dataesr/scientific-paragraphs-categorization huggingface dataset:
exRNA distributions correlate across cell types in human and Drosophila. To further characterize EV RNA repertoires, we next subtracted rRNA reads and submitted adjusted libraries to genomic alignments and expression analyses (Table  2 ). We retrieved GENCODE annotations using Ensembl Biomart for the 1,000 most abundant transcripts in each library and compared exRNA and cellular RNA biotype abundance distributions (Fig. 2 ). Interestingly, a strong positive correlation was observed between human HepG2 and A431 exRNA biotypes (Fig. 2A ; Pearson's r = 0. 92, P = 3 × 10 -3 ). The miscellaneous RNA category was strongly overrepresented in human exRNA, accounting for over one third of A431 and over half of HepG2 exRNA distributions, as opposed to 1% for HepG2 cell RNA. In Drosophila D17 EVs, snoRNAs represented nearly half of the distribution, whereas S2R + EVs contained a majority of mRNAs (Fig.
To test this hypothesis, we took advantage of our vast EV repertoire of human and Drosophila mRNAs to investigate global abundance correlations across orthologs of the two species. Using an integrative ortholog prediction tool  80  , we retrieved 1,140 pairs of orthologous mRNAs represented in our D17 and HepG2 cellular and EV datasets. We first compared cellular relative abundance values, which revealed a strong positive correlation (Figure  S15 ; Pearson's r = 0. 61, P < 10 -4 ). These distributions were largely dominated by abundant mRNAs encoding ribosomal proteins. When comparing the relative abundance distributions of orthologs in EV, we documented a slightly weaker correlation (Figure  S15 ; Pearson's r = 0. 54, P < 10 -4 ). Therefore, while the expression levels of orthologous mRNAs are strongly related, our comparative analysis does not suggest that gene-specific mRNA enrichment to EVs is a globally conserved feature.
Electron microscopy. Steps were performed as previously described  89. Briefly, 10 μ L of fresh EVs preparations diluted in 100 μ L PBS were loaded on previously discharged formvar-coated copper grids and allowed to adhere for 20 min. The grids were then applied to freshly prepared drops of 2% uranyl acetate for 30 to 40 s and washed six times for two minutes with water. Excessive water was removed by absorption and grids were left to dry for 30 min. Samples were imaged on a Tecnai 12 120 kV transmission electron microscope. Contrast was enhanced with the software Photoshop (Adobe).
Reads mapping to RepeatMasker v4. 0. 6 sequence coordinates were counted with BEDTools. Ribosomal RNA sequences were filtered out by first mapping the reads to FASTA files of genes annotated as rRNA in Ensembl. Remaining reads were then re-aligned to reference genomes with Tophat. BAM files were used for expression analyses with Cuffdiff v2. 2. 1 without effective length correction. Transcripts per million (TPM i = [FPKM i /Σ j FPKM j ] × 10 6 ) were used as relative abundance units. A 5 FPKM threshold was applied. For biotype and correlation analyses, the 1,000 most abundant transcripts were considered, which accounted for over 90% of identified transcripts.
Reverse transcription quantitative PCR (RT-qPCR). The M-MLV reverse transcriptase (Invitrogen) was used according to the manufacturer's instructions to synthesize cDNA in triplicate starting from 100 ng of exRNA and cell RNA. Priming was performed with random hexamers (Promega). Real-time PCR was performed on the ABI ViiA7 instrument (Life) using SYBR Green reagent (Applied Biosystems). Cycling conditions were as follows : 50 °C for two minutes and 95 °C for 10 min followed by 40 cycles of 95 °C for 15 s, 59 °C for 60 s. Melting curve analysis was performed. Validated primer sequences targeting exon junctions were retrieved from the GETprime database 86 (Table  3 ).
Statistic tests were performed with GraphPad Prism v6. Datasets are available on GEO under the accession number GSE76173. References 1. Tsui, N. B. , Ng, E. K. & Lo, Y. M. Stability of endogenous and added RNA in blood specimens, serum, and plasma. Clin Chem 48, 1647-1653 (2002). 2. Skog, J. et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat Cell Biol 10, 1470-1476, doi: ncb1800 10. 1038/ncb1800 (2008). 3. Valadi, H. et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 9, 654-659, doi: ncb1596 10. 1038/ncb1596 (2007).
Acknowledgements This project was supported by the  Cancer Research Society of Canada  (grant # 20227 ) and start-up funding from the  IRCM  to EL, as well as a foundation grant from the  Canadian Institutes of Health Research (CIHR)  to JR. EL is a  Junior 2 scholar  of the  Fonds de Recherche du Québec-Santé (FRQS)  and a  Louisa Gale Scholar  of the  Canadian Cancer Society. FAL was supported by scholarships from the  Canadian Institutes of Health Research (CIHR) , the  National Sciences and Engineering Council of Canada , and from  RQS. DG was supported by a  Thelma Adams Fellowship  from the  Montreal Children′ s Hospital Foundation. The authors express their gratitude to core facilities staff, notably  Jeannie Mui  ( McGill Facility for Electronic Microscopy ) and  Odile Neyret  ( IRCM Molecular Biology Platform ).
Statistic tests were performed with GraphPad Prism v6. Datasets are available on GEO under the accession number GSE76173. References 1. Tsui, N. B. , Ng, E. K. & Lo, Y. M. Stability of endogenous and added RNA in blood specimens, serum, and plasma. Clin Chem 48, 1647-1653 (2002). 2. Skog, J. et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat Cell Biol 10, 1470-1476, doi: ncb1800 10. 1038/ncb1800 (2008). 3. Valadi, H. et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 9, 654-659, doi: ncb1596 10. 1038/ncb1596 (2007). TPT1 PABPC1 ATF4 PTBP1 HDGF G3BP1 BRAF Drosophila melanogaster sequences arc1 pabp2 sqd cam rin hmu Data access. Homo sapiens sequences imp Forward primer 5′ -CACGATGAGATGTTCTCCG-3′ 5′ -CACTGGCATGTTGTTGGAG-3′ 5′ -ATGATTACCTGGAGGTGGC-3′ 5′ -AGTTCTTCCAGAAGGACCG-3′ 5′ -GTGACGGTGATAAGAAGGG-3′ 5′ -GTAGAGGAACCTGAAGAAAGAC-3′ 5′ -CTATTGGACAAATTTGGTGGG-3′ Forward primer 5′ -TAGAAGGTATCAGCGACGAG-3′ 5′ -GCATACATTGAGTTTGGTTCC-3′ 5′ -CACGGCAAGATCTTTGTCG-3′ 5′ -GAAACTCACAGACGAGGAG-3′ 5′ -CAAGGGTGACTTTGAGCAG-3′ 5′ -TCTACTGGACGGACTCCTC-3′ 5′ -CTCTACGAATAAGGGTGAACTC-3′ Reverse primer 5′ -TCCTACTGACCATCTTCCC-3′ 5′ -CTTCATCAACCTTAGAACGGAG-3′ 5′ -CTCCTTGCTGTTGTTGGAG-3′ 5′ -GTTGTGCAGGTCAATGAGG-3′ 5′ -TTTAGGAGAGTCCTCCAGC-3′ 5′ -ATGTCATTACTGACAACTGCC-3′ 5′ -GTATTCTTCATAGGCCTCCAG-3′ Reverse primer 5′ -GCCATACCGTAGAACAGCA-3′ 5′ -CGACATTACCTTTATTTGACGC-3′ 5′ -TCCACCTCGACGATATTGC-3′ 5′ -CATCATAGTCACGAATTCTTCG-3′ 5′ -GACATTTCCGAAGCGTGAG-3′ 5′ -TATTTGAAGAGACGGCCGG-3′ 5′ -CGTCCAATCAAATTGTTGTGG-3′.
The parameter χ on the other hand decreases with filter-length. 5 In our simulation, the value of optimal weight vector, w o , is obtained as w o = pinv(H)e where pinv(•) is the MATLAB function for the evaluation of pseudo-inverse. The TEMSE, as expressed in  (56) , is a convex downward function of filterlength. Evaluating TEMSE for different filter lengths can provide us with the optimal value of filter-length required to equalize the given channel and given step-size. In this simulation, we have considered a voice-band telephone channel h n = [-0. 005 -0. 004 j, 0. 009 + 0. 03 j, -0. 024 -0. 104 j, 0. 854 + 0. 52 j, -0. 218 + 0. 273 j, 0. 049 -0. 074 j, -0. 016 + 0. 02 j] [73] and 16-QAM signaling. The eigenvalue spread of the channel is 5. 83 and the ISI introduced by this channel is -8.
His current research interests lie in the areas of signal processing and machine learning, with applications to communications, gene expression data, functional magnetic resonance data, and biomedical data. He has made many fundamental theoretical and algorithmic contributions to many aspects of signal processing and machine learning. He has much expertise in "Big Data", dealing with heterogeneous data, and extracting information from multiple datasets obtained in different laboratories and different times. He has authored over 500 technical publications, including 200 journal papers as well as four books. Professor Nandi is a Fellow of the Royal Academy of Engineering and also a Fellow of seven other institutions including the IEEE and the IET. Among the many awards he received are the Institute of Electrical and Electronics Engineers (USA) Heinrich Hertz Award in 2012, the Glory of Bengal Award for his outstanding achievements in scientific research in 2010, the Water Arbitration Prize of the Institution of Mechanical Engineers (UK) in 1999, and the Mountbatten Premium, Division Award of the Electronics and Communications Division, of the Institution of Electrical Engineers (UK) in 1998.
Acknowledgments The authors acknowledge the support of  COMSATS Institute of Information Technology (Islamabad and Wah Campuses), Pakistan , the  Deanship of Scientific Research at King Fahd University of Petroleum and Minerals  under research grant  RG1414 ,  Saudi Arabia , and  Brunel University London, UK  towards the accomplishment of this work. They also acknowledge the Editor and anonymous reviewers for their support and valuable feedback.
Acknowledgement This work is supported by the  Defense Reduction Agency Basic Research Program , Grants number:  HDTRA1-15-1-0036 ,  HDTRA1-15-1-0027 ,  HDTRA1-15-1-0039 , and  HDTRA1-15-1-00XX  (need  MIT  award number). Figure 10: Measured material refractive index change induced by Co-60 gamma-radiation for (a) a-Si (hydrogenated amorphous silicon); and (b) silicon nitride.
Acknowledgements This research has been funded by the  AHRC  as part of the Crossing the  Threshold  Project ( AH/K00378X/1 ). Grateful thanks are extended to  Jersey Heritage  and the  Société Jersiaise  for their support, and in particular to  Olga Finch ,  Neil Mahrer ,  Jon Carter ,  Ralph Nichols ,  John Renouf ,  John Clarke  and  Neil Molyneux , as well as to  Peter Hoare  and  Anne-Lyse Ravon  for work on the raw materials, and to  Rob Hosfield  and an anonymous reviewer for their comments. Beccy Scott would also like to acknowledge the support of the  Calleva Trust (Pathways to Britain)  project.
Material and Methods Floating plastic debris and surface plankton were sampled in the framework of the participative science activities of Expeditions MED (www. expeditionmed. eu) association from July 6th to August 6th 2013. Sampling was carried out at a total of 33 sites across the Ligurian Sea (NW Mediterranean sea), with distances to land ranging from 0. 3 to 46 km. Fifty four percent of the sampling sites were within the 1-km water strip adjacent to the mainland coast. Geographical coordinates and dates of sampling are available at Pangea Data Publisher http://www. pangaea. de and illustrated in Fig 1. Permission for navigation and research operations in exclusive economic zones Sea was granted from the Governments of France and Italy. Samples were collected using a Manta trawl net with 333 μm mesh size with a rectangular net opening of 60 x 20 cm.
Plastic items were counted, and measured by imaging analysis using the Zooscan system  [24, 25]. Firstly, they were digitally imaged with a Zooscan digital scanner with a resolution of 2400 dpi; each pixel is about 10 microns wide. Image post-processing was performed with the Zooprocess & Plankton Identifier software that gives a set of morphological parameters for each object, including ferret diameter (i. e. the maximal distance between any two points along the boundary of the object) and surface area (mm). Zooplankton of 30 samples (ranging from 0. 5 and 46 km far from land) was also processed, except 3 samples containing too many aggregates to be accurately analyzed with ZooScan. We calculated a plastic plankton ratio by dividing the total concentration of microplastics by zooplankton concentrations for all the 30 stations.
The relationship between plastic concentrations and coastal population densities was performed by consulting the statistical results of the 2012 population census database of the French National Institute of Statistics and Economic Studies (INSEE) listing population categories and their composition  [26]. The Italian coastal populations densities, characteristics, and statistics were consulted on the following official website: http://en. comuni-italiani. it. A total of 407 plastic items were randomly extracted from 28 manta tows to identify their chemical structure by Fourier Transform Infrared Spectroscopy (FT-IR) spectra, using a FT-IR spectrometer (Shimadzu 8400 M) with 4 cm -1 resolution and 40 scans. All spectra were recorded in the absorbance mode in the 4000-600 cm -1 region. Each sample was put onto the diamond cell and compressed between two plates into a thin uniform thickness enough to allow for adequate transmission of IR beam through the sample to the detector and resulting in a better quality spectrum.
FT-IR spectra of the plastic samples were compared with spectra of known plastics to identify polyacrylics (PAA), polyamides (PA), styrenics (homopolystyrene (PS), PS-based copolymers or PS foams) and polymers belonging to the family of the polyolefins, including polyethylene (PE), propylene (PP) and ethylene vinyl acetate (EVA). To analyze the changes in the plastic pollution in relation to the distance to land, we combined our data of plastic abundances (n = 33 distance to land: 0. 3-46 km) with those recently reported by de Lucia et al. for the Central-Western Mediterranean (n = 10; distance to land: 0. 5-18 km;  [23]  and by Cózar et al. for the entire Mediterranean basin (n = 28; distance to land: 7. 6-340 km;  [21]. Furthermore, to characterize the size distribution pattern of plastics we Overall, the data compilation of the sampling sites were grouped into three strips, < 1 km from land (8,053 items), between 1 and 10 km from land (1,830 items), and from 10 km to 46 km (4,469 items) in agreement with the local bathymetry and currents.
32 to 100 mm with particles displaying an asymmetrical frequency distribution skewed toward smaller size classes. Results showed that across the sampling area, small fragments measuring less than 2. 5mm composed 64% of microplastics observed, fragments measuring 2. 5-5 mm composed 27% and larger fragments (>5 mm) represented 9% of the total plastic collected. The median length of plastics was 1. 95 mm with an increase in the size of fragments with the distance from the coast 1. 85, 2. 76 and 3. 86 mm respectively at < 1 km, 1-10 km, >10-46 km. The combined data set of our study with those previously reported for the Mediterranean Sea  [21, 23] , showed higher abundance of plastics towards land and towards offshore regions (Fig  2 ). High concentrations of plastic debris were commonly measured in the 1-km water strip adjacent to coast, ranging from 28,000 to 578,000 items km -2 and with most of the concentrations (56%) above 100,000 items km -2.
Previous studies on the spatial distribution of plastic in Mediterranean have referred to these effects as the major cause of the apparent lack of stable plastic retention areas  [21, 22]. The uneven distribution of coastal populations and land-based pollution sources could also contribute to the heterogeneity observed in the nearshore waters. However, a significant correlation (R = 0. 449, P = 0. 010, n = 26) between surface plastic concentrations and the coastal human population was found for the adjacent coastal area (Fig  3A ). This suggests that a major part of the coastal plastic pollution may come from the nearby land-based sources and coastal maritime activities linked to densely populated zones, as proposed for other regions around the world  [29, 30]. However, in our dataset the differences in numerical concentrations of plastic along the shoreline were due to changes in the abundance of tiny plastic pieces instead of newly introduced large-sized objects.
This was supported by the considerably higher relative abundance of small plastic particles (< 2 mm) in the 1-km water strip adjacent to coast. Hence, the residence time of the plastic pollution entering from land within the nearshore waters seems long enough to undergo an important fragmentation. This is agreement with the model of Isobe et al. [14] ; they noted that the largest plastics (> 5 mm), being more buoyant, are selectively trapped close to the coast by effect of the Stokes drift produced by the wave. Thus, large plastic objects would be commonly washed ashore on beaches to degrade into small fragments before leaving the nearshore waters. A data bank containing the spectra of main plastics has been previously established according to the statistics provided by Plastics Europe  [31].
All the plastics constituting this database are referenced except the poly(vinyl choride) which is only used nowadays in building and construction for long-term applications. Based on this database we were able to identify more than 95% of plastic samples collected since only a few percent of the samples remain unidentified (less than 2%), whereas the most abundant types of plastic debris are PE, PP, PS and PA. In all water strips analyzed, the large majority (from 73 to 79%) of plastic items found and subjected to FT-IR were made of polyolefins (Fig  2   [32, 11, 8]. PE and PP are light polymers (density: 0. 85 to 0. 97 g mL 1 ;  [33, 34]  widely used in the packaging, typically single-use disposable products with a relatively short life time, rapidly ending up in waste and litter stream.
Our results showed a relationship between plastic concentration nearshore and coastal populations (Fig  3A ). Despite a large heterogeneity, the relationship we found opens a way to model the variability and fate of coastal plastic although more data are still required. Other coastal reservoirs of plastic as beaches and coastal seafloor should be also assessed taking into account specific samplings and assessments on floating micro and macro-plastic fraction. The concern about the marine plastic pollution is generating multiple initiatives to prevent, mitigate and monitor this emerging problem. In Europe, the Marine Strategy Framework Directive (MSFD) recognizes marine litter as one of the descriptors for the environmental state of the European seas  [48]. However, our limited understanding concerning input, distribution and transformation of the marine plastic debris make this descriptor difficult to deploy.
Acknowledgments The present study was funded by the  French GDF Suez foundation  through the  ECOSEASTEM  project,  French Ministry of Research and EU's Framework Programme 7 MedSeA  ( EU  contract number  FP7-2010-265103 ). Sampling was conducted by the  French citizen science NGO Expe-ditionMED  and analysed in the framework of the  European Marine Biological Resource Centre (EMBRC-France) research infrastructure in Villefranche sur Mer. The present work resulted in part from a short stay of  A. Cózar  in the  Laboratory of Oceanography of Villefranche (LOV) , supported by the  "Salvador de Madariaga" Mobility Program of the Spanish Ministry of Education, Culture and Sport  (ref. PRX14/00743 ).
The present study was funded by the  French GDF Suez Foundation  through the  ECOSEASTEM  project,  French Ministry of Research and EU's Framework Programme 7 MedSeA  ( EU  contract number  FP7-2010-265103 ). Sampling was conducted by the  French citizen science NGO ExpeditionMED  and analysed in the framework of the  European Marine Biological Resource Centre (EMBRC-France) research infrastructure in Villefranche sur Mer. The present work resulted in part from a short stay of  A. Cózar  in the  Laboratory of Oceanography of Villefranche (LOV) , supported by the  "Salvador de Madariaga" Mobility Program of the Spanish Ministry of Education, Culture and Sport  (ref. PRX14/00743 ).
Hedonic evaluation An acceptability test was carried out by 80 untrained panelists (49 females and 31 males, age 1828). Four samples were assessed in one session during which subjects rated overall acceptability, and acceptability of odor, taste and mouthfeel on a 9point hedonic scale  [8]  ranging from 1 (dislike extremely) to 9 (like extremely) using the Compusense athand ® (Compusense Inc. , Guelph, ON, Canada) sensory evaluation software. In addition, a JustAboutRight (JAR) scale [8] (3: too little, 0: just about right, 3: too much) was included for the basic tastes (saltiness, sweetness, sourness, and bitterness) to determine the compatibility of their intensity in the samples with optimum acceptability levels. Moreover, panelists were asked to identify any additional flavor perceived other than the four basic tastes.
Super-exchange The super-exchange mechanisms in the Mott regime for a spinor gas become rather involved due to the multichannel character of the interaction. A large number of additional spin-exchange phenomena can thus arise in addition to the exchange of the spins found in spin 1/2 FIG. 4:  (a) Oscillation amplitude as a function of the fraction of doublons in the cloud. The data point at the origin corresponds to a situation where all doublons are removed using dipolar relaxation at large magnetic field. The other points correspond to different temperatures. (b) For each point, the doublon fraction is independently estimated by measuring the fraction of atoms which disappear when doubly occupied sites are emptied using dipolar relaxation at large magnetic fields systems. For example, for a spin 3, a two-body state |2, 1 (where one site contains an atom in state with m s = 2, and the next site contains an atom with m s = 1) could become |1, 2 or |3, 0 or |0, 3.
Acknowledgements: This work was supported by  Conseil Régional d'Ile-de-France  under  DIM Nano-K / IFRAF, Ministère de l'Enseignement Supérieur et de la Recherche  within  CPER  Contract, and by  Université Sorbonne Paris Cité (USPC). P. P. acknowledges funding by the  Indo-French Centre for the Promotion of Advanced Research -CEFIPRA. We thank  Martin Robert-de-Saint-Vincent  for his critical reading of the manuscript.
We test a recently developed engineering turbulence model, a so-called explicit algebraic Reynolds-stress (EARS) model, in the context of the atmospheric boundary layer. First of all, we consider a stable boundary layer used as the well-known first test case from the Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study (GABLS1). The model is shown to agree well with data from large-eddy simulations (LES), and this agreement is significantly better than for a standard operational scheme with a prognostic equation for turbulent kinetic energy. Furthermore, we apply the model to a case with a (idealized) diurnal cycle and make a qualitative comparison with a simpler first-order model. Some interesting features of the model are highlighted, pertaining to its stronger foundation on physical principles.
2011 ) and a prototype of the EFB closure described in Sect. 2. 3 (coded by E. Bazile, internal communication), both with a vertical grid size of 6. 3 m. For the LES data, we have datasets from five different simulations with a 2-m resolution  (Beare et al. 2006). Figure  1  compares the results of all these computations for the mean wind speed and mean potential temperature To demonstrate the validity of the boundary conditions used in the model, we plot the mean wind-speed and mean potential temperature profiles on a logarithmic scale, shown in Fig. 3. The model results are compared with the EFB closure implemented in the ARPEGE model and the LES dataset that is closest to the current model in Figs. 1  and 2  (i. e. the NCAR dataset, see  Beare et al. 2006). Clearly, both the models and the LES obey the same logarithmic law near the surface (up to ≈5 m).