dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2023) , no integrative databases store legumes QTL data in a unified format. Therefore, we plan to facilitate the integration of the content from existing legume databases. Other knowledge graph to understand the FIGURE Fetch of expression levels (in TPM) of MtFTa and its orthologs in di erent tissues of the shoot system, in OrthoLegKB. Normalized expression level of FTa and its orthologs in RNA-seq samples (top panel) were queried in Cypher (middle panel), and several properties were returned in CSV format (bottom panel). The expression of FTa genes was queried at the "Sample" level using the "expr" variable. The tissue annotations from the "Condition" nodes connected to these "Samples" were filtered to have only "Condition" nodes connected to the "PO" node "shoot system" or any of its more specific child terms.
Note that in the table, the order of the rows was rearranged to show the diversity of annotations under the "shoot system" term. The number of records returned in the output table and the average response time of the query are shown in light gray below the table. The full table is available as Supplementary Table  S. role of genes are already available. The KnetMiner software was created to analyse genome-scale knowledge graphs, with a recent support for the Cypher graph query language  (Hassani-Pak et al. , 2021). This platform allows to build gene networks based on semantics and information primarily extracted from the literature, including genetic data, phenotypes associated to SNPs or biological pathways. It was recently applied to wheat, generating networks for the TT2 gene involved in pre-harvest sprouting  (Hassani-Pak et al.
, 2021). In the specific case of legumes, the AgroLD triplestore is to our knowledge the only phenomics agronomycentered database aiming at an integrative storage of biological information in the form of a knowledge graph  (Venkatesan et al. , 2018; Larmande and Todorov, 2021). Since Neo4j can handle RDF import and export, thanks to the neosemantics plugin, data exchange between OrthoLegKB and AgroLD could be considered to take advantage of both technologies. This goal is further supported by the ongoing development of the RDFstar extension which could support properties on edges of the graph  (Abuoda et al. , 2022). This would bridge the gap between LPG and RDF technologies for improved interoperability  (Hartig, 2014). While the SPARQL RDF query language is common to all triplestores, Cypher from Neo4j is only used by the proprietary.
However, the open-source GraphQL initiative known as GQL is seen as a potential technology agnostic standardization query language for graph databases  (Donkers et al. , 2020). We envisage that the legume research community will participate in the data collection and provide feedback on OrthoLegKB for regular improvement. Ortho_KB o ered an opportunity to develop a valuable tool for translational research in legumes, OrthoLegKB We decided to select legume species to showcase how the Ortho_KB framework can serve translational research. OrthoLegKB is currently centered on few members mostly diploid cool-season legumes as the identification of orthologs is more straightforward than in polyploid species. Still, having a highquality assembly is crucial for synteny detection and therefore true orthologs identification.
sativum genome assembly from the Zw6 accession  (Yang et al. , 2022). A new assembly of the Cameor genome is expected soon and should improve the assembly and annotation of this region. Furthermore, supplementing OrthoLegKB with transcriptomic data will provide stronger support when searching for FT orthologous genes, by comparing their expression profiles. Fortunately, more legume genomes, have been lately assembled in high-quality using highthroughput chromosome conformation capture sequencing or long-read technologies, namely chickpea  (Garg et al. , 2022)  or common vetch  (Xi et al. , 2022) , which might reveal to be novel sources of data for OrthoLegKB. Thus, the graph will encompass more connected datasets, including information on abiotic and biotic stress response and be useful to a larger part of the legume research community.
, 2016). While the scope of Ortho_KB was limited to plants for annotation reasons, its concept could be adapted for the benefit of other communities. For example, the wealth of draft-assembled diploid genomes profiting the Chelicerates community was recently exploited to highlight the conservation of chemosensory genes through comparative genomics  (Vizueta et al. , 2018). As more qualitative assemblies and associated -omics data are generated across plant and animal groups, we can only anticipate that the need for integrative multispecies databases will increase and Ortho_KB can contribute in this regard.
FIGURESchematic representation of the pipelines used to build Ortho_KB, a NoSQL graph database framework for translational research. (A) The structural pipeline computing homology between genes and synteny across chromosomal regions from selected annotated genomes. All processes included in the pipeline, except those producing the mandatory final outputs, are represented by dark red circles. Processes producing the mandatory final outputs are represented by green circles. (B) General overview of the steps leading to the construction of an instance of Ortho_KB. Datasets that can be managed include RNA-seq data, QTL and functional annotations. As an example, we develop the treatment of an RNA-seq dataset from public or private origin. Alongside a regular extraction of counts, metadata of the samples must be annotated using ontologies to describe in particular the tissue of origin (Plant Ontology) and the experimental conditions to which the sample was subjected to (Plant Experimental Conditions Ontology).
FIGUREMacro-and micro-synteny of the chromosomal regions harboring FTa or its orthologs in M. truncatula, P. sativum, L. culinaris and V. faba. (A) Macro-synteny at the chromosome level. FTa and its orthologs are represented by gray dots on syntenic chromosome sections depicted as lines. Synteny between chromosomes is represented by ribbons. The positions of the two orthologs from P. sativum are shown even though they do not belong to any syntenic block in the database. (B) Micro-synteny of the FTa loci. Genes are represented with arrows indicating the orientation of the open reading frames. Ribbons connect orthologous gene pairs. The IDs of FTa orthologous genes are in orange and ribbons connecting them are filled in dark green. Since the four species have high genome size heterogeneity and variable intergenic sizes, intergenic regions were removed from the plot.
Data availability statement The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found below in the article/Supplementary material. OrthoLegKB with its user-guide is available for legume translational research at http://ortholegkb. versailles. inrae. fr/ browser/. The functional pipeline for synteny is available at: https://forgemia. inra. fr/geapsi/pipeline/specifics_syntenymcscanx. The pipeline to create the translational database is available at: https://forgemia. inra. fr/geapsi/pipeline/specifics_ortho_kb. All scripts used to create the figures presented, including microsynteny from OrthoLegKB data, are available at: https://forgemia. inra. fr/ geapsi/ecp-paper/ortholegkb_data.
Case 1. One population, low %CV To test the simplest case, we have simulated autocorrelation curves of a monodisperse sample (defined by a %CV = 10 %). It has been reported that using the weighted harmonic mean (WHM) for estimating particle size would be a better alternative than the weighted mean (WM) because it matches the average size from the cumulants analysis for low PdI samples  (Farkas & Kramar, 2021). For datasets containing non-negative values, the harmonic mean is lower or equal to the geometric mean, and the geometric mean is lower or equal to the arithmetic mean  (Bullen, 2003). In our analysis, we have compared the usage of WHM or the highest peak value from the distribution (mode) for obtaining R h. The fitted distributions are available for download in Raynals and users can choose their preferred R h reporting method.
Comparison of Raynals to other DLS analysis software Raynals can be compared with other DLS software such as CONTIN  (Provencher, 1982) , SEDFIT  (Brown et al. , 2007)  and the commercial software DYNAMICS (www. wyatt. com/products/software/dynamics. html) (Table  2 ). While the last three programs require installation under a certain operating system, Raynals is available online and can be executed from a browser, which facilitates access to potential users independent of the performance of their computer. One of the strong points of CONTIN is the availability of the code as an open source. However, it is written in Fortran, which limits the possibility of users to adapt it for their personal purposes (e. g. , changing the regularisation matrix). The code for fitting DLS data from Raynals is available on GitHub (https://github.
Acknowledgments We acknowledge technical support by the  Sample Preparation and Characterisation (SPC) facility at EMBL Hamburg, Germany  and the  "Molecular Biophysics'' facility  (french acronym:  Plate Forme de Biophysique MoleculaIre, PFBMI)  at  Institut Pasteur, Paris, France. We thank the users of the  SPC  and  PFBMI  for constructive feedback. OB is funded by the  ARISE fellowship  (EMBL and the  Marie Skłodowska-Curie Actions ). GD-B is funded by the  EMBL International Ph. D. programme. OB thanks the  EU -funded  MOlecular-Scale Biophysics Research Infrastructure (MOSBRI ) consortium  for his  TNA visit  (project No  MOSBRI-2021-50 ).
Extracted lipids were graphitized directly with Automated Graphitization Equipment AGE-3 (IonPlus AG). The AMS measurement was performed in a 240 KV Single Stage Accelerator Mass Spectrometer at the Vilnius Radiocarbon Laboratory. The background of measurements is approximately 2. 45 × 10-3 fM (fraction of modern carbon) using phthalic anhydride. As reference materials were used the IAEA-C2, IAEA-C3, IAEA-C7, IAEA-C9, NIST OXII, SIRI K (carbonate) standards. The 14 C/ 12 C ratio is measured with an accuracy better than 0. 3% (±30 yr or better; Vilnius Radiocarbon 2022). Calibration and combination of 14 C dates was undertaken using the program OxCal v4. 4 (Bronk Ramsey 2009) and the IntCal20 calibration curve  (Reimer et al. 2020). A chronostratigraphic Bayesian model with an outlier analysis (Supplement 1.
ACKNOWLEDGMENTS Research was funded by the project  GAČR GA20-19542S  (Tracing the Neolithic transition through the first pottery),  Grant Agency of Masaryk University , project  APVV-14-0550  (Natura et cultura. The coevolution of mankind and nature between 6th and 2nd millennium BC in the area north of the middle Danube studied on the basis of archaeological and environmental sources) and  VEGA 1/0477/11  (Paleoecological reconstruction of the northern part of the  Pannonian Plain). We want to express our gratitude to  Juraj Lauko , who allowed us to conduct the field activities and collect archaeological material on his property. We want to thank  Jozef Bátora  for his continuous support during the fieldwork campaigns and initial 14 C analysis of pottery material. We thank to  Jack Dury  for inspirational comments that improved the draft of thestudy.
We will search eight databases and grey literature and present a broad synthesis of the available evidence regarding design, implementation and evaluation of LHS in a multilevel perspective. We will follow the latest Preferred Reporting Items for Systematic Review and Meta-Analysis statement for conducting and reporting a systematic review. Two reviewers will independently screen the titles and abstracts against the eligibility criteria followed by full-text screening of potentially relevant articles for final inclusion decision. Conflicts will be resolved with a senior author. We will include published primary studies that use qualitative, quantitative or mixed methods. The assessment of risk of bias will be made using the Mixed-Methods Appraisal Tool. Ethics and dissemination This systematic review is exempt from ethics approval.
STRENGTHS AND LIMITATIONS OF THIS STUDY ⇒ The systematic review will examine eight databases and grey literature, leading to a broad synthesis of the available evidence regarding design, implementation and evaluation of national learning health systems, which addresses an important gap in the literature. ⇒ The review will include primary studies without language and time restrictions, allowing the maximum inclusion of studies published in the field. ⇒ The protocol and the review will follow the latest statements from the Preferred Reporting Items for Systematic review and Meta-Analysis. ⇒ The independence of the researchers in the selection, analysis and summary of the studies as well as the fact that one of the authors will carry out all the steps, will ensure rigour and consistency and strengthen the findings of the review.
Moreover, this approach recognises that implementation challenges cannot be seen as a localised problem for individual adopting organisations, but should be seen as global intervention with effects at the level of health systems,  48 49  supporting the importance of developing a system thinking approach to the integration of knowledge and evidence. 47  This is why, it is timely to define an implementation model of national LHS integrating a multilevel approach that are beneficial to all health system stakeholders, managers, professionals and are conceptualised with and for patients and that clearly responds to how to implement the concepts associated with the model. A preliminary search for existing systematic reviews on the topic has been conducted in Cochrane Database, JBI Database of Systematic Reviews and Implementation Reports and PROSPERO.
LHS have already been the subject of few reviews, but they have been limited in scope, consisting of an inventory,  29  a proposed conceptual framework,  28  a focus limited to a specific context such as primary care,  32  or a particular aspect such as ethics,  50  clinical analytics,  51  the effects of LHS  52  or community relationship. 53  To the best of our knowledge, only two literature reviews aimed to clarify the use of the concept and its operationalisation. 38 54  However, all two were limited to the organisational level without addressing the regional and national level necessary to integrate services in a cross-sectoral approach. Similarly, no distinction is made between the operational and organisational levels. Finally, while one of the two does not present any methodological part,  54  the other used only two bibliographic databases (PubMed and Embase), focused only on conceptual models and not on empirical implementation examples and retained only 17 articles.
Once the concept has been defined, it enables an in-depth analysis of the use of the concept, the associated mechanisms and interventions, their implementation and the results obtained. This approach uses eight steps to: (1) select concept; (2) determine the purposes of the use; (3) identify all uses of the concept; (4) determine the defining attributes; (5) identify model cases of applications; (6) identify additional cases; (7)  identify antecedents as prerequisites and consequences as outcomes and (  8 ) define empirical referents. The first phase will be to carry out a content analysis of the literature, including grey literature, in order to respond to steps 1 to 4 of the conceptual analysis. The data collected will be used to map the definitions present in the literature and the uses and attributes of the concept.
Information sources We developed two search strategies, in collaboration with a Health Sciences Librarian specialising in systematic reviews of the healthcare literature. First, we developed a dedicated search strategy, for the content analysis, aimed at capturing the articles and grey literature involved in defining the concept, its uses and attributes. An initial search strategy was therefore launched in Google scholar. Second, for the systematic review, we develop a search strategy to identify published peer-reviewed studies. We performed initial pilot searches in MEDLINE and CINAHL in order to assess the relevance of the reports retrieved on the basis of their titles and abstracts. This allowed us to refine our search strategies to ensure the capture of more relevant information. A comprehensive search strategy was launched on 15 November 2022, in the eight following databases: Medline (OVID), Embase ( Embase.
Search strategy For the first phase, the content analysis, a dedicated search strategy was launched with no restrictions on languages or dates. Limited to the first hundred references, the search returns 400 results (see online supplemental table 2). For the second step, the systematic review, different search strings have been designed and applied to each of the databases. The complete search strategy was tested by the Health Sciences Librarian. No study period restrictions were applied to the search, nor were there any restrictions based on language or geography. As our team is made up of several researchers who speak several languages (at least English, French, German, Spanish and Italian), for all other languages, the full text will be analysed by a translator specialising in scientific literature.
The complete search strategy across the eight databases is provided (see online supplemental table  3 ). The search returned 4935 records that have been imported into the Covidence software, an Internet-based software that facilitates collaboration among reviewers during the study selection process, consisting of 2085 unique studies after automatic removal of duplicates. In addition, we will search the reference lists of included studies or relevant journals or authors identified by the search, as well as those of any literature reviews that will be excluded from the selection process.
Data extraction Descriptive numerical summary analysis follows the systematic review guideline  60  and will systematically extract the followed items: Reference (APA style), Title, First Author country, Year, Case country, Study design, Study settings, LHS name/institution, Population/ Sample size, Study parameters and level of analyses Open access (operational, regional and national level) and Definition of LHS retained. Data for both qualitative and quantitative analysis will be extracted by two independent authors using a customised form. Again, for consistency, one author will review all included studies. The data extracted will follow the concept analysis guideline  59  and systematically extract the followed items: Related concepts, Concept uses and objectives, Prerequisites or Inputs, Patients role, Professionals roles, Structural and organisational context of the system and organisations, Modes of operation, Coordination structures, Information management, Outputs, Performance dimensions, Performance indicators and Results obtained (qualitative and quantitative outcomes).
Data synthesis We will use a concept analysis framework  59  as a data analysis framework. In addition, all information will be synthesised by level of the implementation (operational, organisational, regional and national level). We will use a convergent synthesis design  68  to synthesise qualitative, quantitative and mixed-method results. Thus, using a thematic synthesis procedure, we will synthesise the objectives and prerequisites for the implementation of the LHS concept. We will then summarise and describe methods and approaches designed to implement the concept focusing, at a minimum, on the patient role, the professionals' roles, the structural and organisational context of the system and organisations, the modes of operation, the coordination structures and the information management.
The τ decays are simulated by TAUOLA  [15]  and their FSR by PHOTOS  [16]. We use KKMC to simulate μ þ μ -ðγÞ and q q production; PYTHIA  [17]  for the fragmentation of the q q pair; BABAYAGA@NLO  [18] [19] [20] [21] [22]  for e þ e -→ e þ e -ðγÞ events; and AAFH  [23] [24] [25]  and TREPS  [26]  for the production of nonradiative final states l þ l -l þ l - and e þ e -h þ h -. There is no generator to simulate the e þ e -→ e þ e -nh process. The Belle II analysis software  [27, 28]  uses the GEANT4  [29]  package to simulate the response of the detector to the passage of the particles.
4 MeV. A systematic uncertainty of 0. 25 MeV is assigned to the measurement of σ E Ã B based on simulation. Assuming that the individual systematic effects are independent, we calculate an alternative value of M min for each effect separately and fit the resulting distribution to obtain an alternative value for the τ mass. By combining the resulting variations of the τ mass in quadrature, we obtain the systematic uncertainty of 0. 07 MeV=c 2. The computation of M min relies on the knowledge of the boost vector of the center-of-mass frame. The boost vector is measured in experimental data using a dimuon sample. Its uncertainty is found to contribute negligibly to the systematic uncertainty on the τ mass.
ACKNOWLEDGMENTS This work, based on data collected using the Belle II detector, which was built and commissioned prior to March 2019, was supported by  Science Committee of the Republic of Armenia  Grant No. 20TTCG-1C010 ;  Australian Research Council  and research Grants No. DP200101792 , No. DP210101900 , No. DP210102831 , No. DE220100462 , No. LE210100098 , and No. LE230100085 ;  Austrian Federal Ministry of Education, Science and Research, Austrian Science Fund  No. P 31361-N36  and No. J4625-N , and  Horizon 2020 ERC Starting  Grant No. 947006  " InterLeptons ";  Natural Sciences and Engineering Research Council of Canada, Compute Canada  and  CANARIE ;  National Key R&D Program of China  under Contract No. 2022YFA1601903 ,  National Natural Science Foundation of China  and research Grants No.
PHY-1913789  and No. PHY-2111604 , and the  U. S. Department of Energy  and research Grants No. DE-AC06-76RLO1830 , No. DE-SC0007983 , No. DE-SC0009824 , No. DE-SC0009973 , No. DE-SC0010007 , No. DE-SC0010073 , No. DE-SC0010118 , No. DE-SC0010504 , No. DE-SC0011784 , No. DE-SC0012704 , No. DE-SC0019230 , No. DE-SC0021274 , No. DE-SC0022350 , and No. DE-SC0023470 ; and the  Vietnam Academy of Science and Technology (VAST)  under Grant No. DL0000. 05/21-23. These acknowledgements are not to be interpreted as an endorsement of any statement made by any of our institutes, funding agencies, governments, or their representatives. We thank the  SuperKEKB team  for delivering high-luminosity collisions; the  KEK cryogenics group  for the efficient operation of the detector solenoid magnet; the KEK computer group and the  NII  for on-site computing support and SINET6 network support; and the raw-data centers at  BNL ,  DESY ,  GridKa ,  IN2P3 ,  INFN , and the  University of Victoria  for off-site computing support.
Our concept involved three steps: (1) Past growing seasons are individually categorized by two scenario factors that are known to influence seed demand: seasonal rainfall (dry/medium/wet tercile), and whether the season was preceded by a national election (yes/no). This results in six possible seasonal scenarios. (2) Data on historic seed demand is used to estimate the statistical association between scenario factors and demand for individual varieties, using linear regression models. The fitted regression coefficients are then used to predict average seed demand patterns under each scenario. (3) The probability of each scenario in the next season is assessed using a seasonal climate forecast and the electoral calendar. An overall demand forecast is then generated by weighting the different scenario-specific average demand patterns by the respective forecasted scenario probabilities.