dataesr/scientific-paragraphs-categorization huggingface dataset:
The number of cohorts and children per meta-analysis differed because of differences in data availability. For all analyses, missing values in covariates were used as an additional group in the categorical variables to prevent exclusion of noncomplete cases. We also performed a complete-case sensitivity analysis to explore any differences with complete-case analyses and sensitivity analyses in which we first excluded children with parent-reported birth weight and then excluded children without ISAAC-based questionnaires on wheezing. Statistical analyses were performed with SAS 9. 2 software (SAS Institute, Cary, NC) and Comprehensive Meta-Analysis (Biostat).
jacionline. org). Also, we observed similar effect estimates for preschool wheezing and school-age asthma after excluding cohorts one by one, indicating no disturbing effect of any particular population (data not shown). After exclusion of the Danish National Birth Cohort, the largest cohort in our meta-analysis (COPSAC) and a high-risk asthma and atopy cohort, we also did not observe major changes in effect estimates (data not shown). Next, we explored the combined effects of gestational age at birth, birth weight SDS, and infant weight gain. The significant correlations were between gestational age and birth weight (r 5 0. 58, P <. 001), between gestational age and infant weight gain (r 5 20. 16, P <. 001), and between birth weight and infant weight gain (r 5 20. 12, P <. 001). We performed stratified analyses and an overall test for interaction.
Strengths and limitations We performed a large meta-analysis of individual participants' data from many birth cohorts throughout Europe. We did not rely on published data, which limits any potential publication bias. The large number of participants enabled us to assess small effects and to adjust for various potential confounders. We presented results from random-effects models, which allow heterogeneity in the true effect estimates between different populations and take betweenstudy variation into account. Another strength is that information on exposures in early life was collected from records and did not depend on long-term participant recall. Misclassification of gestational age is always possible because of the large number of pregnant women who did not know their exact gestational duration.
54, 55 Misclassification of gestational age might have increased the number of children born postterm with a small size for gestational age and children born preterm with a large size for gestational age. Most cohorts used standardized and validated questionnaires to assess wheezing and asthma. This method is widely accepted in epidemiologic studies and reliably reflects the incidence of wheezing and asthma in children. 22, 56 Multiple imputation has been suggested to be the preferable method to deal with missing values. 57 However, we did not have additional data on patterns of missing values and were therefore unable to perform multiple imputations within cohorts. We used missing values in covariates as an additional group to prevent exclusion of noncomplete cases. No differences in results were observed between the missing as extra category and complete case analyses.
European cohorts selected from the existing collaborations on childhood health or asthmarelated outcomes (www. chicosproject. eu, www. birthcohortsenrieco. net, from the European Respiratory Society and the European Community's Seventh Framework Programme FP7/2007-2013-Marie Curie Actions under grant agreement RESPIRE, PCOFUND-GA-2008-229571. Disclosure of potential conflict of interest: I. Annesi-Maesano has received one or more grants from or has one or more grants pending with UE. S. H. Arshad has been supported by one or more grants from the National Institute of Health and Asthma UK and has received one or more payments for lecturing from or is on the speakers' bureau for Thermo Fisher and GlaxoSmithKline. H. Bisgaard has been supported by one or more grants from the Danish State Budget and the Lundbeck Foundation, has consul-Pike has been supported by one or more grants from FSA BLF and has received various travel grants and bursaries, most recently from the European Respiratory Society.
HUMIS The research leading to these results has received funding from the  Norwegian Research Council  under grant agreement  213148  (MILPAAHEL) and the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013 ), project  Early Nutrition  under grant agreement number  289346 , and project  OBELIX  under grant agreement number  22739. INMA Gipuzkoa/Sabadell/Valencia/Menorca Data used for this research were provided by the  INMA-Environment and Childhood Project  (www. proyectoinma. org),which is supported in part by funds. This study was funded by grants from  Instituto de Salud Carlos III  (Red INMA  G03/176  and  CB06/02/0041 ), the  Spanish Ministry of Health  ( FIS-PI041436 ,  PI042018 ,  PI06/0867 PI07/0252 ,  PI081151 , and  PI09/02311 ,and  FIS-FEDER 03/1615 ,  04/1509 ,  04/1112 ,  04/1931 ,  05/1079 ,  05/1052 ,  06/1213 ,  07/0314 , and  09/02647 ),  Generalitat de Catalunya-CIRIT   1999SGR 00241 , the  Conselleria de Sanitat Generalitat Valenciana , the  Department of Health of the Basque Government  (2005111093 and 2009111069), the  Provincial Government of Gipuzkoa  ( DFG06/004  and  DFG08/001 ),  Obra Social Cajastur ,  Universidad de Oviedo , the  EU Commission  ( QLK4-1999-01422 ,  QLK4-2002-00603  and  CONTAMED FP7-ENV-212502 ),  Consejer ıa de Salud de la Junta de Andaluc ıa  (grant number  183/07 ), and  Fundaci o Roger Torn  e.
MAS Data for this research question were obtained by the study centre of the cohort study. The  Multicentre Allergy Study  (1990) was supported by grants from the  German Federal Ministry for Education and Research (BMBF)  under reference numbers  07015633 ,  07 ALE 27 ,  01EE9405/5 , and  01EE9406. NINFEA Data used for this research were provided by the  Cohort Study , which is supported in part by funds of  Compagnia di SanPaolo Foundation ,  Piedmont Region , and the  Italian Ministry of University and Research. PCB Data used for this research was provided by the  Cohort Study , which is supported in part by funds from  National Institutes of Health  grant  R01-CA096525  and  EU  project  OBELIX  (no. 227391 ). PIAMA The PIAMA study has been funded by the  Netherlands Organization for Health Research and Development ; the  Netherlands Organization for Scientific Research ; the  Netherlands Asthma Fund ; the  Netherlands Ministry of Spatial Planning, Housing , and the Environment; and the  Netherlands Ministry of Health , Welfare and Sport.
REPRO PL Data used for this research were provided by the  Cohort Study , which is supported in part by funds from the  National Center for Research and Development, Poland  (grant no. PBZ-MEiN-/8/2//2006 ; contract no. K140/P01/2007/1. 3. 1. 1. )and grant  PNRF-218-AI-1/07  from  Norway through the Norwegian Financial Mechanism  within the  Polish-Norwegian Research Fund. RHEA Data used for this research were provided by the  Cohort Study , which is supported in part by funds of  European Commission. SEATON Data used for this research were provided by the university, which is supported in part by funds from  Asthma UK  and the  Medical Research Council. SWS The Southampton Women's Survey  is supported by grants from the  Medical Research Council , the  British Heart Foundation , the  Food Standards Agency , the  British Lung Foundation ,  Arthritis Research UK ,  NIHR Southampton Biomedical Research Centre , the  University of Southampton  and  University Hospital Southampton NHS Foundation Trust , and the  Commission of the European Community , specific  RTD Programme ''Quality of Life and Management of Living Resources,'' within the 7th Framework Programme , research grant no.
FP7/2007-13  ( Early Nutrition  Project). This manuscript does not necessarily reflect the views of the funders and in no way anticipates the future policy in this area. WHISTLER Data used for this research were provided by the  Cohort Study , which is supported in part by funds from the  Netherlands Organization for health Research and Development (ZON-MW) , the  University Medical Center Utrecht , and an unrestricted research grant from  GlaxoSmithKline , The Netherlands. Clinical implications: Children born at a younger gestational age at birth or higher infant weight gain have increased risks of childhood asthma.
and ww the Centre for Prevention and Supported by the  European Community 's  Seventh Framework Programme   FP7/2007-2013 , project  CHICOS. The research leading to these results has received funding work Programme FP7/2007-2013 (Project  CHICOS ). L. Duijts has received research support from the  European Community 's  Seventh Framework Programme FP7 /2007-2013 (Project  CHICOS ) and is the recipient of a  European Respiratory Society /Marie Curie Joint Research Fellowship  (no. MC 1226-2009 ). The rest of the authors declare that they have no relevant conflicts of interest.
The iodine value (IV) was determined by the Wijs method described in the ISO 3961:2009 standard. For the IV, mean values were estimated for all 116 palms (based either on four measurements recorded in 2002-2004 and 2012 for the 88 surviving palms or on two previous measurements in 2002-2004 for palms that had died since 2004). Regarding the interspecific pseudo-backcross SA569, a total of 115 progeny, as well as the E. oleifera grandparent SA49D, the interspecific parent SA65T, and the E. guineensis parent PO3228D, had been previously analyzed by Montoya et al. [27]  for fatty acid composition and the iodine value of the palm oil in mature fruits. Available individual phenotypic data were used here for a comparative study with the LM2T x DA10D cross. Other phenotypic traits and QTL data available for LM2T x DA10D and SA569 The fruit variety and the individual phenotypic data of 26 vegetative or yield quantitative traits were available from Billotte et al.
Statistical analysis of phenotypic data The iodine value was calculated from the average of all measurements made per palm, as described above. Statistical analyses were performed on phenotypic data for fatty acid composition in the LM2T x DA10D cross. The Gauss distribution of the quantitative data of the cross was checked by the Shapiro-Wilk normality test at the a threshold of 5%. The relationships between phenotypic traits published by Billotte et al. [36]  and the fatty acid proportions estimated in the LM2T x DA10D cross were estimated by calculating Pearson's correlation coefficients at the individual palm level (Table  S2 ). In a second step, the vegetative and production phenotypic data of LM2T x DA10D were standardized as the mean and variance for both dura and tenera varieties to eliminate the Sh major gene effect on traits.
QTL analysis of LM2T x DA10D QTL analyses of palm oil fatty acid composition were performed with MapQTL5  [37]  using the E. guineensis SSR linkage map (Eg_Map) and all available genotypic and phenotypic data for LM2T x DA10D. No QTL analysis of other vegetative or production traits was performed here, as related QTLs are already available in Billotte et al. [36]. Three methods were used for QTL detection as per Montoya et al. [27] : i) A non-parametric Kruskal-Wallis (K-W) test was performed to identify significant marker-trait associations at p, 0. 005. ii) The interval mapping (IM) method was performed with a mapping step size of 1 cM and a maximum of five neighboring markers. To declare the presence of a QTL, the threshold LOD values were estimated at the genome-wide (GW) global risk a of 5% and 1% by the re-sampling method and permutation of the trait data (1000 iterations).
iii) The multiple-QTL model (MQM) method was carried out in conjunction with the automatic selection of cofactors, using the threshold LOD values described above. The threshold value of p,0. 005 in the non-parametric K-W method was adopted on a empiric basis, as it was equivalent in QTL results compared to a GW global risk a of 5% using the different IM and MQM methods. A GW global risk a of 1% was also used in the IM or MQM method to explore the robustness of detected QTL. The confidence interval of each significant QTL by IM or MQM was determined by the LOD -1 method. For the phenotypic values of fatty acids (C16:1, C18:3, C20:0 and C20:1) in trace or in small amounts that did not follow a mixture normal distribution (Figure  S2 ), the Kruskal-Wallis rank sum test was only considered as applicable for data with distributions far from mixture normal distribution  [38].
Acknowledgments The authors are thankful to  Plantation Hacienda La Caban ˜a S. A. (Colombia), Indupalma LTAD (Colombia) , the  Centre de Recherche Agronomique des Plantes Perennes (CRA-PP ) of the  Institut National de Recherche Agronomique du Benin (INRAB) in Benin , the  Indonesian Oil Palm Research Institute (IOPRI) in Indonesia , and the  Centre National de Recherche Agronomique (CNRA) in Cote d'Ivoire  for providing vegetal samples and/or phenotypic data. We are also grateful to  Dr. Brigitte Courtois  ( CIRAD France ),  Dr. Jean-Marc Gion  ( CIRAD France ),  Dr. Brigitte Mangin  ( INRA France ), and  Dr. Dominique This  ( University of Montpellier II, France ) for their scientific advice.
The experiment was part of a PhD fellowship granted by the  Centro de Investigaciones en Palma de Aceite (CENIPALMA) ,  Colombia. This study was funded by the  International Consortium Oil Palm Genome Projects (OPGP)  and its members:  Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement (CIRAD), France ;  Instituto Vasco de Investigacion y Desarrollo Agrario (NEIKER), Spain; Advanced Agriecological Research Sdn. Bhd (AAR) ,  Malaysia; PT Astra Agro Lestari Tbk , Indonesia;  PT Inti Indosawit Subur and its affiliates (Asian Agri Group ), Indonesia;  PT Bakrie Sumatera Plantations Tbk, Indonesia ;  Centro de Investigaciones en Palma de Aceite (CENIPALMA) ,  Colombia ;  Empresa Brasileira de Pesquisa Agropecua  ´ria (EMBRAPA), Brazil;  Felda Agricultural Services Sdn Bhd, Malaysia; Genting Plantations Berhad, Malaysia ;  IOI Corporation Berhad, Malaysia ;  Indonesian Oil Palm Research Institute (IOPRI) ,  Indonesia ;  PT Matahari Kahuripan Indonesia, Indonesia ;  PT SMART Tbk, Indonesia; PT Sampoerna Agro Tbk, Indonesia ; and  SOCFIN Group, Luxemburg.
New challenges are now emerging in these fields with the recent advances in low-cost ultra-fast sequencing, bioimaging and bigdata. As a consequence, databases and software are evolving rapidly, and new algorithms are required to improve computational analyses of massive biological or biomedical data sets. Multi-scale integrative analyses are struggling to deal with the enormous complexity of biological systems modeling and the 'data deluge' that results from nextgeneration sequencing. ECCB is held annually in a different country or region and incorporates the annual national or regional meeting where it is held. Every other year, it is held jointly with the ISMB conference. This year's conference incorporates the 14th French JOBIM ('Journ ees Ouvertes Biologie Informatique Math ematiques'), the annual meeting of the French bioinformatics community.
The industrial and demo track at ECCB'14 provides commercial organizations and academic institutions with the opportunity to present their products or services: software, database, infrastructures, etc. Demo fees give access to two 30-min slots for repeating the demo and reaching a large number of conference attendees. Twelve demos are scheduled, involving among others four ECCB'14 silver sponsors (BioBase, sbv Improver, Koriscale and Totalinux), the French and the Swiss Institutes for Bioinformatics (IFB, SIB), the European Molecular Biology Laboratory (EMBL: Uniprot demo), the French National Institute for Research in Agronomy (INRA: BioMercator demo) and the Galaxy project. A free demo slot was also proposed to several refused paper submissions that described valuable computational methods.
Most other workshops and tutorials are 1-day events, taking place either on Saturday, September 6, or on Sunday, September 7. The very active domain of biological network study is covered by three complementary workshops: (1) 'Logical Modelling and Analysis of Cellular Networks', organized on 1 1 =2 days by Denis Thieffry (Ecole Normale Sup erieure, Paris) and Ioannis Xenarios (Swiss Institute of Bioinformatics, Lausanne); (2) 'BioNetVisA', organized by Ina Kuperstein (Institut Curie, Paris) and colleagues, with the objective of going 'From biological network reconstruction to data visualization and analysis in molecular biology and medicine', and hosting the EMBO lecture by Yosef Yarden (The Weizmann Institute of Science, Rehovot, Israel); and (3) 'Integrative Dynamic Analyses of Large Biomedical Network Data', organized by Natasa Przulj (Imperial College, London) and Tijana Milenkovic (University of Notre Dame, Indiana).
In particular, the advice and experience shared by Torsten Schwede as organizer of the successful ECCB'12 in Basel was invaluable. Thank you Torsten for your almost constant availability! The cooperation and support of ISCB (International Society for Computational Biology) was much appreciated for diffusing the information about ECCB'14 at the international level and for offering student fellowships. We thank all those who provided financial support to the conference, especially our five silver sponsors BioBase, sbv IMPROVER, Koriscale, Totalinux and GPB (Genomics, Proteomics and Bioinformatics, The official journal of the Beijing Institute of Genomics, the Chinese Academy of Sciences and the Genetics Society of China). We also acknowledge support from the French Institute of Bioinformatics (IFB), the French Society for Bioinformatics (SFBI), the CNRS research group on Biology, Computer Science and Mathematics (GDR BIM), the European Grid Infrastructure (EGI), the Research Institutes: INRA, Inria (who sponsored the travel expenses of our keynote speakers), EMBI-EBI and the Italian Society for Bioinformatics that offered student fellowships.
We are grateful to the Oxford University Press production team for the preparation of this special issue and to the staff of the CNRS Alsace regional delegation for taking on the administrative and financial burden of the registration process. We wish to thank the staff at the Congress Centre of Strasbourg and Christine Guibert from the University of Strasbourg for their help in preparing the logistics of hosting the conference, and the city of Strasbourg for providing the ECCB'14 welcome cocktail. Moreover, we are pleased to acknowledge the kind support of the Council of Europe which provided the attendee bags and for agreeing to host the gala evening in its nice reception hall and i347 gardens along the Ill river. We also especially thank Laurence Lwoff, Head of the Bioethics Unit, for her talk scheduled at the conference opening, in which she will share the Council of Europe's concerns about the bio-ethical challenges raised by the usage of biobanks and biomedical data in research and its applications.
Used simulation tools The six partners involved in the comparison study used anything from pure in-house software to fully commercial solutions, but also principles in-between. SINTEF applied a fully in-house software package which constitutes a flowsheet simulator. DTU used a mixture of in-house and Aspen Plus. This means the core rate based columns where developed by DTU which applies to the CAPE-Open standard and the modules can be used in other process simulators implementing CAPE-Open. The remaining partners used Aspen Plus. IFPEN applied an external property package to Aspen Plus. Based on the description in table 4 it can be seen how EDF used a more fine-tuned version, and TNO took advantage of the work by Zhang et al. [2].
The flooding calculations by IFPEN, performed with Aspen plus and KG Tower softwares, show that the column is flooded for the lean loading sensitivity cases <0%. Therefore they are unable to determine pressure loss of the column as indicated in figure 7A. SINTEF is not considering pressure loss and their stripper top pressure is the same as the reboiler pressure. A low pressure loss is calculated by most partners. Only IFPEN seem to calculate a reasonbly high pressure loss, but their calculations also indicate a realtive high degree of flooding, figure  6B. Between partners the calculated pressures are very compareably. It has a low variability, and presuably a lower impact on the final SRD predictions. The reboiler temperature shown in figure  7B  is a direct consequence of the pressure specification in the reboiler, 190 kPa.
If the organization disappears -e. g. , if the Wikimedia Foundation runs out of funds-all the knowledge contributed to the wiki may disappear as well; (iii) No offline access: if a user's internet connection or the central wiki system are temporarily unavailable, the user cannot work; (iv) Handling transactional changes: a user cannot modify multiple pages simultaneously before making modifications visible to other users. All incremental modifications are immediately visible to other users. In some cases, users may observe inconsistent states of the wiki, as in a database system without transactional support  [3] ; (v) Handling disagreements: even when changes to a page are not made with malicious intent, they can still lead to "edit wars"  [4]  when different groups of users disagree on the content that is being contributed and they attempt to cancel or override the other groups' input; (vi) A single point of view: there is only one authoritative entry on each topic, either because only one version is ever kept by the system, or because the latest version is the one that is displayed to the user, and the user typically is not encouraged to compare that latest version with previous ones.
Traditional Wikis According to Ward Cunningham -the creator of the original Wiki-a wiki is "the simplest online database that could possibly work"  [1]. More specifically, it is a collection of Web pages hosted on a server running a wiki engine, which gives them the following characteristics: (1) Page title uniqueness: Each page has a unique title within the wiki; (2) Read-write: A wiki page can be edited directly through a web browser. The textual content of a wiki is usually referred to as wikitext, and is typically written using a simple mark-up language rendered by a wiki engine; (3) Wikilinks: Wikis include internal hyperlinks; these are hyperlinks to other pages of the same wiki, called wikilinks, which are part of the wikitext. The target page of a wikilink can be specified simply by its title, as the title uniquely identifies a page.
However, automatic merge algorithms may produce undesirable results in the meaning of the text; therefore, many algorithms aim to detect the more problematic cases and revert to manual merging. This is the case of Wikipedia. Both strategies require extending the data model of a page. Additional information is necessary to detect editing conflicts: either a flag must be added to indicate the page being locked, or a timestamp must be used to identify out-of-date versions. The cost of the edit operation, as measured by the message complexity, differs depending on the chosen strategy. In the case of manual merges, the process will require many back-and-forth messages, as each user must reload the page and resubmit the resolved conflicts. If m users concurrently edit a page and they all save their changes, then the total number of messages exchanged between the clients and the server is m 2 + 3m -2  [17].
In the following sections, we will represent these choices using the formal concepts introduced so far. We show how the data model and operations of traditional wikis are extended for distributed wikis: Highly Available Wikis, Decentralized Social Wikis and Federated Wikis. The change propagation and conflict resolution strategies strongly define the collaboration model supported by a distributed wiki. We will illustrate the different collaboration models supported by these distributed wikis through extensions of the scenario given for the Wikipedia example (fig. 3 ).