-averaged abundances of atmospheric
    constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
    is the GGG2020 data release of observations from the TCCON station at
    Indianapolis, Indiana, USA
DOI: 10.57967/hf/7687
title: crop-depth
DOI: 10.15468/dl.u4xe59
title: Occurrence Download

description: A dataset containing 682 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Podostemum ceratophyllum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 682 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004616-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14291/tccon.ggg2020
title: 2020 TCCON Data Release

description: The Total Carbon Column Observing Network (TCCON) is
a network of ground-based Fourier Transform Spectrometers that record direct
solar absorption spectra of the atmosphere in the near-infrared. From these
spectra, accurate and precise column-averaged abundances of atmospheric
constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This
is the GGG2020 data release.
description: Contact person: Laughner, Joshua L. josh.laughner@jpl.nasa.gov
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/10.14291/TCCON.GGG2020/</p>LICENSE.txt,  11.5 kB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/10.14291/TCCON.GGG2020/LICENSE.txt"
        > <i class="download icon"></i> Download </a></p>

        tccon.latest.public.tgz,  3.2 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/10.14291/TCCON.GGG2020/tccon.latest.public.tgz"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.15468/dl.uc7qse
title: Occurrence Download

description: A dataset containing 3642976415 species occurrences available in GBIF matching the query:
{
 "OccurrenceStatus" : [
 "is Present"
 ]
}

 The dataset includes 3642976415 records from 88606 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004455-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/7688
title: condiment_cup_rlds
DOI: 10.15468/dl.246zct
title: Occurrence Download

description: A dataset containing 115750 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plecotus auritus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 }
 ]
}

 The dataset includes 115750 records from 1288 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004586-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6/lvrrae/q2tkpl
title: dataverse_download.py

description: Script for automated file downloads
DOI: 10.25346/s6/lvrrae/otfvnj
title: UAVSig Readme.pdf

description: Readme file with details about the data file naming and contents
DOI: 10.25346/s6/lvrrae/hlg4gf
title: generate_spectrogram.ipynb

description: Python (Juypter Notebook) script to generate spectrograms used in the paper
DOI: 10.25346/s6/lvrrae/xjkegb
title: dataverse_download.py

description: Script for automated file downloads
DOI: 10.25346/s6/lvrrae/smrta8
title: UAVSig Readme.pdf

description: Readme file with details about the data file naming and contents
DOI: 10.25346/s6/lvrrae/nbxtkr
title: uavsig_dataset_info.pdf

description: Presentation with information about the dataset collection
DOI: 10.25346/s6/lvrrae/xtfkd4
title: drone_4100_04.mat
DOI: 10.25346/s6/lvrrae/eld0cp
title: drone_3400_00.mat
DOI: 10.25346/s6/lvrrae/jzzd9n
title: drone_4030_03.mat
DOI: 10.25346/s6/lvrrae/gfn2pu
title: drone_3200_00.mat
DOI: 10.25346/s6/lvrrae/aqrmjy
title: drone_3040_02.mat
DOI: 10.25346/s6/lvrrae/rgkure
title: drone_3004_00.mat
DOI: 10.25346/s6/lvrrae/jdicrc
title: drone_3040_05.mat
DOI: 10.25346/s6/lvrrae/5e4vmx
title: drone_3004_01.mat
DOI: 10.25346/s6/lvrrae/jrirhm
title: drone_3001_03.mat
DOI: 10.25346/s6/lvrrae/xk3gbn
title: drone_3020_00.mat
DOI: 10.25346/s6/lvrrae/1z5boj
title: drone_3002_05.mat
DOI: 10.25346/s6/lvrrae/lovnrz
title: drone_2030_02.mat
DOI: 10.25346/s6/lvrrae/7aen4u
title: drone_2400_02.mat
DOI: 10.25346/s6/lvrrae/z4xnmi
title: drone_2001_01.mat
DOI: 10.25346/s6/lvrrae/jlxrqo
title: drone_2030_04.mat
DOI: 10.25346/s6/lvrrae/7djvlv
title: drone_2003_04.mat
DOI: 10.25346/s6/lvrrae/wmvtur
title: drone_2004_01.mat
DOI: 10.25346/s6/lvrrae/0dq4iy
title: drone_1004_05.mat
DOI: 10.25346/s6/lvrrae/bkt9pa
title: drone_1020_00.mat
DOI: 10.25346/s6/lvrrae/rvksx3
title: drone_1200_00.mat
DOI: 10.25346/s6/lvrrae/k9emdm
title: drone_1300_01.mat
DOI: 10.25346/s6/lvrrae/18uvhv
title: drone_0240_05.mat
DOI: 10.25346/s6/lvrrae/vs7rzg
title: drone_0402_02.mat
DOI: 10.25346/s6/lvrrae/hpxvon
title: drone_0230_05.mat
DOI: 10.25346/s6/lvrrae/pclgzr
title: drone_0401_00.mat
DOI: 10.25346/s6/lvrrae/6ty8g5
title: drone_0310_03.mat
DOI: 10.25346/s6/lvrrae/tlgyty
title: drone_0430_04.mat
DOI: 10.25346/s6/lvrrae/qlcbg9
title: drone_0420_00.mat
DOI: 10.25346/s6/lvrrae/zdsqot
title: drone_0340_01.mat
DOI: 10.25346/s6/lvrrae/4pjazq
title: drone_0302_02.mat
DOI: 10.25346/s6/lvrrae/ab6z8m
title: drone_0304_02.mat
DOI: 10.25346/s6/lvrrae/pg28v0
title: drone_0210_00.mat
DOI: 10.15468/dl.z65pxp
title: Occurrence Download

description: A dataset containing 1774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lotus cruentus",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1774 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004496-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6/lvrrae/e86icu
title: drone_0201_03.mat
DOI: 10.25346/s6/lvrrae/93ghkh
title: drone_0103_00.mat
DOI: 10.25346/s6/lvrrae/2usjye
title: drone_0140_01.mat
DOI: 10.15468/dl.8448uj
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stoecharthrum giardi",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004495-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6/lvrrae/wzjo2m
title: drone_0120_02.mat
DOI: 10.25346/s6/lvrrae/9vjyrk
title: drone_0140_05.mat
DOI: 10.25346/s6/lvrrae/11zkdf
title: drone_0034_00.mat
DOI: 10.25346/s6/lvrrae/z31knh
title: drone_0031_00.mat
DOI: 10.25346/s6/lvrrae/6bpml9
title: drone_0041_04.mat
DOI: 10.25346/s6/lvrrae/tbzi9v
title: drone_0043_00.mat
DOI: 10.25346/s6/lvrrae/24hhcm
title: drone_0032_03.mat
DOI: 10.25346/s6/lvrrae/dadnrt
title: drone_0042_05.mat
DOI: 10.25346/s6/lvrrae/e4ej4p
title: drone_0021_05.mat
DOI: 10.25346/s6/lvrrae/bd26sm
title: drone_0012_00.mat
DOI: 10.25346/s6/lvrrae/li2mrg
title: drone_0013_05.mat
DOI: 10.25346/s6/lvrrae/fllkqy
title: drone_0013_02.mat
DOI: 10.25346/s6/lvrrae/qvskjw
title: controller_p2_0001_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/3so6ny
title: controller_p1_0110_01.mat

description: File uploaded via API
DOI: 10.15468/dl.j354vs
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Perca fluviatilis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1820",
 "Year is less than or equal to 1824"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004497-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6/lvrrae/hlgsqu
title: controller_p2_1000_01.mat

description: File uploaded via API
DOI: 10.5061/dryad.83bk3jb64
title: <em>Terniopsis chanthaburiensis</em> (Podostemaceae), a new record for China and its complete plastid genome

description: The genus Terniopsis consists of plants that have not been thoroughly
 studied, with many species remaining taxonomically unresolved. In this
 study, Terniopsis chanthaburiensis is reported as a new record of China
 based on morphological traits. Then, we assembled and annotated its
 chloroplast genome based on genome skimming data. A maximum-likelihood
 tree constructed based on the matK and ITS genes showed that jflcz20230309
 clustered with T. chanthaburiensis (LC625800, LC384161, and LC625815,
 LC625816). This validates our morphological identification. Furthermore,
 the plastome of T. chanthaburiensis has been sequenced, revealing a
 typical quadripartite structure with a length of 130,529 bp. It contains
 105 unique genes, including 73 protein-coding genes, 28 tRNAs, and 4
 rRNAs. Phylogenetic analysis based on the plastid genome reveals that T.
 chanthaburiensis (collection number: jflcz20230309, GPS: 108°47′37.2012″E,
 18°41′48.9624″N, collection date: 9 Mar. 2023) forms a distinct clade
 sister to T. yongtaiensis and T. heterostaminata, with high support values
 (PP = 1.00, BS = 100). The discovery of this river-weed could lay the
 foundation for investigating their biogeographical patterns and species
 evolution.
description: # *Terniopsis chanthaburiensis* (Podostemaceae), a new record for China
 and its complete plastid genome Dataset DOI:
 [10.5061/dryad.83bk3jb64](https://doi.org/10.5061/dryad.83bk3jb64) ##
 Description of the data and file structure *
 **Terniopsis_chanthaburiensis_chloroplast_genome.fasta**\ Complete
 chloroplast genome sequence. * **Terniopsis_chanthaburiensis_ITS.fasta**\
 Nuclear ITS sequence. * **Terniopsis_chanthaburiensis_matK.fasta**\
 Chloroplast *matK* gene sequence.
DOI: 10.25346/s6/lvrrae/krfw8o
title: controller_p2_0110_00.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/kk0i5b
title: controller_p2_1100_04.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/7k4erk
title: controller_p1_0011_04.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/bzgfnh
title: controller_p1_1111_04.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/fjdoio
title: controller_p2_0101_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/w0gndf
title: controller_p2_1010_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/chxukt
title: controller_p2_0101_01.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/fi3air
title: controller_p1_1011_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/m8yjer
title: controller_p2_0110_04.mat

description: File uploaded via API
DOI: 10.5061/dryad.stqjq2cgh
title: Beyond coproduction: A case study in direct funding to advance community-led resilience

description: Knowledge-based actors in academic institutions and government agencies
 increasingly apply coproduction to build the resilience and adaptive
 capacity of frontline communities. However, coproduced climate adaptation
 outputs are predominantly technical, scientific, or data products.
 Frontline communities often seek more practical outputs aimed at immediate
 resilience priorities. In this paper, we describe our community grants
 program, which provided direct funding to frontline community-based
 organizations, as an illustrative case study 1) to expand knowledge of
 what community-led climate resilience means and its impact in practical
 terms, and 2) to build understanding of the opportunities and limitations
 of direct funding for advancing climate resilience. We analyze project
 proposals and post-project semi-structured interviews to increase
 understanding of what frontline community-based organizations mean by
 resilience and how they approach that work. Our findings indicate that
 direct funding can ignite resilience at the local level and enhance trust
 building between knowledge-based actors and frontline communities. But
 direct funding is a resource intensive process and fundamentally focuses
 on making a difference on the ground in specific locations. We conclude,
 first, that academic institutions and government agencies need to take
 frontline communities and their resilience priorities seriously. And
 funding community-led initiatives is one impactful way to ensuring
 localized resilience impacts. Second, direct funding of community-led
 resilience initiatives is an important pathway for the adaptation field to
 broaden its conception of climate adaptation and have a local impact. And
 third, university- and government-based researchers can play an important
 role by assisting frontline community-based organizations achieve their
 resilience objectives and scaling out and up that work.
description: # Beyond coproduction: A case study in direct funding to advance
 community-led resilience Dataset DOI:
 [10.5061/dryad.stqjq2cgh](https://doi.org/10.5061/dryad.stqjq2cgh) ##
 Description of the data and file structure The data included in this
 repository is the following: Interview metadata: This document contains
 de-identified summative data of the 5 interviews conducted for this
 paper.  ### Files and variables #### File: CGP_interview_meta_data.docx
 **Description:** Document contains de-identified summative data from
 interviews. Data is organized by organization and according to theme.  The
 authors carried out coding in a Word document. The following codes were
 applied to each of the 5 transcripts: Project description; Defining
 climate resilience; Challenges and barriers; Partnerships; Research;
 Improving grant making. ## Human subjects data The authors received
 consent from all participants and all data has been de-identified.
DOI: 10.25346/s6/lvrrae/qokwha
title: controller_p1_0010_01.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/uxvwsb
title: controller_p1_1101_00.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/datu4u
title: controller_p2_0000_00.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/neizh5
title: controller_p1_1101_03.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/ovtote
title: controller_p2_1110_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/zefjkm
title: controller_p1_0001_03.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/cgot5x
title: controller_p1_1111_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/rywxur
title: controller_p1_0000_04.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/ltql4s
title: controller_p1_0000_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/ilzpex
title: controller_p2_1011_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/ryzgii
title: controller_p1_1110_01.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/dokhjl
title: controller_p2_0111_04.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/gaehx0
title: controller_p1_0101_05.mat

description: File uploaded via API
DOI: 10.5061/dryad.0k6djhbdq
title: Code from: Geometric-mean fitness does not correspond to long-term survival probability

description: Unpredictable randomness plays a crucial role in the long-term
 sustainability of biological systems. The population growth of a species
 in variable environments is typically described in terms of a long-term
 measure, such as geometric mean fitness or the geometric mean of
 stochastic growth rates. However, a quantitative understanding of the
 relationship between these fitness measures and long-term survival
 probability remains a critical, and often overlooked, aspect of ecological
 modeling. Here, we investigate this relationship using large-scale
 numerical simulations, focusing on the implications for bet-hedging
 strategies. To this end, we develop two individual-based growth models
 incorporating randomly varying growth rates. Our simulations reveal that a
 one-to-one correspondence, or monotonic relationship, does not exist
 between geometric-mean fitness and survival probability. Specifically,
 higher geometric-mean fitness does not necessarily correlate with
 increased survival probability. These findings challenge the assumption of
 a universal, time-independent measure of long-term fitness, and suggest
 that the ”optimal” survival strategy is likely contingent on the timescale
 of observation.
description: # Code from: Geometric-mean fitness does not correspond to long-term
 survival probability Dataset DOI:
 [10.5061/dryad.0k6djhbdq](https://doi.org/10.5061/dryad.0k6djhbdq) ###
 Files and variables We present the code snippets used for the study titled
 *Geometric-mean Fitness Does Not Correspond to Long-term Survival
 Probability* by Takuya Okabe, Jin Yoshimura, and Hiromu Ito. The survival
 probability is estimated using a Monte Carlo simulation in Mathematica. A
 population is initialized with 100 individuals. The size of this
 population is iteratively updated based on a `NextSize` function, which
 determines the next population size from the previous one. This simulation
 is repeated 10,000 times. We record the proportion of simulations
 resulting in extinction and calculate the survival probability as 111
 minus this extinction proportion. #### File: Code.nb **Description:** The
 notebook simulates how a population grows or goes extinct when its
 environment randomly changes over time. Starting with a fixed number of
 individuals, each generation, the population experiences one of two
 environments, and individuals reproduce randomly depending on which
 environment occurs. This process is repeated many times to estimate how
 often the population survives versus goes extinct. The key point is that
 even if a population has good average growth (especially a high
 geometric-mean growth rate), random bad years and chance fluctuations can
 still drive it to extinction. So the simulations show that average fitness
 alone does not reliably predict long-term survival for real, finite
 populations.
DOI: 10.25346/s6/lvrrae/t6mise
title: controller_p2_0010_00.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/ywgtqq
title: controller_p2_1111_04.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/zjzbyf
title: controller_p1_0101_00.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/8jauow
title: controller_p2_0100_03.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/bnmiro
title: controller_p1_0101_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/j42ail
title: controller_p2_1010_03.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/mao3u9
title: controller_p2_0011_03.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/x41rgl
title: controller_p1_0101_01.mat

description: File uploaded via API
DOI: 10.15468/dl.ejfd75
title: Occurrence Download

description: A dataset containing 280 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cichla kelberi"
 ]
}

 The dataset includes 280 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004498-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6/lvrrae/8loc5i
title: controller_p1_1100_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/l72zsr
title: controller_p2_1000_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/h3xpfp
title: controller_p1_1010_01.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/9yp2wi
title: controller_p1_1001_01.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/lkeoqg
title: controller_p2_1011_03.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/4imhjh
title: controller_p2_0011_02.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/gfqwpb
title: controller_p2_1011_01.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/cufywu
title: controller_p2_0111_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/rks4qv
title: controller_p1_1010_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/zbgcbq
title: controller_p2_0110_05.mat

description: File uploaded via API
DOI: 10.25346/s6/lvrrae/6zvadd
title: controller_p2_0001_00.mat

description: File uploaded via API