dataesr/scientific-paragraphs-categorization huggingface dataset:
The orientation of the Glan polarizer is adjusted to ensure that the intensity of the two components of the DFDP beam share equal intensities. The direction of the HWP is controlled by a rotating mount (URS50 + SMC100 controller, NEWPORT), allowing remote tuning of the optical power from the LabView (NATIONAL INSTRUMENTS) program used to control the whole setup. In order to convey the DFDP beam into the microscope scanning head, we use a single mode polarizationmaintaining optical fiber (P3-488PM-FC-2, THORLABS) whose eigenaxes have been aligned with the polarization directions of the DFDP beam. A mechanical shutter controlled by the LabView software is placed ahead of the fiber injection and avoids illumination of the sample before an acquisition is launched, so as to reduce fluorescence bleaching.
ACKNOWLEDGMENTS The authors would like to acknowledge  N. Ortega-Quijano ,  F. Parnet  for their early contribution in assessing the CI-OB modality, and to thank  L. Frein ,  S. Bouhier ,  C. Hamel , and  A. Carré  for their technical help with the electronical and mechanical design of the experiments. The authors thank  C. Chapuis  for her technical assistance in sample preparation and  X. Pinson  for his technical help with the confocal microscope setup. The authors thank the MRic facility from the  BIOSIT joint unit of services , the  University of Rennes 1  and the  CNRS "Mission pour les Initiatives Transverses et Interdisciplinaires" (MITI)  for funding this project. R. D. was supported by the  Université Bretagne Loire , the  Région Bretagne  and the  Institut Universitaire de France.
R. S. was supported by the  PRESTIGE program  coordinated by  Campus France  [ PRESTIGE-2017-2-0042 ], the  Université Bretagne Loire  and the  Fondation ARC  pour la recherche sur le cancer [PDF20181208405]. We thank the  GDR Imabio  for funding P. R. 's and E. G. 's internships. The MRic facility is member of the national infrastructure  France-BioImaging  supported by the  French National Research Agency  ( ANR-10-INSB-04 ).
Shorter time of flights and long-haul routes are the two crucial mission requirements that have led to a new concept of aircraft for high-speed long-haul routes that has been named STRATOFLY MR3. STRATOFLY MR3 is the reference vehicle of the H2020 STRATOFLY project, a highly multidisciplinary project, funded by European Commission within the framework of the Horizon 2020 Program. STRATOFLY is the natural follow-on of a series of European Projects (i. e. ATLLAS I/ II  [2] , LAPCAT I/II  [3] , HIKARI  [4] , HEXAFLY  [5] , HEX-AFLY Int. [6] ) devoted to study the feasibility of the highspeed civil transportation at stratospheric altitudes, with the goal to reduce the duration of antipodal flights of one order of magnitude with respect to current air transport. Main project objectives are to refine the design and the concept of operations of STRATOFLY MR3 vehicle throughout all mission phases, including the crucial subsonic and transonic regimes, reaching the ambitious goal of Technology Readiness Level (TRL) = 6 by 2035 for the concept, developing crucial technologies which may represent a step forward for future reusable space transportation systems.
Multi-bubble Multi-functional Structures The use of dual or multiple bubble structure is exploited for an overall stiff architecture at a lower mass fraction, to achieve lightweight structures with multi-functional roles, such as passenger cabin, multiple split tanks with anti-slosh baffles, engine bays, intake flowpaths, etc. , to eventually integrate all subsystems in an harmonious way. This concept, already explored in the 70 s, can nowadays be studied more into the details thanks to available design and analysis tools. The multi-bubble concept is applied to almost every zone of the STRATOFLY MR3, including the passengers' cabin and the front, lateral and rear cryogenic fuel tanks (see Fig. 5 ). The structure model was generated using the ABAQUS software and is composed of a finite element mesh of about 1,600,000 shell elements.
A one-dimensional propulsion model for MR3 vehicle's propulsion plant (see Fig. 7 ) was built in EcoSimPro  [7] , a transient thermodynamic propulsion simulation platform, to estimate combined ATR and DMR engines performance along the subsonic cruise and supersonic acceleration parts of flight trajectory. The EcoSimPro software is a multi-disciplinary simulation platform, with components in the continuous system modeled using various mathematical relations describing their physical behavior  [8]. The software also enables implementation of several libraries such as European Space Propulsion System Simulation (ESPSS) to model specific systems, such as rocket propulsion components  [7]. An optimization study is being performed at VKI by coupling EcoSimPro and Computer Aided Design and Optimization tool (CADO), see Fig.
8 , to obtain optimal boundary and operational conditions for the best performance values, such as specific thrust and impulse at minimum fuel consumption. CADO is an in-house code optimizer developed at VKI, with the Darwinian Theory based optimization routine  [9] , which includes evolution algorithm consisting of selection, mutation and crossover. By evaluating the engine performance with this algorithm, new design variables are determined, and simulations are repeated in the EcoSimPro. Design variables are determined as air-fuel mixture ratio, combustion chamber pressure and chamber throat area, since most conditions of the engine components are dictated according to the preburner properties. The optimization study and 1D numerical simulations by EcoSimPro have been performed for nine subsonic and supersonic Mach numbers, i.
More Efficient and Greener Propulsion Systems The DMR combustor design will be optimized to reduce NOx emissions, thanks to both engineering and CFD tools, and exploiting dedicated experiments to be performed at DLR-HEG facility. CIRA carried out a Small Scale Flight Experiment numerical simulation selected for validation of CFD results with measurements (TC#1478 at Mach = 7. 36, AoA = -2°, ER≈1. 04, from LAPCAT-II project  [3] ), and to provide NOx, H2O at nozzle exhaust for setting up (and locate) a NOx measurement laser-based technology (TDLAS) to be used during the next HEG Test Campaign. ANSYS-Fluent ® code was used as CFD solver, whereas chemical kinetics modeling (including NOx production mechanism by Zel'dovič) was inherited from LAPCAT-II CFD activities on. MR2. 4 full-scale DMR combustor  [3].
It is worth remembering that the propulsive flowpath is identical between LAPCAT II MR2. 4 and STRATOFLY MR3 vehicles, so the Small-Scale model used for scramjet engine experiment is still used. CFD results on a 6. 5-million elements unstructured grid are shown in Fig. 10. From a detailed analysis of the predicted flow field, two different solutions (with corresponding Y-lines of sight with NO and H2O concentrations) have been elaborated and proposed to DLR-HEG for the TDLAS measurement unit NO-probe location, see Fig. For what concerns the engineering modeling of the MR3 vehicle's DMR engine (by means of EcoSimPro), CIRA has provided VKI with the flow conditions at the intake and isolator calculated by the SPREAD code  [10] , in the Mach number range from 4. 5 to 8, see the sketch of Fig.
Three values of the intake leading edge radii have been analyzed (6. 25, 11. 3 and 22. 5 mm; same value for lower lip, lateral  edges and crotch) by means of ANSYS-Fluent ® code on a reduced geometry domain including in addition to the intake the combustor part too. Unstructured grids have been generated (20-30 millioncells), constituted of tetrahedral cells inside the bulk volume of the domain and of prisms near the solid surfaces to have a better boundary layer resolution. Oblique shock waves start from intake geometry discontinuity and are all captured inside the crotch, while the leading edge shock goes just a little bit outside. The interaction of local crotch bow shock and the oblique shock wave happens internally to the combustor inlet causing an overload with respect to the leading edge zone.
Aerodynamic Database The aerodynamic database (AEDB) developed during the LAPCAT-II project  [3] , based on engineering methods, cross-checked by detailed CFD nose-to-tail simulations and used for the calculation of the MR2. 4 vehicle reference trajectory, is being reviewed, assessed and completed, especially for what concerns: (1) the addition of the effects of (updated) control surface system in the low-supersonic to hypersonic regime (in charge of CIRA using their own surface impact method SIM, part of SPREAD code), and (2) the refinement of the subsonic to low-supersonic regime including again the effects of Flight Control System (in charge of Politecnico di Torino, using engineering methods). It is worth highlighting that this new version of the AEDB refers to the MR3 vehicle external surfaces only, including the flight control system (elevators, ailerons, vertical tail), without accounting for the effects of the propulsive flowpath nor for the viscous effects.
The analysis of all mission phases is a crucial issue for the STRATOFLY Project not only from the point of view of the operations but of course also from the point of view of the technical performance of each discipline. For the first time in fact with respect to the previous high-speed projects, in addition to the Mach 8 cruise condition, also the other flight phases will be tackled and a deeper investigation of the behavior of the aircraft aerodynamics and the propulsive system (including emission) in subsonic, transonic and low-supersonic phases will be analyzed through low and high fidelity simulations. Moreover, test campaigns for noise mitigation, supersonic combustion with and without Plasma Assisted Combustion and emissions measurement at hypersonic speed will be performed and the data package will be crucial to validate new simulation models.
The electromagnetic calorimeter In the data set analysed in this paper, the calorimeter was a compact array of 3 × 3 BGO tapered crystals, each with a front (exit) surface of ∼ 2. 1 × 2. 1(2. 8 × 2. 8) cm 2 and 23 cm length. They were read out by Photonis XP1912 PMTs [10] biased at 850 V. The crystals were obtained by machining bigger spare blocks of the L3 endcap calorimeter [11] and were arranged as shown in fig. 2 ; such a configuration minimizes the dead regions in the detector active volume to the 1 mm irreducible gaps introduced by the painting that shields and protects each block.
Acknowledgments We warmly thank the COMPASS collaboration for their kind willingness to let us run parasitically behind their detector, and in particular  Vincent Andrieux  for his active help. We also thank the  LNF-BTF  and the  PADME collaboration  for giving us the BGO calorimeter, and the  LNF-SPCM , where  Tommaso Napolitano  and  Fabrizio Angeloni  provided the mechanical support structure.
The remaining individuals in the population are susceptible (S) and could contract the virus. The spread of disease in each country evolves according to the following transitions and is governed by the indicated parameters: S α -→ I, I γ - → A, A β - → R, A δ - → D, I β - → R u. Here α is the transmission rate, γ is the identification rate, β is the recovery rate, and δ is the death rate. Using this country-specific model, we then built a global network model of countries utilizing travel data as follows. In the meta-population network model, for a given country i, the status of its population is updated in two steps. First, the state of the epidemic evolves based on the internal population of country i. The transition from day t -1 to t is characterized by the shift from X i (t -1) based on the local, country-specific epidemiological model, where X i (t -1) is a vector of six compartments of the status of country i at day t -1.
In this paper, we used a variant method called replenishment ABC (RABC)  (23). The main challenge of using ABC to calibrate our network meta-population model was the large number of parameters that needed to be estimated. Instead of using ABC to estimate all the parameters for all countries simultaneously, which is computationally expensive and may result in unstable parameter estimates, we used a marginal estimation strategy to estimate each country's epidemiological parameters separately, while still taking the travel data into account. For a given country i, we first reconstructed all six states describing the pandemic situation in all other countries j = i based on their epidemiological data. Based on the travel data, we then estimated the number of cases imported to country i from other countries.
Policy effectiveness was evaluated based on two factors: the percentage of inbound travelers and the epidemiological situation in the receiving country. We evaluated inbound travel in two ways. The percentage of inbound travel capacity is the number of inbound travelers allowed under the policy divided by the number of inbound travelers under normal circumstances. The expected percentage of inbound travel is an adjusted version of the percentage of inbound travel capacity; if the 14-day quarantine policy is applied to people departing a country, we assume that only 5% of travelers from this country are willing to travel. South Korea requires a 14-day quarantine for all arrivals, and data provided by the Korea Tourism Organization supports this 5% assumption (25). After this adjustment, the percentage of expected inbound travelers is obtained by dividing the number of expected inbound travelers by the number of inbound travelers under normal circumstances, which gives us insight into the effect of the 14-day quarantine requirement.
This database tracks the number of flights from one region to another over time, which can be used to calculate the rate of flight reduction and to estimate flight data for other months. We considered the starting day for each country to be the first day the country exceeded 500 total confirmed cases, because the estimation for the number of undetected infectious people is unstable during each country's early pandemic period. For similar reasons, we only analyzed the 92 countries whose total number of confirmed infected cases exceeded 500 by April 15, 2020. The remaining countries were combined into a single fictional country labeled "Other. " All people traveling from this group of countries were assumed to be susceptible. To demonstrate the ability of our model to capture the real evolution of the pandemic, we fit it to real data as follows.
Overall, Figure  1  shows that our model effectively captures the real data (red), as the estimated line (blue) is very close to the observed line and is contained within the confidence interval. To understand how different travel restriction policies affect the pandemic both globally and in each country, we used the estimated parameters for all countries before May 31 together with the travel data to simulate the course of the pandemic during the first 14 days of June 2020 under four different travel regulation scenarios. In the first scenario, we used 2020 travel data during the COVID-19 pandemic. In the second scenario, where all countries are fully open, we used 2019 travel data from the pre-pandemic period. In the third scenario, all countries fully closed their borders. Finally, we supposed all countries use the simplified average control policy.
Based on the parameters and the stochastic model, we generate a data set Data (i) corresponding to θ (i). If the generated data set Data (i) satisfies certain conditions making it sufficiently real-world like, such as having the number of confirmed accumulated deaths greater than 1% and lower than 30% of total confirmed cases and having the number of accumulated recovered cases at least twice the number of accumulated deaths, then we keep θ (i) as a true parameter value to be estimates and treat the generated data {A (i) t , R (i) t , D (i) t } as real observed data. We repeat the process until we obtain 200 underlying true parameter values θ (i)   and the corresponding 200 datasets {A (i) t , R (i) t , D (i) t }. For simplicity, we fix the initial condition of the six compartments in the model as X 1 (0) = [S 1 (0), I 1 (0), A 1 (0), R 1 (0), D 1 (0), R u 1 (0)] = (9999972, 15, 13, 0, 0, 0) and set the simulation time period T = 84 days for all i.
Accuracy Estimation Policy effectiveness is evaluated based on two factors: the percentage of people allowed to travel and the pandemic situation in the country once the policy is adopted. 1. The percentage of people allowed to enter the country under each policy is denoted Tc. This number is calculated using the number of people allowed to travel inbound to the country divided by the total number of people willing to enter the country. 2. The percentage of people that will travel due to each policy is denoted Te. This number is an adjusted version Tc. If a 14-day quarantine is applied to a country, we assume that only 5% of the normal number of travelers from this country are willing to travel under this policy. The choice of 5% is based on the data provided by Korea Tourism Organization.
Data and materials availability: Proprietary flight data for January and February of 2020 are commercially available from the Official Airline Guide (OAG). The flight tracking data is publicly available from the OpenSky Network database https://opensky-network. org. The COVID-19 data is publicly available from the Johns Hopkins University coronavirus data repository https://github. com/CSSEGISandData/COVID-19. Reformatted data and R code used in this study are publicly available at https://github. com/onnela-lab/covid-travel.
Database sources and keys words The literature search was conducted on 10 July 2020 to collect exhaustively available research and reviews dealing with environmental monitoring plans and strategies used by food processing industries. Legislation and guidelines and additional articles were identified from 4 May 2020 to April 2021. The search was performed on different databases: Scopus, Web of Science and Pubmed. For each database, the following search queries were used: The grey literature was also searched in governmental and industrial websites, Google and Google scholar search. Citations retrieved were imported and filtered with Endnote software (version X8. 2).
Literature research characteristics A total of 290 references were identified from 3 databases and other sources. 205 records were listed after de-duplicates removal and relevant studies were selected considering exclusion and inclusion criteria, relevance and text availability (Fig. 1 ). All the records selected in the study are listed in the references (69 papers plus 2 articles about scoping review  (Arksey & O'Malley, 2005)  and PRISMA  (Moher et al. , 2009)  methods). The majority of publications considered in this review were recent (Fig. 2 ), with 40 publications from 2015 to 2021. Most of the publications came from research papers (38%), reviews (22%) and guidelines (19%), followed by book or book chapters (10%), legal rule or regulation (4%), reports (4%), web pages (1%) and symposiums (1%).
OxCal version 4. 4  34  was used for calibrating radiocarbon dates with the IntCal20 curve  35  and for creating agedepth models (Supplementary Information Fig. 2 ). SedaDNA and faecal biomarkers were extracted from a parallel core taken within 2 m of dated core adjacent to the northern crannog. Both cores analysed for sedXRF and were correlated using Ti and Fe element data. Clear peaks in Ti and Fe available in both cores were used as tie points which were then used in software package QAnalySeries  36  to correlate these cores. This information was then used to transpose the age model of the dated core onto the correlated depths of the core used for sedaDNA/ biomarkers. For geochemistry core XRF scanning was undertaken using an ITRAX XRF scanner  37  directly on the split cores scanned at 2 mm resolution using 30 kV, 30 mA settings and a 15 s count time at the British Ocean Sediment Core Research Facility (BOSCORF) at the National Oceanography Centre, Southampton (NOCS).
In total 39 elements were identified including lithogenic indicators (Si, Al, K, Ti, Zr, Rb) and anthropogenic and heavy metal indicators (P, Ca, Cr, Zn, Ba, Sr, Pb). The resultant elemental intensities, measured in counts per second (cps), were vetted to remove unreliable results which occurred at the boundaries of samples and in particularly coarse sediment horizons. Following data control analysis, the remaining elemental relationships were plotted as ratios to Ti as the conservative detrital element. Automated SEM-EDS  38  analysis was carried out using QEMSCAN technology. QEMSCAN is an automated mineralogical analysis system based on a scanning electron microscope that provides rapid determination and quantification of the mineralogy, chemical composition, grain size and shape of a variety of sample types.
Equal volumes of PCR products were mixed (15 μL of each), and 10 aliquots of 100 μL of the resulting mix were then purified using Min-Elute Purification kit (Qiagen GmbH, Hilden, Germany). Purified products were then pooled together before sequencing; 2 × 100 + 7 paired-end sequencing was performed on an Illumina HiSeq 2500 platform using TruSeq SBS Kit v3 (FASTERIS SA, Switzerland). Sequence data were analysed using the OBITools software package  41. First, direct and corresponding reverse reads were assembled using illuminepairedend, and sequences having a low alignment quality score (threshold set at 40) were filtered out. The retained reads were assigned to relevant samples using ngsfilter, keeping sequences matching 100% with tags and allowing a maximum of three mismatches with primers.
Strictly identical sequences were then merged together (dereplication) using obiuniq, keeping information on their distribution among samples. All sequences with only a single copy and/or shorter than 12 bp were filtered out using obigrep. Obiclean was then used to identify amplification and sequencing errors, using a threshold ratio of 5% for reclassifying 'internal' sequences to their relative 'head' sequence  42. Finally, using the sequences were compared with a the global EMBL database (release r117 from October 2013) by running ecopcr. Sequences assigned to non-native taxa were blasted to check for potential wrong assignments (http:// www. ncbi. nlm. nih. gov/ blast/). Extreme caution must be taken before accepting a taxonomic assignment in an environmental sample  19, 43, 44. To reduce risk of misidentifications, only sequences matching 98% to reference library entries and occurring as at least 10 reads per PCR repeat for plants and 5 reads per PCR repeat for mammals were kept.
Pollen and spores, diatoms, chironomids. Standard extraction methods were used for pollen and spores, involving acetolysis and hydrofluoric acid digestion, the addition of an exotic marker (Lycopodium) and mounting in Si oil. Standard keys were used for identification along with the reference collections at the University of Southampton and the Pollen Laboratory and the University of Plymouth. The raw data is in Supplementary Information (Excel File Raw Pollen Data Supplementary Dataset 2). Diatom samples were prepared by digestion with hydrogen peroxide (H 2 O 2 )  47  , after which they were mounted on microscope slides using Naphrax. At least 400 diatom valves were counted at × 1000 magnification using a Nikon Eclipse 80i microscope. Images of selected frustules were captured using the Nikon Digital Sight DS-L2 and Nikon DS-Fi1 microscope attachments.
Acknowledgements We thank  Peter Heintzman  and  Youri Lammers  for laboratory and bioinformatics assistance and  Ludovic Gielly  for laboratory work at Grenoble. The core through the southern crannog (FER 211:064) was granted by the  Northern Ireland Environment and Heritage Service  under Licence Number  AE/16/18. This research was funded by the  Arts and Humanities Research Council of the UK  (Grant no. AH/M005259/1 ) with additional logistic support from the  Department of Communities, Northern Ireland  and the  landowner Lord Belmore.