dataesr/scientific-paragraphs-categorization huggingface dataset:
This is notably the case in megadiverse countries where it is not always possible to obtain, manage and disseminate highly detailed data. This could support the view that rather than aiming at the highest ecological accuracy in the data, the focus should be on a good connection between ecological information and the implementation of legislation. The objective of this paper is thus to analyze whether the elaboration and implementation of BO policies depend on the quality of spatialized ecological data, through a comparison of the availability and use of such data in Colombia and France, at every stage of the process (anticipation, planning, and monitoring/control). The choice of study countries was based on various elements. First, the countries must have similar legislation to enable a comparison of the subtleties of the relevant legislation and its implementation.
In addition, two free private GIS-supported tools were developed by international NGOs with the support of the government. Tremarctos-Colombia, an early warning tool that conducts a preliminary evaluation of the possible impact of a project on the environment, has been available since  2013 (IAvH and TNC, 2019a; Rodríguez-Mahecha et al. , 2015). The Mapping of Alternatives for Equivalents (MaFE) is an open-source software tool that spatially identifies fragments of the same type of affected ecosystem where BO could be implemented  (Colombia, MADS et al. , 2012; IAvH and TNC, 2019a). Both tools are expressly mentioned in the BO manual (hereafter 'Manual' or 'BO Manual') adopted in 2012  (Colombia, MADS, 2012a).
Discussion Quantifying biodiversity losses is a prerequisite for BO, especially in the framework of NNL policies  (Bull and Strange, 2018). Spatialized ecological information thus plays an important role. However, the comprehensiveness of said information differs, notably -but not only-in the case of megadiverse countries. It raises the question of whether highly accurate and detailed information is needed for robust BO policies, or whether a more pragmatic approach is preferable, based on the extent of the available and validated information confronted with the requirements set out in the regulations. Through a comparative analysis of BO policies in Colombia and France, we analyzed the role of spatialized ecological data in such policies, touching upon geographical, ecological and legal aspects.
If ecological and conservation outcomes are the objectives of the mitigation hierarchy and NNL, they stem from political circles rather than a scientific discipline  (Bigard et al. , 2020; Calvet et al. , 2015). Our research shows, however, that scientific data play a role in the elaboration of BO policies and not only in their implementation. In Colombia, spatialized ecological data are used when elaborating mandatory requirements for BO. Conversely, the approach adopted in France entails that spatialized ecological information is used only on a case-by-case basis for purposes of implementing BO regulations. We illustrate this point hereafter.
Policy effectiveness Failure of offsetting can be a result of inappropriate design of the BO, but may also result from failure in implementation  (Moilanen and Kotiaho, 2018). Our research highlights various issues to be taken into account. Mapping. Mapped information may be too static and not necessarily up-to-date (e. g. , Tremarctos-Colombia and MaFE), emphasizing the need for a public portal which centralizes environmental data and information and is regularly updated, such as the SIAC in Colombia. Mapping is nonetheless essential to keep memory and track BO, and thus avoid projects being later developed on BO sites. Mapping is also an important tool in integrating landscape ecology in relation to BO. There is a growing number of studies that illustrate the need for a strategic approach to avoidance and BO, through more strategic planning at the landscape level  (Bigard et al.
Conclusion BO is directly linked to the objective of NNL. It requires to have the most accurate information possible at the finest spatial and temporal resolution. This information must, however, be adapted to the requirements established by national regulations. The way in which spatialized ecological information is used in the framework of BO national policies may vary, and it is possible to question the level of detail and precision needed to implement adequate offset measures. We compared offsetting policies in Colombia and France, and analyzed the availability and use of such information for the elaboration and implementation of such policies. We have shown that the use of spatialized ecological data is not limited to the implementation of BO policies  (France)  but may also be used to develop such policies  (Colombia).
A case in point is the elaboration of mandatory predetermined BO ratios, which are based on the available scientific data in Colombia, but do not appear to have any scientific ground for those adopted in water management instruments in France. However, although a ratio of 1:1 is unlikely to contribute to NNL, where the multiplier is very high the feasibility of the offsetting will likely depend on whether preservation, and not only restoration, measures are allowed, but also on space finiteness. There is nevertheless a necessity to balance the need for legal certainty with that of policy effectiveness, in particular in terms of contribution to NNL. Mapped information is essential, But regular updates are necessary to ensure the latest official information is available to users, through notably a public portal that centralizes environmental data.
Funding this work was carried out with the financial support of the  BEGI (Biodiversité Environnement et Grandes Infrastructures) corporate chair of the University of Paris 1 Pantheon-Sorbonne. BEGI is funded by  Eiffage. The sponsor had no involvement in the study (design; data collection, analysis and interpretation; writing; article submission). The manuscript was communicated to the sponsor prior to its submission for publication, solely for information purpose.
The reports can https://www. geoportail. then be used in the gouv. fr/ environmental licensing process 1. Data from the CORINE 3. http://www. ideam. Land Cover -CLC- gov. co/web/siac/ database (available up consultas-en-linea to 2018), a biophysical 4. Geoviewer, classification and continuously updated inventory of land cover http://sig. anla. gov. produced within the co:8083/ framework of Private tools: Copernicus, the European Earth 1. Tremarctos- observation program. Colombia 3. 0 http:// The change layer has a 200. 32. 81. 75/repo- spatial resolution allowing tremarctos-integrado/ the detection of changes 2. Mapping of on unit of 5 ha or more Alternatives for https://land. copernicus. Equivalents (MaFE - eu/pan-european/corine- Mapeo de Formulas land-cover Equivalentes) software CLC covers mainland 3.
Operation through automatic capture of monitoring data fed in geodatabases by companies subject to offset regulations 4. Thus far, information on offsets only from ANLA, the national environmental authority 5. Proposes and calculates 14 indicators, related to species composition, ecosystem structure/ landscape context, and functions = > to evaluate the loss or gain of biodiversity, as an approach to the principle of no net loss (Corzo et al. , 2018; IAvH and TNC, 2019) Tools for Registration of approved Monitoring reports compliance- offsetting sites in the REAA submitted by project owners checking (Registro de Ecosistemas y Áreas Ambientales) -part of to the competent authority -periodicity determined in the the SIAC geoviewer license (French (Colombia, MADS, 2018) Environmental Code, article Environmental Compliance R.
Data reduction In this work we focus on the EPIC-pn  (Strüder et al. 2001) , EPIC-MOS 1, and MOS 2  (Turner et al. 2001)  data. They were  processed and cleaned by adopting the Science Analysis System sas v18  (Gabriel et al. 2004 ) and the up-to-date calibration files. We initially checked for Cu instrumental emission in the EPICpn CCDs, between 7-8. 5 keV and 7. 8-8. 2 keV, for the source extraction and subsequent high-background screening. We followed the  Piconcelli et al. (2004)  optimised procedure aimed at maximising the S/N in the 4-10 keV band (in the EPIC-pn), rather than using the conservative criterion based on the fiducial rejection of time-intervals of high-background count rates (i. e. between 10-12 keV). The S/N optimisation procedure is necessary to identify any absorption feature that would otherwise be diluted (e.
Following  Piconcelli et al. (2004) , we define this level of background as the max background (see Appendix A for more details). The EPIC source spectra were individually inspected for the possible presence of photon pileup by using the sas task epatplot. The ratios of singles to double pixel events were found to be within 1% of the expected nominal values, and thus no significant pile-up is present. The response files were subsequently generated with the sas tasks rmfgen and arfgen with the calibration EPIC files version v3. 12. In Table  B. 1 we show a summary of the individual observations of the 22 SUBWAYS targets that were selected adopting a threshold of ≥1500 EPIC-pn net counts in the 4-10 keV band.
2. Black hole mass and Eddington ratio distributions of our targets (see Table  1 ) and the comparison samples. The colour scheme for the samples is the same as in Fig. 1. and MOS 2 data in the 0. 3-10 keV range. We applied a blindsearch procedure in each of the 41 observations by adopting four spectral binning methods (for a total of 164 blind-searches; see Appendix C for details). These binnings are grpmin1, SN5, and OS3grp20, using the sas routine specgroup, and the optimal binning of Kaastra & Bleeker (2016, KB hereafter), using the HEAsoft routine ftgrouppha. We find that the spectral resolution delivered by the SN5 and OS3grp20 binning methods is too degraded compared to the grpmin1 and KB ones, and therefore not suitable for the detection of faint, narrow absorption and emission features.
The degrees of freedom corresponding to both models are also recorded. (iv) The above steps were repeated through S = 1000 iterations for each test, which produced a |∆C noise | distribution under the nullhypothesis by mapping the statistical significance of any deviations from NHM due to random photon noise in the spectra. (v) The initial significance of the line derived from the real data |∆C line | was compared to the |∆C noise | distribution so that the number N of simulated spectra with a random noise fluctuation larger than the observed one can be evaluated. In case when the N simulated spectra have |∆C noise | ≥ |∆C line |, the MC statistical significance (P MC ) of the absorption line detection can be calculated as P MC = 1 -N S and reported in Table  2. In order to compare with literature results, and following, for example, T10, we consider as robust detections only absorption lines with P F 99% and P MC 95%.
A182, page 10 of 28 Fig. 5. XMM-Newton EPIC spectra and the corresponding best-fit models focused on the Fe K band. Top: unfolded EPIC-pn (black), EPIC-MOS 1 (dashed red), and EPIC-MOS 2 (dashed green) spectra, between 5-10 keV, of the eight observations where the Fe K absorption line was detected at P MC 95%. The spectra were firstly unfolded against a power law of Γ = 2, and their corresponding best-fitting model (solid red) was overlaid afterwards. Middle: corresponding EPIC data counts and best-fitting model. Bottom: data/model ratio. The presumed absorption features at ∼9. 2 keV and ∼9. 5 keV present in, for example, 2MASSJ105144+3539 and 2MASS J165315+2349, respectively, are simply not significant enough to be considered as detections (see Figs. 4  and E. 1), and hence they were not included in the best-fitting models.
For all samples, bolometric luminosities are consistently computed from the 2-10 keV luminosities assuming a luminosity-dependent bolometric correction  (Duras et al. 2020). The best fit parameters of a linear relation in log space of log(v out ) = A(L bol ) B are A = -3. 88 ± 1. 40 and B = 0. 19 ± 0. 03. Overall, the SUBWAYS data fit right between the low-and the high-z data. We find a Kendall's (rank) correlation coefficient of τ = 0. 45 with a null probability of p null = 1. 8 × 10 -7. The strength and slope of this correlation is partially driven by the six data points in C21, with log(L bol / erg s -1 ) 48, that may be affected by additional uncertainties associated with the magnification factor due to lensing. The low-and high-z fit correlation in C21 (see their Table  10 ) returned a slope of B = 0.
Acknowledgements. GAM and all the italian co-authors acknowledge support and fundings from  Accordo Attuativo ASI-INAF  n. 2017-14-H. 0. MB is supported by the  European Union 's  Horizon 2020 research and innovation programme   Marie Skłodowska-Curie  grant No  860744  ( BID4BEST ). MG acknowledges partial support by  HST GO-15890. 020/023-A , the  Black-HoleWeather program , and  NASA HEC Pleiades  ( SMD-1726 ). BDM acknowl-edges support via  Ramón y Cajal  Fellowship  RYC2018-025950-I. SM is grateful for the  NASA   ADAP  grant  80NSSC20K0438. AL acknowledges support from the  HORIZON-2020  grant " Integrated Activities for the High Energy Astrophysics Domain"  ( AHEAD-2020 ), G. A. 871158. SRON is supported financially by  NWO , the  Netherlands Organization for Scientific Research. M.
Motivation: Studying the genetic makeup of viruses and phages through genome analysis is crucial for comprehending their function in causing diseases, progressing medicine, tracing their evolutionary history, monitoring the environment, and creating innovative biotechnologies. However, accessing the necessary data can be challenging due to a lack of dedicated comparative genomic tools and viral and phage databases, which are often outdated. Moreover, many wet bench experimentalists may not have the computational proficiency required to manipulate large amounts of genomic data. Results: We have developed VAPEX (Virus And Phage EXplorer), a web server which is supported by a database and features a user-friendly web interface. This tool enables users to easily perform various genomic analysis queries on all natural viruses and phages that have been fully sequenced and are listed in the NCBI compendium.
2021 ) which provides a classification of proteins in orthologous groups or Phagonaute  (Delattre et al. 2016)  which displays the genetic context of selected genes across prokaryotic viruses within the internal database. To our knowledge, there is currently a lack of public web services that provide comprehensive genomic comparisons of bacteriophages, eukaryotic viruses, and archaeal viruses especially when user-submitted genomes are involved. As a solution, we introduce VAPEX-a user-friendly and interactive web server aimed at facilitating in-depth examination of natural virus and phage genomes including user-submitted sequences. By utilizing the well-established symbolic representation developed for the WASPS web server  (Badel et al. 2020) , VAPEX can create comprehensive and fully resolved synteny maps for both bioinformaticians and wet lab experimentalists.
Methods The VAPEX web server is composed of three interconnected modules: the VAPEX database, the VAPEX web application and the VAPEX database Updater program. VAPEX database: All VAPEX viral and phage data are contained in a relational database stored locally on a dedicated server. The database adopts a hierarchical linked list structure of virus/phage objects, each carrying several fields for accession numbers, definitions, genome size, and a gene protein list object. Moreover, the database incorporates extra fields to accommodate future expansions. The gene protein list object carries all gene entries relative to a specific genome with the following fields: accession, definition, orientation, coordinates, orthologous cluster id, and centroid accession. The accession field of each gene protein is appended to the accession field of the originating genome for tracking purposes.
All virus/phage and gene fields are extracted from the NCBI GenBank files with the exception of the orthologous gene cluster and centroid fields which are calculated locally at database creation or regeneration. Genes predicted by VAPEX are annotated using centroid definitions. On the server, the VAPEX core database consists of an XML file that is wellsuited for storing linked lists. To improve performance, the XML file is deserialized into memory objects in the server's RAM during the first access. Virus/phage DNA sequences, the translation of coding and centroid genes reside in three separate binary files. Accession numbers link the core database to DNA and protein sequences. At this writing, the VAPEX database carries 15. 288 virus/phage genomes corresponding to 631. 296 protein sequences ranked in 143.
677 orthologous clusters. VAPEX updater: A separate single executable stored on the server carries out at regular intervals all tasks required for a fully automated database update. NCBI GenBank refseq files are retrieved from ftp://ftp. ncbi. nih. gov/refseq/release/viral/ using the FTP protocol and parsed to extract the data to populate the fields of the core database mentioned above. DNA and protein sequences are extracted as well and merged into two FASTA files. The orthologous relationships between proteins sequences are calculated using MMseqs2  (Mirdita et al. 2019)  which generates a list of orthologous clusters and a FASTA file compiling the centroid protein sequences from each cluster. The three FASTA files corresponding to genomic DNA, protein genes and protein centroids are then converted into BLAST-compatible binary format using MakeBlastDB  (Altschul et al.
1990 ) and Diamond-compatible format with Makedb  (Buchfink et al. 2015). The database update pipeline is depicted in Supplementary Material. VAPEX web server: The interface of the VAPEX web server allows the submission of a variety of queries to its database. Context-sensitive hypertext links leading to the help file are provided for all functions and options. VAPEX salient features are listed below: 1) User-submitted annotated virus/phage genomes are compared to the database in order to generate fully resolved synteny maps in nearly real time. The protein sequences are extracted from the annotation and compared with the binary centroid database using BLAST  (Altschul et al. 1990). Matching proteins are assigned the corresponding VAPEX cluster number. Collinear synteny maps comprising the query genome and matching VAPEX genomes are then drawn to scale with individual open reading frames colored according to cluster membership.
To allow for the simultaneous display of protein genes from a large number of clusters, the coloring is obtained with a combination of symbols and hues. The E-values of predicted matching protein sequences are indicated on the synteny map. 2) Unannotated virus/phage sequences can be submitted as well. In this case, VAPEX predicts protein coding capacity in the six possible reading frames and these potential open reading are treated as described above. The query genome is then displayed in the synteny map using six collinear tracks. 3) Smooth user navigation in the synteny maps by the means of zoom, pan and scroll is accomplished with typical mouse/touchpad gestures. Gene identification tooltips are obtained by hovering. Map navigation is executed entirely using HTML 5. 0 canvas properties of modern browsers and does not require data transfer from the server.
4) Text queries are performed on the accession and definition fields of all virus/phage genomes and protein genes. Matching results are linked to synteny queries. 5) User-submitted DNA or protein sequences are matched against the VAPEX database using a choice of BLAST  (Altschul et al. 1990 ) and Diamond  (Buchfink et al. 2015)  algorithms. Synteny links are provided for all matches. 6) All results generated by VAPEX can be exported as text, scalable vector graphics (SVG) or bitmap (PNG) formats for further analysis.
1, multiple open reading frames were detected and identified easily by conducting a synteny analysis with other viruses stored in the VAPEX database (Fig. 1 ). As expected, VAPEX readily confirmed that the nucleoprotein of the bornavirus belongs to a distinct orthologous cluster in comparison to other related Filoviridae. Surprisingly, the RNA-dependent RNA polymerase and glycoprotein encoded by the Wuhan sharpbelly bornavirus belong to the same orthologous groups as the corresponding proteins in related viruses, suggesting a considerably lower diversity in Filoviridae than anticipated. These findings suggested that VAPEX's sensitivity is comparable to that of molecular phylogenetics while offering a broader and more contrastive analysis of the evolution of related viruses.
Readers-Writers Experiment setup. For this experiment, we utilize the standard LTL 3 semantics defined over the B 3 verdict domain. As such, all the local and scope property types are B 3. We instrument readers-writers to insert our monitors and compare our approach to global monitoring using a custom aspect written in AspectJ. In total, we have three scenarios: non-monitored, global, and opportunistic. In the first scenario (non-monitored), we do not perform monitoring. In the second and third scenarios, we perform global and opportunistic monitoring. We recall that global monitoring introduces additional locks at the level of the monitor for all events that occur concurrently. We make sure that the program is well synchronized and data race free with RVPredict  [37]. Measures. To evaluate the overhead of our approach, we are interested in defining parameters to characterize concurrency regions found in readers-writers.
Scope monitors check if a thread is waiting for more than n turns before entering the critical section. We notice slightly less overhead with opportunistic than global for 2-bakery and more overhead with opportunistic on n-bakery. This is because of the small concurrency region (cwidth) which is equal to 1. As such, the overhead of evaluating local and scope monitors by several threads, having a cwidth of 1, exceeds the gain in performance achieved by our approach and hence not fitting for opportunistic monitoring. We also monitor a textbook example of Ping-Pong algorithm  [33]  that is used for instance in databases and routing protocols. The algorithm synchronizes, using reads and writes on shared variables and busy waiting, between two threads producing events pi for the pinging thread and po for the pong thread.
These tools implement vector clock algorithms, such as  [53] , to timestamp events. The algorithm blocks the execution on each property event and also on all synchronizing actions such as reads and writes. Vector clock algorithms typically require synchronization between the instrumentation, program actions, and algorithm's processing to avoid data races  [16]. jPredictor  [19]  for instance, uses sliced causality  [17]  to prune the partial order such that only relevant synchronization actions are kept. This is achieved with the help of static analysis and after recording at least one execution of the program. The tool is demonstrated on atomicity violations and data races; however, we are not aware of an application in the context of generic behavioral properties. RVPredict  [37]  develops a sound and maximal causal model to analyze concurrency in a multithreaded program.