dataesr/scientific-paragraphs-categorization huggingface dataset:
It is therefore impossible from our study to determine whether earlier diagnosis and improved healthcare have had an influence on patients living longer. In addition, the patient population provided by clinicians/POs did not include the more severely affected patients with early disease onset, which would have caused an early childhood death. Therefore, we are not able to determine if the causes of death found in our population would also be prevalent within the more severely affected patients. A limitation of this study was the small sample size and highlights the difficulty of retrieving records of deceased patients with a rare disease. Some deceased patients had been lost to follow up (e. g. , death had occurred in another hospital). Two POs informed us that they were obliged to delete details of deceased members from their database due to information privacy policies.
Acknowledgements The authors are grateful to the  Society for Mucopolysaccharide Diseases, Amersham, UK , for providing UK data for the study. The authors would also like to thank those who supplied data that did not meet the inclusion criteria of the study,  Simon Jones  and  Aimee Donald  from  Manchester University NHS Foundation Trust, UK , and  Jenny Klein  from the  International Advocates for Glycoprotein Storage Diseases (ISMRD) ; and those who responded to our initial query during the feasibility study. The authors would also like to thank  Markus Ries  and  Sven Garbade , from  University Hospital Heidelberg, Germany , for sharing the studies included in their literature review so they could be compared with our findings. Numerus Ltd  provided statistical support.
In this work, a fractional order derivative is introduced to the universal droop control proposed in  [4]. A tertiary level control, based on a sequential logic approach, is added to increase the flexibility of the microgrid. This level allows the secondary controller loops to operate autonomously, as well as the SS. The dynamic performances of the developed four levels hierarchical control are highlighted via simulations using MATLAB/SIMULINK, for a microgrid with three VSIs connected in parallel and a local nonlinear load. The remainder of this paper is organized as follows: Section 2 presents the overall structure of the proposed four levels hierarchical control scheme. The improved primary control level with fractional order derivative including the inner controller is described. The PI centralized controller of the secondary level is presented.
Considering that both the chromene substrate (3) and radulanin A (1) are natural products present in the same liverwort genus,  2, 6  it is questionable whether this rearrangement could occur in Nature. The Supporting Information is available free of charge on the ACS Publications website. Supplementary tables, figures, and schemes experimental procedures and copies of spectra (PDF) * Email: bastien. nay@polytechnique. edu We acknowledge financial supports from CNRS, Institut Polytechnique de Paris (IP Paris), Ecole Polytechnique and Sorbonne Université (SU). BLW 1 thanks CNRS and IP Paris for funding his postdoc fellowship. ST  1, 2  thanks SU for providing a PhD fellowship. BN 1 gratefully thanks Professor Samir Zard  1  for fruitful discussions on the reaction mechanism. We thank Reviewer 2 for suggesting an alternative mechanism that is presented in the supporting information for further discussion.
Input parameters and model calibration We obtained demographic and behavioural data from three main sources: (1) modelling work describing the HIV epidemic and cascade of care in France in 2010  [19] , updated for 2016; (2) the French Hospital Database on HIV (ANRS CO4-FHDH)  [20]  between 2014 and 2017; and (3) cross-sectional survey PREVAGAY 2015 (conducted among French MSM attending gay venues, undertaken in 2015)  [21]. We used previous estimates  [19, 22]  to parameterize both the initial population size in 2014  (53, 200)   1 ; the complete list is given in Table  S1. The HCV transmission rate was calibrated via Approximated Bayesian Computation  [24]  to reflect decreasing HCV incidence rates observed over 2014-2017 in the ANRS CO4-FHDH  [10]  (Supplementary Material S3). Treatment eligibility criteria, treatment rates and sustained virological response (SVR) rates were varied between 2014 and 2019, reflecting changes in treatment practices and DAAs availability for MSM in France (Table  S2 ).
D ATA AVA I L A B I L I T Y S TAT E M E N T Most of the data that support the findings of this study are available from the cited references and supplementary material. PREVAGAY 2015 data are available from the authors upon reasonable request and additional approval from Santé Publique France. Other data are available from the authors upon reasonable request. Anyone can submit a research project to the ANRS CO4-FHDH scientific committee and obtain access to the data after approval by the scientific committee. Applicants should use a standardized form available on the ANRS CO4-FHDH website (https://anrs-co4. fhdh. fr) to describe the context and objectives of the study. The scientific committee reviews the submitted projects twice a year. For successful applicants with adequate statistical expertise, the data can be transferred with French data protection agency CNIL approval; otherwise, the ANRS CO4 FHDH statistical centre analyses the data cooperatively with the applicant.
Materials and methods The guideline was developed according to a well-documented methodology that is universal to ESHRE guidelines  (Vermeulen et al. , 2019). The core guideline development group (GDG) was composed of past members of the guideline group from 2013 and additional experts selected from applicants to a call for experts. All other European experts applying to the call were included as subgroup members, assisting a core group member preparing the guideline on a certain topic. The GDG included two patient representatives, and five patient organizations were represented in the subgroups. Forty-two key questions were formulated by the GDG, of which seven were answered as narrative questions, and 35 as PICO (Patient, Intervention, Comparison, Outcome) questions. For each PICO question, databases (PubMed/MEDLINE and the Cochrane library) were searched from inception to 1 December 2020, limited to studies written in English.
Strong recommendations should be used as a recommendation to be applied for most patients, while weak recommendations require discussion and shared decision-making (Fig. 1 ). For the narrative questions, a similar literature search was conducted. Collected data were summarized in a narrative summary and conclusions were formulated. In case of insufficient data to provide recommendations in reply to a PICO question, a conclusion was also added. For clarity, these conclusions are labelled 'conclusion, not recommendation' in the current paper. The guideline draft and an invitation to participate in the stakeholder review were published on the ESHRE website between 24 June and 15 August 2021. All comments were processed by the core group, either by adapting the content of the guideline and/or by replying to the reviewer.
Acknowledgements The authors would like to thank the experts that participated in the stakeholder review for their constructive and helpful comments. Commission; Participation on a Data Safety Monitoring Board or Advisory Board with ObsEva (Data Safety Monitoring Group) and Myovant (Scientific Advisory Group). A. B. reports grants from  FEMaLE  executive board member and  European Commission Horizon 2020  grant; consulting fees from  Ethicon Endo Surgery , Medtronic; honoraria for lectures from Ethicon; and support for meeting attendance from  Gedeon Richter ; A. H. reports grants from  MRC ,  NIHR ,  CSO ,  Roche Diagnostics ,  Astra Zeneca , Ferring; Consulting fees from  Roche Diagnostics ,  Nordic Pharma ,  Chugai  and  Benevolent Al Bio Limited  all paid to the institution; a pending patent on Serum endometriosis biomarker; he is also Chair of TSC for STOP-OHSS and CERM trials.
Many countries have their own technical manuals detailing what and how should be presented on topographic maps that are often automatically developed on the basis of dedicated topographic databases (e. g. Davis et al. , 2019; Ordnance Survey, 2004). Now, many of the principles developed to automate the production of topographic maps can be implemented in the process of thematic maps development  (Raposo et al. , 2020). The last decade has brought an increase in research papers considering the automatic production of tactile maps (e. g. Barvir et al. , 2021; Götzelmann & Eichler, 2016)  but they focus mainly on production and technological aspects. Most of the existing solutions are based on unmodified geospatial data and do not consider proper cartographic generalization, which impacts the final products' legibility and reduces repeatability of map compilation  (Wabiński & Mościcka, 2019).
Generalization constraints determination In our methodology, we considered different types of generalization constraints (as referred in  Ruas & Plazanet, 1997) : legibility (e. g. minimum point symbol size), spatial (e. g. maximum displacement of features), shape (e. g. alignment of two close line symbols), and semantic (e. g. the percentage of features to be preserved in the final dataset). Considering the characteristics of tactile cartography, we have also followed the hierarchy of the constraint types in our methodology. In the case of tactile maps, legibility is the most important factor. In tactile cartography, it is sometimes even recommended to resign from adhering to the mathematical foundations of cartography in favor of increased legibility. The spatial constraints maintain real-world topological relations on tactile maps, but at the same time, the maximum allowed displacements of features in tactile cartography are higher than in classic cartography.
Similar to the hierarchization of anchor layers, the priorities must also be set for the thematic layers. Two approaches can be taken here. The first is to consider the importance of particular thematic layers for the map's comprehension and informativeness. The second is to begin with the layers, whose generalization would be the most laborious, considering, for example, their geometries -line and area symbols should be fit first. The Python algorithm specifically written for this study adds additional parameters that determine the importance of particular thematic features to eliminate less important ones by applying a selection operator. The algorithm first counts the number of resources of a specific type (occurrences). Those with the least number of occurrences within a dataset (i. e.
rare mineral resources) will be given higher priority during generalization -the algorithm will try to maintain them in the generalized dataset. Then, for each feature in the dataset, in an iterative process, the number of conflicting features (conflicts) is counted. Those with the highest number of conflicting features will be given higher priority. Since the algorithm considers graphic conflicts, it is possible to set the desired dimensions of features to be considered including their size and the minimum horizontal distances between them (Figure  2 ). Lastly, even further proximity of every feature is considered -a number of features falling within a specified buffer around a given feature are counted (proximity). The lower the value of this attribute, the higher the priority of the feature in the generalization processthe algorithm will try to maintain more isolated features in the generalized dataset.
The resulting base and thematic features were exported and further processed in the CartAGen platform -an open-source platform designed for research in map generalization  (Touya et al. , 2019). We used a displacement algorithm available on the platform, called random iterative displacement. It is based on an iterative process that tries to minimize the total number of symbol overlaps in the dataset. At a given iteration, the symbol that overlaps most of its neighbors is chosen and randomly displaced. If the overlap is the same or worse, the displacement is backtracked; else the displacement is validated and another symbol is chosen and displaced (Figure  3 ).
It determines the type of mineral resource, e. g. coal. After the selection procedure using the proprietary Python algorithm, the displacement procedure has been carried out in CartAGen. This step only displaced the features without affecting the numbers and shapes of the features with one exception -the enhancement of the Hel Peninsula. The Hel Peninsula is a very narrow strip of land in northern Poland that is greatly enlarged on maps due to its importance in orientation. The vertices forming its geometry have been moved away using the least squares algorithm, with a principle similar to the embankment distortion  (Touya & Lokhat, 2021)  to enlarge it on the final map (Figure  4 ). For the features displacement in CartAGen, the following assumptions were made. Rivers were symbolized as 0.
Generalization procedure Knowing the final map scale, we were able to calculate the exact numerical values of the generalization parameters to be used in our map development process. The procedure described below has been carried out in ArcGIS software, using the Model Builder module for automatic generation of the basemap. For the generalization of water reservoirs, we have used the selection by attributes to select only the inland seawater out of the entire dataset. We then applied the area feature smoothing using PAEK with a 20 km threshold set. In the case of rivers layer, we have first selected the rivers longer than 100 km that flow through Poland by using attribute and location queries, respectively. Next, we applied PAEK smoothing with a 20 km threshold. The rivers were then aligned (5 km threshold) to the inland seawater features to comply with the real-world topological relations.
For cities layer, we have first selected the cities that could be presented on each of the maps in a designed atlas (those in Poland with population over 200,000) and later enhanced this group by those important in the context of our case study map's topic -those that are within a distance of 20 km from the features in the original thematic content dataset (mineral resources). Finally, the cities were aligned with rivers to maintain topological relations (10 km threshold). • Manual vectorization on georeferenced raster (1:5M) Next, the thematic content was generalized and later fitted to the basemap. The original thematic class consisted of 111 point features. After running the algorithm, 79 features remained (Figure  6 ). The data were then exported to CartAGen for the additional generalization steps described in the methodology section and finally imported back to ArcGIS for the purpose of symbolization and labeling (Figure  7 ).
Preparation for printing This section briefly describes the procedure of the minor manual edits that we carried out as well as the transformation of the flat vector map into a tactile model suitable for 3D printing. The automatically generated map has been imported into Corel software. Although our automatic approach has left us with acceptable results, we decided to perform some final attunements manually to improve map's legibility. First, we eliminated from the map one of the cities (Gdynia) that is usually not represented on small-scale maps of Poland due to its proximity to another major city -Gdańsk. We also deleted two rivers introducing unwanted clutter that usually do not appear on such maps: Neman and Mukhavets. Next, we had to displace some of the labels that the Maplex Engine failed to properly arrange.
The map sheet and legend were then exported as a 3D mesh and further processed in ChituBox slicing software. The tactile overprint map itself and the legend were printed using stereolithography 3D printing with transparent resin on the Sonic Mega Phrozen printer (Figure  13 ). To cut the production costs and time, we decided to print the list of abbreviations using the swell paper method. The fact that we wanted the map to be printed in one piece and the limited dimensions of the printer's build plate required a specific arrangement of the map sheet on the printer's build plate that dramatically increased the printing time, which lasted around 70 hours. We used approximately 500 ml resin. The printing time can be reduced to a few hours when using a different placement strategy and/or printing device.
Data availability statement The resulting maps in the form of both 3D models and flat vector drawings, as well as the Python algorithms used for basemap and thematic data generalization, are available at the dedicated repository: https://doi. org/10. 1080/15230406. 2022. 2105747. The CartAGen plugin repository is available at https://doi. org/10. 1080/15230406. 2022. 2105747.
Acknowledgements The authors acknowledge Fundação para a  Ciência e Tecnologia (FCT, Portugal)  and  ERDF  under Programme  PT2020  to 1)  José A. C. Silva  under Project ref. POCI01-0145-FEDER-016517 (PTDC/QEQ-PRS/3599/2014 ), 2) CIMO ( UID/AGR/00690/2020 ), (3)  LSRE-LCM (POCI-01-0145-FEDER006984 ), and (4) Adriano Henrique from the individual research grant  SFRH/BD/148525/2019. The authors also acknowledge  Ivan M. C. Pinto  for the measurement of the single component isotherms shown in Figure S20 in the Supporting Information,  Kristin Gleichmann  and  Chemiewerk Bad Koestritz GmbH  for kindly providing the binder-free beads of zeolite 5A used in this work,  Ben Slater  from  IMAP  for the proofreading of the manuscript, and  Dr. Jong San Chang  from  KRICT  for his helpful discussions.
, 2017). These simulations benefit from a horizontal resolution (25 km) which is at the upper end of the recent High Resolution Model Intercomparison Project (HighResMIP), part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6;  Eyring et al. , 2016; Haarsma et al. , 2016). However, a key difference is that the HadGEM3-GA3 data set consists in atmosphere-only simulations, whereas the HiRESMP and the CMIP6 have fully coupled simulations. The lack of coupling could lead to some limitations in the representation of PLs and the large-scale environment. Nonetheless, this study demonstrates that the HadGEM3-GA3 present-day simulations show a similar PLs activity with both the literature and with a coupled reanalysis data set. In particular, in order to assess the representation of PLs in the HadGEM3-GA3 model, PL activity in the present-day climate simulations are compared with those identified in the National Centers for Environmental Prediction   (2011) (2012) (2013) (2014).
The two NCEP datasets are based on the same assimilation system and concatenated to span the same time period covered by the climate model simulations. The NCEP-CFS has a horizontal resolution of 38 km (64 vertical vertical levels) and has been chosen for its high spatial resolution, which is relatively close to that of HadGEM3-GA3. The even higher-resolution ERA5 reanalysis (horizontal resolution of 31 km) was not available at the time this analysis began, but future studies will benefit from using it. However, the NCEP-CFS is the only available coupled reanalysis, and its long time period allows a long term comparison of PLs between NCEP-CFS and HadGEM3-GA3.
Polar Lows Tracking and Identification Scheme In order to track and identify PLs, this study makes use of the methodology presented and validated in  Zappa et al. (2014). Using an objective tracking and identification scheme based on criteria applied to the 850 hPa vorticity, the 10-m wind speed and a measure for the static stability, Zappa et al. (2014)  showed that 55% of the 2008-2011 PLs from the observational STARS data set  (Noer et al. , 2011 ) could be automatically detected in European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim  (Dee et al. , 2011)  reanalysis data (∼80 km resolution) and up to 70% of the STARS events were detected in the ECMWF operational analysis (∼9 km resolution). This highlights how PLs are detectable in datasets of sufficiently high spatial resolution.
This tracking and identification scheme for PLs has also been used in other studies, such as  Yanase et al. (2016) ,  Smirnova and Golubkin (2017)  and  Stoll et al. (2018) , showing valuable skill in identifying and tracking PLs in other regions and reanalysis datasets. A summary of the tracking scheme and identification criteria can be found below and more information can been obtained from  Zappa et al. (2014). The objective feature-tracking algorithm TRACK  (Hodges, 1994 (Hodges, , 1995 (Hodges, , 1999) )  is used to track PLs from both the model and the reanalysis data, via the 6-hourly relative vorticity at 850 hPa. Prior to applying the tracking, the data is spectrally filtered to retain the spherical harmonic of wave numbers T41-100, which enables the identification to focus on the spatial scales typical of PLs (∼400-1,000 km) and to provide some smoothing to reduce the high frequency noise present in the vorticity field.
The ocean fraction, averaged over a 1° radius, has to be greater than 75% This set of criteria aids the identification of PLs by searching for their distinguishing characteristics: PLs are intense cyclones associated with gale force winds with a small radius (criteria a and b,  Rasmussen and Turner (2003) ; pages 11-12;  Kolstad (2006)   2018 )), they tend to form in a convectively unstable atmosphere (criterion c,  Rasmussen and Turner (2003) ; page 12;  Noer et al. (2011) ), and predominantly form over the ocean (criterion d,  Rasmussen and Turner (2003) ; page 13). While the adopted thresholds are partly empirical, they have shown good skill in isolating PLs in different regions and datasets. However, while the value of -43 K on the vertical temperature difference has been successfully used in previous PL studies  (Zahn & von Storch, 2008; Xia et al.
Present-Day Representation of Polar Lows In this section, the representation of NH PLs identified in the high-resolution simulations of the HadGEM3-GA3 climate model and in the NCEP-CFS reanalysis is assessed and compared to the available literature based on both observational-and model-based studies. Since there is no real truthful global PLs data set and since there is still a large disagreement between different observational and reanalysis datasets regarding PL characteristics (such as the vertical temperature difference or the maximum wind speed), our results will also be compared against those obtained from another global reanalysis-based climatology of PLs based on different identification criteria and datasets  (Stoll et al. , 2018). The mean and inter-annual standard deviation of PL numbers identified over the NH in the NCEP-CFS reanalysis are 120.
In particular, the spatial distribution of track density in the HadGEM3-GA3 model is very similar to that found in the NCEP-CFS reanalysis, although the maxima are lower than observed. Likewise, the seasonal cycle of PL numbers in HadGEM3-GA3 shows an increase from October to January and then a decrease until March, with monthly PL numbers in HadGEM3-GA3 ranging from around 3 PLs in October to 28 PLs in January. These results are comparable to those found using the NCEP-CFS reanalysis, and indicate similarities in the seasonal cycle and spatial distribution of PLs in the two datasets. To further investigate the representation of PLs in the HadGEM3-GA3 model, other characteristics of PLs have been assessed and compared to NCEP-CFS. These characteristics are the along-track vorticity, the 10-m wind speed and the vertical difference in temperature (ΔT = T500 -SST) found at the maximum vorticity of each PL.