dataesr/scientific-paragraphs-categorization huggingface dataset:
Naming and annotating tDRs To calculate the Sprinzl 13 positions and secondary structure regions of tDRs, they are structurally aligned to the reference database of tRNAs. Nucleotide differences including substitutions, insertions, and deletions between tDRs and the matching source tRNAs are determined from the alignments. Using the source tRNA identity information, the starting and ending Sprinzl  13  positions where the tDR overlaps the source tRNA, and nucleotide differences if they exist, tDRnamer then generates the standardized name for each individual tDR (Fig. 1a ). If the tDR is derived from multiple source tRNAs, synonyms following the same naming convention are created based on all the identified source tRNAs. In addition to outputting a tDR sequence file in FASTA format, a tab-delimited file containing the tDR names, annotations, and sequences is generated, as well as a file containing the alignments of tDRs with source tRNAs in Stockholm 18 format (Supplementary Table  4 ).
Furthermore, the tDRnamer web server version uses NAVIEW  19  to superimpose tDR sequence onto the secondary structure image of its source tRNA for visualization and file download in PNG and postscript formats (Fig. 2 , Supplementary Table  4 ). tDR secondary structure based on minimum free energy is computed using RNAFold  20  with images rendered by Forna  21  and VARNA 22 (Supplementary Fig. 2 , Supplementary Table  4 ).
Grouping tDRs by source tRNAs If tDRs identified in the same tDRnamer analysis run are derived from the same source tRNAs, they are grouped together to visualize all tDR products processed from the same parent molecule(s). tDRs that are derived from mature tRNAs are grouped separately from those derived from pre-tRNAs. Alignment of tDRs with their corresponding source tRNAs is based on both primary sequence and secondary structure. Numeric IDs are assigned to the source tRNAs belonging to each group in sequential order of the tRNA transcript name or GtRNAdb gene symbol. tDRs in the alignments are marked with the numeric IDs corresponding to their source tRNA(s). A text file is generated as output which contains the tDR groups, each with the member tDR list, the source tRNAs, the tRNA isotype, nucleotide substitutions (mismatches) if they exist, and the tDR alignments in Stockholm 18 format (Supplementary Table  4 ).
Data availability The tDRnamer web server is available at http://trna. ucsc. edu/tDRnamer/. Standalone software can be obtained from GitHub at https://github. com/UCSC-LoweLab/tDRnamer and Docker image at https://hub. docker. com/r/ucsclowelab/tdrnamer. Example data can be downloaded from http://trna. ucsc. edu/tDRnamer/data/examples/. Pre-built reference databases for model organisms are available at http://trna. ucsc. edu/tDRnamer/docs/refdb/. The complete set of.
Natural-history cohort The data we used for the simulations came from a prospective natural-history cohort of 23 subjects from 5 centers in Brazil, France, Germany, the Netherlands, and the United Kingdom  [24]. Subjects included in the cohort had a documented MPS IIIA diagnosis, were 2 to 9 years old (median age 4 years old), had no other serious co-morbidity, and were medically stable without potential disease-modifying medicinal product. Data were collected at 6 onsite visits at baseline (assessment day 0), and 6, 12, 18 and 24 months (± 14 days) from baseline. The baseline assessment included a neurocognitive and adaptive behavior assessment, San lippo speci c behavioral and disability assessment  [17]  and quality-of-life questionnaires. Changes from baseline were assessed in terms of cognitive function and adaptive behavior using Vineland Adaptive Behavior Scales, Second Edition (VABS-II) and Bayley Scales of Infant Development, Third Edition (BSID-III), in terms of sleep disturbances using a subject's sleep habits questionnaire and a sleep diary, and in terms of the subject's and parents' quality-of-life using Infant Toddler quality of life questionnaire (ITQoL) and semi-structured interviews of parents.
Simulations The simulations considered a multi-domain analysis consisting of ve outcomes related to the expressive language, daily living skills, and gross-motor, sleep and pain domains. These outcomes were selected because they all represent key domains which parents/caregivers have reported as important symptoms of MPS IIIA to be targeted with future therapies  [15]. We used mixed-effects modeling, including both linear and quadratic trends over time, for the data generation in order to fully capture the natural evolution of the disease. The parameters for these models were estimated using the available information from the natural-history cohort. A joint covariance matrix for all ve models was also estimated based on the natural-history data. De ning such a joint structure for variability allows the random effects for a same patient to be correlated across the outcomes.
This shift was based on expert opinion about meaningful magnitudes of change (treatment effects) on the various outcomes considered. Table  1  displays the observed rates of change in score over time for each of the ve domains in the control group, and the corresponding slopes in the experimental treatment group. Note that the rates of change may depend on the subject's age, at least for some domains such as expressive language and daily living skills. Given that the limited data we had to conduct simulations, we ignored this dependency. We assumed the same variance-covariance structure for both groups (treated group and natural-history cohort), which could also be subject to criticism. We generated 10,000 datasets with a sample size of 46 observations, equally divided into two groups. Each of these datasets was analyzed using either non-prioritized (with equal weights across outcomes) or prioritized GPC, with the following list of priorities de ned following the expert opinions and feedback from the patients' families on what matters the most: (1) Expressive language, (2) Daily living skills, (3) Gross motor, (4) Sleep and (  5 ) Pain (this list of priorities will be referred to henceforth as 12345).
Caregivers feedback also stressed that it is di cult to prioritize these outcomes as the impact and expectations will be different depending on where the child is situated in their disease trajectory. We compared the two groups based on the rates of change in scores of the ve domains over time. Furthermore, we conducted analyses over a range of thresholds of clinical relevance, expressed in terms of the fractions of standard deviations of the distributions of the rates of change for the corresponding outcomes. The p-values for the analyses were based on the permutation distribution  [3]. The power of each test is re ected by the empirical rate of rejection of the null hypothesis of no treatment effect among the 10,000 simulated datasets. We performed sensitivity analyses considering several other possible lists of priorities for the prioritized GPC in order to evaluate possible changes in test results with changing order of priorities.
Introduction Ocean circulation drives most of the global heat and mass transport, greatly impacting climate, biodiversity and human activities. In the open ocean, most of the kinetic energy is contained in mesoscale (50-500 km) structures  (Ferrari and Wunsch, 2009). In particular, mesoscale eddies can transport heat and nutrients through very long distances and time  (Fu et al. , 2010). Satellite altimetry is the only observing system capable of documenting mesoscale ocean geostrophic currents with consistent temporal and spatial resolution. By merging several altimetric datasets into gridded Sea Surface Height (SSH) maps, geostrophic velocities can be derived  (Ducet et al. , 2000). Today, one of the commonly used gridded SSH maps are the DUACS products, distributed by the Copernicus Marine Environment Monitoring Service (CMEMS).
Validation with SST data This section compares the positions of fronts and eddies diagnosed from our reconstructions with those diagnosed from high resolution SST observations. To do so, we use the Fronts Derived from Remote Sensing SST Observations by SEVIRI over Agulhas Region dataset created within the ESA World Ocean Circulation (WOC) project (DOI: 10. 12770/6c776c43-425b-4d29-9934-0822696f15d8) as ground-truth. For each point P i =   lon i lat i   of the detected frontal structures, we compute the flow crossing the fronts using either BFN-QG or DUACS geostrophic currents:  where F low[P i ] = v[P i ] • δ i ∥v [P i ]∥∥δ i ∥ = |cos (∠(v[P i ], δ i ))| δ i =   lat i+1 -lat i-1 -(lon i+1 -lon i-1 )cos(lat i )   is the normal vector of the front at point P i. The values of the flow range from 0 to 1.
The performances are assessed by comparing the mapped products, from BFN-QG and from the operational reference DUACS, with independent datasets. We have carried out diagnostics on mapped SLA (using independent altimetric data) and mapped velocity (using independent drifters and high resolution SST data). The performances of the BFN-QG are not uniform for all temporal and spatial scales. The method fails to improve the mapping of large mesoscale structures (>300km) in comparison with DUACS. This is corroborated by the poor performances of the BFN-QG-derived currents to estimate the Lagrangian transport for lead times larger than 10 days. Future works should investigate the implementation of a multi-scale nudging whose parameters vary with the space and time scales of the dynamics  (Stauffer and Seaman, 1994).
Code and data availability. The along-track SLA (level 3), DUACS gridded SLA and geostrophic currents (level 4) products used in this study are freely available on the CMEMS portal (http://marine. copernicus. eu/). The BFN-QG geostrophic currents and the SST frontal structures are freely available on the WOC portal (https://www. worldoceancirculation. org/). The code of the BFN-QG is available on the Github repository MASSH (https://github. com/leguillf/MASSH).
https://doi. org/10. 5194/egusphere-2023-509 Preprint. Discussion started: 4 April 2023 c Author(s) 2023. CC BY 4. 0 License. The BFN-QG improves the mapping of short, energetic mesoscale structures both in space and time in comparison with the DUACS system. The BFN-QG is able to reconstruct finer coherent structures that are in phase with observations from independent datasets. The spatial effective resolution is improved by a factor of 20% compared to DUACS. The prediction of Lagrangian transport by the BFN-QG-derived geostrophic currents is improved for for lead times up to 10 days in comparison with the DUACS-derived geostrophic currents.
In this technical note, we introduce a web-based application, the soil knowledge library (KLIB), for the compilation and classification of scientific publications on soil process research according to the specific site conditions and experimental boundary conditions. The tool was developed based on the understanding that experimental findings in soil science are highly dependent on soil type, land use and climate. The KLIB, therefore, goes beyond other available digital libraries by providing meta-data on the site conditions and experimental settings for each publication. A number of visualization tools have been developed to explore the contents of the literature database very efficiently in order to support and facilitate the literature search efforts of the users. The KLIB is designed as a collaborative effort to encourage soil scientists to participate by entering their own studies and extending the existing database.
Input of metadata The bibliographic data of each publication including the abstracts are automatically extracted from the PDF file of a publication by just dropping the icon of the file into the KLIB web application. In some cases where this is not possible, e. g. , if the PDF document of a publication was created by scanning a paper document into a bit-map format, these data can be entered manually or extracted from a corresponding BibTeX file. For legal reasons, the original PDF file is not stored and made available in the KLIB. Afterward, the required metadata on site characteristics, sampling design, and key findings can be entered with the help of an intuitive user interface (Fig. 1 ). For experimental research articles, which are the main focus of the KLIB, a number of different categories of metadata can be provided (if available in the publication): a) Type of study: Is it an experimental study, a model application, a methodological study, or a meta-analysis? And in the case of an experiment: Does the study refer to individual sites or multiple sites? Is it a field or a lab experiment? What is the considered time scale? b) Soil & Site: What are the soil types (with different classification schemes for selection: WRB, USDA, FAO, German) and their texture? Which depths were investigated? Additional soil properties such as pH, organic carbon content, and bulk density can be provided optionally.
Exploring the database All process-oriented publications included in the library are supplemented by metadata of different categories: Investigated soil properties, soil management, and soil and site conditions. Besides a classical search for keywords, authors, and date of publication, the KLIB offers the functionality to search its contents based on interactive graphical tools that are designed to visualize complex interrelations within and among the different categories. Five different visualization tools are provided. They are described in the following section, together with typical application examples.
The latter is a "parent" category in the keyword tree containing the four "child nodes" ridge tillage, minimum tillage, zero tillage, and strip tillage which are visualized as well. In this case, there were no publications in the database dealing with bulk density and strip tillage, hence, this point is missing in the visualized network. The publication metadata can be accessed by a click on the grey circles connecting pairwise attributes. The size of the circles corresponds to the number of publications that are provided as a list (Fig. 2D ).
Technical implementation The KLIB is a web-based application that follows modern standards and techniques. For the frontend we are using the framework Angular as a foundation for all continuing functions (ang). The backend is built on node. js with Express. js to handle all the data structure and the connection to the database. While being visible and searchable for all users, all entered papers are connected to a unique login of each person, which gives editing rights only to authors and those who have been given access. The process of entering bibliographic data is supported by the option to extract the DOI from a PDF and retrieve the data from the Crossref-API. This allows us to get all information in seconds without the need to enter it manually. To provide safety, we are using newest standards and techniques like jsonwebtokens for authenticating to the KLIB and on backend site MongoDB to store the data secured.
The entire database is backed up several times a day, so that, in the event of a problem, all data entered can be restored to the most recent version possible. MongoDB provides the speed to prepare the data for complex visualizations in an acceptable amount of time. The JSON format is commonly used to store data and send it through several API calls to the user on the frontend side. We implemented complex algorithms to generate the information for the visualizations and build the different networks that can be explored and adjusted. The presentation itself is handled by the D3. js library, which provides powerful tools to generate smooth networks. The implementation of canvas as the rendering structure is essential for handling big datasets and many points in a network, the conventionally used svg is too slow for our application and causes performance problems on many devices.
Acknowledgements We would like to thank the many colleagues who gave us a lot of advice on the design of the user interface and functionality during the development of KLIB. This project is funded by the German Federal Ministry of  Education and Research (BMBF)  in the framework of the funding measure "Soil as a Sustainable Resource for the Bioeconomy -BonaRes", project "BonaRes (Module B): BonaRes Centre for Soil Research".
Patients were excluded if they had missing data on RCT participation, died during index hospitalization, or were lost to follow-up. One centre exhibited extreme patterns regarding HF hospitalization (HFH) outcomes and was excluded. Data on first HFH and all-cause mortality were obtained over 12-month follow-up. Guideline-recommended medical treatment included renin-angiotensin system inhibitors, beta-blockers, and mineralocorticoid receptor antagonists. To identify independent predictors of RCT participation, a generalized linear mixed-effects model with a binomial distribution was performed using RCT participation as the dependent variable. The country was included as a random effect in the model. The independent variables included were inpatient setting, age per strata (<60, 60-69, 70-79, ≥80 years), female sex, home situation, body mass index ≥25 kg/m 2 , blood pressure ≥100 mmHg, heart rate ≥70 b.
To identify the association between participation in an RCT and outcomes, univariable and multivariable Cox regression analyses were performed with the same independent variables as above and country as a strata variable. Patients were censored at 12-month follow-up visit if they had not yet experienced an event or on the date of death in the analyses assessing first HFH as outcome. Missing data were imputed with multiple imputation (R-package mice; 10 imputed datasets),  7  including the same variables as the regression models. For patients with missing information on the date of hospitalization, time to hospitalization was imputed with half the time to last follow-up. A two-sided P-value of <0. 05 was considered statistically significant. Analyses were performed using R version 4. 2. 1. 8 f 25,621 patients in the registry, 7,374 met exclusion criteria and 18,247 patients were analysed.
Acknowledgements EORP  Oversight Committee ,  Registry Executive  and  Steering Committees  of the  EURObservational Research Programme (EORP). Data collection was conducted by the EORP department from the  ESC  by  Emanuela Fiorucci  as Project Officer,  Gérard Gracia  and  Maryna Andarala  as Data Managers. Statistical analyses were performed by  Lina Benson. Overall activities were coordinated and supervised by  Dr Aldo P. Maggioni  (EORP Scientific Coordinator).
e. R t ≤ O(10η), where R t is the agents distance at the time t and 10η is the order of the correlation scale of the velocity gradients  48, 49  ) the fluid velocity experienced by the searcher is approximately u t ðX ðaÞ t Þ ' u t ðX t Þ þ ∇u t R t , where ∇ u t is the flow gradient evaluated at the target position. As a result, the optimization problem depends only on the separation vector R t and on the entire history of the velocity gradients along the trajectory of the searching agent. We will be enforcing this approximation, which allows us to store Lagrangian trajectories and their accompanying velocity gradient to create a database that can be used to compute the optimal control (see "Methods"). Heuristic control strategies. As a term of comparison, we will consider several heuristic controls that neither require knowledge of the future evolution of the trajectory (required for the computation of the optimal control) nor the memory of its past.
Methods Navier-Stokes simulations for Lagrangian tracers. The target trajectories follow the tracer dynamics _ X t ¼ u t ðX t Þ ; ð3Þ where u is a solution of the Navier-Stokes equations  45, 46   ∂ t u þ u Á ∇u ¼ À∇p þ νΔu þ F ∇ Á u ¼ 0 & ; ð4Þ for an incompressible fluid of viscosity ν. The flow is driven to a non-equilibrium statistically steady state by a homogeneous and isotropic forcing, F, obtained via a second-order Ornstein-Uhlenbeck process  59. For the direct numerical simulations (DNS) we used a standard pseudo-spectral solver fully dealiased with the two-third rule. Details on the simulation can be found in  60, 61. Parameters of the DNS used in this work are given in Table  1. The database of Lagrangian trajectories used in this study is dumped each 15dt ≃ τ η /10. Optimal control equations.
Data availability The Lagrangian target trajectories (including positions, velocities, accelerations and fluid gradients along each particle) used in this work are available for download in the Smart-TURB portal http://smart-turb. roma2. infn. it, under the TURB-Lagr repository  60. TURB-Lagr is a new open database of 3d turbulent Lagrangian trajectories, obtained by Direct Numerical Simulations (DNS) of the Navier-Stokes equations with homogeneous and isotropic forcing. Details on how to download and read the database are also given in the portal. The analysis that support the findings of this study are available from the corresponding author upon reasonable request.
Search methodology Data from different Medline search engines, including PubMed (https:// pubmed. ncbi. nlm. nih. gov/), Google Scholar (https:// schol ar. google. com/), and Science Direct (https:// www. scien cedir ect. com/), were examine to find relevant publications that had been published between January 2013 and December 2022. The papers that are suggested for reporting systematic reviews and meta-analyses. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline (http:// www. prisma-state ment. org/) was followed to obtain the data, and the pertinent medical subject heading (MeSH) word was also used to retrieve the data provided below. For e. g. , "Pathogen transfer from different food sources along with antimicrobial resistance", "AMR Spreading from Different pathogens along with One Health", "Multi drug resistance", "Drug susceptibility tests of different pathogens isolated from different food sources", "AMR assessment method", "MDR", "Egypt", "United Kingdom" "UK" "One Health" "surveillance" are the keywords as well as the MeSH terms that were used.
The search queries were applied using the Fig. 1  Interconnections of complex AMR amongst several health sectors. A schematic diagram for the complex transmission pathways of AMR genes and drug-resistant bacteria between human, livestock and environmental reservoirs. The dashed lines represent potential transmission pathways  [15]. (Reference?) Boolean operators "AND" and "OR. " Fig. 2  depicts the search strategy for the PubMed/MEDLINE database in accordance with PRISMA guidelines.
Data extraction and quality assessment To establish a baseline, full versions of allegedly relevant articles were obtained. The author names, publication year, geography, the total number of isolates, and total samples from each article were collected independently and recorded on a spreadsheet (Microsoft Excel ® 2013) for pre-testing prior to full extraction. Text, tables, and figures were used to extract the data. The results were examined, and a pie chart was used to show the AMR data and the cited articles using Mendeley (version 1. 19. 8).
Identification of studies The initial search strategy approach yielded 506 citations from electronic databases. After 225 duplicates were deleted, 281 records were evaluated for title and abstract. Out of these, 281 full-text papers were assessed, and in the initial systematic search, 133 records were excluded; 79 due to improper screening of data, 15 for no relevant interventions in animals to reduce antibiotics use, 37 were due to being review articles on MDR and 2 due to full access which could not be achieved. Of these 148 full-text articles, 98 were again excluded, of which 54 were excluded because they did not address AMR in the results, 32 were excluded due to irreverent outcomes, and 12 were excluded due to missing essential statistics. This systematic review and meta-analysis included 50 articles in total.