dataesr/scientific-paragraphs-categorization huggingface dataset:
Geant4 VMC The first Geant4 VMC multithreading version, 3. 0, was released in 2014. The developments in this version having already been presented in  [5] , in this paper we just recall the main concepts relevant for the work presented here. Geant4 VMC code was adapted for multithreading using the same approach as in Geant4 multithreading. This development consisted mainly in the replacement of the singleton objects in Geant4 VMC with singletons per thread, including the main VMC interfaces defined in ROOT: TVirtualMC and TVirtualMCApplication and fixing thread-safety issues. A new VMC package, MTRoot, implementing the ROOT output per thread with locking critical ROOT operations has been added and, finally, also the G4Root package, implementing the TGeo Geant4 navigation, was migrated. Like for Geant4 native applications, the switching to the multithreading mode requires migration of the VMC application codes.
Multithreading in FairRoot The migration of FairRoot followed the recipe introduced in the VMC examples. The FairMCApplication class, which implements the TVirtualMCApplication interface, was enhanced with the new functions for multithreading presented in the previous section. Besides the mandatory CloneForWorker(), the InitOnWorker() and FinishRunOnWorker() functions were needed to ensure complete initialisation of the framework applications. The application initialisation was revisited so that the objects relevant to event processing are created and initialised properly on workers. A new virtual function, the overriding of which is obligatory in the multithreading mode, was added in the FairModule class : FairModule* CloneModule() const; to ensure cloning the application scoring objects on workers.
Xylella fastidiosa is an insect-borne bacterium confined to the xylem vessels of plants. This plant pathogen has a broad host range estimated to 560 plant species. Five subspecies of the pathogen with different but overlapping host ranges have been described, but only three subspecies are widely accepted, namely subspecies fastidiosa, multiplex and pauca. Initially limited to the Americas, Xf has been detected in Europe since 2013. As management of X. fastidiosa outbreaks in Europe depends on the identification of the subspecies, accurate determination of the subspecies in infected plants as early as possible is of major interest. Thus, we developed various tetraplex and triplex qPCR assays for Xylella fastidiosa detection and subspecies identification in planta in a single reaction. We designed primers and probes using SkIf, a bioinformatics tool based on k-mers, to detect specific signatures of the species and subspecies from a dataset of 58 genome sequences representative of X.
Introduction Xylella fastidiosa (Xf) is a worldwide insect-transmitted plant pathogenic bacterium that presents a very large host range. Altogether, 563 plant species grouped into 82 botanical families have been reported as Xf hosts (EFSA, 2018a). Plants with a major socio-economic interest such as grapevine, citrus, coffee, and olive trees are hosts of Xf  (EFSA, 2018a). Forest trees, shade trees, ornamentals and landscape species are included in the host plant database making this pathogen a potential worldwide threat  (EFSA, 2018a). Disease management of Xf is impeded by its asymptomatic period that can last several years  (EFSA, 2018b). This bacterial species is genetically diverse as five subspecies including fastidiosa, morus, multiplex, pauca and sandyi are currently described  (EFSA, 2018b).
Then, the individual primer and probe combinations and the six sets of four combinations were tested using Amplify to check the absence of dimer and crossamplification  (Engels, 1993). The specificity of all primers and probes was tested in silico using PrimerSearch (Val Curwen, Human Genome Mapping Project, Cambridge, UK) on the initial set of 58 genomic sequences of Xylella and on the 154,478 bacterial Whole Genome Shotgun (WGS) sequences available in the NCBI database (as on  August 22, 2018). BLASTn of the amplicons were run on the NCBI WGS database to evidence their specificity. Four others primer and probe combinations previously published were used in this study. The first targets the rimM gene of Xf  (Harper et al. , 2010)  and was used as reference protocol. The second targets the eukaryotic rRNA18S gene  (Ioos et al.
e. set n°1: XF-XFFSL-XFM-XFP, set n°2: XF-XFF-XFM-XFP, set n°3: XF-XFF-XFM-XMO, set n°4: XFFSL-XFM-XFP, set n°5: Harper-XFFSL-XFM-XFP and set n°6: 18S-XFFSL-XFM-XFP. The optimized final reaction conditions were performed in a final volume of 10 µL containing 1X of SsoAdvanced™ Universal Probes Supermix (Bio-Rad), 575 nM of primers, 200 nM of probes and 600 ng. µl -1 of BSA (ThermoFisher) and 1 µL of extracted DNA. The optimal thermocycling conditions selected were: 3 min at 95°C, followed by 40 cycles of 15 s at 95°C and 30 s at 60°C. The qPCR assays results were analyzed, with expert verification, using Bio-Rad CFX Manager 3. 1 software and its regression mode. The reaction efficiency was calculated using serial dilutions with the formula: E = 10 (-1/slope).
Design of primers and probes and in silico analysis Species-specific and subspecies-specific long-mers were identified with SkIf  (Briand et al. , 2016; Denancé et al. , 2019)  on genomic sequences. For the Xf species and the subspecies fastidiosa, morus, multiplex, and pauca, one of the two longest long-mers identified by  Denancé et al (2019)  was selected for this study (Table  2 ). For the subspecies fastidiosa sl specific long-mers were searched for on our 58 genome sequences of Xf, using the subspecies fastidiosa, morus and sandyi genomes as ingroups and the multiplex and pauca genomes as outgroups. In total, 3,345 long-mers were identified, ranging from 22 bp to 235 bp (Supplemental data 1). Primers and probes were designed within specific long-mers (Table  3 ). Specific amplifications were obtained in silico on XF genome sequences and WGS bacterial sequences from NCBI at the expected amplification size, without any mismatch for the five primer and probe combinations (XFF, XFFSL, XFM, XFMO and XFP).
The efficiency of each combination was evaluated on serial dilutions of calibrated DNA solutions. The XF, XFM, XFMO, XFP, and XFFSL primers and probes allowed detection of Xf up to 10 pg. mL -1 (4 copies/reaction). XFF primers were slightly less sensitive with a threshold up to 100 pg. mL -1 (40 copies/reaction). On the same DNA solutions,  Harper et al. (2010)  qPCR assay allowed the detection of strains CFBP 8402 (Xfp) and CFBP 8084 (Xfmo) up to 10 pg. mL -1 , and CFBP 7970 (Xff) and CFBP 8416 (Xfm) strain up to 100 pg. mL -1. This makes our new primer qPCR assays good alternatives to Harper's qPCR assay. The three tetraplex qPCR assays (set n°1: XF -XFFSL -XFM -XFP, set n°2: XF -XFF -XFM -XFP and set n°3: XF -XFF -XFM -XFMO) allowed both detection and identification of Xf and its subspecies (Supplemental data 2).
In silico, Xfm primers potentially amplified eight strains of subsp. pauca (CFBP 8072, CoDiRo, COF0407, De Donno, OLS0478, OLS0479, Salento-1, Salento-2) with three mismatches on the forward primer, two mismatches on the reverse primer and one mismatch on the probe, and amplicons had the expected size. We double checked the specificity of these two sets in vitro on bacterial suspensions (Supplemental data 4). Xff primers amplified the three tested strains of subsp. sandyi (CFBP 8356, CFBP 8419 and CFBP 8077) and six of the seven tested strains of subsp. pauca (CFBP 8074, CFBP 8402, CFBP 8429, CFBP 8477, CFBP 8495 and CFBP 8498). The sequencing of all amplicons confirmed the results of the qPCR assays. Xfm primers amplified five of the seven tested strains of Xf subsp. pauca (CFBP 8072, CFBP 8074, CFBP 8402, CFBP 8495 and CFBP 8498).
Identifying Xf at the subspecies level is thus highly important to limit the number of host plants to be eradicated once an outbreak is detected. In this context, on the basis of a large dataset of in-house and publicly available genome sequences of Xf and SkIf, a powerful bioinformatics-tool  (Briand et al. , 2016; Denancé et al. , 2019) , we identified species and subspecies signatures. These long-mers were used as targets to designed primer and probe combinations with different levels of specificity. These combinations target single-copy genes encoding proteins involved in bacterial metabolism. This is the case for the XF primers and probe targeting a gene encoding a ketol-acid reductoisomerase, an enzyme essential in the biosynthesis pathway of the L-isoleucine and L-valine; XFF primers and probe target a gene encoding a restriction modification system DNA specificity, involved in defense against foreign DNA  (Wilson and Murray, 1991) ; XFM primers and probe target a gene coding a DNA methyltransferase; XFMO primers and probe target a gene coding an S24 peptidase involved in a stress-response against DNA lesions and leading to the repair of single-stranded DNA  (Erill et al.
Acknowledgments We thank  Muriel Bahut  ( ANAN technical facility, SFR QUASAV, Angers, FR ) for DNA extraction automatization,  CIRM-CFBP (Beaucouzé, INRA, France ; http://www6. inra. fr/cirm_eng/ CFBP-Plant-Associated-Bacteria )for strain preservation and supply,  Leonardo de la Fuente  ( Auburn University, AL, USA ) and  LSV-ANSES  for sharing strains, and colleagues from  CNBC  for sampling plants in Corsica, France. We acknowledge  Nicolas Denancé  for preliminary experiments to design specific PCR tests. We thank  Charles Manceau  ( Anses, Angers, FR ) for his contribution while applying for funding,  Armelle Darrasse  and  Matthieu Barret  for fruitful discussions and critical reading of the manuscript.
ED salary was funded by  INRA SPE division and Anses. This work received support from the  European Union 's  Horizon 2020 research and innovation program  under grant agreement  727987  XF_ACTORS (Xylella Fastidiosa Active Containment Through a multidisciplinary-Oriented Research Strategy). The present work reflects only the authors' view and the  EU  funding agency is not responsible for any use that may be made of the information it contains.
This is why there have This paper aims to study the influence of the umbrella arch and of face bolts on the settlements induced during the excavation of a shallow tunnel, excavated with the conventional method (i. e. without TBM). The approach relies on three-dimensional finite element simulations using the software CESAR-LCPC  (Humbert et al, 2005). The main objectives of the paper are: -to demonstrate the feasibility of a finite element model that reproduces accurately the geometry of the umbrella arch and makes it possible to investigate the efficiency of umbrella arch to reduce the settlements, -to provide quantitative elements regarding the settlement reduction that can be obtained using the umbrella arch, at least for a given geotechnical context,.
However, changing the geometrical parameters implies the generation of a new mesh; this is generally difficult with graphical preprocessors. Moreover, the succession of excavation steps, with the activation and the deactivation of lining segments, bolts in the tunnel face and pipes of the umbrella arch also make the preparation of data with a graphical interface a difficult and error-prone task, unless a specific tool is developed to automate it. To facilitate the simulation of the excavation of a shallow tunnel with a variable section, we have developed: -a script of commands for the three-dimensional finite element mesh generator GMSH (Geuzaine and Remacle, 2009), -another script of commands, using a specific Python library dedicated to the finite element code CESAR, for the data relative to the material properties, boundary conditions and applied loads.
Influence of the geometry In the simulations above, the mesh reproduces the geometry of the concrete lining. We discuss here the error made if the mesh takes into account a constant section instead of a conical shape, and the influence of this simplification on the conclusions regarding the influence of the pre-reinforcements on the settlements. We have built a new mesh, using the software C-Newtun, developed by Itech (2018) in the framework of the French research project Newtun. This software generates automatically the tridimensional mesh and the data files. The pipes are horizontal and lean on the lining previously built; the simulation takes into account the umbrella arch with a constant length ahead of the tunnel face. Bolts in the tunnel face are represented by bar elements (instead of the homogenized approached presented in section 4.
Acknowledgements The authors thank: -the project  FUI Newtun, and especially BpiFrance  for its financial support; -the partners of the project for fruitful discussions on various aspects of the problem:  Solétanche-Bachy, Egis, RATP, Itech, Armines, Ibisc. Special thanks to Itech for letting us use the software C-Newtun. The authors gratefully acknowledge the useful comments made by the reviewers to improve the initial manuscript.
The PLUMED consortium: A community effort to promote openness, transparency and reproducibility in molecular simulations The PLUMED consortium * *To whom correspondence should be addressed: massimiliano. bonomi@pasteur. fr, bussi@sissa. it, carlo. camilloni@unimi. it, g. tribello@qub. ac. uk Molecular dynamics (MD) simulations have become an important tool for characterizing mechanisms underlying complex processes, interpreting experimental measurements, and predicting the behavior of molecular systems. Success in this broad field has been achieved through more than 60 years of continuous innovation. During this time a wide community of researchers has developed accurate integrators of the equations of motion, effective thermostats, efficient methods for calculating electrostatic interactions, accurate physicochemical descriptions of the system at quantum, classical and coarse-grained levels, a multitude of techniques to accelerate conformational sampling, sophisticated analysis tools, more powerful, personal and dedicated computers and new efficient, user-friendly software  1.
These initiatives include: SimTK a , a platform for sharing software, data, and models for the biomedical computation community; the Open Force Field Initiative b , which has been developed in coordination with the Molecular Software Sciences Institute c (MolSSI) to improve the computer models used in MD simulations; the Centre of Excellence for Computational Biomolecular Research d (BioExcel), whose mission is to improve biomolecular software and to spread best practices and expertise; the Living Journal of Computational Molecular Science e , which publishes "living" educational reviews and best practice papers that are updated on a regular basis; Materials Cloud f , a platform for seamlessly sharing resources in materials science, AiiDA g , a flexible and scalable infrastructure to manage, preserve, and disseminate the simulations, data, and workflows of modern-day computational science, the E-CAM Centre of Excellence h , which supports high-performance simulations in industry and academia, RosettaCommons i , the central hub to contribute and share the ROSETTA  6  source code for computational modelling and analysis of protein structures, the NOMAD laboratory j , which maintains the largest repository of input and output files for total energy calculations in materials science, The Materials Project k , which provides open webbased access to computed information on known and predicted materials, Qresp l , a tool for curating, discovering and exploring reproducible scientific papers, and nanoHUB m , a platform to share simulation software and educational tools for nanoscience.
A more exhaustive list of data repositories has been compiled by Scientific Data n. While these initiatives have laid crucial groundwork to increase the accessibility and reproducibility of MD, their effectiveness is hampered by the fact that it is difficult to use multiple MD codes within the same research project and to carry out development on multiple codes at the same time, as each one is designed with distinct goals and optimized for specific applications. While several methods have the potential to be useful across varying fields and platforms, their applicability is hindered by this lack of interoperability between MD codes. A strategy to resolve this problem was pioneered a decade ago with the creation of PLUMED   8  and the software suite for advanced generalized ensemble simulations (SSAGES)  9  , have since been developed.
Recently, PLUMED has incorporated additional functionalities that surpass those that were originally conceived by its core developers. As a result of a series of technical innovations and the development of an infrastructure which allows external contributions to be easily incorporated into the code (see Box 2), PLUMED has evolved into a flexible open-source library  10. As of today, PLUMED can be used with both state-of-the-art classical and ab initio MD codes, such as ACEMD  11  , Amber 12 , DL_POLY  13  , GROMACS  14  , LAMMPS  15  , NAMD  16  , OpenMM  17  , ABIN o , CP2K  18  , i-PI  19  , PINY-MD  20  and Quantum Espresso  21. Furthermore, PLUMED has also been used to enhance the capabilities of analysis tools such as VMD  22  , and platforms such as HTMD  23  and OpenPathSampling  24.
When new techniques are implemented in PLUMED, they can thus be rapidly disseminated to a large and diverse user base. As a matter of fact, PLUMED has made all these techniques accessible and easy to use for everyone. The impact across multiple communities is further accelerated by the fact that PLUMED uses a simple and unified syntax for all the MD codes and analysis tools with which it can be used. The interoperability that PLUMED provides ultimately allows for cross-validation between different MD software and cross-fertilization of ideas between different fields of computational chemistry, biophysics and materials science. The success of the open-source PLUMED library is due not only to the contributions of the core developers but also to the efforts of an entire community of users and developers.
To acknowledge this working model, here we announce the foundation of the PLUMED consortium, whose mission is to transform how scientists communicate MD protocols towards increasing transparency and maximizing impact of new research. The primary way in which the consortium achieves this goal is through the continued, community-driven development of the PLUMED open-source library, which welcomes the addition of new code from all members of the consortium as well as other researchers. Additionally, the consortium will also collectively strive to promote good practices in enhanced-sampling MD simulations to encourage the highest possible standards of scientific reproducibility. Finally, the consortium will be actively engaged in introducing and training the newest members in the community in the methods that are disseminated via the PLUMED library.
To increase clarity and transparency of MD simulations, we have created a public repository, called PLUMED-NEST p , which all members of the consortium as well as other researchers are encouraged to use to share their PLUMED input files along with all the data required to replicate the calculations presented in their peer-reviewed papers and preprints (see Box 3). This repository will not only promote scientific reproducibility, but it will also serve as an instrument for novice users to learn the basic and advanced techniques implemented in PLUMED through a series of real-life applications in the fields of computational chemistry, physics, and biology. In this regard, the repository will also help us to develop resources for the education and training of the new generations of scientists in the community -an objective that is currently met and that will continue to be met by organizing user meetings, in-person and online tutorials.
The PLUMED consortium will be an open community composed of current and past developers, contributors, and all those researchers whose work builds in part on PLUMED and at the same time drives the development and dissemination of PLUMED. The list of the members of the consortium will regularly be updated on the PLUMED website q and the current PLUMED developers will act as coordinators for this community. We strongly believe that this novel organization, which unifies core developers and contributors to the code, is the most representative way of reflecting the community-driven effort that is the heart and soul of opensource software development, which is a crucial part of any methodological advancement  25. Therefore, we welcome all future members who share our vision.
Box 1: Overview of the PLUMED library PLUMED is an open-source C++ library that can be interfaced with many state-of-the-art MD codes. Its basic functionalities are: i) to retrieve the current atom positions from the main code; ii) to calculate additional quantities, such as coarse-grained representations of the system (collective variables) and external biasing potentials; iii) to communicate external forces back to the MD code and hence to modify the dynamics. PLUMED provides all the functionalities needed to perform MD simulations using well-established enhanced-sampling methods, such as umbrella sampling  26  , metadynamics  27  , and steered MD  28  as well as more recent approaches. These techniques can be used in combination with a large toolbox of collective variables that describe complex processes in physics, chemistry, material science, and biology.
PLUMED can also calculate these descriptors a posteriori on pre-calculated trajectories via the driver utility and can perform various other analyses such as dimensionality reduction or reweighting. PLUMED can be interfaced with the host code by using a single well-documented API that enables the PLUMED functionalities to be imported. The API is accessible from multiple languages (C, C++, FORTRAN, and Python), and is thus compatible with the majority of the codes used in the community. The PLUMED license (L-GPL) allows it to be interfaced also with proprietary software. Several MD codes, including AMBER, LAMMPS, DL_POLY, i-PI, and OpenMM now have the interface to PLUMED natively implemented. The current structure of PLUMED is modular, i. e. new functionalities can be added without changing the core of the code.
Box 2: Overview of the current PLUMED modules Currently, six modules have been contributed to the official PLUMED distribution by groups external to the core developers of the code. All these modules are independent from the PLUMED core and need to be activated when configuring PLUMED. The largest contributed module (VES) implements the Variationally Enhanced Sampling 29 approach and includes a number of basis functions, target distributions, and optimization algorithms. The DRR implements the Extended-System Adaptive Biasing Force method for enhanced-sampling and free-energy calculations  30. The EDS module implements the Experiment Directed Simulation approach to adaptively construct linear restraints that ensure that the biased collective variables sample a new target mean value  31. More recently, three additional modules have been contributed to PLUMED and implement the enhanced-sampling method called logarithmic mean-force dynamics  32  , the permutation invariant vector  33  , a general-purpose representation of the structure of materials that can be used to analyze and simulate transitions between ordered or disordered forms, as in crystal nucleation, and a method to find multiple diverse reaction pathways of ligand unbinding, available in the MAZE module  34.