dataesr/scientific-paragraphs-categorization huggingface dataset:
These and other attributes defined by ODS2. 1 are included as search facets on the obs4MIPs website. Details of how these and other metadata definitions are described in detail on the obs4MIPs website. Once the data (uniquely identified via source_id) are registered on the obs4MIPs GitHub repository (footnote 15), the obs4MIPs Task Team works with the data provider to agree on a set of dataset indicators. In the case of the CERES data, the current status of the obs4MIPs data indicators is given as "[ ]". The color coding is described in Sect. 4. 3 and refinements will be posted on the obs4MIPs website. 17 As discussed above, these qualitative indicators provide an overall summary of a dataset's suitability for climate model evaluation. As described in Sect. 4. 4, a new feature of obs4MIPs permits data providers to include Supplemental Information (SI).
Intersection with CMIP6 model evaluation activities Initially, the primary objective of obs4MIPs was to enable the large and diverse CMIP model evaluation community to obtain better access to and supporting information on useful observational datasets. Obs4MIPs as an enabling mechanism continues to be the primary objective; however, it is now evident that there is added value beyond its original intent. In addition to providing data for researchers, obs4MIPs will be a critical link in support of current community efforts to develop routine and systematic evaluation (e. g. ,  Gleckler et al. , 2016; Eyring et al. , 2016b Eyring et al. , , c, 2020;; Righi et al. , 2020; Phillips et al. , 2014; Lee et al. , 2018; Collier et al. , 2018). With the rapid growth in the number of experiments, models, and output volumes, these developing evaluation tools promise to produce a first-look high-level set of evaluation and characterization summaries, well ahead of the more indepth analyses expected to come from the climate research community.
Summary and future directions This article summarizes the current status of obs4MIPs in support of CMIP6, including the number and types of new datasets and the new extensions and capabilities that will facilitate providing and using obs4MIPs datasets. Notable highlights include (1) the recent contribution of over 20 additional datasets making the total number of datasets about 100, with about 100 or more resulting from the 2016 obs4MIPs data call that are ready for preparation and inclusion; (2) updated obs4MIPs data specifications that parallel, for the observations, the changes and extensions made for CMIP6 model data; (3) an updated CMOR3 package to give observation data providers a ready and consistent means for dataset formatting required for publication on the ESG (Earth System Grid); (4) a set of dataset indicators providing a quick accounting and assessment of a dataset's suitability and maturity for model evaluation; and (5) a provision for including supplementary information for a dataset, information that is not accommodated by the standard obs4MIPs file conventions (e.
g. , code, uncertainty information, ancillary data). A number of these capabilities and directions were fostered by the discussions and recommendations in the 2014 obs4MIPs meeting  (Ferraro et al. , 2015). It is worth highlighting that a number of the features mentioned above, particularly the dataset indicators, have been implemented to allow for a broader variety of observations -in terms of dataset maturity, alternatives for the same geophysical quantity, and immediate relevance for climate model evaluation -to be included. Specifically, in the initial stages of obs4MIPs, the philosophy was to try to identify the "best" dataset for the given variable and/or focus only on observations that had been widely used by the community. More recently, guided by input from the 2015 obs4MIPs meeting and consistent with community model evaluation practices, it was decided that having multiple observation datasets of the same quantity (e.
g. , datasets derived from different satellites or based on different algorithm approaches) was a virtue. Moreover, as models add complexity and new output variables are produced, and as new observation datasets become available, it may take time to determine how to best use a new observation dataset for model evaluation. In this case, rather than waiting to include a dataset in obs4MIPs while ideas were being explored, it was decided that obs4MIPs could facilitate the maturation process and benefit the model evaluation enterprise better by including any dataset that holds some promise for model evaluation as soon as a data provider is willing and able to accommodate the dataset preparation and publication steps. Additional considerations being discussed by the obs4MIPs Task Team are the requirements for assignments of DOIs to the datasets and how to facilitate this process.
An important step has been made as it may be possible to provide DOIs via the same mechanism adopted by CMIP6  (Stockhause and Lautenschlager, 2017)  and input4MIPs  (Durack et al. , 2018). In addition, there is discussion about how often to update and/or extend datasets and whether or not to keep old datasets once new versions have been published. Here, a dataset "extension" is considered to be adding new data to the end of the time series of data with no change in the algorithms, whereas a dataset "update" involves a revision to the algorithm. At present, the guidance from the Task Team is to extend the datasets, if feasible, with every new year of data, and if an update is provided, this would formally represent a new version of the dataset with the previous one(s) remaining a part of the obs4MIPs archive.
The Task Team also has undertaken considerable deliberations on how to handle reanalysis datasets, given that they often serve as an observational reference for model evaluation applications. Initially, the archive contained a selected set of variables from the major reanalysis efforts reformatted to adhere to the same standards as obs4MIPS. These data remain available in the ESGF archive and are designated Analysis for Model Intercomparison Project (ana4MIPs). The dataset is static and not updated as new data become available. A new initiative called the Collaborative REAnalysis Technical Environment (CREATE)  (Potter et al. , 2018)  is curating recent and updated reanalysis data for intercomparison and model evaluation purposes. The CREATE project offers an expanded variable list relative to ana4MIPs and is updated with the newest available data as they are produced by the reanalysis centers.
The key variables are offered for most variables at 6 h, monthly, and for precipitation daily time resolution. The service also contains a reanalysis ensemble and spread designated as the Multiple Reanalysis Ensemble version 3 (MRE3). Finally, obs4MIPs' growing capabilities for accommodating a greater number and broader range of datasets are pointing towards adoption of the obs4MIPs framework for hosting in situ datasets that have value for climate model evaluation. In fact, a likely emphasis of future obs4MIPs Task Team efforts will be to develop an approach to accommodate in situ data. This potential widening of scope in turn suggests the possibility for using the obs4MIPs framework to serve the function of curating and providing observation datasets for the monitoring and study of a more extensive range of environmental processes and phenomena, not specifically focusing on climate model evaluation.
tion. The authors would also like to acknowledge the support of the World Climate Research Programme (WCRP), specifically the WCRP Data Advisory Council (WDAC) for facilitating the maintenance and expansion of obs4MIPs and providing a task team framework to carry out these objectives, as well as the WGCM Infrastructure Panel (WIP) for its fundamental role in developing data protocols, standards, and documentation in support of CMIP. Some work was supported by the U. S. National Aeronautics and Space Administration (NASA) and the U. S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 under the auspices of the Office of Science, Climate and Environmental Sciences Division, Regional and Global Model Analysis Program (LLNL release number: LLNL-JRNL-795464).
The contributions of Duane Waliser and Robert Ferraro to this study were carried out on behalf of the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The contributions of Otis Brown and James Biard to this study were supported by the National Oceanic and Atmospheric Administration through the Cooperative Institute for Climate and Satellites -North Carolina, under cooperative agreement NA14NES432003. We would like to acknowledge the help of Birgit Hassler (DLR) in preparing the ozone model-observation comparison figures with the ESMVal-Tool and Jiwoo Lee (PCMDI) for the comparison figures with the PMP. Financial support. This research has been supported by NASA (obs4MIPs Task), the U. S. Department of Energy by Lawrence Livermore National Laboratory (grant no.
We leverage here the recently introduced stream graph model, which captures both the time and structural components of data  [17]   [16]. We will start our analysis with basic metrics targetting the questions above and we will introduce new stream graph concepts as we need them in the analysis. This paper is organized as follows. Section 2 introduces the G1 cryptocurrency and explains the main ideas and mechanisms behind it. In section 3, we present the dataset under study and show how the stream graphs model interactions from this dataset. In section 4, we use time series and static graph concepts to gain a first insight on the global structure and dynamics of the system. In section 5 we consider both time and structure together but stay at a basic link level in order to understand the interplay between social ties and transactions.
Dataset and stream graph modeling All the data we consider here is extracted from the G1 blockchain which is publicly available  [2]. For our purpose, the blockchain contains three key information: the identities, the certifications, and the transactions. Identities associate a public key (which we also call a wallet) to a user name and represent therefore the members of the system. As explained in section 2. 2, a certification is a directed interaction between a member and a public key, while a transaction is a directed weighted interaction between two public keys. From the blockchain, we extracted a stream of certifications, which is basically a sequence of (t, u, v) triplets, meaning that entity u certifies entity v at time t, and a stream of transactions, which is a sequence of (t, u, v, a) quadruplets, meaning that entity u sends an amount a to entity v at time t.
Conclusion We studied a recent cryptocurrency which, despite its relatively small size, provides a very interesting and publicly available dataset to study transactions within a social environment. Because the data has both a structural and temporal component, neither a pure static graph nor a time serie based model are well suited for its study. We proposed here to rely on the stream graph formalism to study the streams of certifications and transactions. We showed that certifications are often the first type of link occurring between two previously disconnected nodes, suggesting that members of G1 start to meet at social events before making transactions. In this context, the social network shapes the way transactions occur: even when they occur between two members without a certification relationship, this transaction has a much higher probability of occurring between two socially close nodes.
This development can be attributed to convexity of the feasible design space  [3, Sections 1. 3. 5, 3. 4. 3, and 4. 8] , as the (axial) structural stiffness is an affine function of the cross-sectional areas. On the other hand, when the bending stiffness comes into a consideration, convexity does not hold in general. Quite surprisingly, these problems are also much less studied, and to our knowledge only local optimization algorithms have yet been developed  [4, 5]. In this contribution, we investigate the problem of optimum design of frame structures. In particular, we develop four different methods in Section 2: (i) general non-linear optimization solved by the interior-point method of fmincon, (ii) the first-order optimality criteria (OC) method  [1, 5] , (iii) reformulation of the problem into a non-linear semidefinite program (NSDP) solved by PenLab  [6] , and (iv) a suitably modified polynomial optmization (PO) problem (iii) solved globally using polynomial optimization methods  [7]  and the Mosek  [8]  optimizer.
t. K(a)u = f (a), ( 5b ) T a ≤ V , ( 5c ) a ≥ 0, (5d) with being the column vector of the frame elements lengths. Notice that in general, (5) constitutes a nonconvex non-linear optimization problem because of the bilinear objective function (5a) and the polynomial equilibrium equality (5b) with possibly singular K(a). On the other hand, the volume constraint (5c) and the cross-sectional areas non-negativity constraint (5d) are affine functions of the design variables, u and a, and are in turn convex. The optimization problem (5) can be solved to local optimality using standard numerical optimization techniques. In particular, we will solve this problem using the interior-point method implemented in the fmincon function of Matlab.
, n e }, (26a) c 2 sc ≤ 1, (26b) we finally arrive at an equivalent formulation to (19), min asc,csc 0. 5ĉ(c sc + 1) (27a) s. t. 0. 5ĉ(c sc + 1) -f (a sc ) T -f (a sc ) T K(a sc ) 0, (27b) 2 -n e -1 T a sc ≥ 0, (27c) 1 -a 2 sc,i ≥ 0, (27d) 1 -c 2 sc ≥ 0. (27e) In (  27 ), the objective function (27a) and also the constraints (27b)-(27e) are all polynomial inequalities 4  non-negative in the feasible region of (27), which is therefore a semi-algebraic set. The optimization problem (27) can readily be solved by building the (Lasserre) hierarchy of convex linear SDP relaxations, with a monotonously converging objective functions to the global optimum. The hierarchy is generated by the GloptiPoly  [13]  software package interfaced with the Yalmip  [14]  toolbox, and the underlying SDP relaxations are solved by the state-of-the-art Mosek optimizer  [8].
Acknowledgements The work of  Marek Tyburec  was supported by the  Grant Agency of the CTU in Prague ,  SGS19/033/OHK1/1T/11. Martin Kružík  and  Jan Zeman  acknowledge the financial support by the  European Regional Development Fund  through the project  CZ. 02. 1. 01/0. 0/0. 0/16-019/0000778.
We use topology concepts throughout the pipeline to design volumetric layouts from unstructured CAD geometry. From the beginning to the end, decomposed topologies are constrained and analyzed in order to build structured 3D meshes using unstructured ones. We present properties of 2, 3-dimensional manifolds embedded in R 3 for 2-dimensional manifolds to 3-dimensional manifolds conversion. Close links between quadrilateral layout and volumetric layout are then determined. Suitable volumetric layouts are then an essential scheme to build required trivariate isogeometric and hexahedral meshes. Reduced order modeling is a tedious task that requires structured large amount of data. All geometric instances of the population must satisfy isotopological and homologous mesh properties to be efficiently compared and studied whether it is their geometries or their embedded data that is targeted.
Volumetric parameterization With a valid closed cuboid configuration C c that will describe a volumetric layout V C satisfying previous topological properties from  Maquart et al. [40] , we are able to construct a volumetric parameterization. First, we take the quadrilateral mesh extracted from the optimized aligned global parameterization. This quadrilateral mesh can be viewed as a set ordered points. We use the software Rhinoceros 5  [41]  to fit B-Spline surfaces with this specific point grids. We manipulate compatibility and patch refinement with the Rhinoceros software library  [42]. Secondly, for each cuboid, the B-Spline solid is obtained using reconstructed B-Spline boundary surface as boundary conditions. The positions of the interior control points of the solid are calculated in a way to minimize the Laplacian based energy.
Application to reduced order modeling with geometric parameters Our algorithm is entirely incorporated into a Rhinoceros 5  [41]  Plug-In implemented in VB. NET. C++ processes are called from the Plug-In. Some prerequisites are mandatory, such as a consistent pants-tocuboids decomposition. We use for that purpose the ROM (Reduced Order Model) builder proprietary software developed by ANSYS  [44]. This ROM solution works using classical Singular Value Decomposition algorithms  [45, 46]. Response surfaces reconstruction are made with standard kriging tools. Figure  9  gives the standard principle of operation. Recently, this builder has been used to prevent excessive compression of buttock's soft tissues by bony structures in real-time for paraplegic persons  [47]. Many modern numerical models of real-life physics computations pose challenges when used in numerical simulations, due to time complexity and large size.
These material parameters imply a Poisson's ratio equal to ν = 0. 3636, which corresponds to a compressible material. The finite element calculation is classically performed using a total Lagrangian approach, again see e. g. Simo and Hughes  [48]. Based on the results of the full calculation without remeshing, we observe that element quality metrics of the deformed mesh start to deteriorate significantly after t = 0. 5. Consequently, we extract the deformed geometry at this particular time and use our algorithms to create a new isotopological mesh to improve element aspect ratio and overall quality. The new mesh used form t = 0. 5 can be seen in figure  11 (A). In order to evaluate mesh quality, we use as a metric the element shape ratio S r classically available in commercial softwares such as ANSYS.
In the last two decades, technological progress has not only seen improvements to the quality of atmospheric upper-air observations but also provided the opportunity to design and implement automated systems able to replace measurement procedures typically performed manually. Radiosoundings, which remain one of the primary data sources for weather and climate applications, are still largely performed around the world manually, although increasingly fully automated upper-air observations are used, from urban areas to the remotest locations, which minimize operating costs and challenges in performing radiosounding launches. This analysis presents a first step to demonstrating the reliability of the automatic radiosonde launchers (ARLs) provided by Vaisala, Meteomodem and Meisei. The metadata and datasets collected by a few existing ARLs operated by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) certified or candidate sites (Sodankylä, Payerne, Trappes, Potenza) have been investigated and a comparative analysis of the technical per-formance (i.
e. manual versus ARL) is reported. The performance of ARLs is evaluated as being similar or superior to those achieved with the traditional manual launches in terms of percentage of successful launches, balloon burst and ascent speed. For both temperature and relative humidity, the ground-check comparisons showed a negative bias of a few tenths of a degree and % RH, respectively. Two datasets of parallel soundings between manual and ARL-based measurements, using identical sonde models, provided by Sodankylä and Faa'a stations, showed mean differences between the ARL and manual launches smaller than ± 0. 2 K up to 10 hPa for the temperature profiles. For relative humidity, differences were smaller than 1 % RH for the Sodankylä dataset up to 300 hPa, while they were smaller than 0. 7 % RH for Faa'a station.
Nevertheless, it must be also stressed that the system must be regularly stocked and maintained to avoid major issues and high repair costs being incurred. In addition, with changes in the radiosonde technology, updates of the systems might be required to enable the use of a new radiosonde type, with periodical costs (variable, every 3-6 years) which might be substantial for a station. In 2018, the National Oceanic and Atmospheric Administration -National Centers for Environmental Information (NOAA-NCEI) published stories on its website which show the potential benefits of using ARLs (http://www. noaa. gov/stories/up-up-and-away-6-benefits-of-automated, last access: 7 May 2018). Within these stories as well as from the feedback collected within the GRUAN community, several radiosonde stations have reported benefits from the use of ARLs and an increase in the percentage of successful soundings with a potential reduction of missing data in the collected data records.
Using recent European Centre for Medium-Range Weather Forecasts (ECMWF) statistics on the number of stations transmitting data to the World Meteorological Organization (WMO) Information System (WIS) and information provided by the GRUAN community and others, there are about 90 ARLs (Fig. 1 ) providing data for about 700 manual stations. ARL stations cover many countries and remote regions, including Arctic and Antarctic locations, as well as a broad suite of remote Pacific and other island locations. As far as is known, many of the ARL stations only make automated launches. In addition, there are a few more stations, used by research institutions or environmental agencies, not transmitting data via the Global Telecommunication System (GTS) of WIS. The total number of stations operating an ARL worldwide has increased within the last decade (see Tables A1 and A2 in Appendix A).
e. GRUAN data processing based on the raw data collected by the sonde, described in  Dirksen et al. , 2014, and Kobayashi et al. , 2019, is not used). The remainder of the paper is structured as follows. In Sect. 2, a short description of the three ARLs is provided. In Sect. 3, the technical performance of the ARLs is investigated on the basis of statistics comparing the technical efficiency of the ARLs versus the manual sounding stations as well as reporting an analysis of the feedback from station operators collected at the GRUAN sites on the advantages, limitations and technical issues faced to maintain and ensure continuity of ARL operations. Section 4 reports on the effect of the usage of ARLs on the stability and the accuracy of ground-check calibration procedures. Section 5 provides statistics obtained from parallel soundings at different sites for both temperature and humidity profiles.
Section 6 discusses the comparison between observation-minusbackground (O-B) statistics obtained from ARL data and manually launched data, respectively, using the ECMWF short-range forecast fields. Finally, Sect. 7 provides a summary and a description of the experiments which might be performed to design future ARL setups to enable full measurement system traceability to SI units and therefore meet GRUAN requirements for long-term reference climate data. 2 Description of existing ARL systems 2. 1 Vaisala Autosonde: brief history and recent system configurations Automation of upper-air sounding data processing has been making steady progress since the early 1970s and is now widespread  (Kostamo, 1992). The Vaisala Autosonde project was started in late 1992 and a working prototype was presented at CIMO, Vienna, in 1993.