dataesr/scientific-paragraphs-categorization huggingface dataset:
Challenges of Seventh, there is fragmentation, owing to a tendency of creating more and more MFIs rather than merging or creating networks. This is a weakness of the sector because new MFIs have difficulties establishing themselves. This is especially because the government gives support to big players, such as PROCAPEC and UNCACEM. Indeed, these two networks have more than 50% of the sectors' clients, and both are having difficulties. PROCAPEC has been in difficulties for almost 10 years due to bad management, but the government is still trying to redress it. As for UNCACEM, it went bankrupt because of its fragility and its dependence on external subsidies. Finally, there is a lack of data on this sector, which makes it difficult to do a proper assessment of its performance.
CircRNAs expressed in T-ALL and developing thymocytes To study the full spectrum of circRNAs expressed during malignant T-cell development, we analyzed high-depth ribodepleted RNA-seq data of 25 T-ALL patients representing 5 genetic T-ALL subtypes (immature, IMM; HOXA overexpressing, HOXA; TLX1 rearranged, TLX1; TLX3 rearranged, TLX3, and TAL1 or LMO2 rearranged, TAL-LMO; 5 patients per group; GSE110636). Five sorted human thymocyte populations from 2 healthy donors were used as normal T-cell counterparts: 3 CD34 1 (CD34 1 4 2 1 2 , CD34 1 4 2 1 1 , CD34 1 4 1 ) and 2 double positive (DP; CD4 1 CD8 1 CD3 2 and CD4 1 CD8 1 CD3 1 ) populations. One donor's CD34 1 populations were sequenced twice (GSE142179) (Figure  1A ; supplemental Table  1 ). Quantification and annotation of circRNAs by CirComPara detected 68 554 circRNAs.
25 CircTest of significant CLP variations identified 133 circRNAs from 122 host genes with a significantly different   CLP in T-ALL with respect to normal thymocytes. Thus, besides differences in absolute circRNA expression, several genes also display an imbalance of circular to linear transcripts proportion in T-ALL as compared with normal thymic precursors. Matching the circRNA with significant differential absolute expression and CLP between T-ALL and thymocytes revealed that most of the absolute expression variations of circRNAs did not correspond to a varied CLP, indicating that circRNA expression followed the variation of the linear counterpart. Of note, a CLP variation was observed for 54 differentially expressed circRNAs (Figure  3B ), mostly (47/54) concordant with expression changes.
Acknowledgments This work has been supported by  Italian Ministry of Education, Universities, and Research  grant  PRIN 2017 2017PPS2X4_003  (S. B. and G. t. K. ),  AIRC , Milan, Italy Investigator Grant  2017 20052  (S. B. ), MFAG 2018 21771 (V. S. ),  Fondazione Umberto Veronesi, Milan, Italy (E. G. ), Fund for Scientific Research Flanders and Concerted Research Action (GOA) of the Ghent University  (P. V. V. , F. S. , and T. T. ),  ERC   St Grant Consolidator 311660  (S. G. ), and the  ANR-10-IBHU-0002 Saint-Louis Institute program  (S. G. ).
Retinoic Acid Upregulates RBM20 Expression and Corrects Splicing Defects We hypothesized that transcriptional upregulation of RBM20 could be a therapeutic strategy to compensate for loss of function of a heterozygous mutated allele. We interrogated the Gene Expression Atlas database  (Petryszak et al. , 2014)  for conditions that upregulate RBM20 and found that ATRA treatment was associated with upregulation of RBM20 expression in human embryonic stem cells in a genome-wide dataset  (Colleoni et al. , 2011). We confirmed that ATRA can induce upregulation of RBM20 transcript and protein in murine myoblast C2C12 cells (Figures  3A-3C ). ATRA treatment of C2C12 cells induced skipping of RBM20-regulated TTN exons, although the effect was not  significant (Figure  3D ). We thus evaluated ATRA in a more sensitive RBM20-dependent TTN splicing reporter assay in HEK293 cells  (Liss et al.
l ,___I ___. ~~1 1 11 11 I. ___I • _____. expression. Previously published chromatin immunoprecipitation sequencing (ChIP-seq) data revealed three cardiac-specific transcription factors (GATA4, TB5, and NKX2-5) that bind to the promoter region of RBM20 in murine cardiomyocytes  (Luna-Zurita et al. , 2016). Regulation by these factors is consistent with the RBM20 expression pattern in development  (Beraldi et al. , 2014)  and at the tissue level  (Maatz et al. , 2014). Indeed, GATA4 is induced by ATRA as shown by others  (Arceci et al. , 1993)  and our own data (Figure  S3E ). By analyzing published microarray data (GSE52317 from van Berlo et al. [2013]), we found that RBM20 expression was reduced upon cardiac-specific GATA4 depletion in adult mouse hearts in vivo. Further studies are necessary to investigate the effect of GATA4 loss-of-function on RBM20-dependent splicing.
, 2014) , with only four genes, including TTN, CAMK2D, LDB3, and SORBS1, overlapping both datasets. Among these four genes, we observe mis-splicing of TTN and CAMK2D and observe mis-splicing of the same exons previously reported  (Maatz et al. , 2014; van den Hoogenhof et al. , 2018). Calcium mishandling in RBM20 mutant cardiomyocytes has been attributed to the function of RBM20 as a splicing-regulator of several calcium handling genes including CAMK2D and CAC-NA1C  (Maatz et al. , 2014; Streckfuss-Bo ¨meke et al. , 2017; van den Hoogenhof et al. , 2018; Wyles et al. , 2016). We  (Figures 2A and S2D), and others (Streckfuss-Bo ¨meke et al. , 2017; Wyles et al. , 2016) , found that RBM20 regulated the splicing of a small exon (24 bp) in RyR2, which plays a major role in the release of calcium from the sarcoplasmic reticulum (SR) and triggers cardiac contraction.
Cell Reports c'Ce =>ress Variants identified as being in common between III;4, II;4, II;6 and absent in II;3, were first filtered by their frequency in the 1000 genome project, with those whose frequency is higher than 5% excluded. Next, the remaining variants were filtered according to their effects on protein sequences, removing those locating in intergenic, intronic, UTR regions, or having synonymous changes. Third, only the variants in the genes related to heart development or heart diseases (101 genes) were retained. Fourth, variants were checked manually in the raw sequence trace files to remove false positive calls. Finally, the remaining variants were checked against the ClinVar database to exclude those annotated as benign, likely benign, or variant of uncertain significance. Independent clinical sequence validation was carried out on the father (II;4).
A few cells for each clone were resuspended in 20 mL media and used for genomic DNA isolation with 0. 5 mL of DNA Release Additive in 20 mL Dilution Buffer (Phire Animal Tissue Direct PCR Kit (Thermo Fisher)). Finally, 2 mL of the mix was used for direct PCR amplification of the target genomic region using PrimeSTAR GXL DNA Polymerase (Clontech). To confirm that homozygous edits did not result from loss of one of the two alleles, we examined the parental line and found it has three heterozygous variants in the 3 0 UTR of RBM20 at positions Chr10:110836524, Chr10:110837082, Chr10:110837531. We analyzed the RNaseq data and found that all three heterozygous variants are present and expressed in all the edited lines. The top 3 predicted off-targets of the guide RNA were amplified and analyzed via Sanger sequencing to exclude the presence of unwanted editing (data not shown).
The stock samples were adjusted to working stocks of 2 mg/ml and diluted 10-fold using the 0. 1X sample buffer and 5X master mix (200 mM DTT, 5 3 sample buffer, 5 3 fluorescent standards). Samples were denatured at 95 C for 5 min. , and loaded with biotinylated ladder, chemiluminiscent substrate, antibodies (rabbit polyclonal anti-RBM20 15 and anti-aTubulin DM1A (Calbiochem)) and secondary antibodies onto the designated wells in a pre-microplate (Protein-Simple) prefilled with separation gel. Automated electrophoresis (375 V, 25 min, Antibody diluent time 5 min, primary & secondary antibody time 30 min) and immunodetection were performed following manufacturer's instructions. For data analysis, we used the Compass Software (ProteinSimple). The area under the curve of the protein of interest was divided by (normalized) the area under the curve of the loading control protein (a-Tubulin) peak.
Image analysis and calculation of physiological parameters Image analysis and physiological parameter calculation was conducted using commercially available Cyteseer (Vala Sciences)  (Cerignoli et al. , 2012). Contractility analysis was performed using a custom particle image velocity algorithm. Contractility is quantified as the relative change in area of the beating cells, given by the divergence of the measured deformation field, and reported as the peak divergence amplitude  (Serrano et al. , 2018; Sharma et al. , 2017). Data tables were analyzed using R. Comparisons between multiple groups were evaluated for significance using a two-way ANOVA, followed by multiple comparison of means using Tukey's test.
ACKNOWLEDGMENTS The authors would like to thank  Dr. Guangwen Wang , director of  Stanford University Stem Cell Core , for assistance in reprogramming patient cells. This work was supported by the  Steinmetz Cardiomyopathy Fund  (to L. M. S. , in memory of  Michael Steinmetz ), by the  Joan and Sanford I. Weill Scholar Endowment  (to M. M. ), by the  NIH  ( HG000205  to L. M. S. and  R01HL138539 ,  R01HL130840 ,  R01HL13967901 ,  R21HL141019 , and  P01HL141084  to M. M. ), the  NIH National Center for Advancing Translational Science Clinical and Translational Science Award  ( UL1TR001085  to L. M. S. ), the  NIH Common Fund Human Microbiome Project (HMP)  ( 1U54DE02378901  to M. S. ),  BMBF  (CaRNAtion to M. G. ),  DFG  (to M. G. ), and the  Berry Foundation Fellowship  (to J. W. ). The content is solely the responsibility of the authors and does not necessarily represent the official views of the  NIH.
Data sources Four European regions comprising 40 countries, as defined by the United Nations  [12] , were included in this study, namely Eastern Europe (Belarus, Bulgaria, Czech Republic, Hungary, Moldova, Poland, Romania, Russian Federation, Slovakia, Ukraine), Northern Europe (Denmark, Estonia, Finland, Iceland, Ireland, Latvia, Lithuania, Norway, Sweden, United Kingdom), Southern Europe (Albania, Bosnia and Herzegovina, Croatia, Cyprus, Greece, Italy, Macedonia, Malta, Montenegro, Portugal, Serbia, Slovenia, Spain) and Western Europe (Austria, Belgium, France, Germany, Luxembourg, The Netherlands, Switzerland). Cancer cases by sex, age group, cancer type and country were obtained from the GLO-BOCAN 2018 database  [13]. The data for the GLOBO-CAN database are provided by cancer registries.
Acknowledgement This project was supported by  Cancer Prevention Europe) , a consortium of currently nine partner organisations ( Cancer Research UK, London, UK ;  Danish Cancer Society, Copenhagen, Denmark ;  European Institute of Oncology, Milan, Italy ;  German Cancer Research Centre, Heidelberg, Germany; Imperial College London, London, UK ;  Karolinska Institute, Stockholm, Sweden; UK Therapeutic Cancer Prevention Network, University of Leicester , Leicester, UK; Maastricht University, Maastricht, The Netherlands;  World Cancer Research Fund International, London, UK/Wereld Kanker Onderzoek Fonds , Amsterdam, The Netherlands) coordinated by the  International Agency for Research on Cancer, Lyon, France. Ivana Kulha  ´novaalso received support from the  International Mobility of Researchers at Charles University , registration number  CZ.
, 2015b). DACCIWA aims at understanding complex interactions between aerosols, clouds, and their impact on climate and weather in south-western Africa. The study combines in situ and aircraft observations that are further compared with satellite data and models. The intensive field experiment of DACCIWA was carried out in June-July 2016 during the West African monsoon (WAM) (e. g. Knippertz et al. , 2017; Flamant et al. , 2018; Kalthoff et al. , 2018). The aerosol composition in the WAM region is mainly influenced by the large-scale synoptic pattern  (Mari et al. , 2008). During July and September, biomass burning smoke from southern Africa is the dominant contributor during the WAM season and is proposed as a major source for BC, as retrieved by satellite data and simulations  (Huang et al.
To the authors' knowledge, there has been no study of the vertical distribution of BC obtained by unmanned research aircraft in the WAM region so far. Subsequently, the BC distribution within the ABL is presented in general for the whole observation period (2-16 July 2016), in particular for an event (14-15 July 2016). In order to quantify the small-scale vertical BC distribution and to assess the role of small-scale local emissions, the airborne data were compared with ground monitoring and the COSMO-ART (Consortium for Small-scale Modelling-Aerosols and Reactive Trace gases) model of the DACCIWA framework. More precisely, observations for the wind profiler, ceilometer, and gas concentrations are taken into account that were installed 4 km away from the research flights in order to characterise the current weather situation and possible sources for BC.
5 m in constant height is provided by the autopilot system. The flight track follows predefined waypoints that are sent before take-off or during flight to the on-board computer and can be changed according to the specific scientific goals during measurement flights. Observed data and the flight path can be monitored via live transfer at a temporal resolution of 1 Hz. More information on the airplane itself can be found in  Altstädter et al. (2015). The instrumentation was updated for DACCIWA and the set-up is provided in  Bärfuss et al. (2018). All UAS data derived during DACCIWA are available from  Bärfuss et al. (2017). Other aerosol sensors (optical particle counter and condensation particle counter) that are usually on ALADINA did not work properly during DAC-CIWA. One reason for this might be damage to the optical parts after transportation.
Model description of COSMO-ART for DACCIWA In this section, a short description of the model COSMO-ART (Consortium for Small-scale Modelling-Aerosols and Reactive Trace gases) is shown with respect to the simulation set-up for the DACCIWA measurement campaign. COSMO-ART is a comprehensive online coupled model system  (Vogel et al. , 2009)  based on the operational weather forecast model COSMO  (Baldauf et al. , 2011). COSMO-ART includes a comprehensive chemistry module to describe the gaseous composition of the atmosphere and secondary aerosol formation. Chemical reactions are calculated with RADMKA (Regional Acid Deposition Model Version Karlsruhe;  Vogel et al. , 2009) , which is based on RADM2 (Regional Acid Deposition Model;  Stockwell et al. , 1990). Physical processes, including transport, turbulent diffusion, and dry and wet deposition, are treated together with photochemistry and aerosol dynamics using the modal approach.
Every 3 or 4 years, the flow regulator device is sent to the French Laboratoire national d'Essais for check and calibration. NO and NO 2 were measured with a model 42C-TL NO-NO 2 -NO x (Thermo Environmental Instruments Inc. ) with a 0. 05 ppb v detection limit. The model 42C-TL NO-NO 2 -NO x was calibrated before and after the campaign by using a reference NO 2 air mixture, i. e. NO in N 2 diluted with zero air. Reference NO and NO 2 were ISO 6141:2015 certified at 8. 73 and 8. 58 ppm for NO before and after the campaign, respectively, and 9. 28 ppm for NO 2 , both with 5 % precision  (Pacifico et al. , 2019). All data for the trace gases were sampled every 10 s, filtered, and averaged to produce 1 and 30 min values. The data are accessible from  Derrien et al. (2016).
Conclusions This article aims at understanding the relationship between the vertical distribution of BC and ABL processes in southern West Africa. The investigation area is supposed to be one of the major sources for BC emissions worldwide  (Liousse et al. , 2014). But where do those BC emissions originate, especially in the ABL? Beyond surface measurements, the role of BC is difficult to assess within the ABL due to lacking column measurements. ALADINA was applied for meteorological profiling and BC measurements during the extensive field experiment of DACCIWA at Savè, Benin, on 2-16 July 2016. BC was measured with a micro-aethalometer, model AE51, that has proven to be a feasible tool on a UAS, but it suffers from artefacts that were one subject of this paper. Prior to analyses, BC data were corrected with bias caused by the dependence of the instrumentation on internal temperature during ascents and descents.
Acknowledgements. The  DACCIWA  project has received funding from the  European Union Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement no. 603502. Barbara Altstädter  was financially supported by the  German Research Foundation (DFG)  under the project number  LA 2907/5-2. The authors from  TU Braunschweig  wish to thank  UPS  and  KIT  for being part of the  DACCIWA  project. We gratefully acknowledge  Lutz Bretschneider ,  Endres Kathe , and  Birgit Zachrau  for their support in the preparation of the  UAS ALADINA  and during the experiment on site. We thank both referees for their critical input and valuable suggestions for improving the paper. Financial support. We acknowledge support by the  German Research Foundation and the Open Access Publication Funds of the Technische Universität Braunschweig.
Data availability. The data used in this study (https://doi. org/10. 6096/dacciwa. 1618, Derrien et al. , 2016; https://doi. org/10. 6096/DACCIWA. 1686, Handwerker et al. , 2016; https://doi. org/10. 6096/dacciwa. 1659, Wieser et al. , 2016; https://doi. org/10. 6096/baobab-dacciwa. 1701, Bärfuss et al. , 2017) are available on the SEDOO database (http://baobab. sedoo. fr/DACCIWA/, last access: 3 July 2020).
For some objects, we compare our results with already existing models to test the reliability of our methods. Thanks to the increased photometric datasets produced by our project, previously existing solutions have been improved for the asteroids that were selected, and for two targets for which we determine the physical properties for the first time. We provide the scale and volume for all the bodies that are studied with realistic error bars. These volumes combined with the masses from Gaia astrometry will enable precise bulk density determinations and further mineralogical studies. The selected targets are mostly asteroids with diameters larger than 100 km, which are considered to be remnants of planetesimals  (Morbidelli et al. 2009 ). These large asteroids are assumed to only have small macroporosity, thus their bulk densities can be used for comparison purposes with spectra.
Observing campaign In order to construct precise spin and shape models for asteroids, we used dense photometric disk-integrated observations. Reliable asteroid models require lightcurves from a few apparitions, that are well distributed along the ecliptic longitude. The available photometric datasets for selected Gaia mass targets are complemented by an observing campaign that provided data from unique geometries, which improved the existing models by probing previously unseen parts of the surface. Using the Super-WASP (Wide Angle Search for Planets) asteroid archive  (Grice et al. 2017 ) was also very helpful, as it provided data from unique observing geometries. Moreover, in many cases new data led to updates of sidereal period values. The coordination of observations was also very useful for long period objects, for which the whole rotation could not be covered from one place during one night.
We gathered our new data during the observing campaign in the framework of the H2020 project called Small Bodies Near And Far (SBNAF,  Müller et al. 2018). The main observing stations were located in La Sagra (IAA CSIC, Spain), Piszkéstető (Hungary), and Borowiec (Poland), and the observing campaign was additionally supported by the GaiaGOSA web service dedicated to amateur observers  (Santana-Ros et al. 2016). For some objects, our data were complemented by data from the K2 mission of the Kepler space telescope  (Szabó et al. 2017 ) and the TRAPPIST North and South telescopes  (Jehin et al. 2011). Gathered photometric data went through careful analysis in order to remove any problematic issues, such as star passages, color extinction, bad pixels, or other instrumental effects. In order to exclude any unrealistic artefacts, we decided not to take into account data that were too noisy or suspect data.
01 mag. This way, the scale-free dimensions with the most extreme, but still possible shape feature modifications, were calculated and then translated to diameters in kilometers by fitting occultation chords. Some of the calculated models can be compared to the solutions obtained from other methods, which often use adaptive optics images, such as KOALA (Knitted Occultation, Adaptive-optics, and Lightcurve Analysis,  Carry et al. 2010)  and ADAM  (Viikinkoski et al. 2015). Such models are stored in the DAMIT Database of Asteroid Models from Inversion Techniques (DAMIT) database (http://astro. troja. mff. cuni. cz/projects/asteroids3D, Ďurech et al. 2010). Here, we show the nonconvex shapes that were determined with the SAGE method. We have only used the photometric data since they are the easiest to use and widely available data for asteroids.
It should be noted, however, that some shape features, such as the depth of large craters or the height of hills, are prone to the largest uncertainty, as was shown by  Bartczak & Dudziński (2019). It is also worth mentioning here that such a comparison of two methods is valuable as a test for the reliability of two independent methods and for the correctness of the existing solutions with the support of a wider set of photometric data. For a few targets from our sample, we provide more realistic, smoother shape solutions, which improve on the previously existing angular shape representations based on limited or sparse datasets. For two targets, (145) Adeona and (308) Polyxo, the spin and shape solutions were obtained here for the first time.
Scaling the models by stellar occultations The calculated spin and shape models are usually scale-free. By using two independent methods, the stellar occultation fitting and thermophysical modeling, we were able to provide an absolute scale for our shape models. The great advantage of the occultation technique is that the dimensions of the asteroid shadow seen on Earth can be treated as a real dimension of the object. Thus, if enough chords are observed, we can express the size of the object in kilometers. Moreover, with the use of multichord events, the major shape features can be recovered from the contours. To scale our shape models, we used the occultation timings stored in the Planetary Data System (PDS) database  (Dunham et al. 2016). Only the records with at least three internally consistent chords were taken into account.
A rich dataset of 112 thermal infrared measurements is available for (3) Juno, including unpublished Herschel PACS data  (Müller et al. 2005 ). The complete PACS catalog of small-body data will be added to the SBNAF infrared database once additional SBNAF articles are published. For instance, the full TPM analysis of Juno will be included in an accompanying paper that features the rest of the PACS main-belt targets  (Alí-Lagoa et al. , in preparation). Here, we include Juno in order to compare the scales we obtained from TPM and occultations. TPM leads to a size of 254 ± 4 km (see Tables  2  and A.