dataesr/scientific-paragraphs-categorization huggingface dataset:
rcslens. org), Canada-France Hawaii Telescope Lensing Survey (CFHTLenS) (http://www. cfhtlens. org), Instrument (http://ipag. osug. fr/nika2), and Hyper Suprime-Cam (HSC) (http://hsc. mtk. nao. ac. jp/ssp). The final of data are catalogues of peculiar velocities. By measuring redshifts and radial distances of galaxies and clusters it is possible to reconstruct a radially projected map of large-scale motions. Progress in this field will come from all three data sets above. The main science goal of the next generation of cosmological probes is to test the Concordance Model of cosmology. Some major experiments will be operational in the next decade. Planck, decommissioned in 2013, marked a major milestone in CMB experiments. Its proposed successor is the ground-based programme CMB-S4  [532] , which should reach sensitivities below 10 -3 µ K whose main aim is to achieve resolutions, probe larger scales, and measure new observables such as polarisation.
We will also need to extract more observables from the CMB. We need information on in order to constrain inflationary models. As experiments probe larger scales at better resolutions (low and high ), the data analysis and the cosmological tests (dark energy, Dark Matter, the properties of cosmic neutrinos) will require accurate calculations on the growth of large-scale structure, which can only be achieved using N-body simulations  [537] [538] [539] [540] [541] [542] [543] [544]. At the other end of the length scale, there is particle physics. The Very Large Hadron Collider, the successor to the Large Hadron Collider (https://home. cern/topics/large-hadron-collider) (which can achieve energies around 14 TeV), is still in its conceptual phase. It could, if built, probe energies around 100 TeV, allowing it to test physics beyond the Standard Model, possibly including Supersymmetry and Grand Unified Theories, and thus provide clues on the nature of Dark Matter and dark energy (see, e.
For statistical probes such as the CMB and large-scale structure, these data sets have to be analysed as a whole, in order to correlate data. In addition to the volume of data collected, this generates a huge amount of computational data, and requires the appropriate computing power to carry out multiple complex calculations. We are witnessing a Moore's Law in cosmology, where the data volume of experiments increases by a factor of around 1000 every ten years, as shown in Figure  8. In addition to the data volume challenge, we have an algorithmic challenge. The number of computations for cosmological data analysis depends on four main factors: the number of observations N t , the number of pixels N p , the number of multipoles (a function of the resolution and frequency range) N , and the number of iterations N i.
The first three quantities determine the data volume. The data simulation scales at least as O(N t ). The map-making scales as O(N i N t log N t ). The maximum-likelihood power spectrum estimation scales as O(N i N l N 3 p ). has not yet been fixed. Note that the vertical axis is logarithmic: the date volume increases about a thousandfold every ten years (grey dashed line). Note too that we plot CMB, large-scale structure, space and ground-based probes on the same graph. Ground-based probes will always tend to have a larger data volume than space-borne probes, due to the bandwidth limit on data transmission from spacecraft. Longer-running experiments will also have a larger data volume. Planck marked a milestone in data science. It was the first CMB experiment in which the whole data treatment process was parallelised, and where Monte Carlo methods were used in order to cut down on the number of data realisation iterations that were carried out.
There are two main considerations in data analysis: the amount of data, and the complexity of the theory. Future experiments will require sophisticated techniques, and considerable computing power to process the vast amounts of data. Gaia is already collecting data  [555] , while Euclid, the SKA, Enhanced LIGO, and CMB-S4 will soon be operational. Farther ahead, the Evolved Laser Interferometer Space Antenna (eLISA) (https://www. elisascience. org), due for launch in 2034, will also generate huge volumes of data, and will require the necessary computing power to test GR directly, by comparing the data to simulated black hole collapse, inspiralling binaries. What direction will experimental cosmology take over the coming decade? Extracting fainter signals, such as CMB polarisation, or going to very high resolutions requires larger data volumes to provide a higher signal-to-noise ratio, and it requires more complex models to control fainter systematic effects.
Acknowledgments:  George F. Smoot  acknowledges support through his  Chaire d'Excellence Université Sorbonne Paris Cité  and the financial support of the  UnivEarthS Labex programme at Université Sorbonne Paris Cité  ( ANR-10-LABX-0023  and  ANR-11-IDEX-0005-02 ). I. D. acknowledges that the research work disclosed in this publication is partially funded by the  REACH HIGH Scholars Programme-Post-Doctoral Grants. The grant is part-financed by the  European Union ,  Operational Programme II-Cohesion Policy   2014-2020.
These boundary conditions were obtained from a global-scale model MOZART-4 (Model for OZone And Related chemical Tracers version 4)  (Emmons et al. , 2010). In order to simulate accurately pollutant concentrations over Lebanon and Beirut, boundary conditions of the simulations over Lebanon need to be improved. To that end, in this paper, simulations over a larger domain than Lebanon are performed using Polyphemus and are used as boundary conditions of the Lebanon simulation. Since an emission inventory over such larger domain is not available, a global emission dataset is used: EDGAR-HTAP  (Janssens-Maenhout et al. , 2012). This dataset has a grid resolution of 0. 1 Â 0. 1 and it uses modeling to estimate emissions over regions where emissions inventories are not available. In this global dataset, modeling is also used over certain regions such as Europe to improve the spatial resolution of available gridded emission inventories.
Over Lebanon in EDGAR-HTAP, modeling is used, although a gridded emission inventory exists  (Waked et al. , 2012). The objective of this paper is to improve air quality simulations over Lebanon. To that end, we study the sensitivity of the concentrations simulated over Lebanon to the anthropogenic emission datasets and to the boundary conditions used. The paper is organized as follows: in Section 2, the air-quality modeling system Polyphemus used in the simulations of this paper is briefly described. Section 3 presents the global emission dataset EDGAR-HTAP and the local emission dataset used over Lebanon. The impact of emission modeling in the global emission inventory EDGAR-HTAP is studied by comparison to local inventories over Europe and Lebanon, and the impact of the emission dataset used on pollutant concentrations simulated with Polyphemus is evaluated.
25. The Lebanon domain extends The current Lebanese Air Quality Standards (in mg m À3 ) as found in the legislation of 1996  (MoE, 1996)   (Skamarock et al. , 2008). WRF is driven by the input data from the National Centers for Environmental Prediction (NCEP) reanalysis meteorology datasets. The meteorological simulation uses the University of Washington Moist Turbulence scheme  (Bretherton and Park, 2009)  for Planetary Boundary Layer (PBL). The United States Geological Survey map is used over the Middle East/Lebanon domains. Biogenic emissions are calculated using Model of Emissions of Gases and Aerosols from Nature (MEGAN)  (Guenther et al. , 2006) , which is designed for global and regional emission modeling. For anthropogenic emissions, EDGAR-HTAP version 1 is used over the Middle East domain, and either EDGAR-HTAP version 1 or  Waked et al.
Sensitivity to the emission inventory This section presents the global emission dataset that is chosen to perform air-quality simulations over the Middle East, and it compares it to local emission inventories. First, the local emission inventory of  Waked et al. (2012)  over Lebanon is briefly presented. Then, the choice of the global emission dataset is explained. Over Lebanon and the Middle East, the global emission dataset uses modeling to estimate emissions. However, over Western Europe, where local emission inventories are available and yearly updated, the global emission dataset uses modeling only for the spatial allocation of national emissions. The global emission dataset is compared to local emission inventories over Europe and Lebanon. The first comparison is performed over Western Europe, to estimate the impact of using modeling for the spatial allocation of national emissions.
The global emission inventory Although many global emission datasets are publicly available (ACCMIP, ARCTAS, EDGAR4. 2, EDGAR-HTAP, RCP), not all of them may be used to simulate air quality over the Middle East with Polyphemus. A global anthropogenic emission dataset is needed for the year 2011 or an adjacent time period, unlike ACCMIP which is compiled for the years 1850 till 2000 and used to estimate future scenarios. The data needs to be provided with a sectorial distribution, which is not the case of ARCTAS, in order to apply temporal profiles, which represent seasonal, monthly and daily source activity variations. Also, the data needs to include most commonly emitted pollutants (CO, NO x , SO x , NH 3 , NMVOC, PM 10 , and PM 2. 5 ) related to air quality models. Furthermore, the spatial resolution of the data is important in deciding the inventory to be used.
The global inventories EDGAR4. 2 and EDGAR-HTAP are considered suitable for this study, as they satisfy the criteria listed above. Note that in the case of ARCTAS, which is used in the global model MOZART4, the inventory is based on the inventory EDGAR over the Middle East, but with a coarser spatial resolution than EDGAR-HTAP. The Emissions Database for Global Atmospheric Research (EDGAR) is based on modeled emissions only, calculated through the use of surrogate global subsets such as population distribution, aviation paths, etc. EDGAR-HTAP emission inventory is a global inventory that contains emissions reported from countries/organizations such as the European Monitoring and Evaluation Program (EMEP, 2009) over Europe, combined with emissions calculated using EDGAR4. 1 where reported emissions are not available.
Over Western Europe Over Europe, EDGAR-HTAP uses national totals from the EMEP emission inventory, that are then re-allocated spatially using EDGAR4. 1 proxy subsets to get a spatial resolution of 0. 1 Â 0. 1. This resolution is higher than the resolution of the EMEP gridded emission inventory (0. 5 Â 0. 5 ). The impact of the spatial allocation algorithm over Europe can be estimated by comparing the EDGAR-HTAP dataset to the EMEP gridded emission inventory, interpolated to a 0. 1 Â 0. 1 spatial resolution. Fig. 2  shows the emissions of NH 3 , NO 2 and PM 2. 5 from EDGAR-HTAP and EMEP, as used in Polyphemus. In the case of NO 2 , emissions from EDGAR-HTAP are lower over cities than emissions from EMEP, confirming that the spatial allocation is population dependent. In the case of NH 3 , the spatial variations of EDGAR-HTAP emissions are higher than those of EMEP.
Impact of the emission dataset on concentrations To assess the impact of the emission dataset on concentrations, and more particularly the impact of the emission modeling performed in the EDGAR-HTAP inventory, simulations are performed over both Europe and Lebanon. The simulations are compared to measurements and evaluated. The statistical indicators calculated are: the Mean Normalized Gross Bias (MNGB), the Mean Normalized Gross Error (MNGE), the Mean Fractional Error (MFE) and the Mean Fractional Bias (MFB). For O 3 , the MNGE and MNGB are calculated with a cut-off of 80 mg m À3. For hourly O 3 ,  Russell and Dennis (2000)  suggested that the performance criterion is met when both MNGB ±15% and MNGE 35%. For PM, Boylan and  Russell (2006)  suggested that the performance criterion is met when both MFB ±30% and MFE 50%, and that the model performance goal is met when both MFB ±60% and MFE 75%.
Over Western Europe The modeling set-up is the same as detailed in Section 2, except for the simulated domain and the emission inventories used. The domain covers the western part of Europe (35 N e 70 N; 15 W e 35 E) with a resolution of 0. 5 Â 0. 5. 9 vertical levels are considered from the ground to 12 km (40 m, 120 m, 300 m, 800 m, 1500 m, 2400 m, 3500 m, 6000 m, and 12,000 m). The simulations are performed from 15 June 2009 to 31 July 2009. Two simulations are performed using the same input data except for anthropogenic emissions. The first simulation uses the EMEP gridded emission inventory, while the second uses the EDGAR-HTAP dataset. To assess the performance of Polyphemus with the two emission inventories, the outputs from the simulations are compared to the observations of the Airbase network  (Airbase, 2009).
Over Lebanon Using the set-up detailed in Section 2, two simulations are performed: one with the EDGAR-HTAP anthropogenic emission dataset, and the other one with the Waked et al. emission inventory for Lebanon. The simulations are performed for the period from 20 June 2011 to 20 July 2011, thus including the period where measurements are available  (Waked et al. , 2013). The results from the simulations are compared to the available observations done during the summer of 2011, from July 2 to July 13, at a suburban site near Beirut: The Saint Joseph University -Faculty of Sciences campus (USJ site) in the region of  Mansourieh (33. 86 N, 35. 56 E) distant by 6 km from the center of Beirut. Table  5  summarizes the statistics of the comparison for both simulations. For hourly O 3 , the defined performance criterion is verified for both the Waked et al.
Accordingly, the evaluation of national totals without a good proxy dataset could be misleading. Looking at the statistics obtained with both emission inventories compared to the observations at a sub-urban location near Beirut, both inventories performed rather well despite the spatial allocation differences discussed earlier. However, large differences are observed on O 3 and PM 2. 5 concentrations, especially along the coastal line and close to highly emitting industrial locations. Therefore, further work on emission inventories should focus on implanting national inventories that exist in global emission inventories, even though they are not reported to international organizations. For a better model performance assessment, further work should focus on acquiring measurements from more than one station in order to review the performance of the set-up over the whole country and different station types.
Conclusion To improve air quality simulations over Lebanon, sensitivity simulations to the anthropogenic emissions datasets and to the boundary conditions used were performed. The sensitivity simulations allowed us to identify the "good practice" to correctly model ozone and particulate matter concentrations over Lebanon. Comparisons to measurements were performed at one observation site in Beirut suburb (USJ site). Two nested simulations were defined to model concentrations at the USJ site: one over the Middle East and one over Lebanon. Because O 3 is strongly impacted by regional transport, using boundary concentrations of the Lebanon domain from a large-scale model led to a strong over-estimation of O 3 concentrations at USJ. However, O 3 was well modeled when the Middle East simulation was used as boundary conditions.
However, over regions where nation-based emission inventories are not available (or not used), as over Lebanon, the global-scale emission inventories are usually based on modeling only, leading to high uncertainties in national totals. Over Lebanon, the differences between EDGAR-HTAP and the local emission inventory, in terms of national totals and spatial allocation, highlighted high uncertainties both in terms of spatial allocation and emission quantification. National total emissions of EDGAR-HTAP are higher than those of the local emission inventory for NH 3 and SO x by a factor about 3, and lower for CO, PM 10 and PM 2. 5 by a factor between 2 and 3, while they are similar for NO x and NMVOC. The differences found in the industrial and transport sectors for NO x and PM 2. 5 emissions highlighted high uncertainties on the activity data as well as the choice of the emission factors used for power plants, cement factories, and on road emission sources.
traffic count with different automatic counting studies. Over Lebanon, they scaled Beirut emissions using statistics based on origin-destination trips which are the number of daily trips that occur between each origin zone and each destination zone. EDGAR-HTAP estimated traffic emissions using an approach based on the total fuel consumed for transportation combined with estimation of fleet composition and emission factors. The data is spatially allocated afterwards based on the road network and the population density. Many sources of uncertainties originate from the global datasets used in the estimations of key factors such as the quantity of fuel, the distribution between diesel and gasoline vehicles and more generally the fleet composition. For population dependent sectors, such as non-industrial activities and waste disposal sectors, another important difference between the inventories is the base year for which they were made due to the continuous increase in the population.
Beside its inhibitory effects on various signaling pathways, such as T-cell receptor and STAT3, and on cell migration  [23, 24, 25, 26, 27, 28, 29] , little is known about the physiopathological roles of DUSP22. Notably, its implication in oncogenesis was never functionally addressed so far. The status of the second allele of DUSP22 in PTCL with monoallelic 6p25. 3 breakpoints-associated silencing was also not yet studied. Finally, sequence databases indicated the existence of alternative DUSP22 transcripts predicted to encode carboxy-terminally truncated proteins, but their expression levels and functions were never studied. Our goal was thus to investigate the expression status of DUSP22 isoforms in normal lymphocytes and PTCL, the mechanism of second allele silencing in PTCL with 6p25. 3 rearrangements, and whether DUSP22 exerted tumor-suppressor properties.
rearrangements Four alternatively spliced DUSP22 gene transcripts were already deposited in databases (Figure  1A , Table  1 , Supplementary Figures  S1, S2 ). The transcript encoding the known 184 aminoacids protein  [23, 24, 25, 26, 27, 28, 29 ] comprises 8 exons. An alternative transcript with unspliced intron 7 is predicted to generate a 205 amino-acids protein diverging from the former in the carboxy-terminal region. Exon 4 can be spliced from these two transcripts (Δ exon 4), leading to frameshift-associated premature STOP codon, and a predicted 54 amino-acids carboxyterminally truncated protein. Expression of these transcripts and their putative proteins had not yet been evaluated in any physiopathological condition. Here we showed that normal peripheral blood lymphocytes (PBL) predominantly expressed transcripts with unspliced intron 7, over those with intron 7-splicing (Supplementary Figure  S1B , Figure  1C , Table  1 ).
The anti-DUSP22 antibodies used were from SIGMA® (# HPA031394, as in (A)) and Santa Cruz® (# sc-47935), the latter being directed against an N-terminal peptide common to the 3 isoforms. Alpha-tubulin (α-Tubulin) was used as a control for protein loading. respectively), whereas HH cells could not (as reflected by a percentage of ZsGreen positive cells below 5%) and were thus not further studied. FE-PD and 1301 living infected cells were sorted by flow cytometry prior to functional analyses and checked for DUSP22 expression at the RNA and protein levels (Figure  5 , Supplementary Figure  S8 ). Ectopic expression of the DUSP22 205 aminoacids isoform had no effect on proliferation of DUSP22proficient FE-PD cells, and only weakly decreased their viability by slightly enhancing apoptosis (Supplementary Figures  S8, S9 ).
Data were normalized using KLK3 (located on 19q13. 41) as a control gene, but also ALB (4q13. 3), CDH1 (16q22. 1) or CECR1 (22q11. 2) to ensure that there was no alteration of KLK3 copy numbers. Data from tumor DNA were compared with DNA from matching normal tissue from the same patient. Data from cell line DNA, DNA from a series of normal PBL was used as a reference. To validate this real time PCR, we also developed a restriction fragment length polymorphism-PCR assay, performed with fluorescently labeled primers, with numbers of cycles adjusted to fall within the linear range of the amplification. PCR products encompassing SNP rs1046656 were digested by the BssSI restriction endonuclease and quantified using capillary electrophoresis. Allele-specific copy numbers, determined by quantifying the area under curve of each SNP allele's peak, were normalized using KLK3 as a control gene.
DNA methylation analysis Genomic DNA was subjected to sodium bisulfite treatment using the EpiTect Bisulfite Kit, according to the manufacturer's instructions (QIAGEN, Hilden, Germany). Methylation was then analyzed using real-time quantitative methylation-specific PCR (qMSP) and confirmed for selected representative samples using bisulfite genomic sequencing (BGS), using standard protocols  [56]. As for gene expression and gene copy number determination, qMSP was quantified using the using the comparative MNE (Mean Normalized Expression) method  [55]. Data were displayed as percentage of unmethylated and methylated alleles. The primers used for qMSP and BGS analyses were designed using the Primer Express v 1. 0 software (Applied Biosystems) and are listed in Supplementary Table  S4. Specificity was verified by melting curves, gel electrophoresis and sequencing analyses.
Western blot analysis DUSP22 protein levels were assessed by Western blot, following standard protocols. The antibodies used were DUSP22 (HPA031394, Sigma-Aldrich, St. St. Louis, MO 63103, USA, 16514-1-AP, Proteintech, Chicago, IL 60612, USA, and sc-47935, Santa Cruz Biotechnology, Dallas, TX 75220, USA) and α-Tubulin (Sigma-Aldrich).
Mean ± SEM from independent measurements are shown. C. Western blot analysis of DUSP22 expression in 1301 cells infected with the control and DUSP22 isoforms vectors and sorted. The anti-DUSP22 antibodies used were from SIGMA® (# HPA031394, as in (A)) and Santa Cruz® (# sc-47935), the latter being directed against an N-terminal peptide common to the 3 isoforms. Alpha-tubulin (α-Tubulin) was used as a control for protein loading.
ACKNOWLEDGMENTS This study was supported a grant from the  Ligue Contre le Cancer  ( Comités Aquitaine-Charentes ), France, and by the  TENOMIC-PAIR INca program  ( Institut National du Cancer, Paris, France ). We thank  Nathalie Carrère  and  Séverine Verdon  ( Service de Biologie des Tumeurs -Tumorothèque et Centre de Ressources Biologiques Cancer, Centre Hospitalier Universitaire de Bordeaux, France ), for assistance with normal and pathological samples collection and processing,  Jackie Ferrer  and  Chiara Barili  ( Université de Bordeaux, France ) for technical assistance with DNA and RNA extractions, reverse transcriptions, methylation specific PCR analysis and SNP genotyping,  Marshall Kadin  for providing the MAC cell lines,  Keld Kaltoft  for providing the My-La cell line and Laurence Lamant (Inserm  UMR1037 ,  Centre de Recherches en Cancérologie de Toulouse, France ) for providing the FE-PD cell line.