dataesr/scientific-paragraphs-categorization huggingface dataset:
Coalescent approach Individual gene trees were constructed using RAxML (v8. 2. 9)  (Stamatakis, 2014)  with the "-f a" option and 100 bootstrap replicates. We used a GTRGAMMA model which estimates the rates in the general time-reversible (GTR) matrix, the alpha shape parameter of the Gamma model of rate heterogeneity and the empirical base frequencies for the locus. Branches with boostrap support >10 were collapsed using Newick Utilities program nw_ed  (Junier and Zdobnov, 2010). This has been shown to improve the accuracy of inferred species trees  (Zhang et al. , 2017). We then ran ASTRAL-III (v5. 5. 11)  (Zhang et al. , 2017)  using the gene trees that corresponded to our selected loci, first using the default parameters, then using "-t 1" to output quartet support values.
Concatenation approach After alignment, we filled missing individuals at each locus with an empty sequence and concatenated aligned loci using the pxcat function in the program phyx  (Brown et al. , 2017). A GTRGAMMA model was defined using the partition file output by pxcat leading to a different model for each alignment  (Brown et al. , 2017). A rapid bootstrap analysis in RAxML (v8. 2. 9)  (Stamatakis et al. , 2008; Stamatakis, 2014)  using the "-f a" option with 100 replicates was performed followed by a thorough ML search on the original alignment.
The final MyBaits Annonaceae baiting kit was made of 11,583 baits 120 bp long. This baiting kit is available upon request at Arbor Biosciences (http://www. arborbiosci. com). The fastq (R1 and R2) sequences for all individuals are available in Genbank SRA under Bioproject number PRJNA508895 (http://www. ncbi. nlm. nih. gov/bioproject/508895).
Number of Loci Retrieved and Variability Overall, we recovered good average depth for all individuals sequenced (275; min: 45; max: 726) and on average we recovered over 90% of our target with a coverage greater than 10x (Supplementary Data Sheet). For the Annonaceae analyses, we recovered 98 to 468 loci depending on the percentage of reconstructed targeted exon length for the same percentage of individuals (Table  2 ). We recovered at least a fraction of all but one of the targeted loci (468 of 469). A total of 331 loci were reconstructed for over 75% of their length and for over 75% of individuals and this "75/75" The values indicate the percentage of individuals for which we reconstructed the same percentage of the targeted exon region. Phylogenetic analyses were carried out using the 75/75 datasets.
subset was used for tree inference. The total length of these 331 loci was 545 610 bp. For the Piptostigmateae analyses, we captured between 170 and 469 loci (Table  2 ). We captured at least some of all the targeted exons in this dataset. A total of 379 loci were retrieved under the 75/75 rule and used for the phylogenetic inference. The total length of these 379 loci was 766,373 bp. We recovered substantial amounts of non-target sequence data per locus. The typical aligned length of supercontigs was more than twice that of exon alignments (Figure  1 ). On average we recovered 828 bp of off-target sequence data in our Annonaceae dataset and 1 241 bp in our Piptostigmateae dataset to be used for downstream phylogenetic inference. We calculated 75/75 loci for each Annonaceae subfamily and identified 179 loci common across each subfamily locus set.
In the latter studies, the baiting kit was shown to successfully cpature exons across the Ericaceae family too  (Kadlec et al. , 2017). Second, we also used a "degenerated" kit, meaning that for 282 (out of 469) identified orthologous exons we included different species-specific exon variants increasing capture capacity across the family. However, we did not undertake explicit analyses or resequencing to test if our degenerate kit improved capture across Annonaceae or not. We recovered around 500-1,000 bp of off-target sequence data (i. e. , sequence data flanking our targeted regions). Offtarget sequences are mostly composed of intronic data, but it has been shown that non-baited exon regions can also be captured in the process  (Kadlec et al. , 2017). Annonaceae do not have a sequenced genome yet, so it is hard to know precisely what we are recovering in off-target sequences.
Annickia Our data suggest that the African tribe Piptostigmateae is potentially not monophyletic. Indeed, Annickia is resolved as sister with high support to the rest of the Malmeoideae in the gene tree analysis (Figure  4 ), but weakly supported as sister to the rest of the Piptostigmateae genera in the concatenated analysis (Figure  5 ). These results were also confirmed when we increased sampling in the tribe (Figures  6, 7 ) highlighting discordance between the gene tree and the concatenated analyses. In the gene tree analysis, not all loci recovered the Annickia sister to Malmeoideae relationship (41% in the Annonaceae analysis and 64% in the Piptostigmateae analysis). This clearly underlines some conflict in the proper placement of the genus. Nevertheless, this still translated into high LPP support for this branch because the alternative quartet topologies are recovered by significantly fewer loci.
FUNDING This study was supported by grants from the  Agence Nationale de la Recherche  ( AFRODYN :  ANR-15-CE02-0002-01  to TLPC; MAGNIPHY:  ANR-12-JVS7-0015-01  to HS); RE was supported via the  Innovational Research Incentives Scheme  (VENI, nr. 863. 09. 017 ; NWO-ALW , The Netherlands).
The specifications have been updated, and now encourage taking into account activity in terms of hospital stays and number of multidisciplinary consultation meetings, with thresholds being set such as (i) effective patient satisfaction assessment; (ii) effective geographic coverage, without blank areas; and (iii) effective implementation of CRIOAc missions in terms of coordinating the expertise, orientation and information of other agents (community practices, patients, private-sector structures, etc. ). During the 5-year period aforementioned, the national database collecting the data of each multidisciplinary consultation meetings will be used for epidemiological studies and report purposes. A national website for patients and the various health professionals will be created to publicize the system, and optimize referrals and timely treatment before simple situations become complex.
The promotion of education, clinical research and interactivity between each academic discipline and between each labeled centers across the country has synergized the strengths and optimized the management of patients with BJI. By drawing upon the strengths of academic and health ministry expertise, the CRIOAc network represents a potential new model at a national level, for filling knowledge gaps, and enhancing management and innovation in complex diseases. 13 Our study has some limitations: 1) we are not aware of BJI not implemented in the database and the extra cost related when those patients are managed in centers outside the CRIOAc network. However, every cases discussed in multidisciplinary meetings are recorded in the system, centers outside the network more and more facilitate the recruitment of their patients by centers belonging the network, and based on the PMSI database, most of BJI in France are managed in the CRIOAc network; 2) we did not compare the cost and rate of success of BJI managed inside vs.
published. Of note, some national projects were funded or supported by the Health Ministry such as DATIPO in 2009 (comparison of different duration of antibiotics in patients with PJI; Prospective open randomized multicentre non-inferiority phase 3 trial NCT01816009), EVRIOS in 2015 (comparison of different dosages of rifampin; Prospective open randomized multicentre noninferiority phase 3 trial; NCT02599493), and PHAGOS and PHAGOPIED in 2016 (safety of bacteriophages targeting S. aureus in patients with PJI and diabetic foot osteomyelitis; NCT02664740). Indeed, these multiple interactions in the CRIOAc network facilitate the emergence and the feasibility of multicentric studies with high level of evidence. Finally, to optimize the management of acute prosthetic joint infection, and to avoid its complication, some experts from the CRIOAc network directly participated to the literature review and the drafting of 11.
Semi-structured interviews with ten seniors and two technology consultants were conducted following each of the observed matchmaking dialogues. Topics in interviews with both seniors and technology consultants included: goals and motivations concerning the matchmaking dialogue, satisfaction or dissatisfaction with how the matchmaking dialogue was conducted and views on the outcomes of the matchmaking dialogue (see Additional file 1 for interview guides). Interviews lasted twenty-four minutes on average and were audiotaped and transcribed verbatim. Ten interviews were enough to reach data saturation concerning a basic understanding of the matchmaking service. After the completion of phase one, an analysis was made of the matchmaking service and important issues within that service. This analysis served as input for phase two.
Data analysis Thematic analysis was used for the data collected in phase one, using qualitative data analysis software (Atlas. ti version 8)  [46]. First inductive codes were attached to quotes relevant to the research questions. Transcripts were coded independently by two researchers, with one researcher coding twelve of the twenty transcripts, and another researcher eight. Second, researchers came together to discuss their codes in the form of case studies and codetermined overarching themes. Phase two results, were continuously analyzed within the action research group in each co-creation session. The three most important steps for analysis were: codetermining the collective goals for improving the matchmaking service, codetermining the specific characteristics of the matchmaking tool and co-evaluating the use of the tool.
Acknowledgements We would like to thank the participating seniors for welcoming us to their homes. Annette Kemerink ,  Ariette Van Hespen ,  Leroy van den Hoonaard  and  Erwin Tak  (all working for the municipality of The Hague) are especially thanked for working with us within the action research team. Loes Hulsebos  and  Kim van der Beek  (likewise working for municipality of The Hague) are also thanked for their contributions to the tool development process.
Acknowledgements We are thankful to  F. Aprile ,  B. Basso ,  J. Caetano ,  A. Cavaglia ,  S. Derkachev ,  J. Drummond ,  D. Grabner ,  O. Gurdogan ,  P. Heslop ,  D. Kosower ,  F. Levkovich-Maslyuk ,  E. Olivucci ,  M. Preti ,  V. Rosenhaus ,  E. Sobko  for discussions. The work of V. K. was supported by the  European Research Council  ( Programme "Ideas" ERC-2012-AdG 320769 AdS-CFT-solvable ). N. G. and V. K. are grateful to  Humboldt University (Berlin)  for the hospitality and financial support of this work in the framework of the "Kosmos" programme. N. G. wishes to thank  STFC  for support from Consolidated grant number  ST/J002798/1. The work of G. K. was supported by the  French National Agency for Research  grant  ANR-17-CE31-0001-01. G. K. would like to thank the  Galileo Galilei Institute for Theoretical Physics  for the hospitality, the  INFN  and  Simons Foundation  for partial support during the completion of this work.
INTRODUCTION: Fenestrated and branch endografts have been progressively utilized to treat complex aneurysms involving visceral and renal arteries. The technique has matured, and the use of fenestrated and branched endovascular repair (F-BEVAR) has evolved for the treatment of varieties of complex anatomical aneurysms. 3] [4] [5] [6]  Although open remains standard of care in most centers, it is associated with high morbidity and mortality rates and remains an excessive challenge in high risk patients. ] [10]  Prospective analysis of a large standard EVAR database identifies a number of factors associated with peri-operative mortality. These include age, a history of congestive heart failure, aneurysm diameter at treatment, and chronic renal insufficiency. 11 To date, the limited populations reported for F-BEVAR make it difficult to draw or refute equivalent conclusions.
Study population The study was conducted as a retrospective analysis of prospectively collected data at the Aortic Center of CHU Lille, France. All patients with para-renal (PR, including AAA with necks <10mm long, juxta renal aneurysms, and aneurysms with no normal aorta between upper extent of aneurysm and renal arteries) or thoracoabdominal (TAAA) aneurysms who underwent endovascular aneurysm repair with branched (BEVAR) or fenestrated (FEVAR) devices between October 2004 and December 2016 were included. The indication for PR or TAAA aneurysm repair was a maximum aneurysm diameter ≥ 50 mm or a rapidly expanding aneurysm (> 10 mm/year). F-BEVAR was restricted to elective cases because of the delay required to design and manufacture these custom-made devices (CMD). Aneurysms were classified according to the extent of aortic stent graft coverage into categories TAAA Crawford type 1 to 5 and PR aneurysm.
All patients signed pre-operative informed consent for the collection of their data in our study database and for the future use of these data for scientific research. The choice between open and endovascular repair of complex aneurysms was made during a weekly multidisciplinary Aortic conference involving vascular and cardiac surgeons, cardiologists, radiologists and anaesthetists. This retrospective study was undertaken as a clinical audit according to our centres' local regulations. IRB approval was not required. Pre-operative variables collected included demographics, co-morbidities and cardiovascular risk factors, cardiovascular drug intake, previous aortic surgery, maximum aortic diameter and the presence of Marfan's syndrome or previous aortic dissection. Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate (eGFR) less than 60 ml min -1.
Statistical analysis Data were collected in a prospective database with retrospective analyses using SAS software v 9. 4 (SAS Institute Inc. , Cary, NC, USA). Continuous variables were expressed as median with their 25 th and 75 th percentiles. Categorical variables were presented as absolute numbers and percentages. Population means were compared using Student's t tests or Mann Whitney U tests (according to normality assessed by the Shapiro-Wilk test in case of small sample sizes) and using the chisquare test of Fisher's test, as appropriate, for proportions of a categorical variable. Predictive factors for early and late mortality were identified with multivariate Cox analysis. Patients with peri-operative mortality were excluded from late mortality analysis. The linear relationship between the outcome and a continuous covariate and proportional hazard assumption were tested by supremum tests.
Endoleaks and sac changes during follow-up Clinical data on endoleaks, sac changes and limb occlusions during follow-up (> 30 days) were obtained for 402 patients. Endoleaks during follow-up were identified in 118 patients by CTA or color duplex ultrasound. Ninety-eight patients had 1 endoleak, whereas 17 patients had 2 different endoleaks and 5 patients had 3 different endoleaks. Type 1a, 1b and 1c endoleaks were diagnosed in respectively 10, 13 and 3 patients. Ninety-one patients had a type 2 endoleak. Twenty-six patients were identified with a total of 29 type 3 endoleaks. Pre-operative diameters were compared to the last post-operative diameter. Overall, sac shrinkage (> 5 mm) occurred in 218 patients (54. 2 %) and sac enlargement was seen in 38 patients (9. 4 %). One hundred and forty-six patients had stable diameters (36.
Along the previous lines, the aims of the present study are twofold: 1) to identify suitable phenological models for three main phenological timings (budburst, flowering, and veraison) of two leading grapevine varieties (cv. Touriga Franca and cv. Touriga Nacional) currently grown in the DDR; 2) to assess the climate change impacts on these phenological timings and varieties. The datasets and methodologies are described in Section 2. The results are presented in Section 3. Section 4 will provide a discussion and a summary of the main conclusions.
Study Area and Datasets The present study targets the Douro/Porto Wine Region (DDR), located in Northern Portugal (Figure  1a ). The DDR is characterized by Mediterranean-type climates, with typically dry and warm summers, though a wide range of mesoclimates and microclimates do exist throughout the region, mostly driven by the multifaceted orography and distance to the North Atlantic. Important east-west gradients in both temperatures and precipitation can be found within the region, and are typified by its 3 sub-regions: from Baixo-Corgo (westernmost sector) to Cima-Corgo (middle sector) and to Douro Superior (easternmost sector) (Figure  1b ). This spatial variability is further enhanced by important differences in soil properties, though soils are mostly originated from schist bedrocks  [40].
In the present study, phenological data recorded at 12 vineyards ("Quintas") in the DDR, with data available over the period 2014-2017 (4 years), were used (Figure  1b ). The phenological timings were recorded through observations based on the BBCH scale adapted to grapevines and when at least 50% of a pre-defined set of homogenous plants reach the corresponding stage. Budburst (BBCH 07), flowering (BBCH 65) and veraison (BBCH 81) were considered herein  [41]. Data for two main grapevines varieties grown in Portugal were selected: cv. Touriga Franca (TF) and cv. Touriga Nacional (TN). As information for other varieties (cv. Tempranillo, cv. Tinta Amarela and cv. Moscatel-Galego) was indeed very limited and inconsistent among vineyards, they were not taken into consideration. Furthermore, in order to enhance the statistical robustness of the selected models for a given grapevine variety, the phenological timings for the same variety for all sites (and terroirs) were considered for model calibration.
Owing to the relatively small sample size of the DDR dataset for model calibration (12 sites × 4 years = 48 records), the same phenological timings for TF and TN from two other Portuguese wine regions were also used: Lisboa (central-west) and Vinhos Verdes (north-west) (Figure  1a ). Phenological records were available for the following locations (Table  1 ): "Dois Portos-DP" (Lisboa Wine Region), with 20 years of data within the full period of 1990-2014, and "Estação Vitivinícola Amândio Galhano-EVAG" (Vinhos Verdes Wine Region), with records over the period of 2005-2009 (5 years). Therefore, the total sample size is extended to 73 records for each phenological timing and variety, thus enabling a higher statistical robustness in model calibration. A summary of the entire phenology dataset is provided in Table  1.
For the DDR, daily mean temperature records from the meteorological stations installed at the different vineyard sites and over the period of 2014-2017 (4 years) were used (Figure  1b ). For the other two wine regions (Vinhos Verdes-EVAG and Lisboa-DP), the local temperature time series were estimated from the nearest-point of a very-high resolution (~1 km) gridded daily temperature dataset for Portugal  [42]. Phenology and temperature data for the Douro Wine Region were provided by the "Associação para o Desenvolvimento da Viticultura Duriense-ADVID", after collecting information among their members, while phenology data for Lisboa-DP and Vinhos Verdes-EVAG were provided by the "Instituto Nacional de Investigação Agrária e Veterinária", INIAV, and by EVAG, respectively.
Modelling Tools and Performance Verification In this study, the Phenological Modelling Platform, PMP  [14] , was used to test and calibrate different phenological models applied to grapevines. PMP is an intuitive platform that allows users to apply and test different phenological models for several purposes. In this platform, climatic and phenological data were used in order to calibrate the models, i. e. , estimate the best-fit model parameters, for a specific location and a pre-defined time period. PMP estimates best-fit parameters following an iterative optimization procedure, based on the simulated annealing algorithm of  Metropolis, et al. [51]. For each specific location, the input data used were daily mean (T d ), maximum (T max ) and minimum (T min ) temperatures, latitude and observed phenological timings for budburst, flowering, and veraison (in days of the year, DOY).
The AIC takes into account the number of model parameters, with the lowest value corresponding to a model that represents the highest variance ratio in the observed dataset with the fewest parameters (parsimony principle). Further, in order to take into consideration model overfitting, a leave-one-out cross-validation scheme was applied to every simulation, following the same methodology as described by Chuine, et al. [52] , and the RMSE metric was accordingly adapted to Root Mean Square Error of Prediction (RMSEP), defined as: RMSEP = n i = 1 O i -Pi 2 n ( 4 ) where Pi is the predicted value obtained from a leave-one-out cross-validation approach  [53].
Model Performance Verification As previously mentioned, the sample size of the observed phenology dataset used for model calibration is of 73 records for each phenological timing and variety. For TF, the minimum/mean/maximum DOY is 61/77/98 for budburst (from March 2nd to April 8th), 112/138/158 for flowering (from April 22nd to June 7th) and 177/201/222 for veraison (from June 26th to August 10th). For TN, the observed minimum/mean/maximum DOY is 64/78/100 (from March 5th to April 10th) for budburst, 112/140/158 for flowering (from April 22nd to June 7th) and 170/213/235 for veraison (from June 19th to August 23rd). Despite the large spread in the dates of each phenophase, these results show that phenophase timings are commonly earlier for TF than for TN, particularly for veraison. In addition, the correlation coefficients between the time series for DP and EVAG, in their overlapping period  (2005) (2006) (2007) (2008) (2009) , are very high (>0.
Discussion and Conclusions Phenological models are a key tool for viticulturists, as they provide valuable information for management and planning in vineyards  [7]. The accurate prediction phenological timings promotes best practices and the timely implementation of suitable measures to optimize grapevine yields and grape berry quality  [56] [57] [58] [59]. Moreover, future projections of potential changes in the phenological timings may also deliver important information for medium-to-long term planning  [60]. Despite the aforementioned high economic value of the DDR, no previous studies were conducted for this region on phenological modelling and simulation. Unique datasets, combining phenological timings with weather station records, in the Douro wine region were used herein. The weather stations used were installed at the vineyard locations, which is of utmost importance for a proper phenological modelling  [61].
Furthermore, two of the most important grapevine varieties cultivated in the Douro wine region (TF and TN) were selected (cv. Touriga Franca-TF and cv. Touriga Nacional-TN). Despite the relatively large number of sites in the Douro valley (12 Quintas), data is only available over a maximum period of 4 years. This dataset was thereby complemented with data from two other Portuguese wine regions (Lisboa and Vinhos Verdes) and for the same grapevine varieties (TF and TN). This approach led to more robust results, as the sample sizes for model calibration were significantly enlarged. It was herein demonstrated that some specific phenological models are particularly suitable to the simulation of the two selected grapevine varieties. For all phenophases, specific parameter values were chosen within each model (e.