dataesr/scientific-paragraphs-categorization huggingface dataset:
6. We have to use 400 µ m hole for safety with the 45 • incidence. The success rate to make the single and double-layer graphene suspended over 400 µ m hole is still low, and we use 200 µ m hole for double-layer LSG. 2D particle-in-cell (PIC) simulations. We perform 2D PIC simulations for the J-KAREN-P experiment using an open simulation code EPOCH  30. We fix the laser parameters based on the experimental conditions, and linearly polarized Gaussian beam in simulation plane. We consider the target ionization with the laser electric field via barrier suppression, tunneling, and multi photon ionization processes with a standard option of EPOCH. Ionization thresholds of atoms are cited from Atomic Spectra Database  25. The areal density of graphene is σ = 3. 82 × 10 15 cm -2. Our LSG thickness is 1 nm / layer, and thus, the LSG volume density is 3.
Acknowledgements The authors would like to thank the technical support by the  J-KAREN  staff at the  QST/KPSI. This work was supported by the  Ministry of Science and Technology, Taiwan  under Grant No. MOST-103-2112-M-008-001-MY2 ,  104-2911-I-008-504 ,  105-2112-M-008-003-MY3 ,  109-2628-M-008-004-MY3 , and  JSPS KAKENHI  Grant Number  19K21865 ,  19H00668 ,  JPJSBP120203206 ,  20KK0064 , a Grant for the JSPS Core-to- Core Program  " Research and Education Center for Laser Astrophysics in Asia" , and supported by  QST-IRI.
25 4. Define the initial state: compute the initial density matrix 65 5. Propagate the density matrix under the Hamiltonians 6. Extract expectation values from the propagation 7. Fourier transform the expectation values to obtain a spectrum We assume that the reader is familiar with general concepts of NMR but not necessarily with simulation. We take particular care to detail the technical "tricks" which are generally omitted in research papers but are nonetheless essential to perform 70 successful simulations. We present simulated spectra for XAn spin systems with n between 1 and 5 with several excitation schemes. The spectra are simulated using MATLAB live scripts which are available in the Supplementary Material. The code is abundantly commented and is constructed so as to follow precisely the recipe presented in this Paper.
Each object and operation presented in this Paper can thus be related to lines in the MATLAB code, and vice versa. PDF version of the live scripts are available. We strongly advise the reader to read the code in parallel to the Paper. 75 In a second step, we interpret the simulated results by performing an analytical analysis of XAn system using a theoretical framework coming from atomic physics. We show how to construct an eigenbasis and find the selection rules for the allowed transitions. The reader might wonder whether it makes sense to go through all the details of simulating NMR experiments from scratch while there are powerful simulation packages, which are freely available. SpinDynamica  (Bengs and Levitt, 2018)  and 80 Spinach  (Hogben et al. , 2011) , which run on Mathematica and MATLAB, respectively, are probably the most appropriate tools for simulations at ZULF and the people who have programmed these have already gone through the hurdles of making them efficient and versatile for us.
However, it is the Authors' opinion that performing simple simulations from scratch is the best way to get familiar with the quantum mechanical objects of NMR theory. Once one is confident with these objects and their language, one will make the best use of powerful packages such as  SpinDynamica and Spinach. 85  In writing this Paper, the Authors wish to pay a tribute to their regretted lecturer and mentor Prof. Kostantin L'vovich Ivanov, known as Kostya by many, who was taken by COVID-19 on March 5 th 2021  (Yurkovskaya and Bodenhausen, 2021). KS had KI as PhD co-supervisor performing research on long-lived states, parahydrogen induced polarization, and chemically induced dynamic nuclear polarization (CIDNP). KI's deep understanding of underlying physics allowed his group to work in very different directions, for example to combine CIDNP and ZULF NMR.
) 225 To start a simulation, we need to determine the density matrix of the system at the initial point of the experiment. We assume that the sample has spent enough time in the prepolarizing magnet to reach thermal equilibrium, that is, the spin system follows Boltzmann's distribution of states. In this case, the density matrix is given by 𝜌 = , (19) where  ,  and  are the Hamiltonian operator of the spin system, Boltzmann's constant and the temperature, respectively. 230 Operation exp( ) denotes the matrix exponentiation. Note that this operation does not consists of applying () = exp() to each element of the matrix. It is a more complex operation, which is realized in MATLAB by the built-in function expm (rather than exp). is a normalization constant, which ensures that the density matrix has unit trace.
Fourier transform the expectation values to obtain a spectrum The time domain signal is what is measured by the ZULF NMR spectrometer. The final step of the simulation is to transform 335 the measured signal from the time domain to the frequency domain using a discrete Fourier transform. Programming environments such as MATLAB or Mathematica are equipped with built-in fast Fourier transform functions. We will not discuss the mathematics behind this process but we will give a few practical hints. Contrary to high-field NMR, ZULF spectra can be obtained with real magnetic field units (rather than arbitrary units). We will show how such units can be distinctive sinc patterns). We must therefore artificially include relaxation by multiplying the signal with an apodization function, to force the signal to decay to 0.
To obtain spectra without baseline offset and preserving the integral, we propose to use an apodization function which weights all points by 2 expect for the first one 365 𝑆′′ = 𝑆′ 2𝑆′ if 𝑘 = 1 otherwise. (37) In MATLAB programming language, the fast Fourier transform function fft() takes vector ′ ⃗ as input and returns the frequency domain vector which corresponds to the simulated spectrum. Optionally, one may add a second argument  to fft() to where ℱ designated the Fourier transform. The frequency domain signal obtained after this whole procedure has units of 375 magnetic field (e. g. pT). Changing the zero-filling  changes the intensity of the frequency domain signal but preserves the integrals. MATLAB's fft() functions do not generate the frequency vector associated with the Fourier transformed signal.
A second apodization functions was applied to avoid baseline artifacts (see (39)). The apodized time domain signal was Fourier transformed with zero-filling to 65'536 points, 465 using MATLAB's built-in functions. The real part of the Fourier transform is shown on Figure  4. The frequency axis of the spectra was computed using (  39 ) and (  40 ). The spectra are symmetric around zero and so it is common to work only with the positive frequencies as shown in Figure  4. Simulating the sudden field drop experiment is the simplest case presented here. Because the coherence excitation scheme (or mixing) only consists of bringing the spin from high magnetic field to ZF or ULF, the simulation only consists of 470 propagating the high-field thermal equilibrium density matrix under the ZF or ULF Hamiltonian.
Acknowledgements This research was supported by  ENS-Lyon , the  French CNRS, Lyon 1 University , the  European Research Council  under the 725 European Union's  Horizon 2020 research and innovation program  ( Marie Sklodowska-Curie  grant agreement no. 766402/ZULF ), and the  French National Research Agency  (project ' HyMag '  ANR-18-CE09-0013 ).
But the chemical structure of phenolic molecules makes them not well adapted for LC-MS analysis. The expected phenolic molecules (Fig. 1 ) are difficult to charge with the usual positive ionisation, leading to a low sensitivity, while the overall signal is usually lower with a negative ionisation. These problems linked to the ionisation could be one of the reasons for the scarce literature on phenolic NIAS. On the other side, GC-MS has already been used to analyse resoles  [15] [16] [17] , where the main oligomers were found between 100 and 600 Da, but never to identify extracted NIAS due to substituted phenol based resole in can coatings. Theoretical databases and HRMS were used for the identification of NIAS and further mono and bi-dimensional nuclear magnetic resonance (NMR) spectroscopy analyses were done to overcome identification uncertainty.
Two different electron energies were used: 70eV and 10eV. Data were processed with Xcalibur and TraceFinder 4. 1 (Thermo Scientific). Screening for compounds used TraceFinder with a threshold TIC of 10 7 , S/N of 100 and ion overlap at 97%. A fragmentation at 70eV was used for all samples, allowing spectra comparison with NIST 2. 2 database. A second analysis using 10eV fragmentation energy was carried out in order to avoid avoiding fragmentation and approaching the molecular mass of the compounds. The combination of both HRMS spectra is used for the identification process of unknown NIAS: the monoisotopic mass and molecular formulas of fragments were proposed by the software within a 5 ppm mass deviation between theoretical and experimental masses. NIAS could be identified using combinations of molecular formulas, associated rings and double bonds (RDB) equivalent, fragmentation patterns, databases and literature.
Theoretical databases To help the identification of NIAS, a predictive database was created, listing all possible polyester oligomers with a molecular weigh less than 1000 Da. The limit of 1000 Da was chosen as only molecules with a molecular weight inferior to 1000 Da are considered to be possibly assimilated by the organism through the gastrointestinal tract  [2, 24]. Knowing the polyester resin monomeric composition, all the possible linear and cyclic oligomer combinations can be predicted from the successive esterifications. A set of iterative procedures were developed in Microsoft Excel Visual Basic for Applications (VBA) to automatize the process for any monomer composition and to calculate molecular mass for future analysis. More than 250 possible oligomers were obtained with the monomeric composition of the resin used in formulas.
Identification by GC-HRMS Due to their unexpected nature and the use of several raw materials in the coating formulation, NIAS analysis and identification are usually a complex analytical task  [25]. However, the generalisation of HRMS technology and the access to accurate mass is an important tool for the identification of unknown molecules which are absent from databases or without available analytical standards  [26, 27]. Although HRMS analysis treatment can be demanding, accurate mass coupled to calculated databases is a powerful aid to identify NIAS. Literature, particularly for polyester oligomers, was used as well to ensure the identification  [6, [28] [29] [30] [31]. Identification in GC-MS is more complex due to the loss of the monoisotopic mass in most of the cases. The use of 10eV fragmentation energy, in addition to the usual 70eV, allows approaching the monoisotopic mass which coupled to accurate mass help to identify unknown compounds.
The polyester coating without phenolic resin was used to identify NIAS which were associated to the polyester resin. The identification has been done following the protocol presented in Fig. 2. In the case studied in Fig. 2 , fragmentation pattern and proposed molecular formula of the fragments indicate the presence of aromatic rings with at least 8 oxygens and 13 RDB, suggesting that the unidentified NIAS was a polyester oligomer composed of at least two PA. To refine identification, a silylation of the sample  [32]  to differentiate cyclic and linear oligomers was carried out, which led the identification to a cyclic oligomer. In parallel, available databases were compared to   1 ). Polyester oligomers were only identified as cyclic oligomers. This prevalence can be explained by the resin synthesis with high molecular weight.
Different alkylated phenols were proposed by the NIST database with low match results and accurate masses did not match with the molecular formula of predicted oligomers. Taking one of the most intense unidentified peaks as an example, proposed molecular formula and fragmentation patterns were indicating an expected tertbutyl substitution noticeable through the loss of CH 3 (m/z = 191. 0702) and C 3 H 7 (m/z = 163. 0389) from the monoisotopic mass (m/z = 206. 0937) (Fig. 3 ). Its proposed formula was C 12 H 14 O 3 and by considering the presence of tertbutyl substitution on the phenolic ring, the only possible structure was the addition of two aldehyde functions on the aromatic ring. This particular compound identification was suspected to be 4-tertbutyl-2,6-diformylphenol. The presence of that aldehyde substitution was suspected for several unidentified NIAS.
Conclusion To investigate the influence of phenolic resins on NIAS extractions of can coatings, six different model coatings were formulated, each using one specific resole. Different resoles based on phenol, cresol and TbuP were used. Two groups of NIAS were identified in film extracts thanks to   predictive databases of oligomers and HRMS treatment: cyclic polyester oligomers, already reported in literature, and NIAS specifically found in alkylated phenol-based resoles. While the choice of resole had no impact on the quantity of cyclic oligomers of polyester, the use of TbuP-based resoles led to the detection of an important number of specific NIAS among which the most abundant were identified as aldehydes. 4-tertbutyl-2,6-diformyl phenol was directly identified by GC-MS and the presence of a formyl group substituted on the phenolic ring had been demonstrated by bi-dimensional NMR.
an injector temperature set at 280 • C. Helium was used as carrier flow with a 1 mL/min flow. An HP-5MS capillary column (30 m × 0. 25 mm x 0. 25 μm, Agilent Technologies) was used for the separation. The oven program started at 80 • C for 2 min, increased to 270 • C at 10 • C/min, held for 20 min before a last ramp to 320 • C at 5 • C/min and then held for 15 min. The scanning mass range was from 50 to 750 Da. Data treatment was done on MSD Chemstation software. Integration parameters set at a minimum peak area of 10 5 and a threshold of 15 while NIST 14 and Wiley 275 databases were used for tentative identification.
Acknowledgement The authors would like to thanks  Mr Peter Oldring  and  Pr Bernard Sillion  for their advices and assistance throughout this study and the review of this paper. This work was conducted in partial fulfilment of the PhD requirements for  Julien Terrasse  who has received a grant from the  ANRT  ( Association Nationale de la Recherche et de la Technologie, Paris, France ). The research was supported by a contract between The Valspar ( France) Research Corporation SAS ,  ISA (Institut des Sciences Analytiques, Villeurbanne, France)  and  CTCPA  ( Centre technique de la Conserve et des Produits Agricoles, Bourg en Bresse, France ).
Whereas, Figure  3  shows that for this duration of analysis, only the first four defects are detectable, Figure  6  shows that the mathematical postprocessing seems to allow the detection of all the defects present in the analyzed sample. This theoretical result confirms the previous observation. It therefore confirms the interest of SVD decompositions in terms of early detection of defects (and reduction of disturbing effects of the pictorial layer). Following these encouraging theoretical results, we moved on to an experimental study of a partial copy of a mural painting from the cathedral of Angers. It was developed using the "thermoart" device. SVD-type post-processing was developed using the "irexplorer" software package. Let's now discover the work of art studied, the "thermoart" and "irexplorer" devices and finally the experimental results obtained.
The experimental device implemented for the study The experimental device used for the study comprises two modules. The first is a data acquisition module. This is the "thermoart" device developed in the laboratory. On the one hand, it allows a controlled excitation of the analyzed sample. It also allows a synchronous acquisition of the photothermal response of the latter. The second module is a data post-processing software package. This is the "irexplorer" software package. It allows to apply an SVD decomposition to the thermographic film obtained. The latter can be applied over a time range defined by the user. Finally, the software gives access to all the EOFs calculated after SVD decomposition (Fig. 10 ).
In fact, in case of non-formalized, existing relations and similarities among two reference frameworks, only experts on both reference frameworks are able to identify them. These mappings, which we call "implicit mappings", made it challenging to address ecosystems of reference. The modelling of reference frameworks is a research direction that can establish central common points where legal experts and engineers share a language, i. e. , legal and technical requirements are established and understood together. We claim that reference framework models can make legal texts like the GDPR more "operational" from an engineering perspective, by operationalizing the legal text into engineering process activities and bridging them to those specified by technical standards. To support our claim, we take as case study the GDPR Article 35 on DPIA, and confront it with ISO/IEC 29134, the EU Smart Grid DPIA template, and the state-of-the-art CACM metamodel (Common Assurance and Certification Metamodel)  [5]  for modeling reference frameworks, we aim to answer the following research questions: • RQ1: To what extent can information privacy law and privacy protection standards for conducting DPIAs be modelled from a development process perspective? • RQ2: To what extent do the reference framework models of GDPR DPIA match to the ISO/IEC 29134, and to the EU Smart Grid DPIA template? The contributions of this work are: • A model of a relevant excerpt from the GDPR legal text, in particular the articles dealing with DPIA.
Finally, those same assets are used in the assurance projects as evidences through traceability links from the assurance layer (e. g. , an evidence in an assurance case traces to a system component or to testing results). The CACM metamodel  [5]  is a domain-specific language (DSL) proposed to model reference frameworks and, more generally, assurance management needs. Together with the CACM creation, a tool was created providing a modelling framework covering both the reference frameworks ecosystems layer, assurance layers, and traceability means for any system development project. Eclipse OpenCert  [7]  tool can be used to support the assurance activities allowing the modelling of reference frameworks, equivalence mapping models, and many other functionalities for assurance project management that are out of the scope of this paper such as the creation of assurance cases and evidence models, each Fig.
Modelling reference frameworks and equivalence maps Compliance with legal and technical requirements may become troublesome to address during systems development. In order to demonstrate that the development process complies with a given regulation, and trace the features of the development outcomes to the regulation, we require an unambiguous model of the standard or reference framework whose compliance is pursued. One of the initial efforts to provide a reference metamodel to deal with reducing the ambiguity behind regulations, and standards compliance-related activities was the CCL (Common Certification Language)  [9]. It was proven useful to model safety standards such as the EN 50128 standard for railway domain, the DO-178 for avionics  [10] , or ISO 26262 for automotive  [11]. CCL evolved into the CACM (Common Assurance and Certification Meta model)  [5]  to be more expressive in the connection with the actual system architecture  [12].
In this work, we present the first time that CACM and OpenCert are used to model privacy-related reference frameworks. 1  In addition, while several process-or productoriented standards have been modelled, this is also the first time we use them for a legal text, requiring, as we will explain later, a higher degree of interpretation. Apart from reference framework models, mappings between one another aim to reduce assurance efforts thanks to the identification of overlapping assurance requirements and activities derived from the compliance targets (law/standard/ policy in the selected ecosystem). We use another available meta-modeling package in CACM for the creation of equivalence mapping models between reference frameworks. Mapping models help to make explicit a 'matching' between elements included in the standards such as activities, roles, artefacts, requirements or other CACM elements.
All these (except part of the last step about consultation) correspond to an earlier phase of the process, out of the scope of the GDPR, which only focuses on the execution of the DPIA, and which takes for granted all these preparatory activities, whose outputs (PIA plan, risk criteria, descriptions of business processes and information systems to be assessed, etc. ) are regarded by the GDPR as elsewhere generated, pre-existent resources (respectively referred to as methodology; origin, nature, particularity, and severity of risks; nature, scope, context, and purpose of processing operations, etc. ). Or, while both ISO/IEC 29134 and the GDPR anticipated the need to consult with stakeholders (e. g. data subjects, experts), the former provides further details of the contents expected from results to be produced by such consultation.
ISO/IEC The mentioned difference is not a drawback, quite the opposite. It reflects that ISO/IEC 29134 can be more easily approached by technical staff, while, at the same time, its results can be used as a contribution to achieve compliance with the respective GDPR sections. This way, they are complementary, and not a replacement. It has been discussed whether technical guidelines such as ISO/IEC 29134 guidelines support or rather blurs the GDPR's objective as they are too focused in a risks-based approach  [16] ; however, an explicit mapping of the equivalences between these independent documents can support the comprehension of both legal experts and engineers, facilitating their communication, and helping in assurance tasks. Regarding the EU Smart Grid DPIA template, it targets data controllers dealing with data from the Smart Grid and Smart Metering Systems requiring guidance for how to conduct a DPIA with the peculiarities of their domain.
Modelling the ecosystem of reference frameworks This work has been carried out by a focus group of experts on privacy assurance from the EU project PDP4E (Privacy and Data Protection for Engineers)  [30]. A team of two researchers, experts on privacy (including the GDPR and ISO/IEC 29134), was the main responsible for creating the models. One of the researchers has more than 17 years of experience in research, having participated in privacy research projects for almost 10; the other one has been working on privacy-related projects during the last 2 years. They were supported by two other experts on reference frameworks and assurance modelling in OpenCert, with experience in modelling other standards and guidelines. One has a strong background in functional safety standards evolution and knowledge in cyber-security.