dataesr/scientific-paragraphs-categorization huggingface dataset:
Finally, only the first term, δ 0 + δ 1 × Scor e Topo , could favour large modules. Yet, the selected topological descriptors included the size of the modules. This ensured that functional modules of all sizes were compared to random modules of all sizes during the machine learning process. When Score Topo increased following new gene addition, this was mainly because the topological descriptors of the new module were more FM-like, not just because the number of constituting genes increased. TopoFun design was able to minimize the systematic statistical bias uncovered by Nikolayeva and colleagues  (12)  and produced some large modules that were still interpretable as exemplified by GO:0043401∼ steroid hormone mediated signaling pathway. Future developments of TopoFun will include the optimization of the training set by incorporating additional sets of functionally related genes.
We will test TopoFun on different types of GCNs, in particular cell type-specific GCNs constructed from single cell RNAseq data. We will also use TopoFun for various purposes, e. g. the identification of the 'best' functional module of a fixed size including a given gene, the ranking of functional annotations associated with multifunctional genes by including topological information, and, hopefully, the identification of totally new functional modules.
tional de la Santé et de la Recherche Médicale; Université de Montpellier; A. J. was supported by the Université de Montpellier; Centre National de la Recherche Scientifique-Lebanon; Université Libanaise; M. G. X. acknowledges the financial support from France Génomique National Infrastructure, funded as part of the 'Investissement d'Avenir' program managed by the Agence Nationale pour la Recherche [ANR-10-INBS-09]. Funding for open access charge: Centre National de la Recherche Scientifique.
The finite element software ABAQUS has been used to implement the identified elastoplastic behavior. Nevertheless, local phenomena such as filaments buckling and air gap repartition are not modeled. The related problems will be discussed later on where this numerical tool will be tested on the compact tension CT specimen  [4]  and the Single Edge Notched Bend SENB specimen defined in  [7]  where both the optimized deposition and the classical deposition trajectories will be modeled and compared. The structure of the paper is as follows. In Section 2, the modeling strategy adopted for the 3D printed material is presented. First, the local references assignment technique is explained. Then the pre-structured material behavior definition is presented. Next, the experimental setups and results are displayed.
Local References Assignment in Mesh Elements The purpose is to reproduce the printing trajectories inside a finite element model. The finite element code ABAQUS is used in this study. From the CAD file representing the part, the geometry is generated. Then an adaptive mesh is generated using an eight-node brick element with reduced integration C3D8R (i. e. , one integration point per element). The use of C3D8R elements is motivated by the need to reproduce the layer by layer built in the model. This choice allows a simplification of the problem. The elements heights are fixed and must be equal to the layer thickness in order to ensure the reproduction of the built trajectories in a layer by layer process and facilitate the localization of elements in a certain layer (see Figure  2 ). Sci. 2021, 11, x FOR PEER REVIEW 4 of 19 node brick element with reduced integration C3D8R (i.
Fabrication of the Specimen The specimens were designed according to the ASTM D638-03 norm "Standard Test Method for Tensile Properties of Plastics"  [26]. The fused deposition modeling fabrication process was conducted on a Makerbot replicator ×2 with a flat printing configuration. The filament is made of white ABS (Acrylonitrile Butadiene Styrene) material so that a better contrast can be achieved while performing the DIC analysis. The printing parameters described in Table  1  are the same for all the specimens studied in this paper. The slicing software Slic3r  [27]  was used to generate the G codes. This software was chosen since it allows a unique infill angle for all layers via the modifier feature. Three infill angles are used 0 • representing the longitudinal direction of the filament, 90 • for the transverse direction of the filament, and a 45 • angle to study the shear behavior.
Tensile Tests with Digital Image Correlation The tensile test machine Instron 4411 was used to perform the tensile tests. The loading rate was fixed at 1 mm/min. A camera with a resolution of 1280 pixels × 960 pixels was used to record a snapshot every 0. 6 s while performing the test. This frequency gives an accurate reproduction of the tensile curves. The speckle was applied manually through a black paint spray. After collecting the snapshots, the DIC software NCORR  [28]  allows a quantitative analysis of the strain. It tracks the displacement of the speckles on each snapshot during the loading phase and uses it to interpret the kinematic field maps on a specific region of interest (ROI). A subset size of 15 pixels and a spacing of 2 pixels were used for data treatment. The images were treated as described in  [29].
Tensile Tests Results For every performed tensile test, the calculated Young's modulus value will indirectly take into account the existing air gap by computing the engineering stress via the geometrical section. The calculations are made with respect to the D638 ASTM norm  [26] : Young's modulus is calculated as the slope of the tangent to the true stress-strain curve at low stress. To get such a curve, the assumption of volume conservation was made since the volume variation data is not available. The DIC analysis gives an estimation of the average value of the transversal and the longitudinal strain, which are used to calculate the Poisson's ratio values. The yield strength is calculated via the 0. 2% strain offset method. The results are displayed in Table  2. The experimental tensile curves show that the material exhibits different behaviors according to the filament orientation (see Figure  5 ).
σ 0 LT = 4 σ 2 45 • - 1 σ 2 T - 1 2 (5) A value of 11. 65 MPa was found similar to the value found by [31] 12 ± 0. 7 MPa. For the out-of-plane shear yield strength, the torsion test is commonly used to identify its value. The experimental results reported in  [37]  by Balderrama-Armendariz et al. show that the out-of-plane shear yield is about 25 MPa. However, this value cannot be utilized herein since the printing parameters are substantially different. Therefore, both in-plane and out-of-plane shear yield strengths were assumed equal σ 0 TT = σ 0 LT. The Hill criterion was implemented in ABAQUS software using the user-defined Hill's potential function in ABAQUS  [38]. It implies the definition of six different anisotropic yield stress ratios. As σ 0 TT = σ 0 LT , three independent ratios must be introduced as inputs.
Tensile Tests Prediction The finite element model for the tensile specimen geometry was created in ABAQUS software. Three models were later defined by assigning local material references with respect to the printing trajectories. Three different simulations have been carried out to simulate the behavior of each of the specimens according to the suggested model. The part of the specimen pinched between the fixed jaws is encastered and a displacement is applied on a reference point coupled with the part pinched between the mobile jaws. Figure  7  compares the stress-strain curves obtained experimentally with those obtained by finite element simulations. The results show that for all three cases, the elastic behavior is well reproduced with a slight difference because of the simplifications described before.
This provides the following interface: Definition p := ltac:(plot f x1 x2). The plot tactic can take two extra arguments to specify the ordinate range. When absent, the tactic computes the extrema of the function between the endpoints. The plot tactic supports the same configuration mechanism as the tactics interval and integral  [4]. For instance, to obtain Figure  1c , one needs to increase the precision to 90 bits, as follows: plot ( fun x = > 1+ x *. -exp x ) ( -1/32) (1/32) with ( i_prec 90) A new flag has been added to specify the dimension of the bitmap: i_size w h. By default, the tactic produces a plot of size 512 × 384. Other meaningful flags are i_degree to control the degree of the polynomial approximations and i_native_compute to tell Coq to first compile the algorithm to machine code rather than directly interpreting it.
In particular, this implies that we leave efforts in other domains such as hardware-based systems, (most of the field of) software engineering, multi-agent systems, or machine learning out of consideration. The remainder of this section initially describes our research method, including the research questions to be answered by the method. Afterwards, we categorise the different contributions that we identified with the method and summarise the current state of the art. This is accompanied by an assessment of what needs to be done in the specific (sub-)category towards establishing and developing systems with the desired SISSY capabilities as outlined in Section 2. This is later consolidated into a research roadmap (see Section 5) outlining basic directions of necessary research efforts. Finally, this section investigates the correlations of categories of current research efforts to provide an interpretation where a tighter binding is necessary.
We used the following search query to select contributions automatically: (integration) AND (software OR application OR system) We intentionally did not extend the scope to phrases that can be considered as synonyms of self-integration such as selfassembly, dynamic composition, self-/dynamic coordination, self-growing, self-construction, and so on. The basic motivation is that we want to stay with the wording to keep the SISSY focus. Furthermore, the research aims at analysing efforts directly related to self-integration tasks rather than summarising efforts of the self-adaptive and self-organising, autonomic computing or multi-agent communities that may be beneficial for developing SISSY systems. Table  1  lists the considered venues which were searched using the respective databases (ACM DL, IEEE Xplore).
Theory of SISSY systems A considerable part of the ongoing research in the field aims at defining and formalising the fundamental concepts and terminology behind SISSY systems. In that connection, a series of problem classes can be derived from the set of example scenarios discussed in the literature. a) Definitions: Self-improving System Integration (SISSY) itself is defined in  [37]  as the "attempt for the intelligent integration of complex systems that have both adaptive and nonadaptive components or subsystems". More specifically, the paper delineates self-integration as an "ongoing autonomous process for linking a potentially large set of heterogeneous computing systems, devices, and software applications; to meet system goals", and self-improvement as "inventing solutions where none are available and optimising the selection of solutions over time" (which we took as basis for Section 2.
However, there is a lot of work on and innovation in hardware integration, especially with GPUs and FP-GAs, and the chosen venues do not obviously capture this work -we just consider those that have been intentionally presented in the context of SASO-based self-integration. Here, contributions range from re-configurable embedded system architecture  [59]  to integrated neural networks for cooperative multirobot swarms  [60]. Design implications based on the viable systems model for software maintenance are also discussed earlier  [51]. Assessment and research gap: There is still a significant gap between integration solutions for hardware and software reflected by different fragmented communities. For instance, the pervasiveness of the Internet of Things promises further joint efforts on self-integrating both software and hardware systems.
Research Roadmap As with all technical roadmaps, we start with what we currently can do and see whether we can develop applications that start to approach the SISSY vision. This is clearly seen in the research overview presented above. The lines of current research demonstrate that SISSY has incorporated learning, trust among agents, peer-to-peer negotiation or mediation through a third party as in the Brain Patch, and so forth. What has been shown is encouraging -there are a lot of modest applications waiting for SISSY approaches. But our gains have also shown how far we must go. As an example of what remains before we reach the vision of SISSY, we identify three special challenges: true developmental processes, online trade-offs and negotiation among competing goals, and the development of semantically rich languages for SISSY modelling and communication.
Some of these changes could be adding or making use of previously unused parameters and components in a given configuration or usage within an operational environment. Some of these changes could be subtle timing and ordering changes in configurations which lead to novel behaviours (for example, some neural locomotion pattern generators show how a single pattern generator can lead to strikingly different gaits in diverse animals). Some of these changes could be the creation of new manipulable parameters, new behaviours, new configurations, and even new components through merging and other combinatorial processes. Our current starting point is the fruitful research and development of methods and systems that can enlarge and expand themselves (e. g. , intelligent databases or peer-to-peer sensor networks).
In computer science, we have, through protocols of many types, shown that rule-based transactions with others can occur through a variety of means. Also, by recognising and organising the environment, we bypass a verbal common language with situated but meaningful behavioural indicators. Hence when I am in Budapest and don't speak the language, I can enter a bakery and point to what I want and open my handful of coins, letting the baker take whatever is necessary. So, part of our engineering in SISSY systems needs to consider how we design the operational environment so that participating systems could possibly make use of situated transactions not dependent upon messages passed. We have certainly done that already for some Internet applications. We have also suggested special safe spaces "integration playgrounds"  [133, 13]  where systems can experiment with new configurations and study the capabilities of other systems.
That is, one needs to understand what one is trying to do with the new language abilities. Hence the second landmark is to first analyse what information is needed for new behaviours, goals, players (and hence what must be represented) and what new transactions that information is supposed to support. Then these new placeholder terms must be integrated into the domain-specific languages. Landmark 3: Lastly one of the biggest challenges for SISSY (as too in science) is the reconciling of different words, terms, and subcultures that have overlapping meanings. In other words, we must integrate the language used. Landmark 3 is a demonstration of being able to combine and link terms among multiple agents. In Section 3 we introduced five short scenarios that partly differ from the traditional scenarios used in literature: joining a game, joining a caravan of vehicles, joining a search, joining a research project, and joining a surveillance system.
We then investigate SISSY-related research efforts and derive a taxonomy of SISSY technology. During the review process of the queried papers and articles, we analysed the major contributions regarding SISSY technology. 82 out of 187 papers and articles have been selected for further consideration. Here, we classified the paper as belonging to one of the five major categories 1) theory, 2) system, 3) integration, 4) improvement, and 5) consciousness. These major categories have been further refined in terms of 16 sub-categories as discussed in the paper. Furthermore, we kept track of the application scenarios used in the papers. We summarised the findings and the corresponding state of the art according to these categories. As an example of what remains before we reach the vision of SISSY, we pulled out three special challenges: creating true developmental processes, producing methods for online trade-offs and negotiation among competing goals, and the development of semantically rich languages for SISSY modelling and communication.
The impact of these parameters on downstream analyses and biological results drawn from RADseq or ddRADseq data has however not been fully explored yet. In this study, we tackled this issue by investigating the effects of ddRADseq laboratory (i. e. wet protocol) and bioinformatics (i. e. dry protocol) settings on loci reconstruction and inferred biological signal at two evolutionary scale using two systems: a complex of butterfly species (Coenonympha sp. ) and populations of Common beech (Fagus sylvatica). 3. Results suggest an impact of wet protocol parameters (DNA quantity, number of PCR cycles during library preparation) on the number of recovered reads and SNPs, the number of unique alleles and individual heterozygosity. We also found that bioinformatic settings (i. e. clustering and minimum coverage thresholds) impact loci reconstruction (e.
Wang et al. , 2017). These studies highlight the impact of clustering thresholds (e. g. M and m parameters of the STACKS software procedure) on bioinformatic results and summary statistics. Indeed, these thresholds have been shown to influence the number of recovered loci, coverage, number of identified SNPs and error rates  (Mastretta-Yanes et al. , 2015; Paris et al. , 2017; Rochette & Catchen, 2017; Y. Wang et al. , 2017). In agreement with previous works, we found a substantial impact of the minimum coverage (m) and clustering (M) thresholds on ddRADseq loci recovery and reconstruction during the bioinformatic process. The minimum coverage imposes a minimum number of reads to consider an allele. Many alleles are expected to be lost with a high m, while a low m can give too much importance to very rare sequences, and thus potentially to sequencing or PCR errors  (Catchen et al.
Galapagos sea lion (Zalophus wollebaeki) in Finally, combined with the results from  Malinsky et al. (2018)  showing that nonrandom data missingness due to a batch (i. e library) effect had no impact on downstream analyses of the genetic structure. These findings moderate the message from the literature, which commonly presents the bioinformatics treatment as a key parameter of ddRADseq loci reconstruction. If this step indeed has an influence on loci recovery (i. e summary statistics), it only has a weak impact on the biological signal resulting from population genetic analyses, at least for the two models tested in this study.
Teachers of Civic and Citizenship Education Looking into the impact of educational reforms, it is clear that reform is in vain when there is no support of the teachers in schools to implement the change. Furthermore, according to the maximalist citizenship education view  (Hargreaves 2008) , teachers and the school are critical players in the provision of democratic values and hence especially important for citizenship education implementation. Therefore, increased emphasis has been placed on teachereffectiveness and the provision of appropriate teacher training and guidance on pedagogies about civic and citizenship education. To assess the current state and evolution of these elements in Flanders, the ICCS studies are also valuable databases. For example, ICCS 2016 asks teachers what they consider the most important aims of civic and citizenship education at school.
Research Interests or Training of Researchers The results of ICCS 2009 were analyzed and a national report was published (Sistema Regional Furthermore, recommendations for research arose in the interviews held with specialists (November, 2018) in civic and citizenship education. For instance, it was suggested to use ICCS data to strengthen teacher training in civic and citizenship education and to educate principals and organizations that work with families in this area. In addition, it was suggested these results could be used for debating and reviewing policies, programs and strengthening teacher education programs in universities. Researchers should be encouraged to use the ICCS database to develop more in-depth knowledge about this topic. Currently, IDEICE has been promoting use of the data to professors, students, and researchers.
This has resulted in fragmentation and poor coordination of professional development. Half of school headmasters claim that absence of one comprehensive database describing training courses is a major obstacle in efficient planning of in-service teacher training (Balti Uuringute Instituut [BUI] 2015). According to existing regulations, a teacher must take 160 hours of training within five years. This system is criticized by many parties including teachers themselves because this focus on hours of training does not meet actual needs for professional development  (Roon 2014).
The book also contains two chapters related to the ICCS 2009 results. These chapters consider the following topics: • The Italian results in the European Module: This chapter is focused on cognitive test scores and the ICCS 2009 questions about attitudes towards Europe and compares them with those of the other European countries participating in the survey (Caponera and Palmerio 2018); • Students' perceptions of multiple identities, their attitudes towards European institutions and their trust in national, European, and supranational entities: The results show that most students consider themselves to be Europeans and hold positive attitudes towards the European Union and international organizations  (Damiani 2018 ). An agreement has recently been signed between the Italian National Institute of Statistics (ISTAT) and INVALSI under which INVALSI will provide ISTAT-one of the main points of reference for any researcher intending to do secondary analyses-with Italy's ICCS 2016 database, as well as the other international survey's databases.
Štrajn, personal communication, August 8, 2019). We can say that the changes brought about by political independence were relatively gradual in moving toward citizenship education suitable for an independent Slovenia. In fact, Slovenia participated in all cycles of the CIVED/ICCS study. Moreover, those coordinating CIVED or/and ICCS or using those datasets, have been actively involved in curricular reforms, in writing/editing syllabi and textbooks for compulsory subjects on CCE, in university lecturing, and in designing workshops for teachers. One researcher was even involved in the preparation of two coalition agreements between political parties that formed a government. This justifies our belief that CIVED/ICCS has had an impact on the development of CCE in Slovenia; the challenge is to define the nature of both the direct and indirect "impact.
In another indication of impact, the Ministry of Education, Science and Sport adopted a National framework for identifying and assuring quality in education (  2017 ), in which the monitoring of compulsory systemic indicators is envisaged and listed all existing IEA studies including ICCS. For the purpose of this chapter, the titles of professional publications (monographs, articles, and national research reports) in the Slovene language that made an explicit reference to ICCS in the title (also for master's/bachelor's thesis in the key words) were identified from the national database Cobiss. We can assume that those publications could also have "impacts" on national policymaking or practices in teaching, due to the open source and publication in the national language (however, daily newspaper articles or conference presentations are not included in our analysis).