dataesr/scientific-paragraphs-categorization huggingface dataset:
5 and 0. 75 for substitution and insertion/ deletion of an amino-acid at any of the three signature motifs. This biological and statistical data cleaning strategy has been integrated in a program (PyroVir, IDDN FR. 001. 160011. 000. S. P. 2012. 000. 31230, Inserm-Transfert) that provides a fast, automated position-specific process for inferring HIV-1 tropism from V3 env deep sequencing data with improved detection of minor variants. The genotypic rule used to predict CXCR4-usage can be changed according to the virus subtype, particularly for subtypes D and CRF01-AE for which we have developed specific algorithms  25, 26. We used the combined 11/25 and net charge rules to infer the tropism of each virus clone from the V3 amino acid sequence. It requires one of the following criteria for predicting the CXCR4 coreceptor usage of HIV-1 subtype B  27, 28  : (i) an R or K at position 11 of V3 and/or a K at position 25; (ii) an R at position 25 of V3 and a net charge of at least + 5; and (iii) a net charge of at least + 6.
The V3 net charge was calculated by subtracting the number of negatively charged amino acids (D and E) from the number of positively charged ones (K and R). The CM classifier (generic prediction) was used to predict tropism with cleaned data of V3 amino acid sequences  20. Determining the position-specific error rates of deep sequencing along the V3 sequence. As the errors generated during deep sequencing are sequence-dependent, we determined specific error rates at each position in V3. We measured the mean codon error rate, based on the worst error rate of the 3 nucleotides, among the 20 clones at each V3 position. The position-specific error rates were then defined as the upper limit of the 99% confidence interval of the mean frequency of artifactual codons among the 20 clones at each position of V3.
In the present study, forced convection of CuO-water nanofluid in a two dimensional parallel plate microchannel with and without micromixers has been investigated numerically. Two horizontal hot baffles were inserted between the adiabatic plates and three vertical baffles, which were attached on the plates, worked as micromixers in order to improve the cooling process. The effect of Reynolds number, Re = 10, 30, 60, 100, and 150 and nanoparticles volume fraction, from 0 to 4%, were examined on flow field and heat transfer. Different geometrical configurations for the arrangement of the hot baffles were tested. A FORTRAN code based on finite volume method was developed to solve the governing equations and SIMPLER algorithm was used for handling the pressure-velocity coupling. Simulations showed that the presence of micromixers and increasing the Reynolds number as well as nanoparticles volume fraction, increase the average Nusselt number.
RESULTS AND DISCUSSION Four genes encoding the HasN, HasO, HasV and HasY NRPS proteins were identified on contig 13 of the Planktothrix serta PCC 8927 draft genome (accession number CZCU01000013). These genes were predicted to be part of a 48 kb--long biosynthetic gene cluster encoding 16 genes. The four NRPS genes encoded the enzymes required for the biosynthesis of the hassallidin cyclic core. Analysis of the NRPS adenylation domain substrate specificity predicted the incorporation of five threonines, two glutamines, one tyrosine, and one glycine (Table  1 ). The HasO, HasN, and HasY encoded also three epimerization and one N--methyltransferase domains (Table  1 ) to obtain the enantiomeric amino acids and the N--methylated amino acid in the final molecule. The genome assembly of the NRPS regions revealed several tailoring genes in their vicinity that coded for two hydroxylases, reductase and glycosyl transferase, HasB, HasM, HasL and HasT respectively, needed for the macrocyclization and the glycosylation of hassallidin (Table  1 ).
METHODS Planktothrix strain. The benthic strain Planktothrix serta PCC 8927 was originally isolated from a sewage plant of Berre--le--Clos, France in 1989, subsequently made axenic and maintained in the Pasteur Culture Collection of Cyanobacteria (PCC). The Planktothrix serta PCC 8927 genome sequence is available at GenBank under accession number CZCU00000000. 29 nomic comparison. Gene cluster and genomic context analysis were performed on the MicroScope platform  43  including in silico prediction of natural product biosynthetic pathways using antiSMASH 3. 0. 44 Protein BLAST was performed using NCBI BlastP 45 to manually annotate the genes of the hassallidin locus. The substrate specificity of the NRPS adenylation domains was assessed using NRPSpredictor2. 46 Regions of genomic plasticity (RGP) features were analyzed using RGPfinder including SIGI--HMM  47  and AlienHunter (IVOM)  48  as implemented on the MicroScope platform.
AKNOWLEDGEMENTS This work was partially supported by the  French National Research Agency  under Contract  N° ANR--15--CE34--0002--02 , by incentive credits from the  Conny Maeva Charitable Foundation. The  Pasteur Culture Collection of Cyanobacteria  was supported by the  Institut Pasteur. CP was supported by the  Ile--de--France ARDoC  Grant for PhD. The work at the  University of Helsinki  was supported by the  Academy of Finland  grants ( 258827  and  273798 ) to KS and by the  Academy of Finland  grant ( 259505 ) to DPF. AH is student at the  Doctoral Programme in Microbiology and Biotechnology, University of Helsinki. The authors thank  Frédéric Bonhomme  for the mass spectrometry analysis of the purified hassallidin E.
Multi-resolution analysis allows us to analyse interactions between different time series signals and we used this analysis to identify interactions between time series emerging from the RPS game due to different strategies. Finally we use cross-correlational analysis between strategies to identify the causal nature of changes in allelic frequency  48, 58, 59. In this statistical context (signal processing context), cross-correlational analysis between the time series frequencies of two different phenotypes is a measure of similarity of two series as a function of different time lags of one cycle relative to another cycle. The cross-correlation is similar in nature to the convolution of two functions (see  38  for mathematical details of the method). In other words, this last analysis answers the following question: can some strategies drive the cycles of others or are cycles due to some other effect? Modelling and time series analyses are performed under the MATLAB ® environment using the Wavelab toolbox  60.
Acknowledgements We are grateful to  Stéphane Legendre  for his modeling advice and  Donald Miles  for his insightful comments on the manuscript. Moulherat and Clobert were supported by the  European  project  SCALES  funded by the  European Commission as Large-scale   Integrating Project  within  FP7  under grant  226 582. Chaine was supported by an  ANR-JCJC  "Netselect". Sinervo was supported by  NSF   IOS-1022031. This work is part of the  "Laboratoire d'Excellence" (LABEX)  entitled  TULIP  ( ANR-10-LABX-41 ).
For noninvasive bioluminescence visualization of metastasis, Balb/c mice were injected intraperitoneally with d-luciferin (150 mg/kg in PBS; Promega, Madison, WI, USA) and anesthetized with 2. 5% isoflurane-oxygen mixture. After 12 minutes of d-luciferin injection, mice were placed in IVIS 200 Imaging System (Caliper Life Sciences) and imaged for 1 minute. A quantitative assessment of metastasis was performed by determining "regions of interest" in the lungs and measuring bioluminescence intensity using Living Image software. Subcutaneous cancer dissemination model-LPS stimulation protocol. Mice were instilled 3 times per week with PBS or LPS (3 μg/100 μL) (vide supra). After 4 LPS instillations, murine mammary cancer cells 4T1 (2 × 10 5 cells/100 μL in serum-free medium) were subcutaneously injected into flanks of mice (n = 8 mice/group).
Pulmonary histology and immunohistochemistry Metastasis to lung tissues was evaluated by measuring tumor area in lungs and reporting it to the total area of lung tissues analyzed, on 8 hematoxylin-eosin-stained sections per animal using Cytomine software. 26 Proliferating and apoptotic cells were visualized on tumor sections using antibodies raised against Ki-67 and double-stranded DNA as described in supplemental experimental procedures.
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was financially supported by grants from the  Fonds National pour le Recherche Scientifique (FRS-FNRS Télévie , grant  n°7463012F ), the  Centre AntiCancéreux (University of Liège) , the  Foundation against Cancer (foundation of public interest, Belgium) ,  Interuniversity Attraction Poles Program-Belgian State-Belgian Science Policy-Project   P7/30 , and the  Fonds Léon Fredericq (University of Liège ).
The ICE-CAMERA At Dome C in 2013, an ICE-CAMERA was installed on the roof of the shelter where both the HAMSTRAD and the aerosol lidar were set up. This camera was able to take on an hourly rate a picture of the ice crystal grains deposited at the surface of the camera. The ICE-CAMERA (http://lidarmax. altervista. org/englidar/_AntarcticPrecipitation. php) is equivalent to a flatbed scanner. It was built in order to operate unattended in polar regions for the study of precipitating ice grains. Precipitation is collected on a glass plate, where it is photographed with 5 µm resolution hourly. After each scan, the glass plate is electrically heated in order to sublimate the ice grains. Image-processing software is used for the automatic characterization and counting of grains.
The ARPEGE model The ARPEGE model is the global model used for numerical weather prediction at Météo-France. In the present study, the operational configuration has been used with a stretched grid at high resolution over France (10 km) and a coarser grid over Australia of 60 km. At the South Pole, the horizontal resolution is about 50 km and the vertical grid has 70 levels with a first level at around 16 m above the ground. The assimilation tool is based on an incremental four-dimensional variational (4DVAR) method. The physical package used in the ARPEGE model is state-of-the-art, with a turbulent kinetic energy scheme associated with a mass flux scheme for the boundary layer  (Bazile et al. , 2011). The clouds and the microphysics use four prognostic variables such as cloud water, cloud ice, rain and snow  (Lopez, 2002; Bouteloup et al.
Above, the atmosphere is rather isothermal and starts cooling around 400-800 m. All the data sets are very consistent to each other. During the cold episode on 5 March, the lower troposphere is generally colder than during the warm episode, but at 12:00 UTC there is no such a stable planetary boundary layer as observed a day before since the vertical gradient is only of a 3 K over 500 m altitude instead of 20 K over 200 m during the warm episode. Radiosonde, ARPEGE and HAMSTRAD profiles are consistent to each other. At. Vertical distribution of temperature measured by HAM-STRAD (solid line) and radiosondes (dashed lines) and calculated by ARPEGE (dotted lines) on 4 March 12:00 UTC (red line) and 18:00 UTC (orange line) and on 5 March 12:00 UTC (blue line) and 18:00 UTC (green line). Note radiosondes are only available at 12:00 UTC.
Acknowledgements. The present research project  HAMSTRAD  programme (910) has been performed at the Dome C station and was supported by the  French Polar Institute, Institut polaire français Paul-Émile Victor (IPEV) , the  Institut National des Sciences de l'Univers (INSU) / Centre National de la Recherche Scientifique (CNRS) ,  Météo-France  and the  Centre National d'Études Spatiales (CNES). The permanently manned Concordia station is jointly operated by  IPEV  and the  Italian Programma Nazionale di Ricerche in Antartide (PNRA). We would like to thank all the winter-over personnel who worked at Dome C on the different projects: HAMSTRAD,  Routine Meteorological Observations  (RMO), aerosol lidar and BSRN. Thanks to the  British Atmospheric Data Centre , which is part of the  Natural Environment Research Council (NERC) National Centre for Atmospheric Science (NCAS) , for the calculation of trajectories and access to  European Centre for Medium-Range Weather Forecasts (ECMWF) data.
Data availability. The HAMSTRAD data are publicly accessible in France at Météo-France: http://www. cnrm-game-meteo. fr/ spip. php?article961&lang=en. The lidar images are publicly accessible in Italy at INO-CNR: http://lidarmax. altervista. org/lidar/ AntarcticLIDAR. php. The CALIOP images are publicly accessible in the USA at NOAA/ESRL: http://www. esrl. noaa. gov/psd/.
Abstract. Global cloud climatologies have been built from 13 years of Atmospheric Infrared Sounder (AIRS) and 8 years of Infrared Atmospheric Sounding Interferometer (IASI) observations, using an updated Clouds from Infrared Sounders (CIRS) retrieval. The CIRS software can handle any infrared (IR) sounder data. Compared to the original retrieval, it uses improved radiative transfer modelling, accounts for atmospheric spectral transmissivity changes associated with CO 2 concentration and incorporates the latest ancillary data (atmospheric profiles, surface temperature and emissivities). The global cloud amount is estimated to be 0. 67-0. 70, for clouds with IR optical depth larger than about 0. 1. The spread of 0. 03 is associated with ancillary data. Cloud amount is partitioned into about 40 % high-level clouds, 40 % low-level clouds and 20 % mid-level clouds.
A sensitivity study has shown that five (for HIRS) to eight channels (AIRS and IASI) are sufficient, as doubling the number of channels in the retrieval did not change the results. By introducing empirical weights W (p k , λ i ), the method takes into account (i) the vertical contribution of the different channels, (ii) the growing uncertainty in the computation of ε cld with increasing p k and (iii) uncertainties in atmospheric profiles. These weights are determined for each of five typical air mass classes (tropical, midlatitude summer and winter, polar summer and winter) as in  Stubenrauch et al. (1999)  and in  Feofilov and Stubenrauch (2017) , using the spread of clear-sky radiances within these air mass classes. The clear-sky radiances have been simulated for each of the atmospheric profiles of these five air mass classes, using the 4A radiative transfer model  (Scott and Chédin, 1981) , and stored in the Thermodynamic Initial Guess Retrieval (TIGR) database  (Chédin et al.
Cloud types are distinguished according to p cld and ε cld. High-level clouds are defined by p cld < 440 hPa, mid-level clouds by 440 hPa < p cld < 680 hPa and low-level clouds by p cld > 680 hPa. High-level clouds may be further distinguished into opaque (ε cld > 0. 95), cirrus (0. 95 > ε cld > 0. 50) and thin cirrus (ε cld < 0. 50). p cld is transformed to cloud altitude, z cld , using a standard hydrostatic conversion. For the computation of I clr and I cld in Eq. (1), we need (i) surface type (ocean, land, ice/snow), surface temperature and spectral emissivities, (ii) atmospheric temperature and water vapour profiles as well as spectral transmissivity profiles for the atmospheric situation of the measurements. The latter have been calculated using the 4A radiative transfer model, separately for each satellite viewing zenith angle (up to 50 • ) and for about 2300 representative clear-sky atmospheric temperature and humidity profiles of the TIGR database.
The correction led to 76 % and 73 %, respectively, closer to the results using AIRS ancillary data. Over land, without changes in T surf , CA at night and early afternoon is 62 % and 56 % with ERA-Interim and 56 % and 58 % with AIRS-NASA, respectively. Figure  1  presents comparisons between T surf , as used in the cloud retrieval, deduced from AIRS-NASA and from ERA-Interim and collocated surface air temperature, T air surf , from the ARSA database. One would expect that over land T surf would be colder than T air surf during night and warmer than T air surf in the afternoon; this effect should be stronger for warmer temperatures, especially if the climate is dry. SST should be similar to T air surf in the tropics: slightly warmer in midlatitudes and colder in polar regions. The distributions in Fig.
Accounting for changes in atmospheric CO 2 concentration The TIGR database of atmospheric spectral transmissivities was created for an atmosphere with a fixed CO 2 volume mixing ratio of 372 ppmv. However, the atmospheric CO 2 concentration varies latitudinally, seasonally and with time. Both   the increase during the last 10 years and the seasonal variability in the Northern Hemisphere (NH) are of the order of ∼ 20 ppmv. The latter is related to the vegetation and fossil fuel burning seasonality. The difference between an averaged value and actual CO 2 volume mixing ratio can easily reach 10 %. This is a noticeable change, as the concentration enters the power of the exponent in the calculation of the transmissivity, τ. To avoid errors associated with CO 2 changes in the radiative transfer computations, we rescale the transmissivity as τ = exp(-β -α • CO 2 current ), (3) with α = -k • log(τ ref )/CO 2 ref and β = α • CO ref 2 • log(1 - k)/k, where k is the relative CO 2 contribution to the opac-ity of the channel.
Average cloud properties and variability In this section we give a short overview of cloud properties of the AIRS-CIRS and IASI-CIRS cloud climatologies. Monthly L3 data, gridded at a spatial resolution of 1 • latitude × 1 • longitude, have been produced in the same manner as for the GEWEX Cloud Assessment database  (Stubenrauch et al. , 2013) : in a first step, cloud properties and their uncertainties, deduced from the χ 2 method, were averaged per observation time over 1 • latitude × 1 • longitude; in a second step, these were averaged per month. In addition to the monthly averages, the database also includes histograms of the cloud properties. Figure  6  compares normalized frequency distributions of p cld (CP) over 30 • wide latitude bands during boreal winter and boreal summer, separately over land and over ocean.
Global averages of AIRS-CIRS and IASI-CIRS are compared with those from selected cloud climatologies of the GEWEX Cloud Assessment database: the International Satellite Cloud Climatology Project (ISCCP;  Rossow and Schiffer, 1999) , two cloud climatologies derived from observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite, by the MODIS Science Team (MODIS-ST;  Frey et al. , 2008)  and by the MODIS CERES Science Team (MODIS-CE;  Minnis et al. , 2011) , and two cloud climatologies derived from CALIPSO observations, by the CALIPSO Science Team (CALIPSO-ST;  Winker et al. , 2009)  and by the GCM-Oriented CALIPSO Cloud Products (CALIPSO-GOCCP;  Chepfer et al. , 2010). The latter two use vertical averaging (CALIPSO-GOCCP) and horizontal averaging (CALIPSO-ST) to reduce the noise of the relatively small samples.
The latter is more sensitive to thin layers of subvisible cirrus. ISCCP is essentially using two atmospheric window channels (IR and VIS, the latter only during daytime). Considering passive remote sensing, total CA from the GEWEX Cloud Assessment database is about 0. 68 ± 0. 03  (Stubenrauch et al. , 2013) , while CALIPSO-ST provides a CA of 0. 73 because it includes subvisible cirrus. We separately examine daytime and nighttime observations. While all data sets agree quite well on CA, with ISCCP and MODIS-CE providing smaller CA during night (both including VIS information for cloud detection during daytime), CAHR exhibits a large spread due to different sensitivity to thin cirrus: active lidar is the most sensitive, followed by IR sounders. The CIRS results are very similar to the results from the AIRS-LMD cloud climatology  (Stubenrauch et al.
Time series of deseasonalized anomalies in global monthly mean CA, CAEH and CAEL of the three CIRS data sets are shown in Fig. 10  over the time period of  2004 -2016 for AIRS and 2008 -2016  for IASI. To illustrate the effect of the calibration accounting for changes in atmospheric CO 2 concentration (Sect. 2. 5. 2), the time series of the AIRS-CIRS CA anomalies, without this correction, is added. Whereas the uncorrected CA anomalies increase by about 0. 040 within a decade, the magnitude of the calibrated CA and CAEL variations lie within 0. 010 and of CAEH within 0. 005, being mostly stable within the uncertainty range. Latitudinal seasonal cycles of CA, CAH, CAL and T cld (CT) from the different data sets agree in general quite well (Fig. S4  of the Supplement). The most prominent features of the latitudinal seasonal cycles are (i) the shift of the ITCZ towards the summer hemisphere, seen as an amplitude of 0.
The ITCZ characteristics have been determined by fitting a Gaussian around the tropical peak of the latitudinal CAH distributions (Fig. 8 ), per month and year. This yields the latitude of the peak position, the value of the peak itself and the width of the tropical CAH distribution. From Fig. 11  we deduce that the annual NH-SH difference in CAH is 0. 05, with a pronounced seasonal cycle of about 0. 3 in amplitude. Results from the three CIRS cloud climatologies (AIRS with two ancillary data sets and IASI), AIRS-LMD, CALIPSO-GOCCP, ISCCP and MODIS-CE are similar. This seasonal cycle is well related to the one of the ITCZ peak latitude, which moves up to 12 • N in July. It is interesting to note that the width of the ITCZ is smaller in July and August (10. 5-12. 5 • ) than in January (17 • ) and the CAH peak is about 10 % larger in August than in January.
This might suggest a more intense ITCZ (and hence more intense precipitation) when it is located in the NH than when it is located in the SH. All data sets agree well on the ITCZ peak latitude. The smaller maximum CAH values of MODIS-CE and ISCCP are due to smaller sensitivity to thin cirrus, and the reduced seasonal cycle of maximum CAH and of ITCZ width for CALIPSO-GOCCP is due to the inclusion of ubiquitous thinner cirrus, leading to less-well-pronounced CAH minima in the subtropics. The CIRS climatologies reveal the seasonal behaviour of the ITCZ characteristics clearly. Figure  11  confirms and extends the interpretation of the results of  Stephens et al. (2016)  by displaying a relation between the hemispheric difference of CAH and characteristics of the ITCZ, which seems to be more intense when its peak is situated in the NH (smaller width and larger maximum).
Conclusions We have presented two global climatologies of cloud properties, built from AIRS and IASI observations by the CIRS cloud retrieval. This retrieval software package, developed at LMD, can be easily adapted to any IR sounder. The retrieval method itself, based on a weighted χ 2 method on radiances along the wing of the 15 µm CO 2 absorption band, and a multi-spectral "a posteriori" cloud detection, based on the spectral coherence of retrieved cloud emissivities, have been evaluated in previous publications. In this study, we have further demonstrated the reliability of these updated cloud climatologies. IR sounders are especially advantageous to retrieve UT cloud properties, as they reliably determine cirrus properties down to an IR optical depth of 0. 1, day and night. The CIRS retrieval uses improved radiative transfer modelling, employs the latest ancillary data (surface temperature, atmospheric profiles) and accounts for atmospheric spectral transmissivity changes associated with latitudinal, seasonal and interannual atmospheric CO 2 concentration variations.