dataesr/scientific-paragraphs-categorization huggingface dataset:
Agradecimientos Entre CIFOR promueve el bienestar humano, la integridad del medio ambiente y la equidad mediante investigación de avanzada, desarrollando las capacidades de sus socios y dialogando activamente con todos los actores involucrados, para informar sobre las políticas y las prácticas que afectan a los bosques y a las personas. CIFOR es un centro de investigación CGIAR y lidera su Programa de Investigación sobre Bosques, Árboles y Agroforestería (FTA por sus siglas en inglés). Nuestra sede central se encuentra en Bogor, Indonesia, y contamos con oficinas en Nairobi, Kenia; Yaundé, Camerún; Lima, Perú, y Bonn, Alemania. Esta investigación fue realizada por CIFOR como parte del Programa de Investigación de CGIAR sobre Bosques, Árboles y Agroforestería (FTA). El FTA es el programa de investigación para el desarrollo más grande del mundo, dedicado a mejorar el papel de bosques, árboles y la agroforestería para el desarrollo sostenible, la seguridad alimentaria, y frente al cambio climático.
los socios financieros que han apoyado esta investigación se encuentran la Iniciativa Internacional para el Clima (IKI, proyecto 15_III_075) del Ministerio Federal de Medio Ambiente, Conservación de la Naturaleza, Construcción y Seguridad Nuclear de Alemania (BMU); la Agencia Noruega de Cooperación para el Desarrollo (NORAD, acuerdo QZA-016/0110); la Agencia Nacional de Investigación de Francia (ANR, proyecto TRASSE ANR-CONACYT-17-CE32-0012); el Consejo de Investigación Económica y Social (ESRC, por sus siglas en inglés, número de financiamiento ES/K00879X/1); el Centro sobre Economía y Políticas de Cambio Climático (CCCEP, por sus siglas en inglés, número de financiamiento ES/K006576/1 del ESRC); y el Programa de Investigación del CGIAR sobre Bosques, Árboles y Agroforestería (CRP-FTA) con el apoyo financiero de los contribuyentes al Fondo Fiduciario del CGIAR.
Para desarrollar el análisis estadístico se utilizó el Software SPSS versión 22. Los datos fueron organizados y sistematizados mediante tablas de frecuencia y porcentaje. Para el análisis inferencial se utilizó la prueba no paramétrica rho de Spearman, debido a la naturaleza y nivel de medición de las variables, ya que no se ajustan a la distribución normal. Finalmente, para la significancia estadística, se consideró un valor menor o igual a 0,05.
Finally, the measurement routine and data processing procedure will be explained. Due to the very different experimental parameters compared to most publications reporting on VUV-LIBS studies, a catalogue of emission lines identified with the present set-up is compiled in chapter  5. Different dependencies of the emission intensity on the laser pulse energy for neutral to triply ionized Si are investigated as well. The chapter ends with a list of identified emission lines with a subjectively assigned relative strength to assist future line identification problems and to reveal interference-free emission lines. First scientific studies investigating the detection and quantification capability for S and Cl in lunar analogue material with the new VUV-LIBS set-up are presented in the chapters 6 and 7, respectively.
P λ describes a spectral line profile calculated from Doppler and Stark-broadening. α λ and β λ are calculated for various emission lines in the considered spectral range for which the relevant constants could be found in the NIST Atomic Spectra Database  [52] , and then summed for each wavelength. For some elements, additional data is taken from the Atomic spectral line database by Kurucz and Bell  [53]. Finally, the solution to the radiative transfer equation and hence the radiance I λ of the plasma at a given wavelength is I λ = α λ β λ • [1 -exp(-β λ • z)]. (2. 7) Since β λ is directly proportional to the particle number density n, which determines the density n i,m of particles in ionization state i and energy level m, n can be drawn out of β λ and combined with z to form the area density n A = n • z as an input parameter for the simulation.
LIBS analytical procedures For a quantitative elemental analysis with LIBS, the instrument needs to be calibrated. Therefore, a set of calibration samples with well-known concentrations of the elements of interest is analysed. From the recorded spectra, the emission line intensities related to the particular elements are extracted and plotted as a function of the concentration. In the ideal case, which is usually applicable at low concentrations, the signal will increase approximately linearly with the elemental abundance  [7]. Thus, a linear regression can be calculated, which allows to deduce unknown concentrations from measured signal intensities. For higher concentrations, a saturation due to self-absorption is often observed and the slope of the calibration data slowly decreases until it finally levels off.
Normalization Normalization in LIBS means a scaling of the data on a per-spectrum basis with the aim to reduce intensity fluctuations due to varying experimental conditions and matrix effects. The scaling factor used therein is a quantity derived from the respective measurement. Throughout the LIBS community, many normalization methods are used. While most of them are related to the recorded spectrum itself, normalization with the plasma shock wave  [55]  or the ablated mass  [56]  has been reported as well. In their recent review article on normalization methods across different fields of application for LIBS, ranging from terrestrial and extraterrestrial geology over liquid crystal display recycling to food analysis, Guezenoc et al. [57]  conclude that the best applicable normalization is case-dependent, with non-normalized data sometimes even being preferred.
Extraction of spectra The camera is controlled using the software provided with the instrument. The recorded images are saved in a proprietary format, which contains additional information about the detector parameters, such as the exposure time, detector temperature and horizontal and vertical binning. The rotational stage of the grating is not controlled with this software and hence the grating angle must be stored in the file name. With Python routines, which I developed myself, the image data and parts of the metadata are extracted from the binary container. Then, a userdefined range of detector rows is vertically binned to produce a one-dimensional spectrum with numbered spectral channels. For an initial calibration, the wavelength λ i for the spectral channel i is calculated from the grating equation nλ = [sin(32°+ α + ∆α i ) -sin(32°-α)]/g , (4.
Unfortunately, such series of emission lines are rarely available while at the same time all being in the range of detection and of significant intensity. λ/nm E u /eV E l /eV g u g l A ul /s -1 The LIBS spectrum of a Si wafer acquired with 40 mJ pulse energy, on which the sensitivity calibration will be based, is shown in Figure  4. 19. In the detected range, the above requirements are only met by three Si II multiplets located at 126, 152 and 181 nm, shaded yellow in Figure  4. 19. The spectroscopic constants for these lines extracted from the NIST Atomic Spectra Database  [52]  are summarized in Table  4. 2. Involving the ground state or a level nearby the ground state, these lines are likely influenced by self-absorption  [41] , which may result in an inaccurate assessment of the line strength.
Measurement routine and data processing In this section, I will describe the typical measurement and data processing procedure. Except for the dark signal subtraction, which is part of the camera software provided with the spectrometer, all data processing was realized with Python scripts, which I developed myself, using the scientific computing and plotting packages numpy, matplotlib  [103]  and scipy  [104]. After cooling the CCD detector to the desired temperature at the beginning of every measurement session, a dark frame is recorded. For the dark frame, a CCD image is captured with the same detector settings as for the later measurements but without firing the laser. Due to the long exposure times of 8-10 s, cosmic rays are frequently detected. To avoid artefacts in the dark corrected spectra, the dark frame is recorded again, if a cosmic ray was observed.
It is, however, even stronger in the CaF 2 +CaSO 4 spectrum acquired with 25 mJ, opposing this explanation. Neither the NIST data base nor the atomic spectral line data base by Kurucz and Bell lists another transition of the involved elements around the measured position of 165. 7 nm. Another realistic explanation could be a carbon impurity, e. g. due to contamination with organic material during sample handling. The observed C I emission around 165. 7 nm, which is a group of six unresolved spectral lines, is very intense as we will see in the carbonate spectra in the following subsection. The signal level comparable to the neighbouring S I line in the CaF 2 +CaSO 4 spectrum is, however, surprising. Simulations with different initial temperatures, see section 2. 1. 3  for details, predict that the line strength of all six C I lines together is about five times higher than that of the S I line.
7 nm. The spectrum of Na 2 SO 4 also shows only the stronger S I lines at 166. 7 nm and around 180 nm, and the O I triplet at 130 nm, but no emission from Na. The NIST data base for Na lists only transitions from ionized species with a minimum upper energy level of 42 eV for Na II. Thus, emission from Na, which is known for its very intense yellow lines at 589 nm in LIBS spectra recorded in the visible range  [112] , is not expected in the VUV. The very similar K 2 SO 4 exhibits a richer spectrum with multiple K II emission lines but also additional S I, II and III lines, which have not been observed in the sample of pure sulfur. Compared to the NIR emission at 766 and 770 nm from K I, these K II lines are, however, rather weak. The appearance of additional emission lines from ionized sulfur could be explained by a higher electron temperature due to improved laser coupling.
The heterogeneity of the samples detected with Raman spectroscopy in section 3. 3 likely explains large parts of the observed signal fluctuations per sample. This is supported by a more stable signal level per sample for the series involving the finer-grained LMS. A quantitative analysis of the contribution of the sample heterogeneity to the observed signal fluctuations is not possible because the local concentrations at the locations of the LIBS measurements cannot be assessed with the present set-up. The presented calibration curves for non-normalized data further indicate significant matrix effects, by very different signal intensities for the different sample series. Only for the similar configurations of K 2 SO 4 and Na 2 SO 4 in LHS, the obtained calibration curves are close to each other.
Data extraction The average spectrum of the 12 measurements of LMS with NaCl at a concentration of 1. 9 at% Cl is shown in Figure  7. 1. Owing to the slit aperture used in these measurements, continuum emission from the plasma core is widely suppressed and the spectral lines have a typical line width of 0. 17 nm FWHM. In addition to the emission lines of the matrix elements identified in section 5 and also seen in the spectra of the LHS-and LMS-based samples of the S study in chapter 6, four Cl I emission lines are clearly evident at  133. 6  here to extract the Cl emission intensity is composed of four Lorentzian profiles. The wavelength separation between the lines is set to the values given in the NIST atomic spectra database  [52]. The intensity ratios between the four emission lines were found to be similar throughout all spectra in the series, except for those related to the lowest concentration sample, where it was difficult to fit the model to the data.
Limits of detection As for the sulfur study, the three different LODs defined in section 2. 2. 3 are determined. The lowest investigated concentration was 1. 0 at% Cl, and for this sample at least the Cl I line at  134. 7  nm could be identified in all spectra with an SNR > 10. Hence, an LOD 1 of 1. 0 at% Cl can be stated. The predictive estimates of reliably detectable concentrations, LOD 2 and LOD 3 , are less optimistic due to a large variance in the data. For the raw data and for total intensity normalization, they are in the order of 4-7 at%, while they are around  3. 5    Similar to the sulfur-related results in chapter 6, normalization with the total intensity of the spectrum has only little influence on the signal scatter per sample, but slightly increases the linearity of the calibration.
4. R 2 , RMSEC and LOD 3 are almost the same as for O I normalization, while LOD 2 is increased. This similarity between O I and Si II normalization suggests that the deviations observed in the non-normalized Cl data are rather an effect of the spectral region than of the LIBS process itself. An analysis of the temporal behaviour of the O I and the Si II signal over the measurement session reveals a monotonic decrease of the detected intensity for the LMS/NaCl sample series. This may likely influence the Cl I signal as well, but is less evident there due to the varying concentration. Potential reasons for this signal decrease are discussed in the following section.
For O 2 from ambient air to show noticeable absorption (≤95 % transmission) along the 80 cm long optical path, a pressure of ≥1 Pa is required  [93]. Water (H 2 O) vapour, which is likely another large constituent of the residual atmosphere and may as well be desorbed from the sample surface and the walls of the vacuum chamber, also has an in general high absorption coefficient in the region around 130 nm but is negligible below 10 Pa  [140]. The release of H 2 O adsorbed by the sample and the formation of O 2 from ablated sample material are also negligible due to the low ablated mass in the order of 100 ng per laser pulse  [21]. Moreover, the comparison of the LMS/NaCl and the LHS/K 2 SO 4 data in Figure  7. 6a suggests that the signal reduction over time is independent of the actual LIBS measurement itself, since the LHS/K 2 SO 4 data follows the same trend as the LMS/NaCl data despite a large time gap in the acquisition time where no LIBS measurements were made.
Although the results are subject to large uncertainties due to the simplifying approximations made for the simulation, the data suggest that the sensitivity of the set-up at 126 nm is at least two orders of magnitude lower than at 180 nm. Concerning the spectral line broadening, I found a large instrumental contribution in addition to Stark broadening due to the high electron density in the plasma centre during plasma initiation. From measurements with a fibre-coupled mercury lamp, I found that the positions of the spectral lines on the detector depend on the position of the light source. For an extended light source such as the LIBS plasma, the emission lines are detected on multiple detector positions at the same time and therefore appear broadened. The instrumental broadening can be significantly reduced by installing an aperture close to the sample, which effectively creates a more defined source comparable to the fibre-coupled mercury lamp.
Acknowledgements The iModBatt project has received funding from the  European Union 's  Horizon 2020 Programme for research and innovation  under Grant Agreement No. 770054. The authors want to express their appreciation to  Mr. H. J. Kapeller  and  Dr. I. de Meatza  for the scientific discussions and their comments on earlier versions of the manuscript, and to  Mrs. J. Winter  and  Mr. B. Ganev  for correction and polishing of the language.
de 2018). Durch diese Initiativen werden bereits heute öffentliche und private Gelder in Beweis-basierte, offene Architekturen investiert, die etwa im Bereich von Grafikkarten, Speichermedien oder eingebetteten Systemen zur Anwendung kommen sollen. Wie im Falle von Linux/Android in der Vergangenheit bereits beobachtbar, kann eine solche Entwicklung bewirken, dass sich der Einsatz derartiger Systeme von ihren ursprünglichen Einsatzfeldern (hochsichere Anwendungen, wie Luftfahrt, Verteidigung und IT-Sicherheitsmodule) auf andere Geräteklassen ausweitet.
This work has been produced within the framework of the Agence Nationale pour la Recherche (ANR) project TIME-US (Women's and men's remuneration and time budgets in the textile trades in France from the late 17 th to the early 20 th century) which holds the following reference ANR-16-CE26-0018-02. The project leading to this publication has received funding from the ANR. I would like to thank Cristina Borderías, Manuela Martini, Juanjo Romero, the editors and anonymous reviewers who provided extensive and helpful criticism and advice on this article. Earlier versions of this article were presented at the European Social Science History Conference in Belfast (2018) and the World Economic History Congress in Boston (2018).
For instance, it is now commonly accepted that specific bordering practices that used to be predominantly performed at the state territorial borders have diffused inwards and outwards, so that border controls and surveillance occur within or outside state territories: at international airports, within transportation nodes, around special economic zones and virtually everywhere when it comes to control the papers of supposed illegal migrants. With such a turn to ubiquitous border securitization and control, bordering practices have extended to include various networks of public, private and supranational organisations, including carriers and their transportation systems, as well as nonhuman 'actants' with their surveillance technologies, algorithms and databases. The dispersed, fluid and multifarious character of bordering practices appears as the historical connection between pre-existing assemblages meshed into larger wholes and that question key notions such as territorial sovereignty, citizenship or national security.
In that example, territorial discontinuities are identified through a synthetic measure of economic, social and demographic differences between couples of neighbouring cross-border regions. Based on the use of ESPON, harmonized regional database at the Nomenclature of Territorial Units for Statistics (NUTS) 2/3 level, this measure helps identify boundaries where there is an important break due to a territory being younger/older and more/less economically dynamic than its neighbour. In the absence of direct data about cross-border flows, the underlying assumption is that the discontinuities observed in terms of spatial structures can reveal potentials for interaction between crossborder regions. The typology based on these couples of cross-border regions highlights two main profiles of socio-economic differences that are subject to varying interpretations in terms of potential complementarities.
Its committee of experts on cross-border cooperation undertook a survey on the legal framework for cross border co-operation in member states and identified a number of obstacles and difficulties that local authorities have to overcome in order to engage in effective cross-border cooperation. This led to a recommendation of the Committee of Ministers in 2005 pleading its member states to reduce these obstacles. It also resulted in the creation of a database on cross-border cooperation (Matching Opportunities for Regions in Europe, MORE), the aim of which was to provide local and regional authorities with practical support for their cross-border cooperation. The Congress of Local and Regional Authorities have also launched activities to foster the role of cross-border cooperation for democratic stabilization.
Between the late 70's and early 80's, the region was hit harshly by the almost complete closure of the steel factories. The limited success of the national attempts for the conversion of the region pushed the authorities of the three countries in 1985 to agree on a common objective: the conversion of 3 dead-end roads into a single crossroad. This grew into a Joint Declaration for an EDP and simultaneously developed into a 10-year action program. This program was supported by the European Commission for 5 years and split into 3 national Community Interest Programs. This corresponds to one of the first ERDF operation modes under this format, prefiguring the Interreg Community Initiative which took place soon after. The program's leading measure, intended to grant exceptional financial support to business investment, derogating from the existing plans, to quickly attract new activities in the area and, therefore, offsetting the huge loss of employment in the steel industry.
According to our recent research, more than 300 European territorial cooperation structures are listed in academic and institutional databases. However, since there lacks an official or universally accepted definition of a Euroregion, some of the listed organisations could not be defined as such (like forums of exchanging experiences or intergovernmental panels). Euroregions can be defined as organisations that cover a crossborder territory and/or provide specific services for the population in a border area (i. e. , cross-border equipment). The organisation represents a shared desire to cooperate across borders, which is then reinforced by a public institution and ultimately results in joint activities. In the aforementioned study, 267 Euroregional structures have been identified; however, no prior listing or web resource was effectively able to distinguish the "active" from the "inactive" structures (which generally become inactive due to a lack of political and/or financial support).
Since 2016, these interventions allow for search and rescue operations, particularly in the Mediterranean Sea, the reinforcement of control teams and the reception of migrants in order to register them in the database known as the Schengen Information System (SIS), with the digitization of fingerprints corresponding to the European standards of the biometric passport. Given the influx of illegal migrants, Frontex's support has become essential for those states that are obliged to manage considerable flows of migrants. The computer system shared by the member states records all persons entering and leaving the Schengen Area. At the same time, visa applicants in the EU member states' consulates are systematically registered, regardless of whether the visa is accepted or refused. This makes it possible to follow up on individuals, particularly those whose visa application has been rejected by a consulate and who would attempt an illegal crossing.
The Platform also offers a good practice database, networking opportunities, and thematic advice both to those involved in the projects and those interested in the program's policy topics. The Platform also helps interested regions organize a peer review of specific policy challenges. Interreg Europe is one of the four C-strand programs of the European Territorial Cooperation (ETC) goal, known as Interreg. It is one of the two goals of Cohesion Policy co-financed by the European Regional Development Fund (ERDF). (north, south, east and west). They gave public authorities the opportunity to improve the effectiveness of their regional development and cohesion policies. Since 2007, the four programs have merged and public authorities from the EU, Norway, and Switzerland have been exchanging experience, sharing best practices, and building their capacities within one interregional program based in Lille, France.