dataesr/scientific-paragraphs-categorization huggingface dataset:
Histograms of the percent relative differences between SB and GB UVI data are located to the left and correlation diagrams are located to the right. Crosses circled in blue (for OMI) or turquoise (GOME-2) correspond to a COD of less than or equal to 1. Notice that the GOME-2 data set is smaller than the OMI data set because there is only one value per day and no value when SZA at noon is larger than 70 •. The data show a medium dispersion around relative difference means (SD nearly 40 %, means nearly 21 %), the correlation between SB and GB UVI is strong (correlation coefficients r ∼ 0. 95) and the regression lines have a slope larger than unity (1. 08±0. 01 for OMI, 1. 12 ± 0. 01 for GOME-2) with a small intercept. Satellitederived UVI is larger than GB UVI (positive relative difference) in 78 % of cases for OMI and in 73 % for GOME-2.
(2008) , and  Paur and Bass (1985)  ozone absorption cross sections. For the other input parameters, we take the total ozone column (TOC) from OMI (OMTO3), aerosol data from the sun photometers of the AERONET/PHOTONS network  (Holben et al. , 1998)  (we use daily or monthly means of the aerosol optical depth (AOD) at 440 nm, the Ångström exponent (between 440 and 870 nm) to derive the spectral AOD, the single scattering albedo (SSA) at 440 nm) and the surface albedo from  Feister and Grewe (1995). The other input parameters used in the RT model are the midlatitude ozone, temperature and pressure profiles. Note that the sun photometers are operating next to the spectroradiometers. We have compared the simulated UVI to both OMI and GB UVI for several cloud-free cases. The histograms of the percent relative difference between the computed UVI and the measured one are reported in Fig.
5a  for GB UVI and Fig. 5b  for OMI. GB UVI measurements are 1. 7 % lower and OMI UVI are 4. 7 % higher than the simulated UVI, each value being within GB and OMI measurement uncertainty, respectively. Since the TOC is the same for both modelling and OMI, this overestimation of OMI UVI might be mainly related to aerosol parameters and surface albedo, though this parameter value is small. Of course part of the bias might come from differences between the two RT models used and also between the other input parameters. Kazadzis et al. (2009b)  concluded also with an overestimation due to aerosol variability (in time and space). Of course, we have to keep in mind that modelling computations are affected by uncertainties. For this previous modelling, we have chosen OMTO3 but other TOC data could be used, such as the TOC derived from the GB spectra following the method described in  Houët and Brogniez (2004) , relying on a differential absorption technique  (Stamnes et al.
Acknowledgements. Colette Brogniez  thanks several LOA members:  L. Labonnote  for helpful discussions,  R. De Filippi  for automation of data transfer and  F. Ducos  for writing a helpful script. P. Goloub  and  T. Podvin  are acknowledged for their help in selecting the AERONET/PHOTONS data. The sites are supported by  CNES  within the  French program  TOSCA. The SDR site is also supported by " la région La Réunion ". Development of the OUV product has been partly funded by  EUMETSAT. Edited by:  H. Maring Reviewed  by: three anonymous referees.
Sea surface temperature (SST) estimated from the Advanced Microwave Scanning Radiometer E onboard the Aqua satellite and altimetry-derived sea level anomalies are used south of the Agulhas Current to identify warmcore mesoscale eddies presenting a distinct SST perturbation greater than to 1 • C to the surrounding ocean. The analysis of twice daily instantaneous charts of equivalent stabilityneutral wind speed estimates from the SeaWinds scatterometer onboard the QuikScat satellite collocated with SST for six identified eddies shows stronger wind speed above the warm eddies than the surrounding water in all wind directions, if averaged over the lifespan of the eddies, as was found in previous studies. However, only half of the cases showed higher wind speeds above the eddies at the instantaneous scale; 20 % of cases had incomplete data due to partial global coverage by the scatterometer for one path.
M. Rouault et al. : Wind changes above warm Agulhas Current eddies Rainfall Measuring Mission (TRMM), allowed us to demonstrate the impact of mesoscale oceanic features on the overlying atmosphere  (Xie, 2004; Chelton and Wentz, 2005). Chelton et al. (2000)  and  Hashizume et al. (2001)  have combined wind stress estimates from QuikScat and TMI SST in the eastern tropical Pacific to study the impact on the atmosphere of tropical instability waves, oceanic features with periods of 20 to 40 days and wavelengths of 1000-2000 km. Chelton et al. (2004)  used 4 years of filtered QuikScat data to show a ubiquitous picture of mesoscale ocean-atmosphere interaction linked to SST heterogeneity such as fronts, western boundary currents and tropical instability waves. TMI SST, QuikScat wind speed estimate and in situ observations were also used by  Nonaka and Xie (2003)  to reveal SST and wind speed covariability over the Kuroshio Extension east of Japan.
O'Neill et al. (2005)  used filtered monthly AMSR-E SST and QuikScat data to show that the wind stress increases and decreases as it goes over warm and cold meanders of the Agulhas Return Current, respectively. Filtering the data on a large domain, they found a linear relationship between SST perturbation and wind stress. Spatial filtering was used to remove the effect of energetic weather disturbances and remove features with wavelengths longer than about 30 • of longitude and 10 • of latitude  (Chelton, 2004 , O'Neill et al. , 2005). Rouault and Lutjeharms (2000)  measured high values of latent and sensible heat fluxes above a warm eddy south of the Agulhas Current during the SAAMES (South African Antarctic Marine Ecosystem Study) 3 cruise in June 1993. There was a clear homogeneous increase in wind speed estimate estimated with the European Research Satellite 1 (ERS-1) satellite above this warm eddy, which showed a 6 • C perturbation compared with surrounding ocean.
Data SST was derived from the AMSR-E, launched in 2002 by NASA. It is a passive microwave radiometer with six frequencies that measures brightness temperature at 6. 9 GHz, for a 90 % complete global ground coverage within a day, with an accuracy of 0. 4 K  (Chelton and Wentz, 2005). In this investigation, we use weekly data produced by the Remote Sensing System (RSS) at a resolution of 56 km. We used twice daily equivalent stability-neutral surface instantaneous wind speed and direction estimated by the SeaWinds scatterometer on the QuikScat satellite. It is QuikSCAT Version 3 Level 2B Ocean Wind Vectors available in 25 km swath grid and produced by Remote Sensing System. Weekly sea level anomalies (SLA) were obtained from Centre national d'études spatiales (CNES). They are given on a one-third of a degree grid  (Ducet et al.
, 2000). They are based on merged observation of the TOPEX/Poseidon, the European Research Satellite 2 (ERS-2) and the Jason-1 altimeters. We also used surface current from GlobCurrent. Surface current was used to make sure that wind data upstream and downstream of the warm-core eddies were not influenced by the eddies' vorticity at their border as the eddies' speed at the border can be on the order of 1 m s -1. The GlobCurrent product is an optimal analysis of surface current at two different depth (surface and 15 m depth) from a number of satellite and in situ observations, it includes 3-hourly geostrophic Ekman and Stokes components of surface current at 1/4 • resolution for the period 2002 to 2014 and will be extended to 1993-2015. Its main interest is for the open ocean, away from the coast, where the tidal component is likely to be negligible.
Wind speed, SST and SLA were also digitally saved in a common latitude-longitude matrix format. We followed the evolution of the six eddies individually and recorded all cases with SST perturbation above 1 • C. We selected 904 situations spread over the lifetime of the eddies. However, 20 % of the cases had no data above eddies mainly because the satellite path sometimes misses the com- plete eddy or part of it as well as its surrounding water or there is rainfall contamination. This left us with 711 cases. To quantify the relationship between SST perturbation, wind speed increase above eddies and wind speed decrease downstream, we looked at the statistics of the merged data set of cases that presented a wind speed increase above eddies and a decrease downstream and cases that did not. The eddy SST centres ranged from 19 to 12 • C with SST perturbation of up to 6 • C for a mean gradient of 2.
Most of the cases of  O'Neil et al. (2005)  have SST perturbation between -1 and 1 • C, which is clearly too low  (Rouault and LeeThorp, 1996; Lee-Thorp et al. , 1999; Rouault and Lutjeharms, 2000; Rouault et al. , 1995 Rouault et al. , , 2000)). However, in the same region, O  'Neill et al. (2012, Fig. 4)  show an approximate linear relationship for negative SST anomalies and wind speed decrease for (absolute) SST anomalies larger 1 • C, but for positive SST anomalies larger than 1 • C the linear relationship in their figure levels off. Another study in the region shows that the linear relationship levels off for gradient greater than to 1 • C (Supplementary Fig. S4  in  Frenger et al. , 2013). To exclude the fact that wind speed increases over eddies merely were not apparent in along-wind direction due to a large-scale wind deceleration, we looked at 924 cases of wind parallel to warm-core eddies and recorded data on each side and in the centre of the eddies, and the conclusions are quite similar as for the 340 cases where the wind increased above eddies and decreased downstream: a.
Acknowledgements. We thank the reviewers, especially referee no. 3 for his thorough reviews and useful comments that greatly improved the manuscript. Mathieu Rouault  wishes to thank  ESA   GlobCurrent  project, ACCESS,  NRF , the  Nansen-Tutu Center for Marine Environmental Research, IRD  and the  South African Water Research Commission  for financial support. AMSR-E and twice daily wind data were produced by Remote Sensing System, http://www. ssmi. com,and sponsored by  NASA's Earth Science Information Partnerships (ESIP) : a federation of information sites for Earth Science; and by  NASA's TRMM Science Team. Thanks to AVISO,  CNES  and  CLS  for making the T/P ERS JASON merged product available. GlobCurrent products are available for free thanks to ESA funding under GlobCurrent  DUE  project  AO/1-7472/13/I-LG.
Drug sales When people fall sick, they either go to see the doctor, treat themselves with home remedies, or practice self-medication by purchasing non-prescription remedies from a drugstore. In the latter case, sales data are entered electronically in store databases. These data are interesting for infectious disease surveillance because they reflect customer behaviour. Indeed, the class of drug sold, the quantity, and the date of purchase can provide significant information on the age distribution, size, and level of access to health care of a given population. 21.
Medical records When patients attend for medical examinations, physicians ask them questions to collect useful information on their health status, including the date of appearance of the symptoms and their progression over time. These data help physicians define the symptoms affecting the patient. Next, the physicians physically examine the patients to collect data on the signs of the disease. Together, signs and symptoms help the physicians to assign a differential diagnosis and create a list of probable diseases that may be affecting the patient. These records are translated into codes using the International Classification of Diseases, ninth revision (ICD-9). These codes can then be grouped into syndromic categories. 16, 21, 22.
31 The latest version of ESSENCE, ESSENCE II, performs integrated surveillance by analysing de-identified data from the National Capital Region military and civilian health department data. 31 The data collected by ESSENCE II include information on military ambulatory visits and prescription medications, and various data from civilian databases including chief complaint data from civilian emergency departments. 31 Once received, the data are archived and analysed. ESSENCE II transfers information to its users via secure websites. 31 o summarize, users can see data and results in different formats, including a map of the geographic distribution of data sent by users and clusters obtained by scan statistics or lists of alerts emitted after the detection processes. 31 ESSENCE II normally analyses data every 4 h but can also alter the processing period if real-time data are available.
Current impact of laboratories on infectious disease surveillance To evaluate the importance of laboratories in the worldwide surveillance of infectious diseases, a PubMed search of papers in English published between 2009 and June 13, 2014 was conducted. The following keywords, always followed by ''infectious diseases'', were used: ''surveillance system'', ''laboratory-based surveillance'', ''syndromic surveillance'', ''sentinel surveillance'', ''integrated surveillance'', and ''population-based surveillance''. Only surveillance systems using laboratory data were registered. If more than one article described the same surveillance system, the surveillance system was recorded only once. The systems were then tagged according to what they monitor (bacteria, viruses, fungi, parasites, or others), whether they are recognized nationally or internationally, and whether they perform syndromic or diseasespecific surveillance (Supplementary Material Table  S1 ; Fig.
40 Nevertheless, thanks to the global spread of Internet use and the unprecedented interconnectivity of people that this allows, it can be speculated that, in the future, improved syndromic surveillance systems will be coupled with disease-specific surveillance systems, as has already been done for influenza surveillance. 17 any surveillance systems survey few pathogens and not necessarily throughout the year. The surveillance of infections needs to be more global and instantaneous. This is a prerequisite for the detection and notification of abnormal events related to infections, appropriate prioritization of public health threats, and the implementation of optimal strategies and policies. Such approaches appear increasingly feasible with the tremendous expansion of computer resources, networks, and the real-time acquisition and sharing of data worldwide.
Perspectives Recent measurements of the cross section for e + e -→ hadrons at energies less than 5-10 GeV have played a major role in particle physics. The increase in precision and completeness of these data have been essential for progressing in important areas of the electroweak and strong sectors. However even better measurements are necessary to match future needs. Fortunately, the BABAR ISR programme is near completion with results on the few last significant processes to be published soon. Also new experiments are underway: CMD-3 and SND-2 at VEPP-2000, BES3 at BEPC2, and in the future Belle-2 at SuperKEKB. Experimental progress requires an even better control of systematic uncertainties and also resolving inconsistencies in the present data which limit the accuracy of the combined results.
Acknowledgements. We are thankfull to  A. Diez  and an anonymous referee for helping to improve the paper. Maurine Montagnat is supported by the  French CNRS  ( Centre National de la Recherche Scientifique ) and the institutes  INSIS (Institut des Sciences de l'Ingénierie et des Systemes)  and  INSU (Institut National des Sciences de l'Univers). Edited by: O. Eisen Reviewed by:  A. Diez  and one anonymous referee.
ACKNOWLEDGEMENTS We are grateful to  E. Izaurralde ,  N. Kim ,  G. Meister ,  A. Dziembowski  and  R. A Anderson  for the gift of plasmids and antibodies. We also thank the  IGBMC Microarray and Sequencing platform, member of the France Genomique program , for the sequencing of our libraries. We thank all members of the  Pfeffer laboratory for discussion , and  Sophie Cooke  for technical assistance.
FUNDING This work was funded by the  European Research Council  [ ERC starting grant  ncRNAVIR  260767 ] and has been published under the framework of the  LABEX :  ANR-10-LABX-0036  NETRNA and benefits from a funding from the state managed by the  French National Research Agency  as part of the  Investments for the future program. Funding for open access charge:  European Research Council  [ ERC starting grant  ncRNAVIR  260767 ].
Acknowledgments The authors gratefully acknowledge  A Bourret  and  G Hugon  for their technical support in the laboratory and all of the team from " La Solane" and "La Vallonie" Pulmonary Rehabilitation Centers  for their contribution to this work. Nicolas Molinari  is acknowledged for the statistical analysis and  C Stott  for a critical reading of the manuscript. L Ducros  is acknowledged for the critical analysis of muscle capillarization. This study was supported by joint grants from the  Centre Hospitalier Universitaire (CHU)  and the patient association, Association pour l'Assistance Respiratoire au Domicile.
To the best of our knowledge, there is only one SAR available to estimate hydration constants  (Raventos-Duran et al. , 2010) ; it is provided by the GROMHE (GROup contribution Method for Henry's law Estimate) SAR for Henry's law constants. This SAR is based on five descriptors and is optimized on a dataset comprising 61 species. Raventos-Duran et al. (2010)  defined a global descriptor, "tdescriptor", to represent functional group interactions with the sum of the so-called sigma Taft values (σ * , e. g. ,  Perrin et al. , 1981). Similarly, "hdescriptor" is a global descriptor representing the inductive effect of functional groups attached to an aromatic ring through the sum of the meta-, para-and ortho-Hammett sigma values (σ m , σ p and  0. 08  Cooper and Redfield (1975)  α-ketoisovalerate  Cooper and Redfield (1975) CH 3 C(CH 3 )C(= O)C(= O)(O -) 0.
Acknowledgements. The authors acknowledge  French National Agency for Research (ANR)  project  CUMULUS ANR-2010-BLAN-617-01  for providing financial support. The authors are very grateful to the  Agence Nationale de la Recherche (ANR)  for its financial support through the  BIOCAP  project ( ANR-13-BS06-0004 ). Part of this work was also supported by  CEA/CNRS  through contract  CEA 12-27-C-DSPG/CAJ -CNRS 77265. Edited by:  S. Bekki Reviewed  by: two anonymous referees.
Code availability. The mechanism used in this paper is available in KPP format upon request to l. deguillaume@opgc. univbpclermont. fr. Any suggestions and corrections to the mechanism (e. g. , a new experimental rate constant we may have missed, typos) are also welcomed at the same address. The modified version of DSMACC (originally downloaded at https://github. com/barronh/ DSMACC) that was used for the simulations is also available upon request to l. deguillaume@opgc. univ-bpclermont. fr. The Supplement related to this article is available online at doi:10. 5194/gmd-10-1339-2017-supplement.
). Following the same method as Raventos-Duran et al. (2010), multiple linear regression optimization is performed by minimizing the sum 1342 C. Mouchel-Vallon et al. : CLEPS 1. 0 of squared errors (SSE): SSE = n log K hyd,est -log K hyd,exp 2 , (2) i=1 where n is the number of experimental values in the database (n = 65), including both the values compiled and taken into account by Raventos-Duran et al. (2010) and the new carboxylate values. Figure 1 shows both the previous and updated values of the descriptors and the performance of the SAR. The new optimization for carboxylate compounds modifies the descriptors by at most 50 % for the intercept. The other descriptors vary from 1 % ("hdescriptor") to 18 % ("ketone flag") of their initial values. There is greater uncertainty associated with this new optimization; the root mean square error RMSE = 1 n i=1 n log K hyd,est -log K hyd,exp 2 is 0.
Background: The epidemiology of soil-transmitted helminth (STH) and Plasmodium co-infections need better understanding. The findings of the individual studies are inconclusive. A systematic review was conducted to synthesize evidence on the association of STH infection with the prevalence and density of Plasmodium falciparum infection, and its effect on anaemia among children in sub-Saharan Africa (SSA). Methods: Relevant studies published before March 6, 2015 were identified by searching Medline (via Pubmed), Embase, Cochrane Library and CINAHL without any language restriction. Studies on P. falciparum and STH co-infection among children in SSA except for case studies were included in this study. Studies were screened for eligibility and data extracted independently by two authors. The primary outcome assessed was the prevalence of P.
Eligibility criteria All study designs except case studies were included irrespective of language. To be included in the review, studies should have been among children living in SSA; reported prevalence or incidence of malaria, prevalence of malaria-related anaemia or Plasmodium density stratified by the presence of at least one STH species including Ascaris lumbricoides, hookworms or Trichuris trichuria and absence of intestinal helminth infection. Studies that reported immunology of malaria and STH co-infection were also included if they contained information about malaria prevalence/incidence, Plasmodium density and malaria-related anaemia stratified by presence of at least one STH species and absence of intestinal helminth infection. Other studies from SSA in the general population that reported data on children separately were also considered for inclusion.
Search methods for identification of studies Eligible studies were identified by searching Pubmed, Embase, Cochrane Library, CINAHL databases through March 6, 2015. The keywords "malaria" OR "Plasmodium" OR "Plasmodium falciparum" OR "Plasmodium vivax" in combination with helminth "soil-transmitted helminth" OR "geohelminth" OR "Ascaris" OR "Ascaris lumbricoides" OR "Trichuris" OR "Trichuris trichiura" OR "hookworm" OR "Ancylostoma" OR "Ancylostoma duodenale" OR "Necator" OR "Necator americanus" were used (see Additional file 2: Table  S1  for details). Literature search was limited to humans. Furthermore, we searched the African Journals Online database and the reference lists of the previous reviews on malaria and helminth co-infection  [4, 6, 17, 18, 20]. Two reviewers (AD and DD) screened articles for eligibility after excluding the duplicates.
Data collection Relevant information from the selected articles was extracted and entered into a standardized excel sheet by two authors (AD and DD) independently. Any differences were resolved on further discussion with the third author (EV) before including the data in the review. The following data were collected from each included study: author, year of publication, study area, study design, sample size, STH and Plasmodium species investigated, outcome measured, prevalence of STH and Plasmodium spp. co-infection, prevalence of malaria-related anaemia, and Plasmodium spp. density in children infected with STH compared to those who were not infected with intestinal helminths.
Statistical analysis Odds ratio was used as a measure of association. Information about adjusted odds ratio (aOR) of asymptomatic/uncomplicated P. falciparum infection and related anaemia along with 95 % confidence interval (CI) were collected for children who were infected with STH and uninfected with intestinal helminths. When adjusted measures were not reported, raw data for only malariapositive, only STH-positive, malaria-and STH-positive, and intestinal helminth-and malaria-negative were extracted from the tables, figures, texts or summary data of the articles. This information was used to estimate the crude odds of asymptomatic/uncomplicated P. falciparum infection and related anaemia in children infected with STH compared to those uninfected with intestinal helminths along with their 95 % confidence intervals.