dataesr/scientific-paragraphs-categorization huggingface dataset:
LeishCyc  (7) , for the related parasite L. major, has also been established, and in the future these two databases should, ideally, be linked, given the significant degree of similarity in the metabolic networks of these evolutionarily related parasites. TrypanoCyc and the related annotation database allow anyone with an interest to join the annotation team. The size of the consortium helps guarantee the sustainability of TrypanoCyc as does the involvement of permanent staff both at INRA, Toulouse, and the University of Glasgow. The Toulouse bioinformatics facility provides the Try-panoCyc server. TrypanoCyc is freely available and is not password protected. TrypanoCyc database content can be mined in a pathway-oriented manner using the BioCyc-like web interface but also in a network perspective using the MetExplore web server, which allows tailored building and visualization of sub-networks.
FUNDING European Commission  FP7 Marie Curie Initial Training Network 'ParaMet ' [290080 to S. S. ];  ANR  project  MetaboHub  [ ANR-11-INBS-0010  to B. M. ];  Wellcome Trust  [ 085349 ]; The work of  Fiona Achcar  was part of the  SysMO SilicoTryp  project coordinated by  R. B. Funding  for open access charge:  European Commission   FP7 Marie Curie Initial Training Network 'ParaMet ' [290080].
Introduction The history of computing and Artificial Intelligence in particular in USSR and Ukraine is not widely known. One reason is the publication language which was mainly Russian. As not a historian by profession, but taking part in this research, we wish to share with the lecturers the contribution of remarkable people and ideas born in Soviet times in a hope that it could be interesting and inspiring. It is followed by a description of the General Knowledge Machine Group research work, based on the previous experience and a new insight. It represents an original approach to knowledge presentation and learning developed in Kiev, Ukraine. Excerpts and pictures from Website called "Development of Computer science and technologies in Ukraine" are included by permission from the International Charity Foundation for History and Development of Computer Science and Technique ICFCST http://www.
Results Early versions of General Knowledge Machine were developed for UNIX, MS-DOS, Windows operating systems. The latest version supports all platforms of GNU compiler options (any Windows, Linux, UNIX. ). There are working products which can be presented to experts in corresponding areas. Products were tested in various environments -business, medicine, arts. Papers were published in Russia, Italy and UK. The work was featured in the 2006-2007 Edition of the Marquis Who's Who in Science and Engineering as a pioneer research.
Special care has been taken to account for uncertainty in MH retrieval in this estimation process. MHs and CO 2 concentrations were compared to vertical profiles from aircraft in-situ data. We put an emphasis on testing the consistency of estimated MHs to observed vertical mixing of CO 2. Modelled CO 2 was also compared with continuous measurements made at Cabauw and Heidelberg stations. WRF MHs were significantly biased by ∼10-20 % during day and ∼40-60 % during night. Optimized MHs reduced this bias to ∼5 % with additional slight improvements in random errors. The KED MHs were generally more consistent with observed CO 2 mixing. The use of optimized MHs had in general a favourable impact on CO 2 transport, with bias reductions of 5-45 % (day) and 60-90 % (night). This indicates that a large part of the found CO 2 model-data mismatch was indeed due to MH errors.
The use of real observations introduces two further complications in comparison to a synthetic data experiment: (1) the true MH isn't known exactly due to measurement errors, data limitations and methodological uncertainty  (Seidel et al. , 2012)  and (2) a verification of the method by comparing simulated and observed CO 2 abundances is rendered difficult as the observed signal is a result of both, surface fluxes and transport. The first is the very same quantity that we have limited knowledge about and that an atmospheric inversion tries to solve for (or optimize). The latter is affected by other uncertainties besides those in MH  (Gerbig et al. , 2009) , e. g. , deep convection, or horizontal advection. We tried to cope with complication (1) by objectively estimating the uncertainty for each individual MH estimate based on an analysis of high resolution radiosonde profiles, which are part of the UK meteorological office (UKMO) database.
(2013). Since the 12 h resolution of the IGRA data is too coarse to constrain the variogram model sufficiently, we make use of the hourly MHs from the WRF simulations, assuming that the resulting semivariance closely resembles the true variability. This assumption is reasonable since we have chosen PBL schemes that were shown to realistically simulate PBL dynamics  (Hu et al. , 2010). We sampled WRF MHs again separately for day and night. Because we have used WRF MHs as the MH data points, i. e. synthetic data, instead of real IGRA data we can not use the same WRF MHs as trend to calculate the residual terms (Res Zi ) in Eq. (  7 ). Instead we follow the usual procedure to model the diurnal pattern in the WRF MHs as deterministic trend using an oscillating sinusoidal function. The residuals between this model and the WRF MH were then used to compute Eq.
Back Close Full To prescribe combustion fluxes we make use of the 2005 Emission Database for Global Atmospheric Research (EDGAR) on a 0. 1 • × 0. 1 • grid to consider anthropogenic flux contributions (Source: EC-JRC/PBL. EDGAR version 4. 1. http://edgar. jrc. ec. europa. eu/, 2010). Similar to  Steinbach (2010)  we extrapolated country total emissions to the year 2009. The extrapolation is based on BP statistics obtained from http://www. bp. com/statisticalreview. These emissions were then spatially distributed down to the grid level based on the 2005 dataset. Time factors were obtained from the EDGAR database and then applied to yearly fluxes to resolve the daily cycle. Contributions from oceanic fluxes were accounted for by including the  Takahashi et al. (2009)  climatological inventory for the reference year 2000 and revised in October 2009 provided monthly with a spatial resolution of 4 • × 5 •.
CO CO is used as auxiliary tracer to isolate impact from combustion fluxes on CO 2 signals. Initial and boundary conditions for the CO transport were obtained from re-analysed 4-D fields provided as part of the Monitoring Atmospheric Composition and Climate (MACC) project (source: http://data-portal. ecmwf. int/data/d/macc_reanalysis/). The MACC re-analyisis is provided on a 6 hourly, 1. 125 • × 1. 125 • grid with 60 vertical levels. Similar to the CO 2 tracer we obtain anthropogenic emission from EDGAR (Sec. 2. 4. 1). The impact of fire emissions are considered by including flux fields from the Global Fire Emissions Database (GFED; source: http://www. globalfiredata. org) in version 3. 1. We used the 3 hourly fields on a 0. 5 • ×0. 5 • grid  (Mu et al. , 2011). The major sink for CO is atmospheric destruction by hydroxyl radical OH which is computed within STILT.
Evaluation of MH optimization We assessed the skill of the KED optimization by cross-validation, such that each of the 6722 IGRA samples was temporarily excluded from the data set and then estimated with the remaining data. Table  2  shows the results of the cross-validation, which was executed with and without taking MH uncertainty into account to test the validity of the assumptions stated in Sec. 2. 2. 1. A small but significant bias on the order of a few percent remains for some simulations, which decreases when taking MH uncertainty into account. Random errors slightly decrease during day, but are reduced notably when considering MH uncertainty. The correlation values stay at the level before the optimization with rather low values for the case neglecting MH uncertainty. The KED errors were reasonably estimated, from a normal distribution we would expect 68 % of the observed MH to lie within one standard deviation and 95 % within the confidence interval of the KED estimate.
Additional MH data The IGRA data set is limited especially in the temporal resolution. The KED estimation error is a tool that can help to guide the installation of future instrumentation. A particularly promising data set can be obtained from lidars or ceilometers, that are able to continuously observe aersosol backscatter signals, from which MH can be retrieved at relatively low cost  (Eresmaa et al. , 2006). Networks of lidars and ceilometers are already operated throughout Europe  (Haeffelin et al. , 2012). Within the Integrated Carbon Observation System (ICOS 3  ) project a network of atmospheric measurement stations is build for which MH measurements are mandatory for level 1 continental stations. In addition,  Jordan et al. (2010)  demonstrated the retrieval of the PBL heights from satellite based lidar data.
Conclusions We evaluated a method to interpolate MH estimated from data of the IGRA database using the KED approach. The impact of the resulting optimized MHs on regional tracer transport was assessed by comparing two STILT simulations with different kinds of WRF PBL parametrizations (MYJ and YSU) to observations. Referring to the questions posed in the introduction we summarize and conclude: 1. Significant biases in CO 2 at CBW, where the diurnal evolution of CO 2 was captured well, were approximately 7-9 % (day) and 60 % (night) of the regional signal. 2. Simulated MHs were significantly biased with values of -20 % (MYJ) to 10 % (YSU) at day and 40-60 % at night, respectively. RMSE was on the order of 90-116 % with larger values for the YSU scheme. Because of these results, we conclude that mismatches in MHs lead to significant bias and random error in tracer concentrations.
Therefore, biased flux estimates due to mismatches in simulated MHs have to be expected, when using comparable high-resolution transport models in regional-inversions. 3. We conclude that the IGRA data set generally provided enough conditioning data to estimate nearly unbiased MH fields. Biases were reduced from up to 77 % to below 10 % in the cross-validation. RMSE was reduced by up to 30 %, r 2 was unaffected at ∼40-60 %. However, comparison at CBW showed a sensitivity of the estimation to the WRF model in terms of differences in advection and the MHs used as external drift. The latter effect could be mitigated by using additional nighttime MHs observed at CBW. Additionally, we found that models could not reproduce the phasing of the CO 2 diurnal cycle at HEI, which is likely the result of improper modelling of the timing of MH development.
Methods/Design: We conducted a systematic review to identify randomized controlled trials with a low-molecularweight heparin intervention for the prevention of recurrent placenta-mediated pregnancy complications. Investigators and statisticians representing eight trials met to discuss the outcomes and analysis plan for an individual patient data meta-analysis. An additional trial has since been added for a total of nine eligible trials. The primary analyses from the original trials will be replicated for quality assurance prior to recoding the data from each trial and combining it into a common dataset for analysis. Using the anonymized combined data we will conduct logistic regression and subgroup analyses aimed at identifying which women with previous pregnancy complications benefit most from treatment with low-molecular-weight heparin during pregnancy.
IPDMA has been proposed as an advantageous methodological approach when subgroup analyses are hypothesized to be clinically relevant. Analyzing original data from individual patients makes use of a much richer dataset and has greater statistical power than conventional metaanalysis  [31, 32]. Furthermore, for this project, IPDMA will allow for adjustment for covariates that are known to be important in the recurrence of placenta-mediated pregnancy complications. Such an analysis will also enable us to explore clinical, methodological, and statistical heterogeneity more robustly. IPDMA is an attractive method to answer our study questions since it 'dramatically and consistently' has more power to detect interactions between risk groups  [33].
We will synthesize individual patient data from RCTs of LMWH for the prevention of recurrent placenta-mediated pregnancy complications. The overall objective of the meta-analysis is to directly inform clinical practice and the development of clinical practice guidelines. The study is coordinated by the Clinical Epidemiology Program at the Ottawa Hospital Research Institute. Conceptually, the research approach involves four sequential phases: a systematic review, knowledge synthesis planning, data extraction and analysis, and interpretation of results and knowledge translation. The first two phases have been completed and are therefore described below in the past tense. No data have been extracted or recoded for the common dataset and no statistical analyses have been performed; these steps are outlined in the future tense.
Systematic review Electronic search strategies were developed and tested through an iterative process by an experienced medical information specialist in consultation with the review team. The strategy was peer-reviewed prior to execution by an experienced information specialist using the Peer Review of Electronic Search Strategies (PRESS) checklist  [34]. The following search was conducted in May 2013: using the OVID platform, we searched Ovid MEDLINE™, Ovid MEDLINE™ In-Process & Other Non-Indexed Citations, and EmbaseClassic + Embase (strategy included as Additional file 1). We also searched the Cochrane Library on Wiley (including CENTRAL, Cochrane Database of Systematic Reviews, DARE, and HTA). Clini-calTrials. gov and the WHO International Clinical Trials Registry were searched to identify relevant in-process and completed trials.
Strategies utilized a combination of controlled vocabulary (such as 'hypertension, pregnancyinduced' , 'placental insufficiency' , 'heparin, low-molecularweight') and keywords (pre-eclampsia, abruption, and LMWH). Vocabulary and syntax were adjusted across databases. Animal studies were excluded but there were no language or date restrictions on any of the searches. We sought additional references through hand- searching the bibliographies of relevant items. Search results are summarized in a preferred reporting items for systematic reviews and meta-analyses (PRISMA) diagram (Figure  1 ) and details of potentially eligible trials are provided in Tables  2  and 3.
Inclusion criteria RCTs with an LMWH intervention for the prevention of recurrent placenta-mediated pregnancy complications were eligible. The study population of interest included currently pregnant women with prior pregnancies complicated by one or more of the following: PE, placental abruption, SGA newborn (<10 th percentile), pregnancy loss after 16 weeks gestation or two losses after 12 weeks gestation. The principal investigators of potentially eligible trials identified by the systematic review (see Tables 1, 2 and 3) were contacted via email to request additional information about the study population. Once eligibility was confirmed, investigators were invited to participate in the IPDMA and attend the AFFIRM project planning meeting. The lead investigators of the largest and most recently completed trials agreed to contribute individual patient data to this collaboration.
Data from two small trials  [22, 41]  were not included because the investigators did not respond; in one of these trials only a small proportion of the total study population would have been eligible to contribute data to AFFIRM  [41]. Some of the women in the Scottish Pregnancy Intervention Study (SPIN) trial would have been eligible for inclusion in AFFIRM, however, the trial database does not include sufficient detail about the timing of previous pregnancy losses to determine the eligibility of individual participants  [39].
Knowledge synthesis planning A crucial step in the success of the project was the development of the knowledge synthesis and knowledge translation plans. A full-day review team meeting was held in Amsterdam on 4 July 2013. The purpose was to allow for extensive discussion and consensus-reaching on important study variables and outcomes and to consider strategies for merging the existing datasets in a centralized database. Participants included the principal investigators of the included RCTs and statisticians with in-depth knowledge of the trial data. The principal investigators are all practising clinicians (obstetricians and hematologists) who are also knowledge users in this clinical area.
Extraction and recoding of individual patient data The definitions for each variable to be included in AFFIRM's common dataset are documented in a data dictionary to allow standardization across studies and decrease the potential for misclassification and bias. A template for the common dataset has been developed in Microsoft Excel and will be provided to the principal investigator of each included trial. Recoded anonymized individual patient data from each of the trials will populate the Excel template. The recoded datasets for each of the individual trials will be saved on an IronKey™ USB flash drive and sent by courier to the coordinating center in Ottawa. The AFFIRM common dataset will include individual patient data in 10 pre-defined categories: administrative and demographic data, thrombophilia, maternal medical history, pregnancy history, current pregnancy and delivery, infant data, pre-eclampsia outcome, other outcome events, intervention and treatment during pregnancy, and adverse events.
Data synthesis, validation and analysis Once the individual participant data from the primary studies have been merged in the common dataset, descriptive analyses will be conducted to identify data outliers, missing data, and unexpected inconsistencies. The project coordinator will prepare data clarification reports and will communicate with the principal investigators or their delegates to resolve these queries. Next, we plan to conduct preliminary analyses aimed at replicating the findings of the individual published studies, to validate the centralized database and data importation. Once the IPDMA team is satisfied with the merged dataset, the database will be locked and the planned analyses for the IPDMA synthesis will be conducted. The individual patient data will be analyzed in a similar manner to an RCT, however, the analysis will account for clustering at the study level.
These assessments will also be used to inform subgroup analyses and sensitivity analyses to explore whether these biases may have affected the IPDMA analysis. We plan to examine the randomization integrity once the data from the original trials have been combined. We will endeavour to compare the original randomization lists with actual randomization to test the integrity of the allocation concealment. We will also compare the baseline characteristics of participants who have been randomized to the LMWH and no LMWH groups at the study level and aggregate level to see if there are imbalances between the groups that may suggest a lack of integrity in randomization processes.
Ethics, privacy and security The subjects in each of the RCTs all provided informed consent to participate in the original trial. We will not be seeking individual consent for the secondary use of the data for the following reasons: the objectives of the IPDMA are consistent with the original trials, there are no risks or benefits associated with this analysis, no identifying information will be transferred, and it would be logistically time consuming and, in some cases, impossible to contact the women who participated. In order to ensure patient confidentiality any identifying information will be removed from the original dataset before it is transferred. The IronKey™ flash drive includes numerous security features including hardware-based encryption, a random password generator, two-factor authentication, and a self-destruct mechanism which make it extremely unlikely that the dataset can be accessed by anyone other than the intended recipient.
Limitations and challenges One relevant potential drawback of IPDMA is biased pooling of data. Bias can be introduced when eligible studies are missed, when authors do not provide their data for the analysis, when the outcomes are different across studies, and when outcome and covariate data are missing from included studies  [31]. Our recently completed pooled summary meta-analysis was a successful collaboration of five principal investigators  [1]. In addition to the team members from these five trials, the principal investigators of four additional trials have committed to provide data for the AFFIRM meta-analysis. These are the largest and most robust trials completed in this area. The multinational research team has representation from Canada, the Netherlands, France, Italy, Germany, and Finland.
Almost all review team members attended the face-to-face IPDMA planning meeting. To protect against the misclassification of outcomes, the AFFIRM review team discussed each outcome at this meeting until consensus on detailed definitions and diagnostic criteria was reached. Definitions for all variables to be included in the IPDMA common dataset are documented in a data dictionary that was reviewed, revised according to team feedback, and finalized. Despite this, we recognize that challenges will be encountered due to variability in how the variables were originally defined and collected in each of the nine trials. In some cases it will be necessary to consult the original clinical records to obtain complete information for the IPDMA which will be a labor-intensive process. Another challenge is the diversity in language of the original datasets (English, French, Dutch, Italian, and German) that will necessitate translation when the data are recoded.
Acknowledgements This collaborative meta-analysis based on individual patient data is funded by a  Knowledge Synthesis Grant  from the  Canadian Institutes of Health Research (CIHR) , reference number  KRS 126593. The authors would like to acknowledge the contribution of  David Moher  who provided methodological advice during the conception and design of the project. The Knowledge Synthesis Group at the  Ottawa Hospital Research Institute  also played an important role during the systematic review:  Raymond Daniel  downloaded the records from the searches, removed duplicates, and obtained the full-text articles and  Kavita Singh  screened the titles and abstracts of citations to assess potential eligibility.
These extremely efficient simulators haven't, up to now, been used in statistical mechanics. Although well adapted to mechanical simulations, physics engines lack coupling to a thermal bath. The main novelty of our approach is the implementation of Langevin-Euler equation in the ODE software. Moreover we improve the simulation efficiency of this Langevin dynamics by extending the ''global thermostat'' algorithm designed by Bussi and Parinello in 2008  [19]  to physics engines. This algorithm allows much faster yet unbiased sampling of the phase-space. As a first step toward simulating DNA-protein assemblies, we focus here on bare DNA and show how to perform in silico single molecule manipulation of DNA.