cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57841/casdc.0001308
title: 氮化硼/氮化硼体系在界面距离为1.6266埃时的势能面
DOI: 10.57841/casdc.0001309
title: 氮化硼/氮化硼体系在界面距离为1.6226埃时的势能面
DOI: 10.57841/casdc.0001310
title: 氮化硼/氮化硼体系在界面距离为1.6186埃时的势能面
DOI: 10.6084/m9.figshare.23506989
title: Table S1-5.xlsx

description: <strong>Table S1.</strong> The complete results of MR estimates for the correlation between gut microbiota and female reproductive disorders are provided. <strong>Table S2.</strong> The complete results of reverse MR estimates for the correlation between female reproductive disorders and gut microbiota are provided. <strong>Table S3. </strong>The complete results of pleiotropy and heterogeneity are provided. <strong>Table S4. </strong>Utilizing instrumental variables in MR analysis to explore the correlation between gut microbiota and female reproductive disorders. <strong>Table S5.</strong> Employing instrumental variables in the MR analysis to investigate the link between female reproductive disorders and gut microbiota. estimates for the correlation between female reproductive disorders and gut microbiota are provided.
DOI: 10.57841/casdc.0001311
title: 氮化硼/氮化硼体系在界面距离为1.6146埃时的势能面
DOI: 10.6084/m9.figshare.14912637
title: Habitat Data from 'The phenology and clutch size of UK Blue Tits does not differ with woodland composition'

description: Habitat data collected for the manuscript entitled 'The phenology and clutch size of UK Blue Tits does not differ with woodland composition'. All other data associated with the manuscript is available on request. Bird breeding data are housed with the British Trust for Ornithology as part of the maintained National Database on Bird Ringing and Nest Recording. Data can be requested via https://www.bto.org/our-science/data/data-request-system. All temperature data are available on request from the MET Office. <br>
DOI: 10.6084/m9.figshare.14912637.v1
title: Habitat Data from 'The phenology and clutch size of UK Blue Tits does not differ with woodland composition'

description: Habitat data collected for the manuscript entitled 'The phenology and clutch size of UK Blue Tits does not differ with woodland composition'. All other data associated with the manuscript is available on request. Bird breeding data are housed with the British Trust for Ornithology as part of the maintained National Database on Bird Ringing and Nest Recording. Data can be requested via https://www.bto.org/our-science/data/data-request-system. All temperature data are available on request from the MET Office. <br>
DOI: 10.57841/casdc.0001312
title: 氮化硼/氮化硼体系在界面距离为1.6106埃时的势能面
DOI: 10.57841/casdc.0001313
title: 氮化硼/氮化硼体系在界面距离为1.6066埃时的势能面
DOI: 10.57841/casdc.0001314
title: 氮化硼/氮化硼体系在界面距离为1.6026埃时的势能面
DOI: 10.57841/casdc.0001315
title: 氮化硼/氮化硼体系在界面距离为1.5986埃时的势能面
DOI: 10.57841/casdc.0001316
title: 氮化硼/氮化硼体系在界面距离为1.5946埃时的势能面
DOI: 10.57841/casdc.0001317
title: 氮化硼/氮化硼体系在界面距离为1.5906埃时的势能面
DOI: 10.57841/casdc.0001318
title: 氮化硼/氮化硼体系在界面距离为1.5866埃时的势能面
DOI: 10.57841/casdc.0001319
title: 氮化硼/氮化硼体系在界面距离为1.5826埃时的势能面
DOI: 10.57841/casdc.0001320
title: 氮化硼/氮化硼体系在界面距离为1.5786埃时的势能面
DOI: 10.57841/casdc.0001321
title: 氮化硼/氮化硼体系在界面距离为1.5746埃时的势能面
DOI: 10.57841/casdc.0001322
title: 氮化硼/氮化硼体系在界面距离为1.5706埃时的势能面
DOI: 10.57841/casdc.0001323
title: 氮化硼/氮化硼体系在界面距离为1.5666埃时的势能面
DOI: 10.57841/casdc.0001324
title: 氮化硼/氮化硼体系在界面距离为1.5626埃时的势能面
DOI: 10.25415/ujhb.23497496
title: Performance of ESG-compliant Funds versus Traditional Balanced Portfolios:

description: ESG-compliant and balanced funds performance
DOI: 10.25415/ujhb.23497496.v1
title: Performance of ESG-compliant Funds versus Traditional Balanced Portfolios:

description: ESG-compliant and balanced funds performance
DOI: 10.57841/casdc.0001325
title: 氮化硼/氮化硼体系在界面距离为1.5586埃时的势能面
DOI: 10.57841/casdc.0001326
title: 氮化硼/氮化硼体系在界面距离为1.5546埃时的势能面
DOI: 10.57780/esa-nlhirh0
title: GREAT

description: 2021
DOI: 10.6084/m9.figshare.22757087
title: Supplementary file: Differential gene GO enrichment analysis results; Significantly enriched KEGG pathways

description: Differential gene GO enrichment analysis results
DOI: 10.6084/m9.figshare.22757087.v7
title: Supplementary file: Differential gene GO enrichment analysis results; Significantly enriched KEGG pathways

description: Differential gene GO enrichment analysis results
DOI: 10.6084/m9.figshare.22757087.v6
title: Supplementary file: Supplementary Table S3. Differential gene GO enrichment analysis results; Supplementary Table S4. Significantly enriched KEGG pathways

description: Differential gene GO enrichment analysis results
DOI: 10.5285/a12602c6-51b0-459d-9b45-73dd93f6fa4d
title: L chondrite meteorite phosphate microscopy and U-Pb analyses

description: Microscopy (Scanning Electron Microscopy, Cathodoluminescence Imaging) and U-Pb isotopic (Secondary Ionisation Mass Spectrometry) analyses of phosphate minerals in a suite of nine L chondrite meteorites (and one reference analysis of an LL chondrite). The dataset includes multiple SIMS spot analyses of phosphates in each meteorite, as well as images at multiple scales of all grains analysed. The data is reported and analysed in Walton et al., 2022 GCA. Data for following samples: Kyushu BM.1905,67 (P30906) Lincoln County BM.1959,882 (P24052) Monze BM.1951,84 (P30910) Indianola BM.1959,876 (P30907) Alfianello BM.55240 (P30893) McKinney (Sedgwick Museum CRWM 2) PR (Sedgwick Museum 11921) Beenham (Sedgwick Museum 16754) Chateau Renard (L 4361, VNHM)
DOI: 10.26255/heal.hth2-54vt
title: Tweet lemmatization data
DOI: 10.21227/38ed-6n20
title: Everythig you need about simulation of Hybrid Electric Vehicles

description: This data provides an overview of the simulation of Hybrid Electric Vehicles (HEVs) using MATLAB. HEVs have emerged as a promising solution for reducing emissions and improving fuel efficiency. MATLAB offers a flexible platform to accurately model and analyze the complex dynamics of hybrid powertrains, including various components and control strategies. The simulation capabilities enable the evaluation of HEV performance under different conditions, optimization of designs, and exploration of factors impacting energy consumption. MATLAB-based simulations accelerate the development of energy-efficient HEVs, reducing costs and promoting widespread adoption.This data provides an overview of the simulation of Hybrid Electric Vehicles (HEVs) using MATLAB. HEVs have emerged as a promising solution for reducing emissions and improving fuel efficiency. MATLAB offers a flexible platform to accurately model and analyze the complex dynamics of hybrid powertrains, including various components and control strategies. The simulation capabilities enable the evaluation of HEV performance under different conditions, optimization of designs, and exploration of factors impacting energy consumption. MATLAB-based simulations accelerate the development of energy-efficient HEVs, reducing costs and promoting widespread adoption.
DOI: 10.26255/heal.er0o-fcg4
title: OAI-PMH record statistics
DOI: 10.6084/m9.figshare.20306519
title: Serum 14-3-3η as predictor of clinical remission and progression of structural damage in early rheumatoid arthritis following a treat-to-target strategy in a randomized controlled trial

description: 14-3-3η is a proinflammatory mediator critical to joint destruction in rheumatoid arthritis (RA). We aimed to evaluate serum 14-3-3η for predicting disease activity and radiographic progression in patients with early RA in the double-blinded, randomized OPERA trial. 180 patients with early RA were randomized to receive methotrexate (MTX) + adalimumab or MTX + placebo in combination with glucocorticoid injections into swollen joints. Disease activity was measured using the 28-joint Disease Activity Score–C-reactive protein (DAS28-CRP). Clinical remission was defined as DAS28-CRP &lt; 2.6. X-rays of hands and feet were evaluated by the Total Sharp van der Heijde score (TSS). Radiographic progression was defined as exceeding the smallest detectable change (1.8 TSS-units). Serum 14-3-3η was determined by enzyme-linked immunosorbent assay. Multivariate logistic regression models were used to identify predictors of DAS28-CRP remission at 6 months and radiographic progression at 12 months. Baseline 14-3-3η was a borderline significant independent predictor of radiographic progression at 12 months (odds radio = 1.02, 95% confidence interval 1.00–1.03, p = 0.05). In anti-cyclic citrullinated peptide antibody (ACPA)-negative patients, a moderate/high baseline 14-3-3η concentration increased the risk of radiographic progression at 12 months [4/51 (8%) vs 3/9 (33%), χ2 = 4.823, p = 0.028]. No value of 14-3-3η for predicting achievement of clinical remission was found. Serum 14-3-3η was a borderline significant predictor of radiographic progression, particularly in ACPA-negative patients, but not of predicting achievement of clinical remission. Optimal cut-off levels of 14-3-3η for predicting radiographic progression in RA need further clarification.
DOI: 10.6084/m9.figshare.20431017
title: The validity of the Danish version of the Fibromyalgia Impact Questionnaire – Revised applied in a clinical setting: a Rasch analysis

description: The aim of this study was to evaluate the psychometric properties of the Danish version of the Fibromyalgia Impact Questionnaire – Revised (FIQR), when used to quantify the severity of disease burden in a Danish population of patients with chronic widespread pain (CWP), including fibromyalgia (FM). A total of 924 participants diagnosed with CWP and/or FM completed an electronic version of the FIQR via touchscreens in the clinic at referral for specialist care. Data were collected from 1 January 2018 to 3 September 2020. Rasch measurement methods were applied. Rating scale analysis suggested multiple threshold disordering in the 0–10 category rating scale. A principal component analysis suggested assessment of a multidimensional construct. Thus, the Rasch analysis of the full FIQR was discontinued. Instead, Rasch analyses were performed on the two subscales: ‘function’ and ‘symptoms’. By collapsing the rating scale to a 0–4 category scale, the remaining threshold disordering of both subscale was solved. Only the symptom subscale indicated multidimensionality. There was underfitting misfit of item 21 and overfitting misfit of item 12. No significant differential item functioning, defined by sex, ethnicity, or education, was found. The FIQR should be considered as an instrument consisting of three separate subscales representing ‘function’, ‘overall impact’, and ‘symptoms’. We recommend calculating and reporting on both a 0–10 and a 0–4 category scale. Also, if using the total FIQR score as an outcome measure, this should be done with caution, until revision of the rating scale.
DOI: 10.6084/m9.figshare.20431017.v1
title: The validity of the Danish version of the Fibromyalgia Impact Questionnaire – Revised applied in a clinical setting: a Rasch analysis

description: The aim of this study was to evaluate the psychometric properties of the Danish version of the Fibromyalgia Impact Questionnaire – Revised (FIQR), when used to quantify the severity of disease burden in a Danish population of patients with chronic widespread pain (CWP), including fibromyalgia (FM). A total of 924 participants diagnosed with CWP and/or FM completed an electronic version of the FIQR via touchscreens in the clinic at referral for specialist care. Data were collected from 1 January 2018 to 3 September 2020. Rasch measurement methods were applied. Rating scale analysis suggested multiple threshold disordering in the 0–10 category rating scale. A principal component analysis suggested assessment of a multidimensional construct. Thus, the Rasch analysis of the full FIQR was discontinued. Instead, Rasch analyses were performed on the two subscales: ‘function’ and ‘symptoms’. By collapsing the rating scale to a 0–4 category scale, the remaining threshold disordering of both subscale was solved. Only the symptom subscale indicated multidimensionality. There was underfitting misfit of item 21 and overfitting misfit of item 12. No significant differential item functioning, defined by sex, ethnicity, or education, was found. The FIQR should be considered as an instrument consisting of three separate subscales representing ‘function’, ‘overall impact’, and ‘symptoms’. We recommend calculating and reporting on both a 0–10 and a 0–4 category scale. Also, if using the total FIQR score as an outcome measure, this should be done with caution, until revision of the rating scale.
DOI: 10.6084/m9.figshare.19793712
title: Impact of osteoarthritis disease severity on treatment patterns and healthcare resource use: analysis of real-world data

description: To understand treatment patterns and healthcare resource utilization (HCRU) related to osteoarthritis (OA) disease severity in patients in five European countries. Data were drawn from the Adelphi OA Disease Specific Programme™ (2017–18). Physicians classified their patients as having mild, moderate, or severe OA, and provided details on their current prescribed therapy and HCRU, including healthcare professional (HCP) consultations, diagnostics and testing, and hospitalizations. Comparisons between disease severity groups were made using analysis of variance and chi-squared tests. The study included 489 physicians (primary care physicians, rheumatologists, orthopaedic surgeons) reporting on 3596 OA patients: 24% mild, 53% moderate, and 23% severe disease. Both physicians and patients reported decreasing satisfaction with treatment with greater disease severity, despite the number of classes of prescribed drugs and increased use of opioids, which were used in almost half of patients with severe OA. For patients whose treatment was not effective, physicians prescribed the same therapeutic options, which were cycled in subsequent treatment lines, with multiple treatment regimens being commonly used. Patients with greater symptom severity also had more physician consultations, while the numbers of tests/imaging, predominantly X-rays, conducted to diagnose or monitor OA increased significantly with disease severity. The type of HCP involvement in patient management also varied by OA severity. Across five European countries, the use of both non-pharmacological and pharmacological treatments increases with greater disease severity. Those with more severe disease place a greater demand on healthcare resources, with HCP consultations, tests, and hospital visits increasing with severity.
DOI: 10.6084/m9.figshare.19793712.v2
title: Impact of osteoarthritis disease severity on treatment patterns and healthcare resource use: analysis of real-world data

description: To understand treatment patterns and healthcare resource utilization (HCRU) related to osteoarthritis (OA) disease severity in patients in five European countries. Data were drawn from the Adelphi OA Disease Specific Programme™ (2017–18). Physicians classified their patients as having mild, moderate, or severe OA, and provided details on their current prescribed therapy and HCRU, including healthcare professional (HCP) consultations, diagnostics and testing, and hospitalizations. Comparisons between disease severity groups were made using analysis of variance and chi-squared tests. The study included 489 physicians (primary care physicians, rheumatologists, orthopaedic surgeons) reporting on 3596 OA patients: 24% mild, 53% moderate, and 23% severe disease. Both physicians and patients reported decreasing satisfaction with treatment with greater disease severity, despite the number of classes of prescribed drugs and increased use of opioids, which were used in almost half of patients with severe OA. For patients whose treatment was not effective, physicians prescribed the same therapeutic options, which were cycled in subsequent treatment lines, with multiple treatment regimens being commonly used. Patients with greater symptom severity also had more physician consultations, while the numbers of tests/imaging, predominantly X-rays, conducted to diagnose or monitor OA increased significantly with disease severity. The type of HCP involvement in patient management also varied by OA severity. Across five European countries, the use of both non-pharmacological and pharmacological treatments increases with greater disease severity. Those with more severe disease place a greater demand on healthcare resources, with HCP consultations, tests, and hospital visits increasing with severity.
DOI: 10.6084/m9.figshare.23506974
title: Adjusted lean meat percentage values

description: Lean meat percentage values adjusted for slaughter weights, time interval between placement in the climate section and slaughtering, section, sex, and feeding scheme in the weaner section.
DOI: 10.6084/m9.figshare.23506974.v1
title: Adjusted lean meat percentage values

description: Lean meat percentage values adjusted for slaughter weights, time interval between placement in the climate section and slaughtering, section, sex, and feeding scheme in the weaner section.
DOI: 10.34740/kaggle/dsv/5917744
title: Wisabi Bank Dataset
DOI: 10.57745/jjeyig
title: .validated
DOI: 10.57745/xfybky
title: 2020-09-10_003.png
DOI: 10.57745/lzuyuv
title: 2020-09-10_003.hdr
DOI: 10.57745/xr6ljz
title: 2020-09-10_003.raw
DOI: 10.57745/ljnknm
title: DARKREF_2020-09-10_003.hdr
DOI: 10.57745/mufdqw
title: DARKREF_2020-09-10_003.raw
DOI: 10.57745/owyske
title: WHITEREF_2020-09-10_003.hdr
DOI: 10.57745/xytqoo
title: WHITEREF_2020-09-10_003.raw
DOI: 10.57745/agxuir
title: manifest.xml
DOI: 10.57745/y76qgp
title: 2020-09-10_003.xml
DOI: 10.57745/o7cs4d
title: REFLECTANCE_2020-09-10_003.dat
DOI: 10.57745/cuc1cv
title: REFLECTANCE_2020-09-10_003.hdr
DOI: 10.57745/ynkc0w
title: REFLECTANCE_2020-09-10_003.png
DOI: 10.57745/pxrvdu
title: RGBBACKGROUND_2020-09-10_003.png
DOI: 10.57745/rvo6mz
title: RGBSCENE_2020-09-10_003.png
DOI: 10.57745/vstozq
title: RGBVIEWFINDER_2020-09-10_003.png
DOI: 10.57745/tz18dm
title: .validated
DOI: 10.57745/hp8pd5
title: 2020-09-10_004.png
DOI: 10.57745/84684l
title: 2020-09-10_004.hdr
DOI: 10.57745/rsn6ar
title: 2020-09-10_004.raw
DOI: 10.57745/hodqj0
title: DARKREF_2020-09-10_004.hdr
DOI: 10.57745/bxqy8i
title: DARKREF_2020-09-10_004.raw
DOI: 10.57745/lutvls
title: WHITEREF_2020-09-10_004.hdr
DOI: 10.57745/ixztez
title: WHITEREF_2020-09-10_004.raw
DOI: 10.57745/ud5wh4
title: manifest.xml
DOI: 10.57745/eu9wqn
title: 2020-09-10_004.xml
DOI: 10.57745/t0qdif
title: REFLECTANCE_2020-09-10_004.dat
DOI: 10.57745/ersokb
title: REFLECTANCE_2020-09-10_004.hdr
DOI: 10.57745/kjlbqc
title: REFLECTANCE_2020-09-10_004.png
DOI: 10.57745/bynqcg
title: RGBBACKGROUND_2020-09-10_004.png
DOI: 10.57745/tvhz3d
title: RGBSCENE_2020-09-10_004.png
DOI: 10.57745/cpvbxw
title: RGBVIEWFINDER_2020-09-10_004.png
DOI: 10.57745/fayu4l
title: .validated
DOI: 10.57745/nmmi4m
title: 2020-09-10_005.png
DOI: 10.57745/me18op
title: 2020-09-10_005.hdr
DOI: 10.57745/r8o32r
title: 2020-09-10_005.raw
DOI: 10.57745/hwr4tr
title: DARKREF_2020-09-10_005.hdr
DOI: 10.57745/ch4pmi
title: DARKREF_2020-09-10_005.raw
DOI: 10.57745/bdpbgg
title: WHITEREF_2020-09-10_005.hdr
DOI: 10.57745/ulbcln
title: WHITEREF_2020-09-10_005.raw
DOI: 10.57745/qahbim
title: manifest.xml
DOI: 10.57745/ycqhgj
title: 2020-09-10_005.xml
DOI: 10.57745/en9xvq
title: REFLECTANCE_2020-09-10_005.dat
DOI: 10.57745/bgh1j5
title: REFLECTANCE_2020-09-10_005.hdr
DOI: 10.57745/8ncppp
title: REFLECTANCE_2020-09-10_005.png
DOI: 10.57745/xfntqy
title: RGBBACKGROUND_2020-09-10_005.png
DOI: 10.57745/5u02ul
title: RGBSCENE_2020-09-10_005.png
DOI: 10.57745/i5fmgw
title: RGBVIEWFINDER_2020-09-10_005.png
DOI: 10.57745/wdlwbg
title: .validated
DOI: 10.57745/ji3q5r
title: 2020-09-10_006.png
DOI: 10.57745/i4wrie
title: 2020-09-10_006.hdr
DOI: 10.57745/cbq93z
title: 2020-09-10_006.raw
DOI: 10.57745/miuyeu
title: DARKREF_2020-09-10_006.hdr
DOI: 10.57745/q8k4aj
title: DARKREF_2020-09-10_006.raw
DOI: 10.57745/2pgauz
title: WHITEREF_2020-09-10_006.hdr
DOI: 10.57745/t0env5
title: WHITEREF_2020-09-10_006.raw
DOI: 10.57745/dje5wn
title: manifest.xml
DOI: 10.57745/vu7mjb
title: 2020-09-10_006.xml
DOI: 10.57745/jtzuyy
title: REFLECTANCE_2020-09-10_006.dat
DOI: 10.57745/qusyga
title: REFLECTANCE_2020-09-10_006.hdr
DOI: 10.57745/lxre9a
title: REFLECTANCE_2020-09-10_006.png
DOI: 10.57745/xaozqz
title: RGBBACKGROUND_2020-09-10_006.png
DOI: 10.57745/flypcm
title: RGBSCENE_2020-09-10_006.png
DOI: 10.57745/wvmjzf
title: RGBVIEWFINDER_2020-09-10_006.png
DOI: 10.57745/l3ynff
title: 2020-09-10_007.png
DOI: 10.57745/hvw18t
title: 2020-09-10_007.hdr
DOI: 10.57745/mslnuf
title: 2020-09-10_007.raw
DOI: 10.57745/oedl8q
title: DARKREF_2020-09-10_007.hdr
DOI: 10.57745/r3otab
title: DARKREF_2020-09-10_007.raw
DOI: 10.57745/odnnd8
title: WHITEREF_2020-09-10_007.hdr
DOI: 10.57745/jyw9n0
title: WHITEREF_2020-09-10_007.raw
DOI: 10.57745/cpaoxr
title: 2020-09-10_007.xml
DOI: 10.57745/ydgrim
title: REFLECTANCE_2020-09-10_007.dat
DOI: 10.57745/eu1i2n
title: REFLECTANCE_2020-09-10_007.hdr
DOI: 10.5258/soton/d2660
title: Dataset in support of the thesis 'Inference and learning algorithms for wireless iterative receivers'

description: This dataset includes matlab files, which can produce all results figures in the thesis.
DOI: 10.57745/hzgl2v
title: REFLECTANCE_2020-09-10_007.png
DOI: 10.57745/p2ktp2
title: RGBBACKGROUND_2020-09-10_007.png
DOI: 10.57745/wwcqvl
title: RGBSCENE_2020-09-10_007.png
DOI: 10.57745/c7zwab
title: RGBVIEWFINDER_2020-09-10_007.png
DOI: 10.57745/jnzz6o
title: 2020-09-10_008.png
DOI: 10.57745/apa6mq
title: 2020-09-10_008.hdr
DOI: 10.57745/irnbn5
title: 2020-09-10_008.raw
DOI: 10.57745/ajvdc9
title: DARKREF_2020-09-10_008.hdr
DOI: 10.57745/tbc7ms
title: DARKREF_2020-09-10_008.raw
DOI: 10.57745/qlc5kz
title: WHITEREF_2020-09-10_008.hdr
DOI: 10.57745/dye8ga
title: WHITEREF_2020-09-10_008.raw
DOI: 10.57745/p14fku
title: 2020-09-10_008.xml
DOI: 10.57745/bfql7c
title: REFLECTANCE_2020-09-10_008.dat
DOI: 10.57745/fnpr2s
title: REFLECTANCE_2020-09-10_008.hdr
DOI: 10.57745/kccatu
title: REFLECTANCE_2020-09-10_008.png
DOI: 10.57745/bip22o
title: RGBBACKGROUND_2020-09-10_008.png
DOI: 10.57745/vwpcuw
title: RGBSCENE_2020-09-10_008.png
DOI: 10.57745/bptmrk
title: RGBVIEWFINDER_2020-09-10_008.png
DOI: 10.57745/5popzr
title: 2020-09-10_009.png
DOI: 10.57745/ng2bqp
title: 2020-09-10_009.hdr
DOI: 10.57745/5pqugk
title: 2020-09-10_009.raw
DOI: 10.57745/b5xccq
title: DARKREF_2020-09-10_009.hdr
DOI: 10.57745/k90jnd
title: DARKREF_2020-09-10_009.raw
DOI: 10.57745/s8rr64
title: WHITEREF_2020-09-10_009.hdr
DOI: 10.57745/7i1pu5
title: WHITEREF_2020-09-10_009.raw
DOI: 10.57745/mln7uf
title: 2020-09-10_009.xml
DOI: 10.57745/oevigj
title: REFLECTANCE_2020-09-10_009.dat
DOI: 10.57745/5aifj1
title: REFLECTANCE_2020-09-10_009.hdr
DOI: 10.57745/so4bew
title: REFLECTANCE_2020-09-10_009.png
DOI: 10.57745/bj7snz
title: RGBBACKGROUND_2020-09-10_009.png
DOI: 10.57745/y7t8zh
title: RGBSCENE_2020-09-10_009.png
DOI: 10.57745/wg5yvd
title: RGBVIEWFINDER_2020-09-10_009.png
DOI: 10.57745/tcsmtt
title: 2020-09-10_010.png
DOI: 10.57745/z9norp
title: 2020-09-10_010.hdr
DOI: 10.5281/zenodo.8031915
title: Patterns of genetic variation reflect multiple introductions and pre-admixture sources of common ragweed (Ambrosia artemisiifolia) in China

description: Informations about the locations and genetic diversity of <em>Ambrosia artemisiifolia</em> populations in published paper "Patterns of genetic variation reflect multiple introductions and pre-admixture sources of common ragweed (Ambrosia artemisiifolia) in China".
DOI: 10.57745/lrc2ii
title: 2020-09-10_010.raw
DOI: 10.5281/zenodo.8031914
title: Patterns of genetic variation reflect multiple introductions and pre-admixture sources of common ragweed (Ambrosia artemisiifolia) in China

description: Informations about the locations and genetic diversity of <em>Ambrosia artemisiifolia</em> populations in published paper "Patterns of genetic variation reflect multiple introductions and pre-admixture sources of common ragweed (Ambrosia artemisiifolia) in China".
DOI: 10.57745/ezrgzy
title: DARKREF_2020-09-10_010.hdr
DOI: 10.57745/cpx2de
title: DARKREF_2020-09-10_010.raw
DOI: 10.57745/a51z5p
title: WHITEREF_2020-09-10_010.hdr
DOI: 10.57745/hmn3sf
title: WHITEREF_2020-09-10_010.raw
DOI: 10.57745/3utvew
title: 2020-09-10_010.xml