dataesr/scientific-paragraphs-categorization huggingface dataset:
Data availability All data released with this Article can be freely used. The B10K consortium is organizing phylogenomic analyses and other analyses with the whole-genome alignment, and we encourage persons to contact us for collaboration. Genome sequencing data, the genome assemblies and annotations of 267 species generated in this study have been deposited in the NCBI SRA and GenBank under accession PRJNA545868. The above data have also been deposited in the CNSA (https://db. cngb. org/ cnsa/) of CNGBdb with accession number CNP0000505. The mitochondrial genomes and annotations of 336 species have been deposited in the NCBI GenBank under PRJNA545868. Sample information for each genome and the genome statistics can also be viewed online at https://b10k. scifeon. cloud/. The whole-genome alignment of the 363 birds in HAL format, along with a UCSC browser hub for all 363 species, is available at https://cglgenomics.
Nuclear magnetic resonance (NMR) spectroscopy is a method of choice to study the dynamics and determine the atomic structure of macromolecules in solution. The standalone program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and structure calculation is well established in the NMR community. To ultimately provide a perfectly transparent and easy to use service, we designed an online user interface to ARIA with additional functionalities. Data conversion, structure calculation setup and execution, followed by interactive visualization of the generated 3D structures are all integrated in ARIAweb and freely accessible at https://ariaweb. pasteur. fr.
Yet, highresolution NMR is still limited by the macromolecule size and solubility as well as the necessity to obtain isotopically labeled samples in sufficient amount. Three-dimensional (3D) structure determination by NMR relies on efficient and reliable assignment strategies  (3). Specifically, interpretation of nuclear Overhauser effects (NOEs) as structural data is often ambiguous due to chemical shift degeneracy and spectral overlap. Manually assigning NOE cross-peaks to the corresponding atoms in order to derive distance restraints is a tedious process that generally depends on the, possibly subjective, examination by a trained expert. To automate this process and improve objectivity, software packages such as ARIA (4), CYANA (5), UNIO  (6)  or ASDP  (7)  are being actively developed.
The ARIA (Ambiguous Restraints for Iterative Assignment) software package automates the treatment of NMR data and calculation of 3D structures  (4, 8). In an iterative manner, ARIA automatically assigns NOE cross-peaks and converts them into distance restraints in order to compute structure ensembles by molecular dynamics simulation  (9). In the last round of the CASD-NMR (Critical Assessment of Automated Structure Determination by NMR) challenge  (10) , ARIA consistently produced accurate structures with a mean backbone RMSD of 1. 1 Å for 10 targets  (11). Despite being well established in the structural NMR community, the usage of ARIA can be hindered by the complexity of its installation and the sophistication of the configuration and execution tasks. Although being parallelizable, the iterative protocol in ARIA requires access to a computer cluster to reduce execution time.
To improve the user experience for ARIA and provide a larger access to automated NMR structure calculation procedures, we have developed the ARIAweb server, with the aim of guiding users (from novice to expert) through the different stages required for NMR structure determination and providing an online service for computationally intensive calculations. Various software packages are used by the NMR community to process and analyze NMR data prior to engage in structure calculation, each having their own proprietary file formats which needs to be converted into the internal ARIA W42 Nucleic Acids Research, 2020, Vol. 48, Web Server issue format. To circumvent this issue, we propose an online data conversion tool for which there is no equivalent user interface in the standalone ARIA package.
Data conversion The minimal input data to perform ARIA calculations are (i) the sequence of the molecular chain(s) composing the molecule for which a user wants to calculate the structure, (ii) one (or more) list(s) of NOE cross-peaks and (iii) one (or more) list(s) of assigned chemical shifts. The input data for molecular sequence and NMR data (NOE cross-peak and assigned chemical shift lists) consist in formatted text files produced by popular NMR analysis software. Due to the variety of formats to store spectra and chemical shifts information, data has to be converted into the ARIA XML format before setting up a Structure calculation. For a Data conversion project, supported formats for NOE and chemical shift lists are XEASY, SPARKY, NM-RVIEW and ANSIG. Once all input data has been uploaded, the conversion can be processed online (Figure  2 ).
Upon completion of a conversion job, users have the choice to download an archive with the converted data ready to be used with a standalone ARIA installation or to initialize a Structure calculation directly within the main project space. Alternatively, CCPN (Collaborative Computing Project for NMR) projects containing all required data in a formatfree manner  (24) , archived as a single tar. gz file, can be directly accepted as input for Structure calculation without any conversion. Currently, ARIAweb only supports standard amino-acid residues or DNA/RNA bases definitions and incorporation of zinc ions in tetrahedral coordination. We recommend to use the standalone version of ARIA when modified residues or other organic ligands have to be included.
Structure calculation Similarly to the graphical user interface (GUI) of the standalone ARIA program, the Structure calculation service allows users to specify parameters such as input data, NOE assignment criteria, number of conformers to generate or parameters for the solvent refinement. When initiating a Structure calculation from a Data conversion job, mandatory input data are pre-filled and shown in the corresponding forms (Figure  2 ). When using data from a CCPN project, a list of all compatible data entries are listed for each appropriate input data type. Structure Calculation on ARIAweb is designed to guide the user through the main categories of parameters that need to be checked (if default values are used) or specified (if a user wants to change with customized values). The four main categories are Setup (generic information of the project), Data (input data organized by their type), Protocol (parameters related to the ARIA iterative protocol) and Structure generation (generation of structures with CNS).
Results visualization Once a structure calculation job has been submitted and finished, users can download a ZIP archive containing the entire ARIA run directory with the ensemble of conformers (PDB format), NOE violation statistics, NOE assignments and structure validation scores (text format and graphical PDF)  (25). If a CCPN project has been used as input, a new project is generated, notably including new assignments of NOE cross-peaks made by ARIA that can be analyzed further with the appropriate CcpNmr Analysis software  (26). More importantly, results can be inspected online via an interactive visualization dashboard (Figure  2 ). Structure ensembles generated by the server will be displayed interactively for all ARIA iterations with various represen- tations. Aside from the traditional 'cartoon' representation with colored secondary structures elements, users can directly visualize, on the three-dimensional structure, colorcoded statistics such as the average RMS (root mean square) of NOE violations per residue or the RMSF (root mean square fluctuation) of the generated ensemble in 'sausage' representation.
SERVER IMPLEMENTATION An overview of the ARIAweb server implementation and the technologies employed is shown in Figure  3. The web application features dynamic forms such as Data conversion and Structure calculation forms formatted with Bootstrap (https://getbootstrap. com). The content displayed on the client-side comes from the templating system of a Django back-end server (https://www. djangoproject. com). Input data sent to the server are securely saved in a PostgreSQL database (https://www. postgresql. org) using the concept of Object Relational Mapping from the Django framework. To perform and monitor the execution of ARIA jobs on a HPC (high performance computing) cluster, the Django server communicates with the Pasteur Galaxy server  (28)  through the BioBlend REST API  (29). Galaxy is a scientific workflow management system that provides means to build multi-step computational analysis akin to recipes  (30).
Job status is reported to the user in real-time with the following stages: Building, Pending, Running and Success. Finally, the results are displayed as a single page application written in ReactJS (https://reactjs. org) and connected to the back-end with the Django REST framework. This application makes use of the NGL JavaScript library for protein structure visualization  (31, 32). Table  1. Summary of input data and output statistics for the case studies. For each target, the corresponding reference PDB entry is given along with the length of the protein sequence and the number of input NOE cross-peaks used. The number of NOE restraints generated by ARIAweb at the last iteration is also shown. Ramachandran statistics, RMS of NOE restraints violations and bundle precision (mean pairwise RMSD) are presented as indicators for the quality of the generated structure ensembles a Mean RMSD (sd) for backbone atoms of well-ordered residues.
CASE STUDIES To validate the efficiency of the ARIAweb server, Structure calculation projects were set up and performed on a benchmark of seven proteins or protein/RNA complexes, ranging from 56 to 160 amino-acids, for which the solution NMR structure has been solved by experts and deposited in the Protein Data Bank (33) (Table  1 ). Input data consisted in assigned chemical shift lists, lists of unassigned NOE cross-peaks (derived from 2D, 3D or 4D NOESY spectra) and dihedral angle restraints corresponding to the data originally used to determine the deposited PDB structure. The tested entries are: Tudor domain of the human Survival of Motor Neuron (SMN) protein (1G5V)  (34) , HRDC domain of the S. cerevisiae RecQ helicase (1D8B)  (35) , dimeric anti-sigma factor CsfB of B. sub-W46 Nucleic Acids Research, 2020, Vol.
CONCLUSIONS AND FUTURE WORK In a field where the amount of experimental data and sizes of studied macromolecules are continuously growing, improving the usability and accessibility of appropriate software plays an important role in speeding up research. The development of the new ARIAweb server tends to solve most of the limitations of a standalone installation of the ARIA tool, not only for accessibility but also for gathering the successive conversion, structure calculation and analysis steps in one place. Adapting the tool as a web service facilitates the interaction and eases the learning curve with the user base and the deployment of new features on a cross-platform environment. ARIAweb will serve as a useful portal to narrow the differences in technical know-how of users by helping them to manage and perform NMR structure calculation projects through the different stages without the need to install ARIA and its dependencies, or to have access to a computing cluster.
ARIAweb will continue to be enhanced by integrating more experimental or in silico data and by improving the robustness of its automated NOE assignments procedure, e. g. through the use of consensus bundles  (41). Finally, we are committed to make ARIAweb compliant with the new NMR Exchange Format (NEF) standard  (42)  for better integration with nextgeneration NMR analysis software  (43)  and streamlined deposition of atomic coordinates and NMR restraints in public databases.
ACKNOWLEDGEMENTS This work used the computational and storage services (TARS cluster) provided by the  IT department at Institut Pasteur, Paris. We thank  Drs Tru Huynh ,  Bertrand Néron  and  Mathias Ferber  for their help. We are grateful to  Dr Cameron Mackereth ,  Dr Rivka Isaacson  and the late  Dr Chris Spronk  for providing us data for the RBM20, CsfB and MANEC test cases, respectively.
The UNIQUAC model is often used, for example in engineering, to obtain activity coefficients in multicomponent systems, while the CALPHAD method is known for its capability in phase stability assessment and equilibrium calculations. In this work, we combine them by representing the UNIQUAC model according to the CALPHAD method and implementing it in the OpenCalphad software. We explain the harmonization of nomenclature, the handling of the model parameters and the equations and partial derivatives needed for the implementation. The successful implementation is demonstrated with binary and multicomponent phase equilibrium calculations and comparisons with literature data. Additionally we show that the implementation of the UNIQUAC model in the OpenCalphad software allows for the calculation of various thermodynamic properties of the systems considered.
The UNIFAC model is based on a growing databank of parameters that are obtained from experimental data. The development of UNIFAC over time is shown in Table  1 , which shows that more and more phase equilibrium information and excess thermal properties are included, allowing the number of available functional groups to increase steadily. In the 1970s, simultaneously with the development of the UNIQUAC and UNIFAC models, CALculation of PHAse Diagrams (CALPHAD)-type models  [33, 34]  were also developed. Originally, they were mainly used in the fields of inorganic chemistry and metallurgy. Both of these model developments benefited from the availability of computers and have had a strong development during the past 50 years. The CALPHAD technique is applied to alloys, ceramics and hightemperature processes involving binary, ternary and higher-order systems.
Such a system typically includes 10e100 different crystalline phases in addition to gas and liquid phases. Each phase is described with a different Gibbs energy model. CALPHAD includes Long Range Ordering (LRO) for the crystalline phases and Short Range Ordering (SRO) in both solids and liquids. In addition, different kinds of excess model parameters are used to describe the binary, ternary and higher order interaction between the components of a phase. Dealing with so many different phases, a central part of the CALPHAD modeling is a unary database  [35]  where the Gibbs energy for each pure element in each phase is described as a function of temperature, T, relative to reference conditions, up to high temperatures of several thousand kelvin. These Gibbs energy functions are known as lattice stabilities and may include parameters for magnetic ordering.
They are needed because an element may dissolve in many different crystalline phases for which the element itself is not stable. Extensive descriptions of CALPHAD models can be found, for example, in Lukas et al. [36] , Hillert  [3]  and Saunders and Miodowski  [37]. CALPHAD software is able to calculate multicomponent equilibria with hundreds of possible phases and multicomponent phase diagrams. The database contains, in addition to the unary data, model-dependent parameters that depend on the amounts of two, three or more components. There are several commercial companies marketing software and databases for UNIQUAC/UNIFAC and CALPHAD. OpenCalphad is an open source software  [38]. CALPHAD applications typically concern the temperatures up to 2000 K whereas UNIQUAC is normally applied at temperatures up to around 400 K.
Another difference is that UNIQUAC models are based on excess Gibbs energy or activity coefficients, whereas the CALPHAD models are always based on a molar Gibbs energy expression; however, as the activity coefficients are calculated from the molar Gibbs energy, this difference is not very important. For applications, a major difference is that CALPHAD software and databases usually consider more than 100 different solid crystalline phases with different molar Gibbs energy models, whereas applications of the UNIQUAC model usually involve few solid phases. In the CALPHAD method, all models are described using a molar Gibbs energy for each phase and the models can be quite different for different phases. One reason to avoid activity coefficients is that their modeling may cause inconsistencies between the molar Gibbs energy and the chemical potentials.
The integration of both types of models in a single software allows the calculation of equilibria between complex solids described with CALPHAD models and liquids and polymers described with the UNIQUAC model. The free OpenCalphad software  [38]  was selected because it is publicly available, the source code is open for developing new models and it is written in the new Fortran standard. The OpenCalphad software can perform multicomponent equilibrium calculations and provide all thermodynamic properties of interest, such as enthalpies, entropies, chemical potentials and heat capacities as well as phase diagrams.
The molar Gibbs energy and the molar excess Gibbs energy In CALPHAD, the molar Gibbs energy for a phase a is expressed as eq. (  1 ): G a m ¼ X i x a i + G a i þ RT X i x a i ln À x a i Á þ E G a m ( 1 ) x a i ¼ N a i N a (2) E G a m ¼ X i X j > i x a i x a j L a ij þ X k > j x a k L a ijk þ / (3) where the summation over + G a i represents the contribution from the lattice stabilities explained in section 1. The term multiplied with RT is the ideal configurational entropy and E G m is the excess Gibbs energy. In CALPHAD, it is preferred to use the E as a presuperscript because the normal superscript position is reserved for the phase label as CALPHAD normally deals with many different phases. The excess Gibbs energy is described by regular solution parameters, L, for binary and higher order interactions which are constants or linearly dependent on the temperature.
There is interest to combine calculations using CALPHAD data for calculations at ambient temperatures to study, for example, corrosion with water and other fluids. Most CALPHAD calculations involve systems with 8-10 components and there is a particular unary database that provides data for the pure elements in different crystalline states as well as in liquid and gas species. This makes it possible to combine and extend descriptions of binary and ternary assessments to multicomponent alloys. In detail CALPHAD always models the integral Gibbs energy, as in eq. (  1 ), expressed as a function of temperature and composition using model parameters. The chemical potentials and activity coefficients are derived from this numerically. Unlike CALPHAD, the UNIQUAC model, developed by Abrams and Prausnitz  [14] , is an expression of the molar excess Gibbs energy, g E.
For liquids with strong SRO, such as molten salts or ionic components, there are special models like the 2-sublattice ionic liquid model  [39]  or the quasichemical model  [40]. In addition, several excess parameters depending on binary and ternary interactions are used in the excess Gibbs energy in eq. (  3 ). Chemical potentials and activity coefficients are calculated by the software using eq. (  5 ). Based on the reasoning so far, it is useful to represent the UNI-QUAC model in the CALPHAD method and implement it in software based on the CALPHAD method, such as, OpenCalphad. Analytical expressions of the first partial derivatives of molar Gibbs energy with respect to the components have been implemented in the software. Analytical expressions for the second derivatives are used to speed up convergence  [41] , but have no effect on the final calculated results.
Results The equations for the Gibbs energy calculation that include the contributions from UNIQUAC were translated into a Fortran script and added into the OpenCalphad software. This code is publicly accessible (http://www. opencalphad. com). This section is used to confirm the successful implementation of the UNIQUAC model in this software. First, the implementation of the UNIQUAC model in the OpenCalphad software is confirmed for artificial systems. Second, it is used to calculate thermodynamic properties and phase diagrams for binary, ternary, and quaternary systems. In the end, its ability to assess interaction parameters of a ternary system is tested. All the systems in this section were chosen from the open literature.
Initial tests of the implementation In order to verify the implementation of the UNIQUAC model in the OpenCalphad software, two steps are performed in this work. First, the implementation of the combinatorial excess Gibbs energy in the UNIQUAC model is tested by comparison of calculated results of thermodynamic properties obtained by Fortran code implemented in OpenCalphad, and that written independently based on the UNIQUAC model. In these calculations, structure parameters, qðAÞ ¼ 1:4, rðAÞ ¼ 0:92, qðBÞ ¼ 4:93, and rðBÞ ¼ 5:84, are used. The results are shown in Fig. 1. From this figure, we conclude that OpenCalphad calculates the combinatorial excess Gibbs energy according to the UNIQUAC model correctly. Second, the residual part of the UNIQUAC model was implemented in OpenCalphad along with the combinatorial part.
Calculation of binary systems The implementation of the UNIQUAC model in the OpenCalphad software is tested for its capability to calculate the miscibility gap in the liquid phase using the system acetonitrile (A) -n-heptane (B). The calculations are based on the binary interaction parameters in Table  3  and compared to the experimental data of Palmer et al. [50]. The results are shown in Fig. 3. The miscibility gap is evident from the Gibbs energy curve, see Fig. 3 (a) and the fact that the chemical potentials have a minimum and a maximum, see Fig. 3(b). The activity coefficients and the miscibility gap as a function of temperature have also been calculated, see Fig. 3(c)  and (d). Again, good agreement is obtained between the experimental and calculated data, illustrating the ability of the implementation of the UNIQUAC model in OpenCalphad to calculate phase equilibria in binary liquid-liquid systems.
Calculation of ternary systems In industrial processes, two types of ternary systems with partial miscibility are of interest. If there is one partially miscible binary, the ternary system is defined as type I; if there are two partially miscible binaries, the ternary system is defined as type II  [53]. To illustrate these types of partial miscibility, we selected two ternary systems: acetonitrile-benzen-n-heptane (type I) and n-hexaneaniline-methylcyclopentane (type II). Their isothermal phase diagrams are calculated by the implemented UNIQUAC model in the OpenCalphad software and compared with experimental data  [50, 51] , see Fig. 4. The interaction parameters for the calculations are taken from Tables  2  and 3. Generally, the miscibility gap of a binary or multicomponent liquid system changes with temperature.
Future applications include the possibility to combine calculations using the UNIQUAC model for the liquid phase together with the standard CALPHAD models for solid phases. In addition, this work could encourage applications of the UNIQUAC model to polymer systems by implementation of modified UNIQUAC models in the OpenCalphad software. interaction energy between i and j, Du ji ¼ u ji À u ii q total surface area, q ¼ P i x i q i q i normalized surface area for i, q i ¼ xiqi q m i chemical potential of i r i interaction contribution to i t ji interaction between i and j F total volume, F ¼.