dataesr/scientific-paragraphs-categorization huggingface dataset:
Repeatability On April 17th, 2020 the AQG#B01 was transported to the facilities of the laboratory Géosciences Montpellier on University campus and operated in the basement of the building. The distance between the Larzac observatory and Montpellier is about 100 km and there is 640 m difference in altitude. The transport to Montpellier was the second displacement of the AQG#B01 after its first delivery to the Larzac observatory in November 2019. This implies the turn-off, deconnection, displacement and cold restart of the instrument. The data were compared to FG5#228 measurements at both sites. Small-scale repeatability was assessed using repeated gravity measurements on the same position in the gravity lab in the basement of Géosciences Montpellier. Vertical gravity gradients were additionally estimated with a relative gravimeter (Scintrex CG6).
For the description of the 2p2h-MEC (meson exchange current) contributions the model makes use of the fully relativistic calculations from  [28]  which allows for a proper separation of neutron-proton and proton-proton pairs in the final state via the analysis of the direct-exchange interference terms  [29]. The combined SuSAv2-MEC model, covering the 1p1h and 2p2h channels, has been shown to be capable of reproducing the nuclear dynamics and superscaling properties observed in (e, e ) reactions  [20, 21, 30] , which serves as a stringent test for nuclear models, whilst also providing an accurate description of existing neutrino data  [18, 19, [30] [31] [32]. To date, SuSAv2-MEC is the only fully relativistic model that can be extended without approximations to the full-energy range of interest for present and future neutrino experiments.
While such an approach relies on substantial approximations, which will be discussed in Sec. II, it is still the only option available today for the majority of models and, more importantly, is the technique used in neutrino oscillation measurements. Therefore, the implementation of more sophisticated neutrino interaction models, such as SuSAv2, even in such a very approximated approach, is important in order to improve the predictions for the oscillation measurements. The comparison to cross-section measurements is then crucial in order to estimate the systematic uncertainties induced by the usage of such approximated approaches in measurements of neutrino oscillations. In this manuscript we present, in Sec. II, the implementation of the SuSAv2 models in the GENIE event generator, alongside a discussion of all the approximations involved.
The comparison of the SuSAv2 2p2h implementation with other 2p2h implementations is then shown in Sec. III. In Sec. IV, the RMF, SuSAv2 and SuSAv2-GENIE models are compared for the 1p1h channel at T2K kinematics together with a dedicated analysis of T2K CC0π measurements with a restriction on the outgoing nucleon momentum, allowing a first test of some of the key approximations built into neutrino interaction event generators. The SuSAv2-MEC implementation is also tested against other recent T2K semi-inclusive measurements (CC0π with and without protons) in Sec. V where an analysis of the single-transverse variables is also shown. In the Appendices A-C, we test the SuSAv2-MEC implementation for T2K CC0π inclusive data and compare the SuSAv2-MEC implementation with the Valencia one in both inclusive and semi-inclusive reactions.
Further work will focus on more stringent tests through the implementation of the RMF spectral function into event generators and by exploring the predictions in a wider region of hadronic kinematic phase-space (ideally using a fully semi-inclusive version of RMF). The T2K semi-inclusive CC0π measurement of interactions with protons less than 500 MeV  [59]  provides an opportunity to compare the RMF 'semi-semi-inclusive' model predictions to data, which is shown in Fig. 5  alongside the SuSA-GENIE predictions using the factorisation approach. In order to make this comparison the RMF predictions are added to the SuSAv2 2p2h and pionabsorption predictions from GENIE (that is to say, the SuSAv2 1p1h is replaced by an RMF prediction). In this manuscript latter always stems from GENIE's implementation of the Berger-Sehgal pion-production model  [66] , from which the predictions are fed through GENIE's 'hN' FSI model to account for pion absorption.
0 1 2 3 E ν (GeV) 0 1 2 3 σ ν (10 -39 cm 2 ) Empirical (GENIE, ν) Empirical (GENIE, ν) SuSAv2 (GENIE, ν) SuSAv2 (GENIE, ν) Valencia (GENIE, ν) Valencia (GENIE, ν) FIG. 1. Total 2p2h cross section for muon-neutrino and anti-neutrino interactions on Carbon for the "Empirical" model available in GENIE, the SuSAv2 2p2h model discussed in this manuscript and the Valencia model as implemented in GENIE  [5, 44]. Comparison of muon-neutrino single differential 1p1h cross sections on Carbon at T2K kinematics as a function of the muon kinematics as both an inclusive (top panels) and a 'semi-semi-inclusive' cross section (bottom panels), the latter meaning that a restriction that there are no protons with momenta above 500 MeV is applied. In the inclusive case the RMF, SuSAv2 model and SuSAv2 GENIE implementation are compared.
ACKNOWLEDGMENTS We thank the  GENIE collaboration  for their helpful input regarding the model implementation. In particular we thank  S. Gardiner  for facilitating the simple update of our implementation into GENIEv3. We also acknowledge  J. E. Amaro  and  I. Ruiz-Simo  from the  University of Granada  for providing us detailed information and results about the 2p2h hadron tensors employed in this implementation. We also are grateful to many members of the T2K collaboration for interesting discussions pertinent to this work. This work was partially supported by the  Spanish Ministerio de Economia y Competitividad and ERDF (European Regional Development Fund)  under contracts  FIS2017-88410-P , and by the  Junta de Andalucia  (grant No. FQM160 ). GDM acknowledges support from a  Junta de Andalucia fellowship  ( FQM7632 , Proyectos de Excelencia 2011), a  P2IO-CNRS grant , and by the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie  grant agreement No.
For illustration purposes, we consider a 1 =({Duration((a 1 , 1, 2)}, r 1 , ondemand) in the "supervision process" BP. a 1 is transformed into two timed automata: T A ad is shown in Figure  2a  and T A rd is shown in Figure  2b. a 1 can start consuming r 1 only if the clock t is less than 2 (i. e. , defined as an invariant) and will execute successfully only if its temporal duration is met (i. e. , defined as a guard). We implemented our transformation rules using ATLAS Transformation Language (ATL) which is a model-to-model transformation language  [22]. a1 Ready a1 W orking t ≤ 2 U a1 F inish t = 0 start! t ≥ 1 && t ≤ 2 done? Listing 1 is an excerpt of an ATL rule for transforming a resource allocation with spot blocks into a network of timed automata. Figure  6c     • Spot instance: When a is defined as ({Duration(a, M inD a , M axD a )}, r, spot instance), a is transformed into two timed automata T A aa and T A ra.
Various research works address the issue of formal specification and verification of temporal constraints in BP models. For instance, Cheikhrouhou et al. in  [2, 3, 13]  proposed rules to transform BPs modeled in BPMN language and enriched with relative and absolute temporal constraints into a formal language (timed automata). Then, using UPPAAL, they verified the satisfaction of some CTL properties in order to verify the temporal consistency of BPs. Furthermore, Huai et al. [40]  verified BPMN models using Timed Petri Nets by analyzing process structure such as deadlock and testing if there is a conflict between model temporal constraints. However, neither (cloud) resource representation nor pricing strategies are studied. We mention that several works deal with formal verification of resource allocation and activities temporal constraints.
doability started with model checking to verify some Computation Tree Logic (CTL) properties that support matching temporal constraints of both activities and cloud resources. Then, we analyzed the impact of verification on the optimization approach in terms of objective function and response time. Finally, comparing our results to those of CloudSim simulator took place. Due to lack 525 of real datasets that could be used for optimizing the BPs deployment cost, we randomly generated a simulated dataset defined from the ranges presented in.
520 doability started with model checking to verify some Computation Tree Logic (CTL) properties that support matching temporal constraints of both activities and cloud resources. Then, we analyzed the impact of verification on the optimization approach in terms of objective function and response time. Finally, comparing our results to those of CloudSim simulator took place. Due to lack 525 of real datasets that could be used for optimizing the BPs deployment cost, we randomly generated a simulated dataset defined from the ranges presented in.
The mathematical formalism, which is based on the projection of the integral transport equation, allows for an explicit linear system solving the spatial moments of the angular flux simultaneously for all regions and surfaces of the HCC. The discretized transport equation consists of two linear systems per HCC formally similar to those used for homogeneous cells. The 3D HCC implementation is an upgrade of the XYZ solver, namely IDT (Integro Differential Transport)  [4] , of in the code APOLLO3 R. IDT has been already benchmarked with realistic 3D full-core simulations, the results of which have been published in reference  [13]. In this work, we are more concerned about the mathematical framework of the HCC coefficients.
Linear Short Characteristics and Heterogeneous Cartesian Cells (HCC) The IDT solver is a discrete-ordinates neutral-particle transport code based on XYZ geometry. In the past years, IDT has been extended to Heterogeneous Cartesian Cells (HCC) to model fuel pins of nuclear reactor in their exact geometries without need of spatial homogenization,  [6]. The HCC model has proven accurate results while saving the number of spatial meshes and, thus, computational time and memory. Furthermore, because the 3D extension is based on locally extruded geometry, it allows for the modeling of non extruded 3D geometries, as the assembly top/bottom nozzles, plugs and grids. Because of the discrete ordinates, the angular integrals are approximated by quadrature formula composed of N d directions, 1 4π 4π dΩ f (Ω) d=1,.
Acknowledgements One of the author, E. M. , would like to express sincere gratitude to  R. Sanchez , for its never-ending support, and  Y. S. Ban  and  Professor H. G. Joo  from the  Department of Nuclear Engineering of the Seoul National University , for the fruitful and precious collaboration that gives a deep help to the V&V of the IDT solver. Also, authors would like to thank  B. Martin  and  J. -M. Do , for the DDM implementation undertaken during the internship in SERMA. Finally, the authors thank  Électricité de France (EDF)  for partial financial support.
As shown in Fig. 1 , the exposure modeling process is performed in 4 steps. The first step is the generation of an emissions inventory based on the activities of individuals living in a territory, managed by the OLYMPUS tool. The second step is to diagnose air quality using the CHIMERE 3D model, which provides hourly concentration fields of pollutants at the kilometric scale. In the third phase, a statistical downscaling module allows refining the air quality diagnosis by creating sub grid concentration gradients within the urban space. Finally, the intersection of citizen urban trips and fine-scale air quality maps makes it possible to consider the dynamic exposure of all individuals in the population.
CHIMERE uses the reduced chemical mechanism MELCHIOR2 that was designed for the regional production of oxidants on a regional to continental area and takes into account 44 species (including 19 organic compounds) and 120 gaseous reactions. The aerosol module represents primary particles, biogenic and anthropogenic secondary organic aerosol species, sea salts, dust and water, all distributed into 9 size bins ranging from 40 nm to 10µm. In this work, CHIMERE was first implemented at the continental (resolution 0. 68° x 0. 46°) and national (resolution 0. 205° x 0. 135°, about 15 x 15km²) scales to provide chemical boundary conditions for the Île-de-France target study area (see domains in Fig. 2 ). Such a nesting configuration makes it possible to better represent the major European urbanized areas, as well as the emissions from the North Sea maritime corridor, which have an impact on the composition of the background atmosphere of the French territory during the period of study -and especially during the anticyclonic situation of January 2009.
As for meteorological inputs, we used simulations of the WRF model (https://www. mmm. ucar. edu/weather-research-and-forecastingmodel) performed on 3 nested grids that are broader than the CHIMERE simulation domains in order to constrain the pollutant fluxes at the limits of the domains. The European domain is forced by NCEP meteorological fields (http://www. ncep. noaa. gov), and by analyzes of model outputs at a resolution of 1° every 6 hours. The WRF urban canopy module (UCM) was not activated due to the lack of descriptive data on urban coverage in the simulated areas. To compensate, we activated on all simulations the option of urban parametrization of CHIMERE which allows to correct the turbulence, and consequently the urban boundary layer height, over an anthropized area. This correction reduces wind speed at ground level by 20% and increases the sensitive heat fluxes at the surface.
This is why it is critical, in the long term, to implement a module for indoor atmosphere allocation, including exchanges with surrounding outside air. Recent works make it possible to envisage such a functionality (ANSES, 2019). In the end, the histogram shown in red in Fig. 10  represents the distribution of the exposure obtained using this innovative OLYMPUS-CHIMERE + downscaling and mobility approach. The data shown in this last figure suggest that pollutant exposure in metropolitan areas may be much more heterogeneous than previously thought. In our case, indoor environments have not been specifically simulated, and mobility is reduced to commuting. Despite the low temporal representativeness of these events, the road micro-environments are likely to present strong break-up concentrations with the urban or peri-urban background atmosphere simulated at the CTM scale.
Conclusions In this work, we have implemented a new platform for modeling air quality and the exposure of individuals, on the Greater Paris area, for the year 2009. The objective of this work was to evaluate the impact of a finer representation of air composition in dense urban areas -and especially near the traffic routes, but also to assess the potential contribution of the mobility of individuals, in the calculation of their exposure. The simulation works were carried out with the OLYMPUS tool, for the generation of an activity database centered on the individual and for the calculation of the associated atmospheric pollutant emissions. The emission dataset produced by OLYMPUS on this area has been validated in a previous study. The results of the air quality simulation conducted by CHIMERE, using the OLYMPUS outputs, showed a very good understanding of the pollution gradients observed at the scale of the metropolis.
Lastly, we addressed the question of exposure evaluation, by showing that standard approaches highly underestimate the values calculated using refined air quality data and daily trip of individuals in the city. For this purpose, we estimated the exposure of a given individual in Greater Paris, first using the CHIMERE concentration data at its place of residence, and then using a dynamic approach integrating the agent mobility and the statistically refined CHIMERE concentrations along its daily trips. This individual was randomly selected from the synthetic population created by OLYMPUS. Our results show that this mobility-based approach produces a much more heterogeneous set of exposure values than in the classical approach, with particularly high values during the trips. These high values do not significantly alter the average daily exposure (39 µg/m 3 versus 28µg/m 3 on the selected day).
Acknowledgements The work presented here received support from the  French department Val-de-Marne , the  French Ecological transition agency (ADEME ) the  PRIMEQUAL program  ( POLL-EPXO / Convention 1862C0012 ), the  French National Agency for Research  ( VITE! / ANR-14-CE22-0013 ) and the  Île-de-France region  ( DIM R2DS  and DIM QI²). It was initiated in the frame of the LABEX Urban Futures and performed using HPC resources from  GENCI-CCRT  (grant no. 2017-t2015017232 ). We specially acknowledge AIRPARIF for providing data.
Distributed Online Social Networks (DOSNs) have been proposed to shift the control over user data from a unique entity, the online social network provider, to the users of the DOSN themselves. In this paper we focus on the problem of preserving the privacy of the contents shared to large groups of users. In general, content privacy is enforced by encrypting the content, having only authorized parties being able to decrypt it. When efficiency has to be taken into account, new solutions have to be devised that: i) minimize the re-encryption of the contents published in a group when the composition of the group changes; and, ii) enable a fast distribution of the cryptographic keys to all the members (n) of a group, each time a set of users is removed from or added to the group by the group owner.
I. INTRODUCTION A Decentralized Online Social Network (DOSN)  [1]  is an Online Social Network (OSN) implemented in a distributed and decentralized way. Instead of being based on a single service provider which manages the whole system by storing all the users' data, a DOSN consists of a (dynamic) set of peers, such as a network of trusted servers or a P2P system, which collaborate to implement the services needed to provide users with a seamless social network experience. Therefore, DOSNs shift the control over users' data from the single OSN provider to the peers that build up the DOSN (i. e. , to the users these peers belong to), thus solving some usual social network management issues, such as scalability, operating costs, and user privacy with respect to the single OSN provider  [2] ,  [3].
This paper addresses the previous issue by proposing an enhanced approach for enforcing the user privacy preferences in a DOSN. This approach improves the current encryption based mechanisms by exploiting the strength of the Logical Key Hierarchy model (LKH)  [10]  for managing the key for contents encryption. In particular, the main advantage introduced by the proposed approach is that it enables to efficiently execute the redistribution of the group keys required to manage efficiently the dynamism of DOSN user groups in the case of user removal. An experimental campaign run over a real data set extracted from Facebook do confirm the quality and viability of our approach.
A. The Facebook Dataset Although recent studies improved the understanding of the structural properties of OSNs (such as centrality, number of interconnections, or diameter), the analysis of the features  of the groups created by users has received little attention from the research community. As a result, currently there are no models that describe the structure and the features of social groups. In this paper, to evaluate the performance of the proposed approach, we are interested in measuring the size of social groups, and the number of users that are added to or removed from them over time. For this reason we implemented a Facebook application, called SocialCircles! 1  , which exploits the Facebook API to retrieve the following information: • ego network of the registered users, which contains the friends (known as alters) of the registered user (ego) and includes information about the direct connections between the alters.
B. Size of groups in Facebook Since our Facebook dataset is a collection of ego networks, we decided to split the whole dataset inspection by independently analyzing each ego network. We used the dataset to derive the possible social groups that could be defined by registered users. In particular, we analyzed the size and the number of social groups that could be derived from the ego network of each registered user by exploiting: i) the friendship relations between their friends, ii) the music interests, iii) the school information, and iv) the amount of interactions  occurred among users and their friends. The friendship social groups have been identified by using a classical label propagation algorithm  [32]  for community discovery. Instead, the social groups based on Music, School and Interactions have been identified by using cluster analysis.
The member list of a group contains, for each user of the group whose profile is visible, the following information: i) the identifier of the user, ii) the joining time, and iii) the administrator who has added the user. The proposed crawler is used to explore periodically the members of the group, thus permitting us to obtain information about the number of users who join or leave the different groups over time. The dataset obtained from the HTTP-crawler contains 18 private groups of three different types: work & education, news & information, and entertainment. Since our dataset is a collection of groups, we decided to split the whole dataset inspection in many independent analysis of each group. After collecting data of each group for 50 days, we perform a detailed analysis of the average number of join and leave operations, as well as on the number of users of each group.
VI. EXPERIMENTAL RESULTS This section provides a quantitative evaluation of the proposed approach. To this aim, we developed a realistic simulation by using the P2P Peersim simulator  4. The simulation dataset is the Facebook one described in Sec. V-A. To conduct our tests, we leveraged information about users' groups shown in Sec. V and we created a number of different groups whose size ranges between 1 and 10000 members. In particular, for social groups defined starting from users' ego networks (see Sec. V-B) the number of initial members does not exceed 500 individuals, while the private Facebook groups we examined have maximum number of initial members equal to 10000 (see Sec. V-C). For this reason, in our simulation, each user creates three different groups: small group (G s ), large group (G l ), and big group (G b ).
Both R packages snpnet and bigstatsr allow for fitting penalized regressions on individual-level genetic data as large as the UK Biobank. Here we benchmark bigstatsr against snpnet for fitting penalized regressions on large genetic data. We find bigstatsr to be an order of magnitude faster than snpnet when applied to the UK Biobank data (from 4. 5x to 35x). We also discuss the similarities and differences between the two packages, provide theoretical insights, and make recommendations on how to fit penalized regressions in the context of genetic data.
Introduction Penalized regression with L1 penalty, also known as "lasso", has been widely used since it proved to be an effective method for simultaneously performing variable selection and model fitting  (Tibshirani 1996). R package glmnet is a popular software to fit the lasso efficiently  (Friedman et al. 2010). However, glmnet cannot handle very large datasets such as biobank-scale data that are now available in human genetics, where both the sample size and the number of variables are very large. One strategy used to run penalized regressions on such large datasets such as the UK Biobank  (Bycroft et al. 2018)  has been to apply a variable pre-selection step before fitting the lasso  (Lello et al. 2018). Recently, authors of the glmnet package have developed a new R package, snpnet, to fit penalized regressions on the UK Biobank without having to perform any pre-filtering  (Qian et al.