dataesr/scientific-paragraphs-categorization huggingface dataset:
4b ). With the dataset composed of only the top 10 % longest Nanopore reads, Canu yielded six OsHV-1 contigs ranging from 28 to 210 kb (Fig. 4b ). The 28 kb contig consisted of the U S surrounded on its left side by one copy of TR L -X-IR S and on its right side by one copy of TR S. The four contigs ranging from 45 to 54 kb share the same general structure; that is to say, a fragment of the U L region followed by a copy of IR L -X-IR S -U S -TR S. These four contigs are differentiated by the relative orientation of the U L and U S fragments (same or inverted orientations) and their orientation with respect to the IR L -X-IR S fragment (Fig. 4b ). It was likely that these four contigs correspond to the four major OsHV-1 isomers described by Davison et al. [7]. In order to verify this observation and to quantify the relative abundance of the four isomers, we have screened all the reads long enough to cover at least a part of both U L and U S regions.
osHV-1 phylogenetic analysis In order to determine the relationships of the OsHV-1 genomes from this study with those known so far, we constructed a phylogenetic tree from the alignment of the two genomes we generated in the present study (viruses collected in 2016), seven OsHV-1 genomes available in public databases (viruses collected before 2016) and four representatives of the 21 genomes acquired by Delmotte-Pelletier et al. [34]  (viruses collected in 2018). This analysis confirms that the OsHV-1 virus sampled in Thau lagoon (France) in 2016 belongs to µVar clade and that genomes reconstructed from the same sample with either the Nanopore or the Illumina sequencing data are really close to each other (Fig. 8 ).
e. 500 kDa for OsHV-1). We therefore demonstrate, that TFF is a powerful tool to purify unculturable viruses from clinical and environmental isolates. Then, we performed a high-quality DNA extraction that allowed us to compare the capabilities of long-and short-read sequencing technologies (Illumina and Oxford Nanopore Technologies) to de novo assemble OsHV-1 whole genome. To date and to our knowledge, there is no maintained bioinformatic pipeline for reference-free and de novo assembly of long DNA viruses with large inverted-repeat like OsHV-1 for either short-or long-read sequence. Usually, long-and short-read sequencing technologies are combined to de novo assemble Herpesvirus whole genomes  [48, 98]. Conversely to what is usually done, we have successfully tested two bioinformatic pipelines to independently analyse the long-and short-read datasets, and to reference-free and de novo assemble two OsHV-1 whole genomes.
Acknowledgements We thank the staff of the  Ifremer station at La Tremblade (ASIM) ,  Frédéric Girardin  and his team ( Plateforme des Mollusques Marins de La Tremblade PMMLT ) and  Christophe Stavrakakis  and his team ( Plateforme des Mollusques Marins de Bouin PMMB). We also thank  Louis Boismorand  and  Marc Leroy  for technical assistance. We are also grateful to  Jean-Christophe Avarre  and  Marie-ka Tilak  ( ISEM ) for fruitful discussions and advice concerning Nanopore sequencing technology.
Funding information J. D. was supported by a grant from the  University of Montpellier. C. P. was supported by a grant from the  Ifremer Scientific Board  and from the  Nouvelle-Aquitaine region. A. D. M. was financially supported by Ifremer, by  EU DG SANTE  through the European Reference Laboratory for mollusc diseases, and by  DGAL  through the  National Reference Laboratory  for Mollusc Diseases. This work benefited from support from the  'Laboratoire d'excellence' (LabEx) CeMEB , through the exploratory research project  HaploFit  and the use of the 'environmental genomics' facility (http://www. labex-cemeb. org/fr/genomique-environnementale-1). This work was also supported by the  Ifremer Scientific Board , through the HemoVir and GT-oyster projects and by the  'Fond Européen pour les Affaires Maritimes et la Pêche' (FEAMP ,  GESTINNOV  project  n°PFEA470020FA1000007 ).
The authors acknowledge the  Pôle de Calcul et de Données Marines  (PCDM; https://wwz. ifremer. fr/en/ Research-Technology/Research-Infrastructures/Digital-infrastructures/Computation-Centre)  for providing DATARMOR computing and storage resources. Some data were produced through the GenSeq technical facilities of the  « Institut des Sciences de l'Evolution de Montpellier »  with the support of  LabEx CeMEB , an  ANR 'Investissements d'avenir' programme  ( ANR-10-LABX-04-01 ). This study is set within the framework of the  'Laboratoires d'Excellences (LABEX) '  TULIP  ( ANR-10-LABX-41 ). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
All supporting data, code and protocols have been provided within the article or through supplementary data files. Three supplementary figures and two supplementary tables are available with the online version of this article. 000895 NCBI under Bioproject ID PRJNA823871. Nanopore data have been deposited to SRA under accession number SAMN27363714 with base-called fastq reads under accession number SRR19025776 and raw fast5 and slow5 file under accession number SRR19039499; Illumina fastq reads have been deposited to SRA under accession number SAMN27363675. OsHV-1 assembled genome from Nanopore data have been deposited to GenBank under accession number ON411413; OsHV-1 assembled genome from Illumina data have been deposited to GenBank under accession number ON411412.
Data analysis Plant parameters were analyzed for each species separately for the effects of drought (one drought vs. recurrent drought event), neighbor plant identity, soil depth sampling (top vs. deep soil layer) and their interactions. Soil microbial parameters were analyzed at the rhizotron level because they could not be associated to a particular plant species or individual. We used mixed linear models [lme function of R package "nlme"  (Bates and Pinheiro, 1998)  and r. squaredGLMM function of R package "MuMIn"  (Kamil, 2016)  to calculate R square values] to assess whether RB, RE, root morphological traits (SRL, RTD, Rth, RD, and Diam) and soil microbial parameters (sum15, H , and D) differed according to the drought treatment (one drought vs. recurrent drought) and neighbor plant identity (or plant species composition for soil microbial parameters) and their interactions.
Acknowledgments We are grateful to  David Degueldre ,  Jeremy Devaux ,  Pauline Durbin , and  Thierry Mathieu  from the platform " Terrain d'expérimentations " [supported by the  LabEx CeMEB  and  ANR  " Investissements d'avenir" program  ( ANR-10-LABX-04-01 )] for their continued support and help in the planning and maintenance of the experiment and help during plant harvest. We also thank  Catherine Roumet  and  Pascal Chapon  for their advice and technical support and  Florence Volaire  for helpful comments during writing.
Governments provide policy incentives to increase adoption rates of electric vehicles and achieve sustainability goals. This paper investigates the impact of UK financial purchase incentives on new registrations of electric fleets whilst moderating for change in gross domestic product (GDP). We use a unique dataset of new registrations of electric fleets in the UK for a 20-year period. Our results show that financial purchase incentives positively impact new registrations of electric fleets, and this effect is positively moderated by GDP change. Marginal analysis reveals three categories of adopters that purchase electric fleets at different levels of policy and GDP change: insensitive adopters, standard adopters, and sensitive adopters. Overall, financial incentives may be more effective in fostering the adoption of electric fleets when set to levels that are conditioned on the level of GDP change.
Dependent variable: New registrations We follow the related literature that uses new registrations of EVs as dependent variable  (Lévay et al. , 2017; Jenn et al. , 2018; Münzel et al. , 2019; Clinton and Steinberg, 2019)  since it reflects new sales of EVs granting an accurate measure of adoption. We use data on new registrations of EVs sold to the commercial sector. According to the Society of Motor Manufacturers & Traders (SMMT) 12 , there are three different types of commercial sales: business, fleet and fleet captive. Table  1  provides SMMT definitions for each of these different sale types. Specifically, our data is an aggregation of new registrations of electric vehicles (passenger cars) and electric light commercial vehicles (vans) from business, fleet and fleet captive sales from the SMMT 13 and does (not) include hybrid vehicles 14.
15 We cross-checked other websites holding information on EV policies to ensure we collected all relevant financial purchase incentives for the commercial sector. We searched databases such as: International Energy Agency (IEA) https://www. iea. org/policies (IEA, 2020), European Environment Agency (EEA) policy database https://pam. apps. eea. europa. eu/ (European Environment Agency, 2020), and the European Commission website https://ec. europa. eu (European Commission, 2020). After a thorough search of multiple databases, we designate PICG and PIVG as our independent policy variable. 16 Financial policy incentives were not included in the cumulative policy variable. Instead, dummy variables were used to represent this incentive. of EVs and hybrid vehicles across European countries 17.
Moderating variable: GDP index We retrieve monthly data on the GDP index from January 1999 to December 2019, as measured and reported by the Office for National Statistics (ONS). GDP index measures the percentage change in GDP (ONS, 2021). The ONS sets the year 2016 as the base year (2016 = 100), in line with the UK National Accounts 2019-"The Blue Book" (ONS, 2019b) 18. We use GDP index instead of total GDP in our analysis; since the GDP index is seasonally adjusted for inflation and is calculated monthly. We use GDP index as a moderating variable to gain a deeper understanding of the effectiveness of financial policy incentives on the adoption of EFs in the UK.
, 2017). Therefore, to proxy for the demand for energy, we use monthly UK fuel imports (excluding oil), as obtained from the Office for National Statistics (ONS). Government revenue: To the extent that higher government revenues will translate to higher government expenditure  (Friedman, 1978) , we expect higher government revenue to increase the capacity of the UK government to subsidize sustainable technologies, including EV fleets. We collect monthly data on government revenue from the Trading economics database. UK unemployment rate: High levels of unemployment are associated with lower levels of purchasing power of sustainable technologies such as EVs at an individual and household consumer level  (Mersky et al. , 2016; Münzel et al. , 2019). However, at a macroeconomic level, unemployment is associated with recessionary periods (International Monetary Fund, 2010) during which firms' financial positions deteriorate  (Cowling and Liu, 2011).
Accordingly, we posit that unemployment negatively affects firms' decisions to adopt sustainable technologies. We collect monthly data on UK unemployment rates using the OECD database  (OECD, 2021). CPI:  Barabanov et al. (2021)  find that firms in countries with a lower consumer price index (CPI) are more likely to invest in sustainable technologies thereby, being more likely to invest in sustainable technologies. We also control for inflation using the consumer price index (CPI). For monthly CPI, we used data from the OECD database  (OECD, 2021). Time trend: We follow  Egnér and Trosvik (2018)  and calculate a three-year time trend variable. The coefficient captures the The grant allowed a rebate. of 25% towards the cost of the vehicle up to £5,000. The vehicle must be within the M1 category b , as defined under EU Directive (EC) 2007/ 46/EC.
Adoption of electric fleets from 1999 to 2019 Fig. 2  shows the number of new registrations of EFs during our sample period. We observe that the number of new registrations is relatively flat from January 1999 to January 2011. Pozzi and Cassetta (2019)  highlight that there were limited purchases of commercial electric vehicles and EV model availability in the early 2000's (Bloomberg New Energy Finance, 2019). Accordingly, we observe a limited number of sales of EFs between the years of 1999 to 2011; this is reflected in a substantial number of zeros in our dataset for our dependent variable prior to January 2011. Interestingly, January 2011 coincides with the introduction of the PICG, which was followed by a rapid increase in the number of new registrations for all EFs.
Empirically testing EFs = α + βPolicy + Z + ε (1) EFs = α + β 1 Policy + β 2 GDPchange + β 3 (Policy × GDPchange) + Z + ε (2) In Equation (1), EFs is the total number of new registrations for electric fleets, α is the intercept,Policy is the average of PICG and PIVG in pound value, Z is a vector of control variables, and ε is the error term. In Equation (2), we introduce the moderation effect of GDP change, captured by the interaction term (Policy × GDP change). 21 We collected data on charging infrastructure from Zap-map. This data is available quarterly, from the years  2015 -2019 (Zap-map, 2022)). We estimated the two variables: time trend and charging infrastructure from the years 2015-2019. We find that that the two variables are significantly correlated. Thus, we suggest that this is because both variables capture the time trends associated with advancements in technology, including charging infrastructure, and improvements in the capabilities of EVs.
The relationships between different performance selection traits and environmental impacts were evaluated by Monteiro et al. in individual growing pigs. This study concluded that genetic selection to improve feed conversion ratio is the best option to benefit both performance and environmental impacts. The authors also suggested using a similar approach on actual data (e. g. , information collected by genetic companies). Another important insight from this study is that improving performance can be a way to improve environmental sustainability too. Indeed, the findings presented by Chen et al. revealed a significant correlation between sow gut microbiota and litter size, providing another piece of evidence that several responses are connected in animal science and that an overall assessment should be preferred instead of focusing on isolated impacts.
Infinite matrix dose rates were calculated from these using the conversion factors of Sanderon  [96]  and adjusted for attenuation by grain size and chemical etching using the datasets of Aikten  [97]  and Bell and Zimmerman  [98] , respectively. These were reconciled with the measured beta doses (TSBC) rates and an estimate of the cosmic dose contribution in a dosimetric model to obtain total environmental dose rates. The total dose rates varied with position in the stratigraphy, with lower values at the base of the section, 2. 1 mGy a -1 to higher values at the top, 3. 4 mGy a -1. The burial doses of 6. 4-1. 8 Gy, together with dose rates of 2. 1-3. 4 mGy a -1 , correspond to depositional ages in the range of 3. 1 ± 0. 2 to 0. 9 ± 0. 1 ka. Depositional ages of 1. 8 ± 0. 3 ka (250 ± 280 CE), 0.
p-XRF analysis technique Chloride determinations in gels were performed with a portable XRF instrument (Tracer-Brucker) with a 4 × 3 mm analysis window and a vacuum system for the detection of light elements, with tension at 40 kV and current at 13µA. The duration of each analysis was 60 s. S1PXRF software was used to perform the analyses and Brucker Spectra software was used to analyze the resulting spectra and to link the peaks in the spectra to the corresponding elements. Precise determination of chlorides in the gels was performed by the standard internal method (K peak, produced by the 1% KNO 3 ). Calibration curves were plotted with the ratio of the area under the Cl peak to the area under the K. The detection limit of Cl is 0. 01 ppm.
Salt analyses The morphochemical analyses of the salt e orescences + dark crust were performed with two scanning electron microscopes equipped with an Energy Dispersive Spectrometer (EDS). The rst is a TM3030 Hitachi microscope working in a Low Vacuum Mode with an accelerating voltage of 15 kV and connected with Quantax 70 Bruker EDS system; the second is MIRA3Tescan microscope working in High Vacuum with an accelerating voltage of 25 kV. In each case, samples were glued on the sample holder by the means of a carbon adhesive pad. The mineralogical composition of the samples was determined by an Empyrean diffractometer from Malvern-Panalytical, in a Bragg-Brentano geometry and equipped with a ltered copper anode. The Inorganic Crystal Structure Database (ICSD-Pan) was used to identify the best correlated phases using Highscore Plus software (@Malvern-Panalytical).
Microclimate measurement and ECOS-RUNSALT model For three years (October 2017 to October 2020), temperature and relative humidity parameters were recorded every hour in situ. Outdoors, the data were provided by Météo-France. Indoors, two intercalibrated sensors (Vaisala DL2000MR) were installed in the lower and in the upper room. Beside microclimate characterization, these data are also used to de ne the runs of the ECOS-RUNSALT model. The RUNSALT software was developed by  Bionda (2002 Bionda ( , 2006) )  on the basis of the ECOS thermodynamic model of  Price (2000). This interface permits to calculate, for a saline solution in equilibrium condition, the order of precipitation of the salts likely to appear for a given environment. Either a speci c temperature is set and the relative humidity is varied or a speci c relative humidity is set and the temperature is varied.
Thermodynamic modelling The chemical analyses by IC and ICP-AES of representative samples of the salt e orescences present inside (upper and lower room) and outside the dovecote are reported in Table  1. As expected, nitrate and potassium are major ions whatever the situation (indoor and outdoor). The presence of sulphate and calcium indicates a contamination by render particles or other sulphate sources. Traces of sodium, chloride and magnesium are also detected. These ionic compositions have been introduced in the ECOS-RUN SALT model. The corresponding microclimatic data measured on site (Fig. 4 ) were used to de ne the temperature and relative humidity boundaries imposed on the model. For each salt, the temperature set is the median value. Relative humidity will vary between lower and upper outliers.
The age of the water contained in these aquifers is therefore so old that it has inspired the use of terminology borrowed from paleontology; as a result these aquifers bear the nickname 'Fossil Aquifers'. In arid zones groundwater is a source of life and as such it is difficult to find a balance between preservation and use. This is made more difficult when the necessary data required to study these systems is inaccessible, and even more complicated when such systems are transboundary and therefore shared between two or more countries. Considering the complexity of the issue, and its political sensitivity, the UNESCO International Hydrological Programme (IHP) and the World Bank decided to call upon international experts to support the preparation of a text that could provide valuable indications on the sustainable use and management of these water resources.
As a result of this meeting guidelines were formulated by a group of experts and the publication was initiated. It should be pointed out here that the authors contributed to this title under their own personal capacity. They were selected for their knowledge and expertise both in this specific field as well as within a specific region. The case studies as well as the data and the indications provided in the chapters, refer mainly to situations existing in arid and semi-arid regions, although non-renewable groundwater resources are also found in humid and permafrost regions. One such example from a temperate climate, is the Albian-Neocomian aquifer system located in France, in the Parisian basin, composed of two reservoirs, the Albian and the Neocomian, which are hydraulically linked. According to the indications provided by the French Agency ' Agence de l'Eau Seine-Normandie' , the system covers 84,000 km 2 and its total estimated reserves are around 655 billion cubic meters.
■ The value of detailed monitoring of groundwater abstraction and use, and the aquifer water-level and quality response to such abstraction, cannot be overemphasised. This should be carried out cooperatively by the water resource administration, stakeholder associations and individual users. The existence of time-limited permits subject to periodic review will normally stimulate permit holders to provide regular data on wells. It will be incumbent upon the water resources administration to make appropriate institutional arrangements -through some form of aquifer database (databank or data-center) -for the archiving, processing, interpretation and dissemination of this information. ■ Many aquifers containing large reserves of non-renewable groundwater are transboundary, either in a national sense or between autonomous provinces or states within a single nation, and there will much to be mutually gained through : • formation of a high-level steering group and a joint technical group; • operation of joint or coordinated groundwater monitoring programmes; • establishment of a common groundwater database or mechanism for information sharing; • adoption of coordinated policies for groundwater resource planning, harmonization of relevant legislation and regulations, and procedures for joint resource management and conflict prevention and resolution.
The NW SAS dat abase and model simul at ions The implementation of a shared database permits studies to be carried out simultaneously at each of the project's head offices and by each of the respective administrative authorities for water within each of the three countries. Creating this database involves multiple diverse operations at over 9,000 water points, including collecting, homogenizing the systems for classification and identification, reviewing, detecting faulty data, correcting, and validating. This management tool contains data of high quality and is now available for use. Management with full factual knowledge of the Aquifer System is facilitated by the availability of a mathematical simulation model. This model provides predictions given various management scenarios. The reference period chosen for the simulations is the historical period 1950-2000, assuming the initial situation as existed in 1950.
As such, the OSS, through the NWSAS project, has developed a database containing all present and historical information on all water points, their levels, and their flows. This database is operational and accessible to the three countries. In this respect, the goodwill of the three water authorities in the communication of information has been exemplary. Moreover, the NWSAS Model is available and operational within each of the three countries. A mechanism is needed to guarantee the maintenance, the development and the permanent updating of two tools -the Database and the Simulation Model. In addition to the maintenance of the database and model, the three countries have agreed to the regular exchange of data and information. This data exchange serves as a basis for the formulation of common policies and strategies, including: a) the necessary continuation of the NWSAS project's work on improving knowledge of the system and of its exploitation, N O N -R E N E W A B L E G R O U N D W A T E R R E S O U R C E S b) the setting up of a mechanism for continuing dialogue and its institutional anchoring within an international organization -the OSS, c) the progressive and evolutionary nature of the consultation mechanism, meeting the growing needs for cooperation and collaboration in the management of the NWSAS water resources.