dataesr/scientific-paragraphs-categorization huggingface dataset:
Modeling has shown that crop yield increases in Europe of 17% for wheat and 24% for potato, and even more for total biomass, can be achieved with only 20% increases in some basic photosynthetic parameters  (Harbinson & Yin, 2022). In the future, more complete crop models that incorporate a wider range of mechanisms and processes and recent innovations could enable better predictions about how the most promising approaches for increasing photosynthesis will function at crop scale. To further explore the data collected and the traits identified in the database (WP1), and to facilitate the development of the roadmap (WP5), an exhaustive analysis of the literature has been carried out in WP4 ('International cooperation') and an in-depth inventory of the scientific productivity in distinct plant research fields has been made.
These analyses made use of 24,000 publications retrieved from the WOS database (2015-2019) and provided an exhaustive view of the main actors (scientists and institutions) involved in these fields of research in Europe. A total of 15 focus group coordinators were then identified from these main institutions. To strengthen interactions between Europe's research institutions and between hubs of plant research in Europe, the coordinator of each focus group was asked to identify and contact experts with relevant scientific expertise in their respective fields. Each of these focus groups carefully evaluated a different subtopic of crop yield, sustainability and nutritional quality to add any information needed to reinforce, broaden and detail the current identified options for future crop F I G U R E 3 Outcome of the CropBooster-P project scenario analysis.
ACKNOWLEDGMENTS This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No. 817690. The authors thank  Aleksandra Malyska  (PlantETP) and  Axel Sommer  (SOMMERRUST; https://www. sommerrust. com/en/about) for their support and guidance on Scenario Analysis carried out under CropBooster-P,  Sven Warris  ( WUR ) for developing the user interface for the CropBooster-P database, and  Dr. Annick Bleys  ( VIB-UGent ) for her comments and input to the manuscript.
Data collection and analysis procedures A female psychologist (CV) dedicated to the study called the 5 participants in 2018, 6 months after ICU discharge. She has a researcher status and did not know the participants before the study. Interviews were audio-recorded and transcribed. We chose the Interpretative Phenomenological Analysis (IPA) technique to explore their content  [22, 23]. This method was designed to understand the complex system of meanings attached to a unique, subjective and eminently intimate phenomenon  [22] [23] [24]. According to IPA recommendations, a small sample (1-8) is required in order to highlight their intimate meaning making process related to this experience  [24]. There was no pre-established script, only one question "Can you talk to me about your ICU experience?" was asked.
Then, she assessed the connections between subthemes, and identified the major themes, which are described in the results section. Lastly, she produced an interpretative account, highlighting and analyzing the experience through experiential themes and by illustrating the discourse. Then, the main themes and the interpretative account were reviewed by CV and LF (clinical psychologist and expert in IPA). Throughout this study, we pay close attention to meet the scientific rigor criteria established for qualitative analysis  [25, 26]. We followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist  [27]. To simplify the data analysis process, the data were anonymized only after data analysis was completed.
Acknowledgments We would like to thank  Davide Bufalini ,  Soumangsu Chakraborty ,  Pierre Heidmann ,  Anthony Houppe ,  Bogdan Ganchev ,  Monica Guica ,  Nicolas Kovensky , and  David Turton  for interesting discussions. This work is supported in part by the  ANR  grant  Black-dS-String   ANR-16-CE31-0004-01 , by the  John Templeton Foundation  grant  61149 , by the  ERC   Grants 787320-QBH Structure and 772408-Stringlandscape , and by the  DOE  grant  DE-SC0011687.
This approach is similar to that previously described in the literature  [22]. The second approach updates the registration correction iteratively as a part of the FP reconstruction. The registration process involves iteratively: 1) reconstructing the sample based on the available data, 2) predicting the data based on the current iterate, 3) registering the images to the predicted data. We evaluate these two methods by simulating a FP data set with random, known registration errors and perform reconstructions using the different registration approaches. Figure  4  shows that the first registration approach fails on the simulated data, and that the second, iterative, approach is able to achieve a reconstruction with an FRC correlation coefficient almost as high as if the registration were carried out using the known error values.
Experimental method To demonstrate and evaluate the FP implementation on DFXM instrumentation, we carried out two experiments: First, in the transmission geometry using a commercial resolution calibration sample (JIMA RT-RC 04, Japan); and second, in the Bragg (i. e. dark-field) modality, using an epitaxial film of BiFeO 3 containing isolated dislocations and sub-micrometer domains. The DFXM measurement sampled the (002) pseudocubic reflection in a symmetric (i. e. specular) Bragg geometry. In both cases, data sets were recorded both with and without the decoherer. The experiments were performed at the hard x-ray microscope at beamline ID06  [36]  at the European Synchrotron (ESRF) at 17 keV with a relative bandwidth of ≈1. 4 • 10 -4. The energy bandwidth and source size for the experiment were therefore typical of those expected for hard x-ray microscopy experiments.
Conclusion and outlook The reconstructed amplitude and phase maps from the BiFeO 3 film demonstrate that FP may be used for the coherent reconstruction of DFXM data sets. The resolution increase beyond that of diffraction limit set by the NA of the objective lens is marginal. However, we are able to recover the complex amplitude of the scattered wave front and the aperture function. This ability to recover phase offers two key advantages over classical DFXM; the quantitative phase is critical when characterizing samples where contrast originates from strain-free defects. Furthermore, access to the quantitative phase allows us to correct for de-focus, which is readily seen in the current implementation of DFXM. At the same time, the phase-and amplitude maps of the objective aperture can be used to characterize x-ray lenses during their use as objective lenses for full field microscopy.
Less deformed (but still extended) crystals, however, give rise to dynamical diffraction patterns, where there is no simple connection between the scattered wave front and the lattice strains -a problem shared by any other x-ray diffraction technique. In this work we only measured the projection of the scattering function through the direction of the scattered beam. However, a natural extension of this technique would be to attempt to resolve this depth dimension. This could potentially be achieved by "rocking" the sample through a small angle (as in BP and BCDI) and thus adding another dimension to the data set. In BPP, where the sample is not rocked, the depth dimension is resolved by back projecting different limited projections through the thickness of the sample. However, this approach is not compatible with the extended illumination used in this work, as we can only measure the projection through the full thickness.
| The mountain invasion research network The Mountain Invasion Research Network (MIREN, www. mount ainin vasio ns. org) was founded in 2005 as a first global effort to apply the known principles from plant invasion ecology in mountainous environments  (Kueffer et al. , 2008 (Kueffer et al. , , 2009)). From the start, the main goal has been to link detailed observations at the local-scale from a broad range of mountain regions, to come to global conclusions on common patterns (and divergence from them) regarding mountain plant biodiversity  (Kueffer et al. , 2014). The core of the network has been the underlying road survey protocol, which allowed flexible application all across the world, yet a standardized baseline of data collection that could be maintained for a long time. While research topics and techniques have diverged throughout the years, the core business of MIREN remains to increase the spatial and temporal extent of the road survey.
g. , soil characteristics,  Hengl et al. , 2017)  or topographic variables  (Amatulli et al. , 2018)  or through optional add-on studies (see section below). Each taxon should be classified as native or non-native to that region by the participant using local floras and databases. As a general rule, plant species introduced into the country or mountain range after AD 1500 are considered as non-native, although regional deviations are welcome if properly justified. For noteworthy records (e. g. , first records or new high/low elevation records of native or non-native species), specimens should be collected outside of the plots (when possible) and placed in a herbarium to facilitate identification and to inform local floras  (Walsh & McDougall, 2018).
| Repeated monitoring To understand long-term dynamics of redistributions of native and non-native plant species, all regions should strive for regular long-term monitoring, preferably with a periodicity of five years (and ideally with at least partial overlap in observers, to reduce observer bias). To facilitate monitoring, all plots should be permanently marked in the field, for instance with magnets or metal tags that can be relocated with a metal detector or colored sticks or plastic seal security tags in remote areas where their removal is unlikely. In addition, precise sub-meter GPS coordinates should be taken at least once. Photographs should also be taken of each transect to visualize changes over time, document data collection, and facilitate relocation of plots. Surveys and resurveys should always be done at peak biomass or flowering to minimize the risk of missing species with early or late phenology.
, 2021) , and survey plots have also been used to assess the distribution of plant pathogens (Phytophthora species) in Australia  (Khaliq, 2019). Once the participants begin contributing data to the MIREN global road survey database, they can suggest add-on studies to apply across all regions that go beyond the existing scope of the survey protocol-as long as it is based on a standardized protocol that can be implemented fast, simply, and at low cost by collaborators. To maximize participation and to discuss new proposals, data quality, and complementarity, ideas for add-on projects should be developed together with the MIREN steering committee.
| Data submission and accessibility The MIREN survey design is a robust and standardized field survey protocol that provides data contributors among others an opportunity to include regional data in research that addresses globally scaled ecological questions. To be included in MIREN's global road survey database, regional data must be submitted to the MIREN data managers using a standard data format. An overview of how the database is structured and which metadata are stored is provided in Supporting Information S2. While in the first survey in 2007, only non-native species were monitored, we now only accept data submissions from new regions that surveyed all vascular plant species, both native and non-native, as partial species pools drastically limit the amount of research questions that can be answered with the data.
| RE SULTS The standardized protocol for recording plant species communities along mountain roads has been thoroughly tested in the field on all continents except Antarctica (Figure  4 ). (Figure  4 ). The global database currently includes circa 2700 plots and >100,000 observations of >5,000 vascular plant species. One of the most striking findings of the global MIREN surveys to date has been to document the importance of roads in facilitating mountain invasions. Specifically, we found that non-native species richness in roadsides decreases with increasing elevation, but generally peaks in the lower third of the elevation gradient  (Alexander et al. , 2011). In a review including among others the MIREN road survey data, we found that only 2. 1% of the non-native species found in alpine areas can be considered as true alpine or mountain plants based on their temperature affinity  (Alexander et al.
, 2012; Ratier Backes et al. , 2021). In doing so, the protocol remains simple, for example with plots close to roads remaining easy to reach, and thus applicable in many mountain regions even when fieldwork sites need to be easily accessible. This provides another strength of the protocol: it can be repeated in many places, so that general patterns at the global scale can be detected through multi-region replication  (Alexander et al. , 2011; Lembrechts et al. , 2017; Seipel et al. , 2012). In summary, data collected within the MIREN survey framework can be useful for regional and global studies in a large variety of fields, ranging from classical biogeography and community ecology to ecological modeling and global change research.
| Opportunities Many drivers of global change act rapidly and interactively, and intensify over time, so assessing their impact on global biodiversity urgently requires comparable data collected on a truly global scale. The MIREN road survey protocol has already demonstrated its potential to explain crucial patterns in native and non-native species redistributions along mountain roads, but there are a range of further applications that can be explored. For example, due to its simplicity the protocol can readily be implemented in many more mountain ranges and regions. Increasing the number of participating regions, all with their unique combination of climatic conditions and anthropogenic pressures, would further increase the potential to draw general conclusions about the interacting effects of climate change and roads as anthropogenic disturbance on mountain plant communities  (Guo et al.
, 2018). This is particularly important for regions currently under-represented by the existing MIREN survey sites (Figure  4 ), such as Africa, Eastern Asia, and central America, regions for which long-term biodiversity data are often lacking  (Maestre & Eisenhauer, 2019). Despite these spatial gaps, MIREN has already more than doubled in size on its road to becoming a global-scale network since it was first established in eight regions. New participants would thus be able to place their region into a much larger spatio-temporal picture and, as time passes, get an increasingly strong grasp of how species distributions are changing dynamically, regionally, and across the world. With its potential to answer important local questions, and feed into the growing multi-region database, we hope that the MIREN road survey protocol will become the protocol of choice for those interested in native and non-native plant biodiversity dynamics   (McDougall, Alexander, et al.
, 2011). For example, it can inform policy makers on some of the impacts of urban expansion and new infrastructure projects in mountains, as well as identify new nonnative species before they become problematic. The protocol can also provide essential biodiversity variables for global monitoring efforts  (Jetz et al. , 2019)   (Randin et al. , 2020). The survey approach can similarly be expanded by adapting it for use along other linear introduction pathways for non-native species, such as rivers, railroads or hiking trails (see 4. 2 above), or by connecting it with other standardized global biodiversity surveys and assessments, such as GLORIA  (Pauli et al. , 2015) , sPlot  (Bruelheide et al. , 2019) , the Global Inventory of Floras and Traits (GIFT;  Weigelt et al. , 2020) , the Global Naturalized Alien Flora (GloNAF) database  (van Kleunen et al.
, 2015) , and the BioTIME database  (Dornelas et al. , 2018). The connection to other datasets can be done either via the exact geographic location submitted with the MIREN plot-level data, or via the species names which have been standardized with major taxonomic backbones, such as World Flora Online (http://www. world flora online. org). Finally, the protocol has already shown to have great potential for teaching, for instance by training undergraduate and graduate students in vegetation sampling, while also having relevance for local policy and management, for example as demonstration sites (Figure  5 ).
Within each of the three plots at all 20 sample sites along the three roads, observers record all vascular plant species (including both native and non-native species) and visually estimate vegetation cover (eight percentage cover classes with 1 = <0. 1%, 2 = 0. 1-1%, 3 = 2-5%, 4 = 6-10%, 5 = 11-25%, 6 = 26-50%, 7 = 51-75%, 8 = 76-100%) and record abundance (number of individuals in three classes; 1 = 1-10 individuals (or ramets), 2 = 11-100 individuals, 3 = >100 individuals) of each species. The detailed sampling protocol is provided in Supporting Information S1 and can also be downloaded from the MIREN website (www. mount ainin vasio ns. org). Taxa should be identified to species level using up-to-date local floras. Before being included in the global database, submitted regional species lists undergo taxonomic harmonization to detect synonyms for the same species in different regions, and to correct spelling problems.
, 2012), in a sample plot on a volcanic gravel slope in the Argentine Andes; (e) non-native Verbascum thapsus on a roadside in the highly invaded lowlands of the Andes in central Chile; (f) Trifolium pratense in northern Norway, where the species is rapidly moving uphill along mountain roadsides et al. , 2020) and "WorldFlora" (Kindt, 2020). First, species names are matched with World Flora Online (http://www. world flora online. org), and if not found there, they are searched via the additional databases included in the Taxonomic Names Resolution Service (Boyle et al. , 2013). All changes of species names are transmitted to the submitting region for verification or correction, before the dataset enters the global database (Figure2).
ous professionals, field assistants, and students have contributed to the collection of these data. SH and ARB gratefully acknowledge the support of iDiv funded by the German Research Foundation(DFG-  FZT 118, 202548816). JJL received a postdoctoral fellowship from the Research Foundation Flanders (FWO, grant nr. 12P1819N). The work from JJL, JC, and IN is supported by a research grant from the FWO (grant nr. G018919N). Fieldwork in the Northern Scandes is achieved using INTERACT Transnational Access funding. LAC and AP acknowledge support from FONDECYT 1171005, 1180205, CONICYT PIA CCTE AFB170008 and Grant ANID PIA/BASAL FB210006. JMA received funding from the European Commission Horizon 2020 research and innovation program under grant agreement 678841. VA was supported by the Universidad Nacional de Cuyo (SIIP 2019 UNCUYO).
MV was supported by a research grant from the BiodivClim Call 2019 (grant nr. TACR SS70010001) and together with JM by long-term research development project RVO 67985939 from the Czech Academy of Sciences. We also thank the Fondation Herbette, University of Lausanne, for financial support to JMA for the workshop "Distributed ecological observatories and long-term monitoring of mountain biodiversity" held in September 2019 that lead up to this paper. Finally, we are grateful to the editor and two anonymous reviewers for providing helpful comments to improve the manuscript. Open Access funding enabled and organized by ProjektDEAL.
DATA AVA I L A B I L I T Y S TAT E M E N T MIREN road survey data from 2007 to 2015 are available on Zenodo (Seipel, Tim, Haider, Sylvia, & MIREN consortium (2021). MIREN survey of plant species in mountains (v0. 1) [Data set]. Zenodo. https:// doi. org/10. 5281/zenodo. 5529072) and through GBIF (https://www. gbif. org/publi sher/76388 ab6-61ca-439a-ab09-e1fe7 3eb224a).
To date, all survey data collected before 2016 are available through Zenodo (https://doi. org/10. 5281/zenodo. 5529072). Any researcher can also request the full MIREN database from MIREN data managers for global analyses. The structure of the database, with its plot-level table with accurate coordinates, and easy linkable species information, allows smooth integration into larger global integrative projects (e. g. , data is currently inte-.
High-throughput sequencing and other omics technologies have shone a light on the large inter-individual variation in microbial community composition and metabolic processes. Methodological bias adds to this complexity, further complicating the development of therapeutic strategies such as dietary intervention or fecal microbiota transfer (FMT). Data integration, achieved through the systematic collection and analysis of available, high-resolution data and through the development of standard operating procedures (SOPs) for sample collection, processing, and storage, and for data analysis and sharing, strengthens translational biomedical research. The main objective of the INTIMIC knowledge platform is to promote studies on microbiome, nutrition, and health in order to understand the impact of the microbiota on human health.
Approach A catalogue of relevant data for the field is being produced for the purpose of data sharing. Many datasets from studies connecting the microbiota, nutrition, and health exist at the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL) HDHL-INTIMIC knowledge platform (IKP) partner institutes, within the other JPI HDHL INTIMIC consortia and other places within Europe and beyond. More and more journals require deposition of data as a prerequisite for publication: several databases are available, but a unified system for metadata and annotation is often lacking. Further, European data protection regulations need to be fulfilled when storing human personalized data, which requires, among others, informed consent for storing the data for specific purposes, disclosure about storage place and use of data, and the ability to withdraw consent and to delete personal data.
These requirements are usually not fulfilled when personalized human data from ongoing studies would be stored in currently existing public data repositories. The central scientific and technical concept of this JPI HDHL INTIMIC platform is to:   [16]. This will result in FAIR data sharing for microbiome-nutrition-health data. We involve other relevant communities (e. g. , ELIXIR, BBMRI, metabolomics society, NFDI4Health) to prevent repetitions and to make it possible to link to other FAIR initiatives. For instance, this project is one of the use cases for the Food and Nutrition community in ELIXIR. We are also performing a number of case studies that will highlight the potential of using shared datasets. This facilitates the interest in data sharing by highlighting that sharing normally leads to more scientific output (knowledge, publications, and visibility).
Case studies can also help identify solutions for proper attribution of credits when merging shared data deposited in a database. This aspect is of special relevance when omics datasets are used, most of which are largely unexploited by authors in their published studies. Data sharing is also closely connected with the definition of standardized microbiome guidelines, reference microbiomes, and strategies and tools for microbiome research. Finally, all activities are connected to training, dissemination, and networking (see Figure  1 ). Key in the development on the platform is the definition of a reference microbiome which is done in WP3. Important for the use case is the development of standards, which is done in WP2 and WP4. In order to perform, the use case's rich (meta) data should be collected in a interoperable way; this is done in WP1.