dataesr/scientific-paragraphs-categorization huggingface dataset:
Indeed, this somewhat 'borderline' status of new storytelling between oral and written media makes it a particularly interesting site for the analysis of a phenomenon such as postposition that is traditionally found in formal written varieties but for which there is some, albeit limited, evidence in oral French. The French Oral Narrative Corpus will therefore be at the centre of this analysis, as the springboard for an exploration of medium, register and genre; and it will be referred to in the article as the 'new storytelling' corpus. However, given the highly specific nature of the corpus, I will present, where possible, some comparisons with three other small corpora representing different registers and media: i. a subset of twenty conversational narratives taken from the CRFP corpus: these are informal conversational stories from the same source as Cappeau's data and will be known as the 'mini-CRFP' corpus in order to distinguish the subcorpus used for this paper from the full CRFP corpus; 18  ii.
In the case of spatiotemporal elements at the head of the phrase, these are particularly important for the performance of the story in terms of its evolution in time and space. In other words, the spatiotemporal positioning of events and descriptions in the evolution of the story, and the progression of narrative events in sequence, both seem to play a role in increasing the presence of two particular contexts in which postposition might -and in a number of cases does -occur. Indeed, at times both types of usage of postposition appear to be somewhat formulaic, something which is also highly compatible with the performed oral story. It is difficult to know whether we can go as far as describing either of these contexts for postposition as a genre feature. Certainly, relative to the other types of oral data examined, and bearing in mind Cappeau's research, new storytelling seems to constitute an oral discourse genre where levels of postposition of the subject are raised and the reasons for this might be connected to other features of the genre, notably its narrative structure and its performance context.
In terms of broader questions of register and medium, when new storytelling is viewed alongside the other mini-corpora analysed, it is clear that the presence of postposition ranges from relatively rare to extremely rare and tends to be restricted to certain types of structure. Questions of register and medium are undoubtedly relevant. Incises, for example, are tightly linked to medium and register: they are widespread in the formal written medium of literature, almost non-existent in informal oral varieties and present in not insignificant quantities (albeit minority rather than dominant), in the more formal 'borderline' genre of new storytelling. Similarly, in the case of relatives, postposition seems also to be related to medium and register; it is certainly attested in the dataset analysed here, but productivity is very limited in even the most formal varieties of the oral medium, with particular types of relative dominating (où and que), as they do in other less formal oral varieties.
For all elements of an integrated cancer prevention research programme, effective and well-resourced population-based cancer registration systems will be required. This is an essential requirement both to define the size and scale of the problem and to monitor the impact of interventions. Modern cancer registries will also need to contain appropriate identifiers and be fully integrated into national information systems so that data linkages can be formed with both research datasets and routine health and other information sources. This will, in turn, require robust solutions to address questions of data security and confidentiality and ethical considerations regarding patient choice and patient integrity.
These would be supported by a range of platforms, networks and infrastructures and draw together a wide network of partners. Training and capacity building would be integral to the initiative. The conduct of prevention research and the collation of information on cancer prevention would be translated through to an evidence-base on which cancer control policy could be based. Inherent to the philosophy of CPE would be the sharing of resources (including existing research platforms, such as cancer registries, screening registries, clinical databases and biospecimen repositories etc), the sharing of data (establishing multicentre, trans-national research projects to provide sufficient statistical power to identify modest-size effects and making use of multidisciplinary approaches); and by the creation of a central repository in Europe of information pertinent to cancer prevention (a European Knowledge Hub on Cancer Prevention).
Suitable and acceptable legal frameworks would be established within CPE to permit information exchange, to monitor regulations and to highlight potential and actual barriers to progress through any implemented legislation. There are a number of large prospective cohort studies in Europe, both in adults and children/adolescents, which permit the study of the causes of cancer and other NCDs throughout the life-course. Often the maintenance of these research platforms nationally is difficult and failure to identify long-term support jeopardizes the potential benefits. A good example is the 30 or so cohorts which were a part of the EC-financed BBMRI-LPC  [43] , including a total of around 2 million participants and comprising datasets on exposures, clinical outcomes as well as associated biobanks, the latter of which in turn cooperate through the EU-funded infrastructure BBMRI-ERIC  [31].
Both population cohort data and biospecimens offer major research platforms for understanding the causes and prevention of cancer. There are other studies of different design e. g. multi-centre case-control studies, randomized clinical or community-based trials, and the evaluation of natural experiments within or between countries which offer additional opportunities for prevention research. Bringing together such platforms and new initiatives under a co-ordinated prevention agenda would bring major added-value to future and past EC research investment; in contrast, to abandon these now would result in a failure to realize the benefits of prior investments. The development of an alliance of organizations focused on cancer prevention would provide a focal point for reflection on professional training and career development within the context of a network of leading institutions, resulting in fellowships, courses, PhD programmes etc.
This would be particularly valuable in the area of cancer prevention which involves different disciplines and where no simple career pathway is evident. The proposed CPE Knowledge Hub would provide policy-makers access to data on cancer burden, risk factor prevalence, attributable fraction of cancers associated with known risk factors and effective preventive interventions. The evidence-base would not stop at identifying risk factors or potential interventions but would evaluate the effectiveness of preventive interventions supported by legislation, regulation and other policy initiatives in the context of broader assessments. This exercise should not duplicate existing efforts in collating data from these different domains but, where possible, would draw upon existing resources and work in cooperation, providing links, where applicable, to existing sources of information.
In parallel, recognized leadership in cancer prevention in Europe would serve as a reliable resource both for collating but also interpreting the scientific evidence-base for prevention and making this available to the EU and national policymakers. International cooperation would provide such evidence in an independent, autonomous manner. The outlook of CPE would be designed to complement parallel initiatives on treatment, such as the recently established Cancer Core Europe  [44]. Indeed there are many areas of overlap in relation to methodology (e. g. laboratory, epidemiology, biostatistics and bioinformatics), platforms (e. g. equipment, biobanks and database linkage) and opportunities to build on the understanding of underlying mechanisms of carcinogenesis for translational research both to the clinic and population settings.
Conclusion An international consortium to launch, evaluate and incrementally improve evidencebased prevention strategies within Europe will further the prospects for ensuring populations have access to and benefit from the effective cancer prevention to which they are entitled. Sources: Incidence data  [1] ; Risk factor attributable fractions  [17]  Figure  3a. Cancer caused by alcohol in Europe: proportions of all cancers and number of cancers that could be prevented by alcohol control. The 7. 1% of all cancer cases in Europe attributable to alcohol consist predominantly of cancers of the breast, colorectum and lip, oral cavity, oropharynx and hypopharynx, but also cancers of the oesophagus, larynx and liver. Sources: Incidence data  [1] ; Adult per capita consumption of alcohol for 2000  [19] ; Risk estimates  [20] ; Methodology  [21].
Performance and presentation of the results Performance in the forced-choice task was expressed as a percentage (maximum performance 100%). In the Yes/No task, performance was calculated using a sensitivity index: d-prime = Z(Hit rate) -Z(False Alarm rate) with Z being a Z- score. Within each analysis, Z-score values were corrected for infinite scores (in accordance with  Snodgrass & Corwin, 1988). A d-prime value of 0 corresponds to chance level performance and larger d-prime values correspond to above chance level performance. To get a better view of the data, the estimated number of participants for a given correct percentage was also calculated using a kernel density estimation  (Allen, Erhardt, & Calhoun, 2012). This allowed us to get a continuous representation of the data in the forced-choice and Yes/No tasks that cannot be visualized via classical bar or box plots.
, 1976 dataset). The shape of such a function would then explain why participants are about 60% correct after a year of retention interval  (Nickerson, 1968; Shepard, 1967)  and why 12 years later, participants are still above chance level in our study. A crucial question that remains to be answered is how is it biologically possible that simple pictures that have been presented just three times and for only a few seconds, are still able to drive explicit choices a decade later? These memories might have been left in a dormant state  (Dudai, 2004; Lewis, 1979)  until they were woken-up through the presentation of the stimuli. Certain neuronal models using Spike Time Dependent Plasticity (STDP) mechanisms have shown that a few exposures are enough to create hyper-selective neurons  (Masquelier & Thorpe, 2007).
Supernovae. Supernovae mark the death of massive stars and are the prime process by which heavy elements are distributed through the Universe driving evolution in the stellar population. THESEUS will significantly advance our understanding of the SN explosion mechanism, detecting SNe at the very moment of emergence, gathering comprehensive, prompt data and alerting follow-up communities to new events. The birth of a new SN is revealed by a burst of high-energy emission as the shock breaks out of the star (giving access to measurements of the progenitor star radius). This has been spectacularly captured just once, in a serendipitous Swift XRT observation of SN2008D  (Soderberg et al. , 2008) : SNe are usually found only days to weeks after the explosion, as radioactive heating powers optical brightening.
Acknowledgements S. E. acknowledges the financial support from contracts  ASI-INAF I/009/10/0 ,  NARO15 ASI-INAF I/037/12/0  and  ASI 2015-046-R. 0. R. H. acknowledges  GA CR  grant  13-33324S. S. V. research leading to these results has received funding from the  European Union 's  Seventh Framework Programme  for research, technological development and demonstration under grant agreement no  606176. D. S. was supported by the  Czech  grant  16-01116S   GA ČR. Maria Giovanna Dainotti  acknowledges funding from the  European Union  through the  Marie Curie Action FP7-PEOPLE-2013-IOF , under grant agreement No. 626267  (" Cosmological Candles ").
, 2010; Dayan et al. , 2015 and references therein). The majority of studies on convective systems in the Mediterranean that rely on satellite data are based on measurements provided by infrared or water vapor bands available from geostationary satellites, due to their fine-scale (few km at nadir) and high temporal (~15 min) resolutions. Convective activity detection using these data is achieved by means of sophisticated image classification techniques that permit the discrimination between deep convection and cold cirrus clouds (e. g. ,  Levizzani et al. , 2010; Bedka, 2011 , Proud, 2015). However, there are a limited number of studies specifically on COV clouds in the region. In contrast to geostationary satellites, polar-orbiting satellites that carry microwave sounding instruments (such as NOAA and MetOp) overpass the same location on the globe twice daily, thus requiring a number of platforms with distinct equatorial crossing times to have multiple diurnal sampling.
Compared to infrared data, microwave has the advantage that it can penetrate non-precipitating clouds and therefore provides three-dimensional information on cloud structure. Passive microwave sounders are able to detect COV as a result of the strong scattering from frozen hydrometeors present in these clouds. Rysman et al. (2016a)  documented COV in the Mediterranean using microwave data from the Advanced Microwave Sounding Unit (AMSU) module B during an intensive observation campaign for the HyMeX project (SOP-1; 5 September to 6 November 2012). They used a method first proposed by  Hong et al. (2005)  for the tropical region, in which a differential relationship between water vapor sensing channels of AMSU is used for COV detection. They found based on two case studies that COV had high ice content up to 12.
The direct, simple methodology developed by  Hong et al. (2005)  and assessed by  Rysman et al. (2016a)  in the Mediterranean and  Rysman et al. (2017)  at near-global scaleis applied in order to detect and characterize COV activity. The layout of the article is as follow: Section 2 describes AMSU data and their known issues, the method applied to detect deep convective clouds and perform the cloud microphysics characterization. Sections 3 and 4 group the main results, with a first part (Section 3) centered on the differences between COV and DC, and a second part addressing the COV spatio-temporal distributions. Specifically, Section 3 lays out a microphysical characterization of COV that confirms that COV is a distinctive subset of DC in the Mediterranean. A comparison of the spatio-temporal distributions of COV relative to that of DC is also presented in this section.
In the present study we did not apply a scan-dependent bias correction to the data. We discarded data from N16 after 2007 due to both scan asymmetries and radio interference data, and considered only the period of 2005-2008 for the analysis of spatial and diurnal variability of COV, however it includes N15 data for the period of 2007-2008. Microphysical properties of COV data were studied using only N18 MHS data, and thus, minimizing scan-dependent bias effects.
(2012). A comparison between these AMSU-derived products and other two independent data sets specially focused over the Mediterranean Sea was performed by  Alhammoud et al. (2014). The latter is of particular importance given the scarce in-situ measurements over the sea, which makes satellite data virtually the only source of widespread observations over maritime areas. In addition, coastal areas that are often affected by extreme weather events are also well resolved in the presented analysis. AMSU-B/MHS data is now available for over 15 years, and a DC and COV climatology is now available for the whole of mid-latitudes. In addition to support for regional model validation, it could be interesting to relate the COV diagnostics with other proxies; for example, one of hail, recently proposed by  Ferraro et al.
Acknowledgments This work was supported by the  Direction Générale de l'Armement (DGA)  within the  PRECIP-CLOUD  project, by the  French   ANR-14-CE01-0014   MUSIC  and  ANR-12-SENV-0001  REMEMBER projects, and by the  Earth2 observe project  (funding from the  European Union 's  Framework Programme  under grant agreement number  603608 ). AMSU/MHS data are available at NOAA's Comprehensive Large Array Data Stewardship System. Data set: TOVS. Dataset name format is:  NSS. (AMBX|MHSX). (N* |M2 ). Dyyddd, where yy = year ( 05  through  08 ), ddd is the Julian day (001 through 365 or 366); example:  NSS. AMBX. NK. D05333. S0133. E0317. B3922324. GC. In this work, AMSU raw data and DARDAR_CLOUD product were obtained with support from the  INSU-CNES French Mixed Service Unit ICARE/climserv/AERIS.
Acknowledgements We acknowledge the support from: the  Engineering and Physical Sciences Research Council (EPSRC) ,  UK ('COTS' and 'HyperTerahertz' programmes ,  EP/J017671/1  and  EP/P021859/1 );  European Union FET-Open  grant  ULTRAQCL 665158 ; the  European Cooperation in Science and Technology (COST)  Action  BM1205 ;  Centre National de la Recherche Scientifique (CNRS ), France; and a  Royal Society   International Exchange grant  ( IE120898 ). E. H. L. and A. G. D. are grateful for support from the  Royal Society and Wolfson Foundation.
05 to 0. 001 for a same FC. To validate the robustness of RNA-seq data, we compared them with the expression of a selection of genes analysed by RT-qPCR. Both specific (5 BP, 11 CT, 7 RM) and common DEG to all three rhizobia (13), up-or down-regulated genes, and those localized on different replicons, were chosen. The characteristics of genes tested are listed in Additional file 1: Figure  S5. Two constitutively expressed reference genes (uppS and hisB) were used for qPCR normalisation. RT-qPCR values of genes plotted vs. respective RNA-seq data showed a strong correlation of gene expression between the two methods (BP: 0. 82, CT: 0. 77, RM: 0. 92), validating our RNAseq data (Additional file 1: Figure  S6 ).
Processes such as sensing, chemotaxis, flagella-driven motility and swarming, were all detected as regulated functions in our transcriptomic datasets. These functions are crucial for bacterial colonization of roots and have been found to be induced by root exudates in many rhizospheric bacteria  [44] [45] [46] ; differences in the responses to these functions may strongly influence the competitivity of bacterial symbionts  [49]. We observed that the general chemotaxis and flagella-driven motility processes seemed to be regulated differently in the three bacteria. In RM we could observe the upregulation of a whole region (RHI36v1_1529-1540) containing operons coding for chemotaxis (che and mot), flagella biosynthesis (flg, fli, fla, flb, flh) and flagellar motor components (fliGNM and motA).
Eighteen RNA samples (3 bacteria × 2 conditions × 3 biological repetitions) were sent for synthesis of corresponding cDNA libraries and sequencing to GATC Biotech (Konstanz, Germany). cDNA libraries were prepared according to the manufacturer's instructions (Illumina TruSeq™ RNA Preparation) and labelled to sequence 2 to 3 libraries per lane (at least 50 million reads per library, read length of 36 bp) on a Genome Analyzer II (Illumina). Raw data sequences were submitted to ArrayExpress (www. ebi. ac. uk/arrayexpress) under accession: E-MTAB-4144.
Statistical and functional analysis of transcriptomic data RNAseq reads were mapped to CoDing Sequences (CDS) of each genome (extracted from the Microscope annotation platform  [136]  using CLC-Genomics workbench v5 (CLC Bio, Aarhus, Denmark) with standard mapping options. Only unique mapped reads (UMR) were considered and used to calculate read counts per CDS. Ribosomal RNAs were discarded from next analyses. Estimates of variance-mean dependence in read counts per CDS data (RCD) from the three replicates for each condition, and tests for differential expression based on a model using the negative binomial distribution, were performed using DESeq (R module)  [137, 138]. First, a normalization of read numbers for replicates in each condition was performed (by estimates of size factors in DESeq and normalization), then differential expression values (Fold-Change) and statistical values (pVal and adjusted pVal) assessing the false discovery rate (FDR) were calculated.
qPCR analyses The primers used for quantitative PCR are listed in Additional file 1: Figure  S5. The uppS and hisB genes were used as reference genes  [43]. For qPCR, 0. 5 μg of total RNA was reverse-transcribed with 200 U of Super-Script II (Invitrogen) using random decamer primers (2. 5 μM, Ambion) at 25 °C for 10 min and then at 43 °C for 1 h. qPCR were performed on the Stratagene MXP3005P system using Power SYBR green master mix (Applied Biosystems). PCR started with a 10 min incubation at 95 °C, followed by 40 cycles consisting of 30 s at 95 °C and 30 s at 60 °C and 1 min at 72 °C. Primer specificity and the formation of primer dimers were checked by dissociation curves. PCR efficiency was calculated using the linear regression method on the log (fluorescence)-percycle-number data using Stratagene MXpro software.
Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose. ac. uk including the URL of the record and the reason for the withdrawal request. Herbivores alter plant biodiversity (species richness) in many of the worldÕs ecosystems, but the magnitude and the direction of herbivore effects on biodiversity vary widely within and among ecosystems. One current theory predicts that herbivores enhance plant biodiversity at high productivity but have the opposite effect at low productivity. Yet, empirical support for the importance of site productivity as a mediator of these herbivore impacts is equivocal. Here, we synthesize data from 252 large-herbivore exclusion studies, spanning a 20-fold range in site productivity, to test an alternative hypothesis -that herbivore-induced changes in the competitive environment determine the response of plant biodiversity to herbivory irrespective of productivity.
This dataset included measures of plant community composition from all sites and aboveground net primary productivity (ANPP) from half the sites, as well as a number of herbivore community and site characteristics (see Methods). To quantify herbivore-induced changes in biodiversity, we calculated the log response ratio (ln(G/UG)) of plant species richness (average number of species per plot) outside (grazed, G) vs. inside (ungrazed, UG) exclosures. We used two common dominance metrics Ð Berger-Parker Dominance and SimpsonÕs Dominance 18 Ð to evaluate changes in dominance with herbivory. Change of both metrics was calculated using log response ratios. We picked these two measures of dominance as both are robust to changes in richness at levels encompassed by our datasets (>5;  18, 19  ), and thus can vary independently of richness.
Results Consistent with previous theory and several empirical studies 2,8,9,13 , we found a positive relationship between changes in species richness in response to herbivores and ANPP, but the amount of variation explained was low (Fig. 2a ). Contrary to theory, herbivory did not decrease species richness at low productivity. Instead, herbivory had, on average, either neutral or positive effects on richness across the entire 20-fold range in ANPP. Because not all studies in our dataset measured ANPP, we used mean annual precipitation (MAP) as an ANPP proxy. This was possible due to the relationship between MAP and ANPP in our dataset (linear regression: R 2 =0. 21, p < 0. 001, F-stat106 = 27. 63) as well as in grasslands and savannas globally  20, 21. Even with this expanded dataset, richness responses were poorly related to MAP (Fig.