dataesr/scientific-paragraphs-categorization huggingface dataset:
By simulating many random data sets, we find that the degree of anti-correlation observed in GRAVITY and KI/AMBER data could be explained if the true luminosity errors are 0. 6 dex. Our measured errors by comparing various methods appear to be somewhat smaller 0. 3 -0. 5 dex (Appendix A). Still this bias warrants caution in interpreting the results in terms of varying hot dust structure with source luminosity.
Acknowledgements. J. D. , M. B. , and A. J. R. were supported by a Sofja Kovalevskaja award from the Alexander von Humboldt foundation and in part by NSF grant AST 1909711. SFH acknowledges support by the EU Horizon 2020 framework programme via the ERC Starting Grant DUST-IN-THE-WIND (ERC-2015-StG-677117). M. K. acknowledges support from JSPS.
Acknowledgements. J. D. , M. B. , and A. J. R. were supported by a Sofja Kovalevskaja award from the Alexander von Humboldt foundation and in part by NSF grant AST 1909711. SFH acknowledges support by the EU Horizon 2020 framework programme via the ERC Starting Grant DUST-IN-THE-WIND (ERC-2015-StG-677117). M. K. acknowledges support from JSPS log L bol, 14-195 keV erg s -1 = 1. 1157 log L 14-195 keV erg s -1 -4. 2280. (A. 1) We also collect their optical (5100 Å) continuum from BAT cat- alog and 12 µm nuclear emission from Asmus et al. (2014) to confirm the consistency of different methods to derive the bolo- metric luminosity. Following the 5100 Å bolometric correction of Trakhtenbrot et al. (2017), we use, log L bol, 5100 Å erg s -1 = 0. 916 log νL ν (5100 Å) erg s -1 + 4. 596. (A. 2) For the MIR data, we first convert the 12 µm flux to 2-10 keV intrinsic flux according to Asmus et al.
Graph transformation theory relies upon the composition of rules to express the effects of sequences of rules. In practice, graphs are often subject to constraints, ruling out many candidates for composed rules. Focusing on the case of sesqui-pushout (SqPO) semantics, we develop a number of alternative strategies for computing compositions, each theoretically and with an implementation via the Python API of the Z3 theorem prover. The strategies comprise a straightforward generate-and-test strategy based on forbidden graph patterns, a variant with a more implicit logical encoding of the negative constraints, and a modular strategy, where the patterns are decomposed as forbidden relation patterns. For a toy model of polymer formation in organic chemistry, we compare the performance of the three strategies in terms of execution times and memory consumption.
Approaches to the implementation of analysis techniques on graph transformation systems can be divided into native, translation-based, and hybrid  [31]. We follow a hybrid approach where all three strategies are implemented in Python using the Z3 SMT solver and theorem prover  [37]  for computing decompositions and embeddings. Our approach was inspired by an active research area in graph rewriting that features a number of other implementations of analysis techniques, e. g. , for termination, confluence, or reachability as discussed in  [31]. At the core of our implementation, we precisely mirror the category-theoretical structures encoding graphs, morphisms, overlaps, compositions of graphs and constraints in terms of a class architecture in Python and utilising the Z3 Python API. The declarative nature of SMT solving, where models are only determined up to isomorphism, is a good fit for the categorical theory of graph rewriting, allowing a very direct translation.
Following standard combinatorial arguments along the lines of  [25] , we can construct an ordinary generating function for these numbers by (1) dressing each vertex with a power of some formal variable x, each edge in a "path" with y and each edge in a "directed loop" with z, and (2) multiplying the OGFs for copies of the different types of connected components: G (x, y, z) := ∑ k, ,m≥0 x k y z m • (# of iso-classes with k vertices and + m edges) = 1 1-x ∏ p≥1 1 1-x p+1 y p ∏ q≥2 1 1-(xz) q y,z→1 ---→ 1-x ((x;x) ∞ ) 2. The expansion of G (x, 1, 1) (i. e. of the OGF of iso-classes counted by number of vertices) permits to identify this series as the OGF of the integer sequence A000990 on the OEIS database 1  , with sequence entries (for n = 0,. , 10,. ) it transpires that the rigid directed graphs are enormously constrained in their structure compared to general simple directed graphs.
Implementation and Experimental Evaluation We provide a Python package called ReSMT (author: N. Behr) as an open-source project via GitLab  4  , whose current version 0. 0. 3 contains both a full online documentation  5  as well as dedicated GCM 2020 Supplementary Information materials  6. The computational core of our implementation is a theory (a set of definitions and constraints) in the Z3 theorem prover 7   [37] , which due to its declarative nature allows for a direct encoding of our categorical constructions. Using Z3 through its Python API, we can reflect the structure of the theory in an object-oriented design, where classes represent concepts of the problem domain, such as graphs and graph morphisms, spans, rules, pushouts, etc. , and generate assertions in Z3 encoding the defining properties of these categorical structures.
As a remedy, our ReSMT package is based upon an alternative encoding of finite sets utilising the enumeration sorts 8 provided by Z3. For the aforementioned example, this alternative encoding reads as follows: 7 set, els = z3. EnumSort( set , ( The above code yields an instantiation of a Z3 enumeration sort set called 'set' as well as a list of Z3 constants els (containing three constants of sort set with names 'x1', 'x2' and 'x3'). After the above call, the enumeration sort set as well as the individual constants may be utilised in a fully analogous fashion to other types of Z3 sorts and constants, yet internally provide additional information to the Z3 solver instance, encoding the finiteness axiom. We refer the reader to a dedicated section 9 of the ReSMT online documentation for in-detail performance experiments and simplified versions of the ReSMT algorithms for finding rule overlaps, demonstrating in particular the feasibility of using enumeration sorts for curating injective partial set overlaps with or without additional cardinality constraints.
Implementation Strategies for Curating Rule Overlaps Our current ReSMT implementation (version 0. 0. 3) consists of approximately 1800 lines of Python 3 source code and is provided with an in-depth API documentation 10. The core task implemented in the form of three alternative variants of algorithms is the curation of rule overlaps modulo structural constraints, currently supported already for the general data structure of typed directed multigraphs. We will present here some of the key aspects of our implementation in the setting of untyped directed multigraphs In order to encode the necessary constructs for our three different strategies, we require a number of additional data structures and logical assertion generation methods, all of which are documented in full detail both in the ReSMT API reference as well as in several sets of tutorial examples on the documentation page of the package.
All experiments were performed via our ReSMT Python package (version 0. 0. 3) executed in Python 3. 8. 2 and with Z3-4. 8. 8. 0 on a computer running macOS Catalina 10. 15. 6 with a 2. 30GHz Intel(R) Core(TM) i7-3615QM CPU and 16 GB of RAM. The entry n/a signals experiments that were not possible to complete under the experimental conditions in an order of hours per run. Note that for experiment P4, the number of candidate overlaps could only be estimated (cf. main text). Experiment name P1 P2 P3 P4 (G A , G B ) (I d-e , O c-e ) (I b-c 2 , O c-c 2 ) (I b-c 4 , O c-c 4 ) (I b-c 7 , O c-c 7 ) # candidate overlaps 8 49 2426 1. 17.
Experiments and Evaluation We present in Table  1  the experimental results for the computation of the full set of admissible overlaps of rigid graphs for four different pairs of input graphs (G A , G B ) (chosen from the in-and output interfaces of the rules of Example 3), and for the three different strategies. We invite the readers to consult the GCM 2020 Supplementary Information section of the ReSMT online documentation for the precise specification of each of the computational experiments. In particular, we provide precise instructions on how to replicate these experiments by executing Jupyter notebook GCM2020. ipynb provided as part of the ReSMT GitLab repository. The examples P1 to P4 were chosen to illustrate the fundamental effect that graph constraints may have on the computational complexity determining injective partial graph overlaps, and with the data type of rigid graphs as introduced in Example 2 providing a prototypical example of a graph-like structure defined via negative constraints.
relevance to the present paper. Assuming that the sets of vertices and edges of a given graph G have been encoded as enumeration sorts vG and eG (cf. Section 4. 1), the source and target functions of G are instantiated as Z3 functions: 8 srcG = z3. Function( srcG , eG, vG) 9 trgtG = z3. Function( trgtG , eG, vG)8 See e. g. this tutorial: https://ericpony. github. io/z3py-tutorial/advanced-examples. htm 9 API experiments: https://nicolasbehr. gitlab. io/ReSMT/py and ipynb examples/ReSMT-API-experiments. html 10 ReSMT API documentation: https://nicolasbehr. gitlab. io/ReSMT/API-reference/Reference. html(Injective) graph homomorphisms ϕ ≡ (ϕ V , ϕ E ) : G A → G B may then be encoded as follows: 10 phiV = z3. Function( phiV , vGA, vGB); phiE = z3. Function( phiE , eGA, eGB) 11 v1, v2 = z3. Consts( v1 v2 , vGA); e, e1, e2 = z3.
Comparing this to the sequence A000273 on the OEIS database, which gives the number of isomorphism classes of directed simple graphs without self-loops counted by number of vertices, and which reads for 1, 1, 3, 5, 10, 16, 29, 45, 75, 115, 181,. (4) n = 0,. , 10 1, 1, 3, 16, 218, 9608, 1540944, 882033440, 1793359192848, 13027956824399552, 341260431952972580352,. ,.
17 oth countries possessed the atomic bomb and hoped for an advantage or a deterrent potential to bring this threat to its destination with intercontinental missiles. During this heated period, the Soviet Union initially had a technological advantage. Thus, the age of space exploration began with Sputnik-1, the first man-made satellite on an orbit in the Low Earth Orbit (LEO), on 4 October 1957. Only a few days later, on 3 November 1957, the follow-up mission Sputnik-2 succeeded in bringing the first living creature into orbit, the female dog Laika. Sputnik-2 may therefore be regarded as the first test toward manned space flight as it was controversially discussed until then even whether living beings could survive in weightlessness for a longer period of time. The biomedical data obtained on this mission also contributed significantly to the success of the Vostok-1 mission with Yuri Gagarin.
In a second wave, 2825 satellites will be distributed at slightly different altitudes (data and further information can be found in Ref. 81 and the references therein). As of April 1, 2020, OneWeb has launched 34 more satellites, and Starlink has launched 240 more satellites. The images were created using the online tool of the CelesTrak Orbit Visualization website. (b) Concept of space debris removal employing the ion beam shepherd (IBS) concept. 82 The debris object will be pushed out of its orbit by momentum transfer from impinging ions generated in an ion thruster of an external satellite. The thrust of the ITT (impulse transfer thruster) has to be compensated with an additional thruster (ICT, impulse compensation thruster) to keep a fixed distance between the satellite and the debris object.
(c) Number of trackable objects in orbit. Data taken from Orbital Debris Quarterly News (NASA), Vol. 22, Issue 1, February 2018. The graphs include all objects that have been officially cataloged by the U. S. Space Surveillance Network. Also included are two relevant recent collisions. On January 11, 2007, China deliberately destroyed one of its weather satellites with a projectile of unknown design, resulting in the largest increase in space debris particles to date. About two years later, on February 10, 2009, the first collision of two communications satellites [Iridium (US) and Kosmos (Russia)] occurred, also with a significant increase in the number of scrap particles. even be that small that tracking from the Earth's surface will not be possible. The literature on the IBS concept mainly deals with the influence of the sputter products on the performance of the impulse transfer engine.
133, 134 alculations of the extraction process were initially possible using supercomputers only but are now feasible on personal computers due to their enormous increase in performance. 135, 136 Details about the methods used to model the beam extraction can be found elsewhere. 137 Figure  7 (a) shows exemplarily an ion beam extraction from a plasma via a grid system showing three beamlets. Figures  7(b ) and 7(c) show the space charge distribution for a single beamlet with compensation and the shape of the plasma meniscus, respectively. The simulation has been carried out with KOBRA. 9] [140]  A comparison between IGUN and KOBRA was published by Hanke and co-workers. 141 Tartz and co-workers have combined the IGUN code with a charge-exchange model to simulate the grid erosion for determining the thruster's lifetime.
Furthermore, beamlet-beamlet interaction (BBI) is take into account, which may have an influence on ion transparency. An equivalent representation (but without including BBI) is shown in (e). Both (d) and (e) are equivalent representations of a so-called unit cell for a hexagonal arrangement. (f) Calculated relative neutral particle density along a single extraction channel assuming free molecular flow. The density was calculated for the following parameters: screen diameter of 2 mm, screen thickness of 0. 25 mm, screen-accel gap of 0. 5 mm, accel diameter of 1. 5 mm, accel thickness of 1. 5 mm, accel-decel gap of 1 mm, decel diameter of 2 mm, and decel thickness of 1 mm. The result of the calculated transmission probability is 0. 137. The calculation was performed using the angular coefficient method from the COMSOL MolecularFlow module.
6] [157]  An extended global model approach including power transfer from RFG to plasma and neutral gas heating but limited to cylindrical discharge vessel geometries was published by Chabert and co-workers. 158 For the simulation of the RIT as a complete unit including thermal modeling of the engine, commercial tools such as COMSOL can be employed, as shown by Dobkevicius and Feili, where beam extraction simulation was supported by IBSIMU. 159 Volkmar and Ricklefs introduced a self-consistent scripted code based on global model assumptions and providing performance data for RITs. 160 The code supports 3D coil geometries and has the advantage of low central processing unit (CPU) requirements. Reeh et al. have extended this code introducing an ion beam extraction module and a neutral gas transmission calculation.
As a typical example, we will discuss the modeling of the plasma inside a RIT. The modeling can be divided into electromagnetic field generation, plasma production, multi-species dynamics, and ion extraction. Some software packages exist, which can be used to simulate either of these tasks individually or combined to solve the problem at hand. XPDP1-XOOPIC is a popular PIC open-source code for devices with plasma confined in the planar, cylindrical, or spherical geometry. 243 Accounting for the external circuit and the neutral gas interaction is possible in 2D and 3D. COMSOL is a commercial package that can be used to simulate plasma in a given ion thruster geometry along with the neutral gas flow. 244 Traditionally codes such as IGUN, IBSimu, and KOBRA3D are used to design ion extraction systems and beamlet formations.
The RF-plasma simulation and ion extraction grid lifetime were investigated for gridded ion thrusters. wind interaction with the neutralized thruster beam. 248 0] [251]  Furthermore, a multiscale modeling of thruster-plumes using a 3D PIC method was developed  [252] [253] [254]  and the plume simulation using modern graphics processing unit (GPU) computing has been discussed. 255 More recently, additional extensive tools such as Smilei and PICLas have been introduced to simulate the plasma with multiple ion species along with neutral gas distribution. 256, 257 e at JLU designed PlasmaPIC for modeling RITs. 258 Apart from describing inductively coupled plasmas, the code can also be used for a wide range of low-pressure low-temperature plasmas. It is an object-oriented code written in C++. PlasmaPIC is a fully threedimensional software.
It is suitable for describing plasmas in electrostatic as well as electrodynamic fields. A unique characteristic of PlasmaPIC is the incorporated massive parallelization of all program routines, which makes the code highly efficient. PlasmaPIC also distinguishes itself by the possibility of handling arbitrary geometries confining the particles described, i. e. , discharge vessels of various geometries or test chambers with defined locations of the pumps. The MCC module within PlasmaPIC assumes a neutral gas of a known particle density distribution as a background gas. Elastic scattering, excitation, and ionization are considered in electron-neutral collisions. In the case of ion-neutral collision, only the elastic collisions are accounted for in PlasmaPIC. Assuming a hard-sphere model, all collisions can be described by a uniform and isotropic scattering in the center of mass frame.
The special but in the context of GIEs very important type of elastic CEX scattering in ion-neutral collisions is treated explicitly in PlasmaPIC. Cross sections for the scattering processes were taken from the plasma simulation tool Xoopic. For the modeling of an inductively coupled plasma of a RIT, a common approach is to separate Maxwell equations into an electrostatic and an electrodynamic part. The electrical fields from both parts are then added following the superposition of fields. Dirichlet boundary conditions are incorporated at the boundaries. For the MCC module, a description of the neutral gas distribution is required. For this purpose, a DSMC module is implemented into PlasmaPIC. It can describe neutral gas densities in arbitrarily shaped vessels. Thereby, initially, the neutral gas density is calculated, and then, the plasma is simulated based on this density.
However, the plasma simulation considers the neutral gas distribution as constant in time. Thus, it is assumed that the influence of the plasma on the neutral gas is negligible. If this assumption does not hold, the neutral gas simulation and the plasma simulation have to be iterated self-consistently to account for the influence on each other. Using this technique, neutral gas densities and its influence in vacuum test facilities can also be calculated. We performed a simulation of a Xe-plasma inside a RIT-1 using PlasmaPIC on 384 CPU cores over 225 rf-cycles. A realistic neutral gas density of 8. 5 ⋅ 10 19 m -3 over 45 μs was assumed. Figure  12(c)  shows the neutral gas distribution in the ion thruster derived using the DSMC module. This gas distribution is then used as input distribution for MCC module for the calculation of binary collisions.
328 The flux of the soft component is coupled to the solar activity cycle and shows fluctuations over one or more orders of magnitude (cf. Fig. 19 ). 329 The solar cycle has a period of roughly 11 years. Figure  19  shows the correlation between the number of sunspots and CMEs. The envelope of the number of sunspots was smoothed over 5 months. The number of CMEs per month is smoothed over a period of 13 months. Clearly visible is the correlation between the sunspot number and the number of eruptive protuberances. The CME data are from LASCO (Large Angle Spectrometric Coronagraph), a detection system on the SOHO satellite. LASCO data are automatically analyzed according to CME events using the CACTUS software. 330, 331 The Earth's shows a decrease in regulation voltage with the increase in TID but always provides an output within safe levels for the load.
State machines can be hardened by assuring a lock-up-free behavior in case an invalid state is generated by SEE. 334 ii) The qualification of components by accelerated and nonaccelerated irradiation tests in comparable radiation fields. The latter is the method of choice for the qualification of custom-off-the-shelf (COTS) components, which marks a popular approach in modern space system designs. 335, 336 All major space agencies maintain databases with test results of COTS component irradiations, such as NASA/GSFC. 337 9] [340] [341]  However, the qualification of displacement damage in crystal lattices and the effects of TID are much harder to predict and depend on the specific design technology, the choice of semiconductor resistivity and doping distributions, as well as thicknesses of passivation layers and other surrounding passive materials, such as packaging, alloys of pads, and contacts.
ACKNOWLEDGMENTS This work was supported by the  Federal Ministry for Economic Affairs and Energy  under Contract Nos. 50RS1502 ,  50RS1709 ,  50RK1948 ,  50RS1707 , and  50RM1530  and in the framework of the  MINOTOR  project, the  NEMESIS  project, and the iFACT project that have received funding from the  European Union 's  Horizon 2020 research and innovation programme  under Grant Agreements Nos. 730028 ,  870506 , and  870336. Furthermore, EU regional funding via the  EFRE scheme of the State of Hesse  is gratefully acknowledged. The authors are also grateful for seed funding by the  Research Campus of Central Hessen (RCCH)  and for co-funding in frame of the funding scheme " Forschung für die Praxis 2018 " of the  Hessian Ministry of Higher Education, Research and the Arts. The authors would also like to thank  Elisa Monte  for her active support in creating the figures.
In the last module, a decision will be made whether the implementation strategy will be stopped (in case of perceived success), continued, or redesigned. Figure  4  illustrates the workflow of the ItFits-toolkit. An overview of the main working components of the ItFits-toolkit is summarized in Table  1. Within the four modules, the ItFits-toolkit employs a systematically guided but flexible step-by-step process, including stakeholder-based co-creation. The Normalization Process Theory (NPT) explains that successful integration and embedding are achieved through people (individuals and groups) working together  [35]. Therefore, engagement and consultation of staff involved in the implementation work and in iCBT service delivery are a core feature of the toolkit. Stakeholders are individuals which either actively affect the iCBT service (e.
Primary outcome The effectiveness of the ItFits-toolkit will be expressed in the extent to which the ItFits-toolkit is able to increase the degree of normalization of the use of the iCBT services compared to usual implementation activities. The degree of normalization is the extent to which staff involved in service delivery and referral consider the iCBT service to be a normal part of their routine practice. It will be measured with the 20-item Normalization MeAsurement Development tool, short NoMAD  [41, 42]. The NoMAD is a self-report instrument measuring the degree of normalization by focusing on four constructs as defined by the Normalization Process Theory  [35] : coherence, cognitive participation, collective action, and reflexive monitoring. The NoMAD shows high internal consistency and has been validated in heterogeneous samples across languages and settings  [42] [43] [44].