dataesr/scientific-paragraphs-categorization huggingface dataset:
The process-based high resolution ORCHIDEE simulation and the TRENDY v7 ensemble, with the so-called "S3 simulation" (see the TRENDY simulation protocol, LeQuéré et al. 2018), include the impact of CO2 590 fertilization, climate change and land use change for forest, grassland and cropland sectors; they do not explicitly treat the wetland, settlement and other land sectors as in the NGHGIs. They account for the evolution of living and dead biomass as well as SOC for all categories while for NGHGIs it is not mandatory for all subcategories (i. e. , dead biomass). Finally, there is significant uncertainty associated to the DGVMs' fluxes both from i) the forcing data, including datasets of land-use changes and the coverage of different land 595 use change practices, ii) model parameters, and iii) structural uncertainty in models (i.
contrary to the NGHGI estimates, which are relatively stable. Thus, the initially reasonable agreement between the two datasets(2000)(2001)(2002)(2003)(2004)(2005) becomes a difference well outside the uncertainty range of the NGHGI in 2017 (290 Tg C difference between GCP and NGHGI, with an NGHGI uncertainty of only 30 Tg C). Between 2011 and 2018, GCP (-241 Tg C mean) (red bars) shows, as well as large inter-annual variability, an increase in the CO2 sink. The strongest sink between inversions (mean -381 Tg C) is reported by CarboScopeReg which, similar to EUROCOM, also shows 695 high fluctuations. This fluctuation partly reflects the fact that all other inversions are results from ensembles of inversion systems each with different inter-annual variations, while CSR is a single inversion system (just a small ensemble with differing prior error structure and different set of atmospheric station data used).
The first edition of the Emissions Database for Global Atmospheric Research was published in 1995. The dataset now includes almost all sources of fossil CO2 emissions, is updated annually, and reports data for 1970 to n-1. Estimates are provided by sector. Emissions are estimated fully based on statistical data from 1970 till 2015, while for the years beyond 2015 a Fast Track (FT) approach is applied based on BP data and other proxies to extrapolate.
Data availability All raw data files reported in this work which were used for calculations and figures are available for public download at https://doi. org/10. 5281/zenodo. 4288883 (Petrescu et al. , 2020). The data we submitted are reachable with one click (without the need for entering login and password), with a second click to download the data, consistent 1260 with the two click access principle for data published in ESSD (Carlson and Oda, 2018). The data and the DOI number are subject to future updates and only refers to this version of the paper. Data Discussions Preprint. Discussion started: 18 December 2020 c Author(s) 2020. CC BY 4. 0 License.
( 2019) and BU inventories from EDGAR v5. 0, CEDS, and PRIMAP. EDGAR v5. 0 reports the same sources as the UNFCCC, but CEDS reports emissions from Energy (1A+1B), IPPU and Waste up to 2014, and PRIMAP only for Energy and IPPU. All BU datasets show a good match for overlapping sectors, Energy and IPPU (Fig. 1, sum of sub-280 sectors 1A, 1B).
690 contrary to the NGHGI estimates, which are relatively stable. Thus, the initially reasonable agreement between the two datasets(2000)(2001)(2002)(2003)(2004)(2005) becomes a difference well outside the uncertainty range of the NGHGI in 2017 (290 Tg C difference between GCP and NGHGI, with an NGHGI uncertainty of only 30 Tg C). Between 2011 and 2018, GCP (-241 Tg C mean) (red bars) shows, as well as large inter-annual variability, an increase in the CO2 sink. The strongest sink between inversions (mean -381 Tg C) is reported by CarboScopeReg which, similar to EUROCOM, also shows 695 high fluctuations. This fluctuation partly reflects the fact that all other inversions are results from ensembles of inversion systems each with different inter-annual variations, while CSR is a single inversion system (just a small ensemble with differing prior error structure and different set of atmospheric station data used).
on CO2 emissions 335 and removals from the LULUCF sector (excluding energy-related emissions, but including emissions from land use processes such as responses to environmental drivers (i. e. , climate change and CO2 fertilization) on managed land 12. change, emissions from disturbances on managed land, and the natural sink on managed land), expanding the scope of that work by adding TD estimates from inverse model ensembles and additional BU models run with higher- resolution meteorological forcing data over the EU27+UK. 340 Land CO2 fluxes result from CO2 emissions/removals from one land type converted to another (e. g. , forests cleared for croplands), as well as emissions/removals from land occupied by terrestrial ecosystems (depending on the dataset, this may be from managed or unmanaged land, which complicates comparisons with NGHGIs).
Discussion started: 18 December 2020 c Author(s) 2020. CC BY 4. 0 License. Discussion started: 18 December 2020 c Author(s) 2020. CC BY 4. 0 License. Open Access Open Access Earth System Science Data Earth System Science Data IAP RAS Tier3 top-down river pCO2 data from Tier3 top-down Bayesian analysis in the CO and NOx coverage, or spatial Detailed gridded data can be Pierre Regnier fast-track fCO2 inversion CarboScopeReg 0. 1° x 0. 1° resolution maps of annual averages of fossil CO2 anthropogenic emissions from EDGAR v4. 3. 2 Assimilation of satellite atmospheric concentration data: total column CO from IASI, and tropospheric column NO2 from OMI GloRiCh (Hartmann et al. , regional 2014), lake pCO2 database inversions of CO from Sobek et al. (2005); and NOx river channel slope and emissions using EMEP/CEIP as width calculated from GLOBE-DEM (GLOBE-Tier 3 top-down approach, prior knowledge Task-Team et al.
The rift valley in the central part of the Endeavour segment hosts five long-lived vent fields underlain by the existence of intra-crustal melt lenses at ∼2. 6 km below the seafloor  22. Four ridge-parallel wide-angle seismic profiles (RFR96-01, -03, -05, and -08) were acquired aboard R/V Sonne in 1996 (Fig. 1b ). Along each of the profiles, six ocean-bottom hydrophones (OBHs) were deployed at 4 km interval. The details of the acquisition parameters are given in the "Methods" section. The OBH data contain strong crustal arrivals (Pg) and reflections from the Mohorovičić discontinuity-Moho (PmP). In addition, we observe wide-angle reflections that seem to originate in the mantle at a source-receiver offset range of 7-20 km, ~1-2 s after Pg arrivals (Fig. 2  and Supplementary Fig. 1 ). We apply an advanced imaging technique to these wide-angle reflection data.
6 ). To verify that the migrated images are consistent with reflection arrivals, we also present the post-stack time migrated image (Supplementary Fig. 7 ). The similarities between the pre-stack and poststack migrated images confirm that they are real images originating from the mantle. The depth obtained using travel time modelling of these reflections is consistent with the migrated images (Supplementary Fig. 8 ). Uncertainties in the depth of these reflections are primarily due to the uncertainties in the mantle velocity structure. Supplementary Fig. 8  indicates that the upper reflection lies at 11 ± 0. 5 km and the lower reflection at 14. 5 ± 0. 5 km. To assess uncertainty in the velocity model, we performed a pre-stack depth migration of OBH data along profile RFR96-01 using three different velocity models: (1) lower limit of the tomography velocity model, (2) the tomographic velocity model and (3) upper limit of the tomographic velocity model.
Methods Seismic data acquisition. Twenty-four ocean-bottom hydrophones (OBH) were deployed along four ridge-parallel profiles. Along each profile, six OBHs were deployed at a 4-km interval over 20-km distance (Fig. 1 ). OBH525 did not provide any data along profile RER96-05, and OBH534 was offline of profile RER96-08, and hence was not used in the data analyses. The shots were fired along ~50-km long profiles, providing maximum offsets of ∼35 km (Fig. 1b ). Except for profile RFR96-05, the data were acquired using a single BOLT Inc. airgun of 32 l, fired at 140 bar, towed at 15-m water depth. The dominant frequency of the source was 6 Hz. For profile RFR96-05, a PS100 Sleeve gun (60 l) was used instead. The shot spacing was 40 s (equivalent to ∼90 m). OBH 501-506 were deployed along profile RFR96-01, OBH 511-516 along profile 96-03, OBH 521-526 along profile 96-05 and OBH 531-536 along profile 96-08.
Acknowledgements We thank  Heinrich Villinger  and  Fares Mehouachi  for helpful discussions and valuable suggestions that substantially improved the paper. We are grateful to  Heinrich Villinger , chief scientist of the R/V Sonne cruise SO111 in 1996. We would like to thank  Tim Stern  and two anonymous reviewers for their constructive reviews, which improved the paper significantly. Funding from the  Germany Science Foundation  ( DFG grant   GR1964/2-1 ) and  German Federal Government (BMBF  grant  03G0111A ) is acknowledged. The research leading to these results has received funding from the  European Research Council  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013)/ ERC Advance Grant agreement n°339442_TransAtlanticILAB. The work is IPGP contribution number  4160.
Data availability The following figures are based on the raw data used in this study: (1) Figures  2, 3  and 5 in the main text. (2) Supplementary Figs. 2, 3, 4, 5 and 7. The raw ocean-bottom seismometer data are available on the German PANGAEA database. The processed data shown in Fig. 3, Supplementary Figs. 5, 7 and 8 the German PANGAEA database.
, 2019) , identifying novel molecular controls of autophagy  (Marshall et al. , 2019) , engineering a synthetic switch to control stomatal opening  (Papanatsiou et al. , 2019) , and defining the first complete blueprint for an immunity pan-NLRome (Van de  Weyer et al. , 2019). This breadth of topics demonstrates that research in Arabidopsis continues to be influential from the perspective of both plant biology and biology more generally. In many cases, the qualities of Arabidopsis that attracted researchers over the past half century (compact size, short generation time, ease of transformation, genomic, and informatic resources) still enable breakthroughs to be made apace. We turn now to efforts to coordinate such resources, and highlight newly generated large datasets that will, in turn, enable further discoveries.
| Proteomics The Proteomics subcommittee reports that over the past year a significant development in Arabidopsis research came from a study by  Mergner et al. (2020)  that quantified the total number of detected Arabidopsis proteins (more than 18,000), their dynamic expression range (up to 6-fold changes in abundance) and their phosphorylation state (43,000 sites across the proteome). In addition,  McWhite et al. (2019)  generated a complementary database of stable protein complex organization from 13 plant species, including Arabidopsis. These datasets are exciting resources that are available for further analysis and are being integrated into existing community portals such as Proteomics DB (https://www. prote omics db. org) and ATHENA (http://athena. prote omics. wzw. tum. de:5002/master_arabi dopsi sshin y/).
| Epigenetics and epigenomics Arabidopsis has been the workhorse for elucidating mechanistic underpinnings of numerous epigenetic phenomena. These studies have both discovered and emphasized the importance of small RNAs, histone modifications, and DNA methylation during epigenome establishment and maintenance, in detection of self from non-self, and in responding to various environmental challenges. This research is aided by a new community-facing Arabidopsis RNA-seq database, ARS, which contains gene expression data from more than 20,000 publicly available RNA-seq libraries (http://ipf. sustc. edu. cn/pub/ athrn a/). This resource will dovetail with a soon-to-be released resource of whole genome sodium bisulfite sequencing datasets.
| Bioinformatics Over the past year the Arabidopsis bioinformatics community had to overcome the unfortunate loss of funding for the Araport resource. Fortunately, other community projects have stepped up to maintain some of its important features. This includes the hosting of the JBrowse tool at TAIR (https://bit. ly/2Qhb5xC) and the Thalemine instance hosted by the BAR (https://bar. utoro nto. ca/thale mine). The Bioinformatics subcommittee highlights two outstanding datasets that focus on different aspects of the plant-pathogen response  (Cao et al. , 2019; Laflamme et al. , 2020). They also highlight a newly released "eFP-Seq Browser" that enhances exploration of RNA-seq through the visualization of read map profiles and summary gene expression levels across two large compendia  (Sullivan et al.
| Metabolomics The Arabidopsis metabolome is the best studied of all plant species and is used as an exemplar for studies in crop species. The MASC metabolomics subcommittee continues to support the integration of genomic data from natural populations with ecologically relevant metabolomic data that can reveal how a plant has ultimately adapted to environmental stresses. The subcommittee makes the case that as metabolomic platforms become more cost-effective, and as sensitive as NGS (Next Generation Sequencing) platforms, that metabolomics be considered an equal partner to sister techniques in order to develop a "full picture of a plant. ".
| Natural variation and comparative genomics During the period of the current decadal roadmap the interrogation of natural variation has been an area of clear success. The hugely successful 1001 Genomes project has led to the development of software tools for further analysis of these publicly available datasets. These including the ViVa: Visualizing Variation  (Hamm et al. , 2019)  and the AraPheno/AraGWAS tools  (Togninalli et al. , 2020). However, there remains plenty of Arabidopsis geographic variation that has not yet been analyzed. This is highlighted in the MASC country report from Turkey that looks at the distribution of the accessions available for order from the Nottingham Arabidopsis Stock Centre (NASC, Figure  2 ). This suggests that there are many accessions growing across diverse geographic locations (including Turkey) that are currently underrepresented in the easily accessible available germplasm.
| Systems and synthetic biology During 2019 there has been significant activity in the research area of the MASC Systems and Synthetic Biology subcommittee, particularly with the development of BAR-integrated software tool to analyse protein-protein and protein-DNA interaction networks (http://bar. utoro nto. ca/inter actio ns2/) and in the TuxNet software that analyses RNA-seq data to infer gene regulatory networks (https://omict ools. com/tuxne t-tool). The subcommittee has been active in the organization of external meetings with the inaugural International Plant Systems Biology Meeting taking place in France in September 2018, with a follow-up event in Venice postponed until 2021 (https://meeti ngs. embo. org/event/ 20-plant -systems). Despite reporting a downward trend over the past decade, the ABRC distributes annually almost twice as many seed stocks as NASC (190K versus 100K).
| Plant immunity Despite losing government funding over 5 years ago, TAIR continues its excellent biocuration services via an innovative and successful subscription model  (Reiser et al. , 2016). TAIR has expanded its operations to include collaborations with both PhyloGenes (www. that facilitates the publication of brief, novel findings, negative and/ or reproduced results that may lack a broader scientific narrative. Each week TAIR loads 50-90 papers with the term "Arabidopsis" in the title or abstract into their curation queue. This includes a steady number of papers that report on new functions for previously characterized genes and an increase in the number of papers that describe high-throughput experiments and contain large datasets. For a variety of reasons, curating from some papers can be challenging so TAIR have produced a document to advise researchers how to make the details of their research more "findable" (https://conf.
arabi dopsis. org/displ ay/COM/Resou rces). Fortunately, the implementation of these recommendations will be facilitated by a closely linked international community and will undoubtedly be a topic discussed for inclusion within the next roadmap. The BAR resource continues to be a central hub for researchers to interrogate and visualize their expression data. In addition to its expansion to include data from many other plant species, the BAR is far more than just an "eFP Browser. " The BAR website includes access to a broad set of genomic tools and widgets that have a focus on the analysis of Arabidopsis.
However, there remain significant gaps in our knowledge, including a lack of understanding of the complex linkages between available 'omic data sets or the more simple knowledge of how plants sense many of their required nutrients. Improvements in this area are needed to build a fully predictive model that is accurate across time. Fortunately, there is an acknowledgment that bioinformatics training and the development of digital infrastructures are key for the future in depth analysis of Arabidopsis-derived datasets. The loss of funding for Araport was disappointing for the community and, although its key activities have been picked up by TAIR, the BAR and the Genome Context Viewer, efforts are needed to ensure that community resources have longevity. This requires the integration of international infrastructures, particularly between Western and Eastern hemispheres.
In some areas international cooperation is excellent, such as in the coordination of conference planning, yet elsewhere it can be improved. These challenges include, but are not limited to, implementation of effective mechanisms of data sharing, cultural and language differences, and availability of global funding initiatives. With this update, MASC calls on all Arabidopsis researchers to consider areas for inclusion in the next decadal roadmap. We expect participation from long-time community leaders, such as the North American Arabidopsis Steering Committee (NAASC), and collaborators from the United States, Germany, and Japan. We also expect that there will be contributions toward decadal priorities from a broader group of MASC members, especially those representing countries with significant and increasing Arabidopsis research, such as China or India.
| P OSS IB LE ARE A S FOR IN CLUS I ON IN THE NE X T DEC ADAL ROADMAP • What are the strategies that might be used to build globally sustainable digital infrastructures to support the integration of multiomic datasets? • How can both the data and metadata from complex multi-omic experiments be collated and shared for the benefit of the wider community in order to feed into translational pipelines? • How can we integrate mechanistic and quantitative genetic insights to enable plant acclimation to vastly different climates, within a very short time period? • How can the community build internationally cohesive and diverse collaborative teams of scientists to answer important questions in plant science? Over the next year, these ideas will be developed and will coalesce during discussions at a MASC-supported discussion session at ICAR2021 in Seattle.
datasets. The BAR has obtained funding from Genome Canada that will allow the development of a custom "eFP" view in ePlant for a researcher's own RNA-seq data as well as the initiation of several new ePlants. The International Plant Phenotyping community provides excellent links between Arabidopsis research and that conducted in other plant species. The MASC annual report includes brief updates from the International Plant Phenotyping Network (IPPN), European Plant Phenotyping Network (EPPN) and European Infrastructure for Plant Phenotyping (EMPHASIS). An important general feature of these networks is that they host regular calls for applications from researchers to access phenotyping infrastructures where they do not have them available at their home institutions. The European Infrastructure for Plant Phenotyping (EMPHASIS) project is arguably the most interesting development in this area.
The Present Study This article reports results of facial EMG responses collected as part of a larger study that included other classes of dependent variables (EEG, autonomous nervous system measures, and voice analyses) as well as an exploratory examination of potential regulation influences by the presence of another person. As it would be impossible to report this massive data set in a single article, several reports on different response measures are currently in preparation. Past research in this area has often put the emphasis on the measurement of significant increases in activation at specific time points as a result of a particular appraisal manipulation. In some cases, combinations of different appraisal checks have been manipulated (e. g. ,  Aue & Scherer, 2011). Importantly, in this study, we separately compare pleasant vs.
IP Stimuli Visual Stimuli We chose human faces since they have the advantage that basic features (eyes, nose, mouth, etc. ) are the same across all visual stimuli. In addition, they are equally familiar to all participants. Thus, candidate stimuli for pilot study 1 (facial portraits of female and male persons between 18 and 40 years old) were retrieved from the Face Research database (DeBruine & Jones, retrieved 2015, Face research lab, University of Glasgow Institute of Neuroscience and Psychology), the Dallas Face database  (Minear & Park, 2004)  and the Radboud Faces database  (Langner et al. , 2010). To increase the number of pleasant faces (in total, we had 236 portraits of different faces) and to amplify the difference between pleasant and unpleasant faces, we used the beautification tool in ArcSoft PhotoStudio6  (ArcSoft, Inc.
Auditory Stimuli We chose voices to correspond maximally to the face stimuli as part of human individuality. In addition, like faces, they are equally familiar to all participants. There is evidence that voices vary substantially in pleasantness. Unpleasant voices are often raspy, grating, husky, or shrill. In addition, there are distinctive voice parameters that are strongly related to the perceived pleasantness of a voice, such as Harmonic-to-noise ratio (HNR, r =. 66**), jitter (r = -. 65**), or shimmer (r = -. 70**; see  Beermann, Gentsch, Wu, Trznadel & Scherer, 2015). The auditory stimuli (258 voice samples from speakers between 20 and 45 years old) were obtained from the Saarbruecken voice database which contains voices of healthy persons and persons with massive voice pathologies  (Pützer & Barry, n.
Procedure To assess the exclusion criteria (see above), participants answered a background questionnaire online before they came to the laboratory. In addition to the relevant questions concerning their health status for the potential exclusion, participants were asked to complete a set of disposition assessment scales. 1 These data were not used in the current analysis. Participants were told that they were taking part in an experiment on social perception in which central and peripheral bodily reactions are recorded (not reported here). The experimental task consisted of indicating whether the person to be judged, whose face, voice, or preferred odor were experimentally presented, was likely to be more introverted or more extraverted. They all participated in two laboratory sessions one week apart.