dataesr/scientific-paragraphs-categorization huggingface dataset:
In this scheme (see Figure  7(c )), some basic components are selected from the existing studies to construct an initial configuration of meta-atoms. Then, the structure evolution is realized by genetic algorithm (GA) or neural network until the meta-atoms conforming to the specific properties are found. For the GA, a few iterations are often sufficient to find the best configuration. Compared with traversing all possible configurations, the computational cost of FEM is significantly reduced. For the neural network, the dataset for training is obtained by FEM according to a certain number of configurations. With a well-trained neural network, the best configuration that meets the specific properties can also be found among all configurations. The authors provide four cases to illustrate the implementation of the scheme.
In our design, the dataset is obtained by plane wave expansion (PWE) method, and the trained neural network can predict two different geometric structures for the same bandgap width, which are shrunk type and expansion type. The edge state can be obtained in this common bandgap frequency range. For the interface formed by two structures, we confirm that the edge state localization of the wide common bandgap structure is higher than the narrow common bandgap. Moreover, the spin excited edge state shows directional propagation and is able to turn around sharp corner without back scattering effect. Our work shows that the structure design based on ML allows the realization of advanced properties such as topological states. Some recent works have also shown the ability of AE in mechanical structure design.
We discretized the frequency domain according to the different topological properties of the bandgaps and obtained the dataset analytically. Through data training, TNN can map the structures obeyed by the specific topological properties, which allows us to design the topological interface mode at the end. Another attractive work on mechanical beams was done by Wu et al. [125]. The highlight of this work is that they used neural networks to replace the element concept in the conventional discretization methods for nonperiodic system, see Figure  8(d). They train neural network to connect the input and output response of an individual material unit. In addition to the first unit, the other units take the output response of the previous unit as the input response. By simply defining the boundary conditions and frequency requirements, the cross-sectional area of each unit can be adjusted by the minimisation condition between the overall output response and the target output response, thus achieving the overall design.
MLIPs are trained over the DFT datasets, and thus exhibit the same order of accuracy and inherent flexibility to study novel materials. MLIP-based MD calculations can be also conducted using the same platform as that of the common MD calculations on the basis of empirical interatomic potentials. In order to briefly explain how MLIPs can address the critical challenges in the evaluation of lattice thermal conductivity of a given material, we would like to categorize materials as those with high and low symmetrical lattices. For highly symmetrical structures like graphene, the BTE solution is more efficient than classical MD simulations. The main computational bottleneck of BTE method is to acquire the anharmonic interatomic force constants. In a recent study for the thermal conductivity of several bulk and 2D structures, it has been confirmed that MLIPs can substantially accelerate the evaluation of anharmonic interatomic force constants while they show close agreement with DFT-based estimations  [143].
Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Research funding: This work is supported by the  National Key R&D Program of China  (Grant Nos. 2020YFA0211402 ), the  National Natural Science Foundation of China  ( 11902223 ), the program for professor of special appointment ( Eastern Scholar ) at  Shanghai Institutions of Higher Learning , the  High-Level Foreign Expert Program , the  Fundamental Research Funds for the Central Universities. D. T. acknowledges financial support through the  "Ramon y Cajal" fellowship , under Grant No. RYC-2016-21188 , from the  Ministry of Science, Innovation, and Universities , through Project No. RTI2018-093921-AC42  and from the  Universitat Jaume I  through Project No.
Lead isotope provenance studies of archaeological artefacts rely crucially on the availability of reference data from raw material sources. The OXALID database, a collection of Excel sheets with Pb isotope data of ores and artefacts, is still the most cited data source in archaeometry. However, OXALID has not been updated for several years and contains almost exclusively data from Europe, particularly from the Mediterranean area. Digitalisation and open science philosophy currently revolutionise the use of machinegenerated data by developing digital data infrastructures. A modernised Pb isotope reference database, which is tailored for, but not limited to archaeometric research, is hence overdue. Here, we introduce GlobaLID, a FAIR (findable, accessible, interoperable, reusable) and extendable database and a web application with interactive and statistical tools for user-friendly data handling up to publication quality.
g. ,  Berger et al. , 2021; Longman et al. , 2018; Pollard & Bray, 2015). The basis of Pb isotope provenance studies is the comparison of isotope signatures from objects with those of (ore) minerals (Stos-  Gale & Gale, 2009). Successful application necessitates that reference data are abundant in statistically relevant dimensions and detailed metainformation such as location, geological setting, ore deposit type, sample mineralogy and the instrument used to generate the data are available. The quality of published Pb isotope data shows significant variation. It depends heavily on the selection and preparation of samples, analysis quality, and the (raw) data-processing procedures, which often are not (completely) reported in the publications. OXALID (Oxford archaeological lead isotope database), compiled by Noel H.
Gale and Zofia A. Stos of the University of Oxford (Stos-  Gale & Gale, 2009) , unquestionably is the bestknown Pb isotope database for ores and archaeological artefacts coming mainly from the Mediterranean area. This becomes the core of our GlobaLID database. The structure of OXALID, freely downloadable data in Excel sheets sorted according to countries, renders it very easy to use without deep knowledge of tectonics, isotope geochemistry, regional metallogeny or geology, which certainly contributes to its widespread usage. However, OXALID has not been renewed since 2012 due to closure of the analytical facility. It therefore does not contain the most current data and its geographical coverage is largely limited to southern Europe. Recent years saw a refocusing on the geological background of Pb isotope systematics in archaeometry  (Albarède et al.
, 2012 (Albarède et al. , , 2020;; Artioli et al. , 2020; Baron et al. , 2014)  and the publication of reference data lists including extended metadata such as geological and geochemical information on study areas  (Hsu & Sabatini, 2019; Killick et al. , 2020). However, while convenient to use and set up, published spreadsheets are fundamentally flawed for serving as data repositories as they are an unwieldy medium that neither allows the continuous expansion to integrate newly published datasets, the attachment of adjustments, nor an interactive usage. These technical limitations quickly render the sheets outdated and the format unsuitable to modern research. Moreover, their accessibility might be limited by publishing restrictions or pay walls, for example. The University of Oxford/  ERC FLAME project (2014-present)  was the first to move beyond compilation of provenance data in Excel sheets by creating an interactive GIS-based environment for filtering data  (Perucchetti et al.
, 2021). It is, however, not yet available for the public. IBERLID, an interactive database of ores from Spain and Portugal (García de  Madinabeitia et al. , 2021) , represents another modern approach and constitutes a large step forward to make Pb isotope data in combination with geological meta-information internationally available. GlobaLID responds to the open-source demands of analytical data. It is an openly accessible research infrastructure for a worldwide and collaborative collection of Pb isotope reference data of ores, which enables interactive and interoperable use of the data. The database is growing over time and will exceed the applicability of the OXALID and other previously published databases by its substantial meta-information, including geological and geochemical parameterisation.
GlobaLID will contribute to overcome access restrictions resulting from language barriers or pay walls, for example. The web application framework 'Shiny'  (Chang et al. , 2021)  and several specifically designed R-functions are the backbone for a web-based application that allows us to interactively access the database and to generate high-quality 1D, 2D and 3D graphs with consistent standards. Various options for filtering, plotting, and comparison with the user's research data are available. The GlobaLID application and database follow the FAIR principles  (Wilkinson et al. , 2016) : (1) Findable (F1-4): the Pb isotope reference data are no longer distributed in individual data collections or websites; data and metadata are assigned to a unique and persistent identifier (the DOI of the database).
(  2 ) Accessible (A1,2): data and metadata are retrievable and accessible. (3) Interoperable (I1-3): data and metadata use a broadly applicable language; vocabulary follows the FAIR principles; data and metadata include references to each other. (4) Reusable (R1. 1-1. 3): data and metadata are completely described and attributed. The release includes a clear and accessible usage licence. Data and related metadata meet community standards and are individually referenced with original publications. GlobaLID offers tools for comparing the user's own data with the Pb isotope database and for creating useful and user-adapted diagrams meeting publication standards. Quality control of the database is still ongoing and new data will be added continuously. Research groups generating new data are invited to contribute their data.
Compilation of the data The database for GlobaLID  (Westner et al. , 2021 ; https://doi. org/10. 5880/fidgeo. 2021. 031) was compiled from Pb isotope data of several sources: (1) the authors' personal databases, comprising data on ore minerals generated in their research as well as values from redigitalised and born-digitalised publications in journals, books and book sections, which were substantially expanded over many years of research by our group; (2) OXALID and references used therein; (3) reference data collected by F. Begemann and S. Schmitt-Strecker, Max-Planck-Institut für Chemie, Mainz, and generously shared with one of us in 2014, including 5000 datasets of ores and artefacts; (4) the database of  Blichert-Toft et al. (2016) , with 6700 datasets. This compilation currently comprises more than 20,000 datasets of Pb isotopes of ores and minerals relevant for archaeometric research from many regions of the world (Figure  1 ).
GlobaLID strives to be a digital heritage, and complete compilation, storage and memory of Pb isotope data in archaeometry. Thus, no pre-sorting or exclusion of data was performed. However, the quality of the data strongly depends on the instrument used and the state-of-the-art calibration and correction method applied to the machine-generated data. Particularly in older publications this information is very rarely reported and entries in the database therefore would always remain incomplete. The data quality can be inferred from the analysis or publication year of the original data. For details on the analytical setup and methodology, the user is referred to the original publications referenced in GlobaLID. The compiled number of datasets, however, is at first limited for an interactive use, because the structure of Pb isotope data and meta-data in publications is far from being homogeneous.
This issue was recently depicted by García de  Madinabeitia et al. (2021)  for their compilation of the IBERLID database. In particular, coordinates of the analysed samples are missing in many publications. While working through published lists in detail, widespread lack of much essential information became obvious. Consequently, setting up a Pb isotope database adhering to the FAIR principles  (Wilkinson et al. , 2016)  required complete revision of the datasets, including data and reference verification, detailed search for missing meta-information, and standardised (re)calculations of the different Pb isotope ratios. For revision, verification and (re)calculation, the free programming language R (R Core Team, 2018) was chosen. Original scripts were written by one of us (T. Rose) for the calculation of (for example) model age parameters.
Because all this is very time-consuming work, a global database with accurate and high-quality meta-information cannot be compiled and, even more importantly, revised in a reasonable amount of time by the core team of GlobaLID alone. Therefore, the Pb isotope community is invited to participate in this process and to submit additional data. Revision of data and meta-data is and will be carried out in geographical sections. The Pb isotope data of every region whose revision is completed by the core team or community collaborators is added to the public database. The database is stored in a data repository and is findable via its DOI. The most complete and recent version of the database used in the application hence comprises all regions, which are fully revised and published in the repository.
In this way, the database will continuously grow. In addition, GlobaLID allows users to publish their own Pb isotope data sets as an alternative to conventional publishing-for example, if datasets are considered too small or lacking a publishable project context. For now, the compiled database only includes ore minerals from natural occurrences. Rock data can be retrieved from the geoscientific literature and specific databases (see, e. g. , http:// georoc. mpch-mainz. gwdg. de/georoc/ and references therein). However, the isotope signatures of country rocks and their minerals components (e. g. , K-feldspar) are not necessarily related to those of ore minerals from the deposits and therefore are not per se useable for provenance studies. The database currently also does not include archaeological materials.
Objects found in specific regions are not necessarily indicative of a local isotopic fingerprint as they depend on the archaeological interpretation and hence bear a high potential for circular argumentation. Since GlobaLID enables users to visualise their own data in comparison to the reference data, such data can be included by users for case studies. Slags and other metallurgical remains from historical sites in close vicinity to ore deposits, or ingots with clear indication of the originating district, might be considered better pathfinders and commonly are a genuine representation of the ores utilised in historic times. Since GlobaLID is an ongoing project, these materials are planned to be added to the database in the near future. F I G U R E 1 World map with coverage of Pb isotope reference data available (status of the map 18/1/22).
Structure of the database The GlobaLID database  (Westner et al. , 2021)  consists of several elements of information: (1) coordinates and geotectonic details; (2) Pb isotope ratios; and (3) Pb isotope model parameters. This information was taken from the original or additional publications and the parameters were calculated from the respective equations. Duplicate datasets were discarded whenever existing data were simply republished. Each potential duplicate was individually cross-checked by comparing sample number, reference, mining site or a combination of these attributes before exclusion. Datasets from repeated measurements or from completely repeated procedures-that is, including laboratory Pb separation, of previously published specimens-are included in the database. The first block of the database provides detailed geographic and geological information about the samples.
As the terminology throughout the publications is not always complete and unambiguous, completion or alignment was required. Regional information includes country, political province/region, county, mining area, mining site and a column for additional information on the sampling site. While mining areas and mining sites originate from the original publications, the modern administrative units were extracted from the NOMINATIM database, an open-source geocoding tool  (Hoffmann, 2013)  based on the geographical coordinates of the sites to include concise and up-to-date information. Georeferencing is provided with latitude and longitude in decimal coordinates according to EPSG 4326 (WGS84, compatible with Google Maps and OpenStreetMap, for example), and an additional column supplies information about the location precision-that is, in case the exact sampling site could not be located.
Minerals/sample description lists the sample phase assemblage as provided by the original publication. This information is crucial to discern radiogenic ingrowth or for detailed studies on the mineralogy. Sample numbers were taken from the original publication. The formation period of the deposit is provided in the column 'geological period' and was either withdrawn from the original publication or from additional publications. The second section of the database comprises the Pb isotope ratios of the samples. All commonly used Pb isotope ratios are listed: 206   204 Pb isotope. Since numerous publications lack some of the ratios, missing values were calculated to ensure consistency. All data ever acquired are included in the database, even though values generated before 1974 were uncorrected and had much higher errors than data generated with today's techniques.
In the web application, such datasets can be excluded by filtering. Additionally, the instrument used and the year of the first publication of the data are supplied. The third block contains the calculated model parameters-that is, model ages, μ ( 238 U/ 204 Pb) and κ ( 232 Th/ 238 U) values. These calculated values may distinguish between metal sources with different initial U, Th and Pb values  (Albarède et al. , 2016). This information is not necessarily provided in the original publications and the models used might be different. Therefore, the calculated model ages, μ and κ values for the four most commonly used models are given  (Albarède et al. , 2012; Albarède & Juteau, 1984; Cumming & Richards, 1975; Stacey & Kramers, 1975). R scripts for their calculation were written by one of the authors (T.
Application The application is based on the R package 'Shiny'  (Chang et al. , 2021) , which was designed as a framework for interactive web applications written in the programming language R (R Core  Team, 2018). It provides access to the most recent database version and to visualisation of the data on maps and a wide variety of plots without the need to download the database or have knowledge in programming with R. The application aims to include the most common tasks of the Pb isotope data workflow. Various filters therefore enable precise selection of the reference data. A one-click match function allows the selection of reference data that overlap with data uploaded by the user. This facilitates subsequent manual refinement of the selection by the exclusion of (for example) deposits that are considered to be archaeologically unrelated.
Thus, it allows researchers with different backgrounds (e. g. , earth sciences, archaeometry/ archaeometallurgy or archaeology) and data handling skills to work effortlessly with the application. The map included in GlobaLID provides instant information about the coverage of regions with Pb isotope reference data. Plots are provided in an interactive mode to allow a detailed inspection of the different reference data. Additionally, they are provided in a static mode that can be downloaded in publication quality. The selected reference data can be downloaded as a spreadsheet, and a reference list for all selected data is included in the download by default. The features of the app rely on several R packages, most importantly dplyr  (Wickham et al. , 2021) , leaflet  (Cheng et al. , 2021) , ggplot2  (Wickham, 2016) , plotly  (Sievert, 2020)  and DT  (Xie et al.
, 2021). Own functions were only written for very specific tasks (e. g. , calculation of model age parameters). The application can be accessed via https://globalid. dmt-lb. de/ and its source code is available from the project's github repository (https://github. com/ archmetalDBM/GlobaLID-App). GlobaLID currently provides analytical tools for common lead deposits, which give positive model ages. Deposits with anomalous ratios, resulting in negative model ages, such as few deposits in Europe and many elsewhere (China, central and southern Africa, North American Mississippi Valley Type (MVT) deposits) require other tools such as IsoPlotR  (Vermeesch, 2018) , especially the means to create isochrons for sources of anomalous ratios, and to fit archaeological data to them.
Structure of the application The GlobaLID web application provides a user-friendly platform for the database and is mostly self-explanatory. Detailed information on how the application works and valuable hints about the details of some features can be found on the 'Instructions' page. A navigation menu leads through the features and an additional panel contains the different filters. On the 'Map' page, the georeferenced data are visualised on a map or satellite image (Figure  2 ) together with some predefined plots as a preview. The 'Explore' page is dedicated to the individual creation of diagrams for viewing, interactive use and download/printing according to the user's needs. The 'Upload data' page allows users to safely upload their own research data as. csv or. txt files and enables a comparison with the reference data provided.
No personal user account is necessary for uploading and working with one's own research data in the application. To keep unpublished data private, uploaded research data will only be temporarily stored and automatically deleted from the server when the application is closed. The filter settings can be downloaded, and the user can upload the same file repeatedly; therefore, the plots can be easily rebuilt. 'Download' offers options to download created plots and selected datasets from the GlobaLID database as well as one's own datasets enhanced with calculated age model parameters, for example. 'References' lists all references with full text citation and DOI that are currently included in the GlobaLID database. 'Resources' provides R scripts specifically developed for GlobaLID for independent usage.
The 'About' page introduces the core team of GlobaLID and mentions all contributors and further people to be acknowledged. All necessary formal information is contained in 'Legal Notice & Privacy'. 'Contribute' provides a form for the contributors to upload new or updated datasets. This page is password protected to exclude spam. If you are interested in becoming a contributor, please contact the GlobaLID core team (globalid@bergbaumuseum. de) or one of the authors.