dataesr/scientific-paragraphs-categorization huggingface dataset:
II. The computational model for in-flight ice accretion In this Section, we present the computational model we employ to predict ice accretion in aeronautical applications. It consists in a multi-disciplinary framework loosely coupling an in-house Lagrangian particle tracking code with the open-source Computational Fluid Dynamics (CFD) solver SU2  [37]  and the ice accretion solver PoliMIce  [5]. The framework flowchart is reported in Fig. 1. The computational model describes a multi-phase dispersed mist flow. With reference to Fig. 1 , first the aerodynamic field developing around the airfoil, or more generally the aircraft, is reconstructed using the SU2 RANS solver described in Sec. II. A. Then, the field solution is passed to our in-house particle-tracking software, PoliDrop, see Sec. II.
A. Collection Efficiency The first experiment concerns the GLC-305 airfoil exposed to a subsonic mist flow reproducing warm weather conditions. Temperature is well above the water freezing point and, therefore, the current investigation is focused on collection efficiency predictions only. The test-rig detailed set up and the complete measurements database are reported in  [35]. Table  2  reports the experiment nominal conditions together with the uncertainty maximum and minimum bounds. Uncertainty bounds are established according to the IRT calibration report  [52]. The goal is to propagate the uncertainty affecting the parameters of the experiment namely, the angle of attack AoA, the mach number , the free stream pressure and temperature  ∞ and  ∞ and the MVD, to the numerical predictions of the collection efficiency over the airfoil surface.
Funding Sources G. Gori  would like to acknowledge that this work was partially funded by the  European Commission 's  H2020 program  through the  UTOPIAE Marie Curie Innovative Training Network  ( H2020-MSCA-ITN-2016 , Grant Agreement number  722734 ). A. Guardone acknowledges funding from the  European Union's Horizon 2020  under grant agreement No. 824310 ICE GENESIS.
Pamart, et al. Studies in Digital Heritage, Vol. 6, No. 1, Publication date: June 2022 re-use any viable and efficient solutions from one project to another. Moreover, this pitfall must be combined with a wide range of evolving imaging and capture techniques, applied in variable contexts for different purposes. From this statement, anyone can foresee that the chance of having in the near future a single, generic and standardized solution covering all possible current and future applications is close to zero. Due to novel digitization efforts, the Cultural Heritage community is collecting an overgrowing mass of heterogeneous data with a high risk that the majority of these datasets will not be reusable in the future because of a lack of documentation. Such a scenario is not so foreign, as it already occurs in our daily practice.
Barcodes propose today interesting features (robustness, capacity, ease of use) and a high technology readiness level. An application for CH documentation is explored in this work. Among 2D barcodes, the Quick Response code  [Pandya et al. 2014]  thanks to its large capacity, 360 readability and error/damage correction abilities has been experimented for the purpose of this research. To this aim, we conceived and experimented a system allowing to document the of a Digital Heritage asset from its own photographic-based surveys. This article presents a versatile and CH-oriented framework entitled MEMoS and standing for a Metadata Enriched Multimodal dOcumentation System. MEMoS is aiming to define a operatorfriendly solution to integrate essential metadata and paradata during data acquisition.
Collec-Science (INRAE) Collec-Science (CS, www. collec-science. org) is collaborative software dedicated to the data management of collected samples in the framework of scientific experimentations developed by Eric Quiton  [Quinton 2021 ]. The application domain is earth science and biology. CS is an open-source solution distributed under an AGPL license. CS helps to handle the registration, storage, conservation and sharing of two types of elements, containers and samples using many possible configurations. A labeled object is associated with free-from or normalized metadata to ensure data provenance and traceability through the places visited during its lifecycle. CS is adapted to samples collected on the field and QR code labeling is integrated to identify and track any item. A CS instance (service and related database) is commonly accessible on the web for collaborative scenarios, but it can also be installed locally to allow its use in remote places where internet connection is not accessible or stable  [Plumejeaud-Perreau et al.
Links between MEMoS and AIOLI are numerous and could be implemented quite rapidly as QR code decoder is already implemented. Some examples include automatic geolocalisation, inviting collaborators, temporal state management, loading a predefined template for annotations or terms from thesauri, and linking to uniform resource identifiers (URIs) and universally unique identifiers (UUIDs). On the semantic side, an interesting bridge with MEMoS is foreseen as AIOLI processes, including annotation, have been recently formalized in CIDOC-CRM.
MEMORIA (MAP Research Unit) Memoria is an Information System (http://memoria. gamsau. archi. fr/projet/) aiming to record the process through which a digital resource or activities were achieved  [Dudek and Blaise 2017]. Memoria is a web platform enabling to describe and depict a scientific result especially in historical and heritage sciences. Users can build the research process directly through the interface, including the tools, the workflows and even the choices made during their work to create a digital output. Memoria is based on an internal and collective initiative to create a wheel of activities (including digital surveys) with corresponding definitions for each term. Interaction with the database envisioned as a knowledge-based systems are made directly via the website or through PDF forms, where users can add or modify descriptors to document instruments, objects of studies, temporal coverage, or format-related information.
humanities. science) and further toward their long-term archival compliant CINES prerequisites handled by a stand-alone software (aLTAG3D). ArcheoGRID is free-access and the data are hosted in HumaNum (https://www. huma-num. fr/about-us/) a Digital Humanities Infrastructure with which large scale harvest methods are currently envisioned at European and international reach. A metadata enriched system for the documentation of multi-modal digital imaging surveys 2:7 Studies in Digital Heritage, Vol. 6, No. 1, Publication date: June 2022.
In DH current practices, it is common to mix data from different sensors, resolutions, scales, spectrums, temporal states and users -acting as many modalities -aiming to build a representative digital documentation of a CH object. From this definition, it is possible to state that CH practices are commonly and intrinsically multimodal as they usually involve some of the cross-modalities above-mentioned. Taking into consideration all those variables, data provenance surely will become -or has already become -more and more brain teasing. It is inefficient and problematic to carry out a multi-source reconstruction for data fusion after data is collected, which is a motivating factor behind why a solution is needed to address or integrate this issue during data acquisition. Indeed, in most scenarios exploiting digital models, a metadata-based description is mostly achieved -and required -in the advanced step of a DH project, usually when data are going to be circulated to the scientific community, the institutions, or the public.
MEMOS, A METADATA ENRICHED MULTIMODAL DOCUMENTATION SYSTEM MEMoS is currently envisioned as a three-part framework to sequence, describe, encode and display meaningful metadata attached to an image set at the time of capture. The description is performed beforehand using a structure inspired from the W7 ontological model as described in Fig. 4. The encoding is achieved with common and simple 2D barcodes. The display is illustrated in the following section 4. 3, showing MEMoS uses in different case studies. Our approach is currently at an experimental testing stage. The results presented below were obtained using several libraries and softwares, but MEMoS would benefit from a dedicated software and hardware framework as depicted in the illustration below (Fig. 4 ). The concept behind the use of barcodes to incorporate metadata into the acquisition stage has an analogy to the well-known clapperboard used in cinematographic industry.
Which is the section dedicated to reporting the hardware/software implications such as instruments, devices or applications and other supports used for data capture. How encompass the "action" sphere and give a place to expose methods, techniques or procedures exploited. Why is dedicated to including contextual contents and purposes or any information that motivated the action performed. The spectrum of this section is vaguer than the previous but can be filled with elements related to the project itself or the expected outcome of the dataset. In this way, any Activity, understood as a flexible digital event (project, mission, a capture set, a subset or even a single resource) is therefore defined by the cross-relations between the seven elements enriched with free-form and context-dependent descriptive metadata.
For the development of Microsoft Tag Service, the multinational presented the High-Capacity Color Barcode (HCCB)  [Grillo et al. 2010]  and later the HCC2D with encoding capacity up to 2KB/sq2, but this promising solution was discontinued in 2015. More recently, other solutions [Melgar and Farias 2019] including Just Another Barcode (JAB)  [Bechtold et al. 2020 ] has re-introduced polychromy into 2D barcodes. For the same volume of data, a QR code should be 2. 5 times bigger with comparable error compensation performance. JAB source code also has the benefit of being released under GNU LPGL. For this work, a monochromatic QR code has been chosen but JAB presents an interesting alternative especially if its robustness is validated with multi-band imaging. At the current stage of development, python-based libraries (PyZbar or qrcode 7.
3. 1) or free solutions (QR-Studio, InkScape) were tested to generate barcodes from a single or a batch of JSON files. Moreover, for this preliminary stage the choice of a static solution (JSON file embedding) has been made for the benefit of encrypting human readable content into the barcodes. However, the alternative of a dynamic QR code, in which a simple URL or URI is encoded instead, could offer editable metadata at the cost of relying on a purely web-based system. In this scenario, a barcode is used to embed a unique identifier (UUID) linked to a MEMoS platform allowing to create and edit in a more flexible and collaborative way. This solution will also have the advantage of limiting capacity needs and therefore the possibility to use more compact and robust barcodes (e. g. , semacode or datamatrix).
Project or mission or one-shot level documentation For this experiment made in November 2019 a unique QR code has been integrated to a calibration chart along with other coded targets. The chart was moved to different areas of the survey, each one represented with a detailed orthoimage a scene of the south wall painting previously surveyed by a global orthomosaic. The aim was to test the detection and decoding of a QR code while varying sensors and resolutions. The QR code was integrating synthetic and basic information as an attempt to memorize structured metadata to help data management of the digital collection from the Notre-Dame des Fontaines chapel in La Brigue, detailed in subsection 4. 3. 5.
Object level documentation This scenario is illustrated by data sets from an imaging practical workshop for the Swiss Conservation and Restoration Campus. In this context, each group of students was asked to analyze different objects with several imaging techniques (including photogrammetry, RTI and infrared thermography). MEMoS was used experimentally to encode the acquisition stage including metadata and paradata related to the group, the technique, and the object documented. As an example, A metadata enriched system for the documentation of multi-modal digital imaging surveys 2:15 Studies in Digital Heritage, Vol. 6, No. 1, Publication date: June 2022 information such as material, techniques and alteration were integrated as the aim of the course was to assess and understand which techniques enable or help the interpretation of observable degradation phenomenon and mechanisms (see WHAT section in Fig.
Collection level documentation Since the fire of Notre Dame de Paris, our laboratory has been involved in the scientific worksite to provide meaningful and useful insights for the ongoing restoration and reconstruction process, by means of a digital survey. As all data collected aims to be integrated in the digital clone -made accessible to all scientists involved. Through an augmented 3D viewer, data provenance reaches unparalleled levels in this project. The MAP laboratory has been commissioned, among other things, to digitize the architectonic fragments of the destroyed crossroads of the transepts. Each fragment from the keystones and the oculus revealed during clearing aims to be replaced in their initial position in the digital double. In this context, each 3D model has to be tracked and associated with cross resources (pictures, photogrammetric image set, database, etc.
Dataset-level documentation As introduced in previous sections, MEMoS' key target is the documentation of a multimodal digital survey. In this domain, current practices indeed involve generally more than one technique, scale, or spectrum to document a single temporal state of a CH object. Such data acquisition campaigns are usually complex in the number of devices and amount of expertise required to prevent data fusion issues. In practice, multimodal surveys are actually sequenced or structured similarly to filming, hence the idea of using the MEMoS QR code system as a clapper-board. The example given is a "simple" multimodal acquisition held in the Saint-Martial chapel from the Palace of the Popes in Avignon combining laser scanning, panoramic and different sequences of close-range photogrammetry.
LIMITS AND PERSPECTIVES Although the technical hardware/software implementation is currently at an early stage, MEMoS has already provided promising results. Above the added value of having self-documented data sets illustrated by the case-studies, other outcomes have been experimented. Unsurprisingly, MEMoS appears to be a time-saving method to sort, organize and even apply some preprocessing steps exploiting the linkage between data and metadata. The most interesting results were obtained with the collection-level based documentation applied for the digitization of the lapidary remains from Notre-Dame de Paris (Fig. 2  and 9 ). MEMoS has been integrated as a metadata scheme in the A metadata enriched system for the documentation of multi-modal digital imaging surveys 2:19 Studies in Digital Heritage, Vol.
6, No. 1, Publication date: June 2022 ArcheoGRID shared deposit platform. Therefore, for each JSON file detected in the arborescence, a specific routine has been developed to create a digital collection associating a virtual object with all of its corresponding resources (images, point clouds, etc. ), and the extensive metadata described using MEMoS. With this experiment, a fully automatic metadata verification and completion has been achieved, greatly improving data provenance and lineage from on data capture to a centralized and shared repository. Quite obviously, MEMoS is oriented for image-based surveys and is fully compliant with photographic-based techniques (photogrammetry, computational photography, and technical photography) even though some works use 2D barcodes patched on images [Hill and Whitty 2021] as a possible way to extend the compatibility to other imaging techniques.
CONCLUSIONS In this paper, we have presented MEMoS as a system conceived and developed to improve data provenance and management CH multimodal digitization and digital documentation practices. Our proposal offers the possibility to include in the data-stream, meaningful and useful metadata or paradata that most of the CH knowledge domain and expertise would benefit from. A solution is proposed to exploit a versatile metadata enrichment inspired on the W7 ontological model directly integrated at capture time using 2D barcodes. By anticipating and automating metadata and paradata description, our system aims to contribute to a fluent transition of CH practices over data lifecycle renewal and toward the FAIRisation of CH data. The overview of CH-oriented data management solutions exposed the growing needs and expectations in term of interoperability to embrace the variety of tools and methods used by several expertise fields.
In articulation with other tools, MEMoS could participate in increasing the value and the knowledge from current digital documentation crossed-practices. The technical implementation of our system, including software and hardware requirements, is currently at experimental phase but the possible and viable solutions presented aim to orient further development to reinforce user-friendly and versatile priorities. The illustrated case studies prove MEMoS' efficiency in variated and rich data acquisition contexts as its description schema can be adapted to different levels of DH projects. More globally, this work aims to contribute to DCH studies long term strategies by reinforcing the capitalization of knowledge and the reinvestment of experiences for further reuses. In more prospective uses, we imagine that MEMoS will enable sense-making graphical descriptions of complex multimodal data sets exploiting InfoViz methods.
Such interactive representations, if integrated or in dialog with 3D viewers, could also be enriched with a query system to create innovative ways to explore and help the interpretation of CH digital documentation. When a critical mass will be approached, future works will focus on harvesting and analysis methods to reveal the overlapping of modalities in correlation with semantic enriched spatialized annotations. Through these means, the goal is to derive from the concept of multi-modality to progressively deepen the notion of intermodality, understood as the combined and intentional use of multiple modalities for information carriers through digital contents. A metadata enriched system for the documentation of multi-modal digital imaging surveys 2:21 Studies in Digital Heritage, Vol. 6, No.
Lab Notebook Context Capture (Cultural Heritage Imaging) Recently, Cultural Heritage Imaging (CHI) made a first attempt to transpose the laboratory notebook for CH oriented projects with the release of Digital Lab Notebook: Context Capture (DLN:CC). DLN:CC is a stand-alone open-source software released under GNU license Version 3. The aim of this software is to document the making of all the digital resources related to a CH project [Schrorer and Mudge 2017]. DLN:CC enables metadata-enriched documentation at three levels: project, session and capture set. This way, users can collect, organize and re-use the GUI information stored (only locally) in a PostgreSQL database. Aware of the ongoing turnover of CH experts to FAIR data, the package includes an X3ML mapping engine linked to a conceptual model in CIDOC-CRM compliant description to export a project and linked resources in RDF format.
Acknowledgments to the  Department of Conservation and Restoration at the Bern Academy of the Arts  for the use of the fire-damaged painting (section 4. 3. 2) used as a case study during the common module Research Skills for Conservation-Restoration coordinated by the  Swiss Conservation and Restoration Campus. Fig 2 and 9: Thanks to the Public Establishment in charge of the conservation and restoration of  Notre-Dame Cathedral  for supporting the  Notre-Dame scientific action  coordinated by the  CNRS  and the  Ministry of Culture  and granting access to the site and the remains presented in section 4. 3. 3. Figure 10: Acknowledgments to the Avignon tourism department and the conservation department of the Pope's  Palace  for the access of the restricted chapel Saint-Martial surveyed during the  IMAPI  project ( UMR PRISM/LAM Sorbonne Université ) presented in section 4.
Digital Lab Notebook Context Capture (Cultural Heritage Imaging) Recently, Cultural Heritage Imaging (CHI) made a first attempt to transpose the laboratory notebook for CH oriented projects with the release of Digital Lab Notebook: Context Capture (DLN:CC). DLN:CC is a stand-alone open-source software released under GNU license Version 3. The aim of this software is to document the making of all the digital resources related to a CH project [Schrorer and Mudge 2017]. DLN:CC enables metadata-enriched documentation at three levels: project, session and capture set. This way, users can collect, organize and re-use the GUI information stored (only locally) in a PostgreSQL database. Aware of the ongoing turnover of CH experts to FAIR data, the package includes an X3ML mapping engine linked to a conceptual model in CIDOC-CRM compliant description to export a project and linked resources in RDF format.
We focus on waterlogging stress and barley as case studies, but the principles could be generically applied to any crop or biological variable. A fundamental contribution of our approach is the ability to functionally categorise big datasets. Armed with knowledge of stress prevalence and pattern using this method, scientific practitioners can (1) more intuitively identify the most appropriate adaptation within stress patterns that are more probable for their environment and (2) transfer adaptations across regions within any given stress type  35, 38. Building on foundational insights from our previous waterlogging experiments conducted using a range of genotypes and treatments in controlled environments  39  , we enumerate the effects of waterlogging on photosynthesis and phenology and then use these insights to improve the capacity of the internationally renowned model APSIM to simulate the impacts of waterlogging on crop growth  40.
When x is at or below field capacity, y = 1; y linearly decreases with increasing x until the point at which the soil is saturated (y = 0). These functions were incorporated into the APSIM software platform to enable improved simulation of crop responses to waterlogging as part of an integrated system. We calibrated the waterlogging-enabled framework using published data from field observations across five countries (Australia, Argentina, China, Canada and Ireland; Supplementary Table  1 ). Including the new waterlogging functions significantly improved the performance of APSIM in simulating the biophysical impacts of waterlogging relative to the default version of the model, with the root mean square error (RMSE) for waterlogged yield loss predictions decreasing from 0. 3 to 0. 1 (Fig. 1b ).
Of all GCM outputs, rainfall is perhaps the most uncertain. A key reason for using the data from 27 GCMs was to better quantify the spatiotemporal distribution of and variability in precipitation during the growing season. We downscaled the GCM datasets using the NASA/ POWER gridded historical weather database  64. However, previous work has shown that interpolated gridded data tends to be conducive to producing rainfall events that are smaller in quantum but more frequent, which can lead to lower surface runoff and higher soil evaporation  64. In a crop model, this could reduce plant water and nitrogen uptake, resulting in the propagation of errors that impact on variables such as biomass and yield. Using agricultural systems models with observed data before spatially interpolating point-based results may thus represent a more preferable approach for reducing uncertainty in model outputs.