dataesr/scientific-paragraphs-categorization huggingface dataset:
Spade outline We have developed Spade, a system that provides users with top-k most interesting aggregate queries identified automatically in a given RDF graph. For instance, from the Foodista dataset, Spade recommends "the number of recipes by category" (Figure  2(a) ) and "the number of recipes by ingredient and category" (Figure  2 (b)). Fig- ure 2(b) is interesting as there is a peak of sugar usage in fruits and desserts (the two yellow cells), leading to a huge variance among ingredients/categories. Users may further refine a given aggregate, e. g. , selecting the dessert category allows zooming on its semantic subclass thaiDesserts etc. Inspired by classical data warehousing, we define a (potentially multi-dimensional) aggregate centered around a set of facts, which are nodes of the RDF graph, e.
In the third case, the summary divides RDF graph nodes in equivalence classes based on flexible criteria on their incoming/outgoing properties and/or their types (when present). Nodes in the same class tend to have many common properties, making them interesting candidates to be analyzed together as a CFS. Other CFS selection criteria, e. g. based on another summary or the results of a given query, can be easily plugged in here. Next, for each CF, Direct Properties and Derived Properties are Enumerated to obtain all possible CF attributes. The (possibly missing, or multiple) values of these attributes are computed for each CF and stored in the RDF database (RDF-DB in Figure  3 ). A null is used to record absent values. Spade derives the following properties: (i) counts, e. g. , how many ingredients a recipe has; (ii) keywords, e.
DEMONSTRATION SCENARIOS We will use publicly available graphs, including: Foodista; NobelPrizes 4  (90K triples) and DBLPArticle (20M triples)  5. The RDFQuotient summary is shown as a first overview of the data as it provides a quick glance on their content and might inspire users during the demonstration steps. Our interactive scenarios enable users to get insights from large RDF graphs, refine them and deepen their analysis through semantic-based roll-ups and drill-down. • MDA recommendation Users choose a dataset, an IF and k, the number of desired aggregates, and visualize the top-k results. A specific CFS, among those found by Spade, can also be chosen. • Customized CFS selection Guided by the summary, users can select nodes and/or properties to specify a customized set of data. Resources that comply with the given criteria will be considered as a CFS and processed by Spade.
High-resolution 3D modeling is enabled by the SeisSol software package that couples seismic wave propagation with frictional fault failure and off-fault inelasticity, and is optimized for high-performance computing (see "Numerical method" in Methods section). The resulting dynamic model of the Kaikōura earthquake sheds light on the physical mechanisms of cascading ruptures in complex fault systems. Our model reproduces key characteristics of the event and constraints puzzling features including a large gap separating surface rupture traces, the possibility of significant slip on the subduction interface, the non-rupture of the Hope fault, and slow apparent rupture speed. We show that the observed rupture cascade is dynamically consistent with regional stress estimates and a crustal fault network geometry inferred from seismic and geodetic data under the assumption of low apparent friction.
Teleseismic data. Our model without slip on the subduction interface satisfactorily reproduces long-period teleseismic data. Synthetics are generated at five teleseismic stations around the event (Fig. 8 ). We translate the dynamic fault slip time histories of our model into a subset of 40 double couple point sources. From these sources, broadband seismograms are calculated from a Green's function database using Instaseis  47  and the PREM model for a maximum period of 2 s including anisotropic effects. In the long period range considered (100-450 s) the fit to observations is satisfying (Fig. 10 ). The effect of gravity, significant for surface waves at those periods, is not accounted for in the synthetics due to methodological limitations of Instaseis. In conjunction with our restriction to the 1D PREM model instead of incorporating 3D subsurface information, remaining differences between synthetics and observed records are expected.
Methods Numerical method. We solve the coupled dynamic rupture and wave propagation problem using the freely available software SeisSol  56, 57  (https://github. com/SeisSol/ SeisSol) based on the Arbitrary high-order accurate DERivative Discontinuous Galerkin method (ADER-DG). SeisSol employs fully adaptive, unstructured tetrahedral meshes to combine geometrically complex 3D geological structures, nonlinear rheologies, and high-order accurate propagation of seismic waves. Our model (Fig. 3 ) includes a geometrically complex fault network, high-resolution topography  58  , 3D subsurface structure  59  , and plastic energy dissipation off the fault  60, 61. A high-resolution model is crucial for accurately resolving rupture branching and (re-)nucleation processes. The degree of realism and accuracy achieved in this study is enabled by recent computational optimizations targeting strong scalability on many-core CPUs  [62] [63] [64]  and a ten-fold speedup owing to an efficient local time-stepping algorithm  37.
Acknowledgements The work presented in this paper was supported by the  German Research Foundation (DFG)  (projects no. KA 2281/4-1 ,  GA 2465/2-1 ,  GA 2465/3-1 ), by  BaCaTec  (project no. A4 ), by  KONWIHR-the Bavarian Competence Network for Technical and Scientific High-Performance Computing  (project  NewWave ), by the  Volkswagen Foundation  (ASCETE, grant no. 88479 ), by  KAUST-CRG (GAST , grant no. ORS-2016-CRG5-3027  and FRAGEN, grant no. ORS-2017-CRG6 3389. 02 ), by the  European Union 's  Horizon 2020 research and innovation program  ( ExaHyPE , grant no. 671698  and  ChEESE , grant no. 823844 ), by  NSF   CAREER award   EAR-1151926 , by the  French government  through the  UCAJEDI Investments  in the  Future  project  ANR-15-IDEX-01  managed by the  National Research Agency (ANR) , by the  Hong Kong Polytechnic University   startup grant  ( 1-ZE6R ), and by the Hong.
Data availability The authors declare that all data supporting the findings of this study are available within the paper and its Methods section. In particular, all data required to run a simulation of the Kaikōura earthquake can be downloaded from https://zenodo. org/record/2538024. We provide a detailed readme file summarizing the data and data formats provided. We used the following projection: WGS 84/UTM Mercator 41 (EPSG:3994).
Faults in software implementations target both data and instructions at different locations. Bellcore attack is a well-known fault attack that is able to break CRT-RSA. In response, cryptographic libraries such as OpenSSL are designed with protection. In this paper, new faults locations are shown on OpenSSL implementation of the CRT-RSA signature running on Intel and ARM processors. Among those faults, one restores the Bellcore attack on the OpenSSL library despite a protection and another is a complete new fault that exploits the OpenSSL protection to get RSA private key. Quite surprisingly, one of the exhibited faults is, ironically enough, made possible because of the existence of such protection. Mbedtls library is also analysed in this paper. A way to find all exploitable faults on monobit flip fault model is also detailed.
Introduction Fault attacks against cryptographic implementations consist in triggering anomalies during the execution of a program in order to retrieve sensitive data such as cryptographic keys. Dan Boneh et al. [6]  demonstrated the feasibility of such attack on RSA signature that use the Chinese Remainder Theorem (CRT). They have shown that faulting a computation of the signature modulo p or q allows an attacker to retrieve the RSA private key. This attack, known as Bellcore attack, is not possible if a fault occurs on both computations of signatures modulo q and modulo p. Christian Aumller et al. [2]  have shown that the fault can also occur after the signatures modulo p or q are computed, namely when they are used in the recombination stage.
Daniel Gruss et al. [15]  show the possibility to use this attack remotely, using high precision timers available on JavaScript. Pierre Carru  [10]  shows that even in a trusted execution environment using TrustZone, a cryptosystem can be broken by rowhammer. More general faults on cryptographic applications like the one exposed by Éric Brier et al. [7]  on CRT-RSA are also exposed to rowhammer attack on the public elements of the cryptosystem, such as its modulus. Our paper reports that a naïve bit-reset analysis of a cryptographic library suffices to find relevant fault locations. However, more sophisticated tools would greatly help to better identify more numerous weaknesses. For example, Marie-Laure Potet et al. [20]  use symbolic and concolic execution to find exploitable faults that rely on modifying the control flow of a software.
Instruction structure In order to be able to understand the fault that are described in this paper, the structure of some instructions has to be formulate. For Intel processor, only a mov instruction is interesting. This instruction have the following structure mov OFF(%REG BASE),%REG DEST, in which %REG DEST is the register where the read data will be stored to and where OFF(%REG BASE) is the AT&T syntax that indicates that the data to be read is located at address %REG BASE+OFF, where REG BASE is a register that contains a memory address and OFF is an offset value. For example a local variable of a function can be read related to the stack frame register rbp as follows: mov -0x14(%rbp),%rax. On ARM processor, this paper focus on five classes of instructions that are briefly describe here.
Faults research automation Despite this paper aim is not to release a fault analysis tool, this section gives the methodology used to find the exploitable faults described in the next section. In this aim, a signature oracle and a control process are required. On the one hand, the signature oracle process aim is to sign a message with a faulted OpenSSL cryptographic library. On the other side, the control process is responsible for creating a fault. More specifically, the fault consists in flipping a bit from 1 to 0 (or from 0 to 1 depending of the model) in OpenSSL cryptographic library. text section, and run the signature oracle process using fork() and execv() POSIX functions available on GNU Linux Operating System. The fault is simulated by modifying directly the bits in the OpenSSL file on the hard disk.
-Step 4: Attack. If Alg. 6 returns success, then the attacker has successfully installed an APT (Advanced Persistent Threat), that is a permanent fault in the code (until restart of OpenSSL). Thus the attacker quickly launches signatures, collects there erroneous results, and executes the GCD attack of Eqn. (1) using genuine signatures collected at step 2. Note that the rowhammer attack requires cache eviction to force the CPU to read data in DRAM instead of the cache.
Mitigation Even though fault attacks are usually complex to thwart in practice, mitigations still exist. First, data scrubbing can be applied to check whether some instructions in memory are corrupted. This solution consists in a parallel task that periodically looks for errors by comparing potential faulted instructions with a clean version of them. However, this incurs memory and time consumption overheads. Alternatively, since the faults described in this paper alter target function parameters, using inline functions could be used to mitigate the faults. Using PSS padding should also be considered to mitigate our faults. Finally, since the fault on BN div is due to the attempt of OpenSSL to correct it, a recommendation could be to return an error when CRT-RSA was badly computed instead of trying to correct it.
Models of such solutions are essential to explore the interactions between consumption, production, and transportation as well as economic, environmental and technical phenomena. Multi-agent systems (MAS) can contribute to explore and develop such solutions since MAS can simulate how multiple stakeholders work, interact, and influence each other. The MAS simulations make it possible to simulate systems which consist of agents with different or conflicting objectives. Agents often collaborate towards a specific goal and need to communicate and share results. Different languages and vocabularies are domain-specific, and often cause problems for the agents in a system. It requires a common language to ensure that messages are interpreted correctly between agents  [3]. Therefore, ontology can be applied to establish effective communication between agents.
Method The study is designed to compile the relevant contributions from previous publications and to analyze their results in relation to multi-agent modeling design for the energy domain. This study firstly conducts a literature search of ontologies and multi-agent systems for the energy domain. The literature search was performed during the first quarter of 2019. To retrieve the relevant articles for this literature study, four online databases are selected that are relevant in the fields of energy, and MAS and ontologies: ACM digital library, IEEE Xplore, Web of Science, ScienceDirect. The review covers books, conference proceedings, academic journal articles, research articles, and review articles. Other forms of publications, such as newspapers, posters, etc. , were not considered since their publication forms are not for scientific research purposes.
There was no limitation on the publication years for the literature search. The data collection was divided into three rounds with relevant keywords. The keyword search was only applied to titles due to a large number of the literature in the fields and the concerns of the relevance in the selected domains. The first round focused on the multi-agent systems in the energy domain. To avoid excluding any relevant study, the search strings were: ('multi-agent' OR 'multiagent') AND ('energy' OR 'electricity' OR 'heating' OR 'grid' OR 'electric' OR 'power' OR 'wind  ')  The strings, in the first round, resulted in 1433 publications. The result from each database is shown in Table  1. All these 1433 publications were imported to the reference management software-Endnote (https://endnote. com/). To dismiss the duplicated publications, i.
e. , articles which were obtained through multiple databases or strings, 856 articles were removed by this criterion. The remaining 577 articles were selected for further analysis. This study searched the remaining articles with 'ontology' OR 'ontologies' in titles, abstracts, and keywords, and resulted in 24 articles with full-text. Based on the text mining in the analysis software NVivo (https://www. qsrinternational. com/nvivo/ home) and careful review, the 24 articles were separated into six sub-domains (shown in Table  2 ). Majority of the selected articles only address one sub-domain, and one article  [8]  addresses three sub-domains (energy management, microgrid, and buildings), and another article  [9]  addresses two sub-domains (power system and microgrid). The publications show that the application of ontologies in the field of MAS for the energy domain was mainly conducted after the year 2004, with focus on the sub-domain of grid control between 2004 to 2014, and expanded into the sub-domain of electricity market since 2014.
Multi-agent-based modeling techniques have been used to integrate real-time intelligent decision-making in building control. For instance, an indoor environment that actively supports its inhabitants can be created with these techniques  [57]. These modeling techniques also include unpredictable user-behavior, fluctuating weather conditions, and grid imbalances  [52, 58]. For instance, the study by Anvari-Moghaddam et al. [52]  demonstrates how MAS is used to optimize management strategies for a building through computer simulations in combination with third-party software such as MATLAB and GAMS. Hence, studies show that energy consumption can be reduced without compromising the inhabitants' comfort level in residential buildings. In the study  [52] , a smart grid is simulated with several residential buildings, conventional and RES.
MAS Interoperability and Ontology In a MAS, it is important to set up a communication language for meaningful conversations between agents. The agents communicate through message exchange so-called Agent Communication Language (ACL). ACL is the existing interaction language standard for exchanging knowledge between agents. For a given Communication act «F(P)», the «F» part refers to the MAS and is regulated by the ACL standard, and the «P» refers to the domain knowledge. In our case, «P» refers to the «Energy Domain» or the «Energy Ontology»  [114]. However, even an agent development environment supporting the same Agent Communication Language (ACL) and content language are implemented in two MASs, it does not mean that the agents in the two MASs can share any useful information because different ontologies are used in the two MASs  [91].
As more applications of MAS in the energy domain for advanced functions and MASs are not expected to operate in isolation from each other, the interoperability challenge raises due to an increasing requirement for data and information exchange between systems. Therefore, there is a need for full interoperability and open standards for the MASs in the energy domain  [91]. The interoperation issues of existing multi-agent systems have highlighted in the literature, particularly the issues of the use of different ontologies. Meanwhile, it is important to establish the same language, especially a common ontology for the communication between agents.
Standards for agent communication and interoperability A standard for the communication between agents has been proposed by the Foundation for the Intelligent Physical Agent (FIPA  [116]. The FIPA standards have been popularly used by MAS developers in the computer science community and FIPA was formally accepted as a standards committee of the IEEE Computer Society In 2005  [109]. Such standardization promotes open specifications for the interoperability between agents and MAS  [117]. The FIPA standards include specifications for the agent communication language, communicative acts, content languages, and message transport protocols. It also includes a standard that proscribes the agents that a MAS must implement to be FIPA compliant The FIPA-ACL specifies the syntax, the content of the message provides the semantics of the message including the content language and the ontology  [118].
The messages built under the ACL structure allow the definition of various elements (e. g. , performative, sender, receiver, content, language, and ontology, among others) and various communicative acts (e. g. , agree, cancel, confirm, not-understood, etc. )  [9]. Meanwhile, the correct interpretation of the meaning of the message is assured, the ambiguity is removed about the content  [21]. The MASs in  [3, 47, 48, 52]  all apply the FIPA-ACL. There are other ACL investigated in the literature as well  [119, 120] , e. g. , Open Agent Architecture (OAA) in the work of Praca et al. [42]. MASs developed by different platforms can interoperate with these FIPA standards, but it doesn't mean that useful information can be shared between agents if the MASs employ different ontologies  [21, 91]. It requires MASs share a common vocabulary, so the messages may be interpreted correctly among agents  [47].
The design of internal agent behavior and interaction in a MAS mainly concerns the agent communication models as in the majority of the selected literature. The design of agent communication usually includes messages (message content) and message exchange (protocol). Messages and protocol are usually described in the UML diagrams as class diagrams and sequence diagrams, e. g. , in  [20] , the communication sequence and communication parameters are introduced. The content of a message comprises two parts: content language (provides the syntax or grammar of the content) and ontology (consists of the semantics or lexicon of a message)  [91]. The ontology-based agent communication model can be shown in Figure  8. MAS developers usually use JADE to create agents because JADE agents communicate by exchanging message in compliance with the FIPA ACL.
The FIPA Semantic Language (FIPA-SL) is popularly adopted as the standard content language  [123]. In FIPA-SL, an ontology comprises a list of concepts, predicates, and actions specific to the domain of communication. However, the structures of ontologies in the selected literature are different. For instance, the ontology in  [124]  is defined in the form of EBNF and includes seven parts (policy, modality, trigger, subject, behavior, target, and constraint), and the ontology in  [20]  contains four parts (ID, type, parameter, and value). When designing a MAS, developers usually introduce the syntax and semantics of the domain ontologies and application-specific ontologies applied in the MAS and describe the purposes and functions of the ontologies. For instance,  [124]  applies a policy ontology in their MAS.
This mechanism should allow information and knowledge sharing. At the same time, the system should be flexible to deal with several processes. Therefore, a communication standard should be defined, ensuring that agents in the system use terms with the same meanings  [129]. The FIPA is the de facto standard for agent development  [9]. FIPA provides different interoperability standards, e. g. , the standard agent communication language (FIPA-ACL), which make it possible to integrate different MASs  [130]. However, it does not mean that agents belonging to different MASs can share any useful information if the MASs use different ontologies. The ACL provides a framework for the communication standardization between agents, but the standard only defines the structure of messages and interactions.
Meanwhile, Luncean et al. [131]  states that "An ontology is used to represent knowledge that is shared between different entities. It provides terms and vocabulary used to represent knowledge so that both sender and receiver can understand" Several ontologies already exist in the energy field. In  [16, 52] , the main goal of ontologies is to support the interactions between energy management of buildings and the smart grid. It is important to mention that the design of an ontology itself does not contribute to energy savings or energy-neutral building environments. However, it brings several benefits to the design of the software process of a MAS. First, it gives a deeper insight into the modeled domain and system functionality. Secondly, it reflects upon the data types and required communication between agents.
Limitations and Future Work This paper applies a transparent scoping review methodology through the entire process. To ensure a broad search of the literature, the search strategy includes four online databases, resulting in over 1400 articles. However, the search result may still not identify all relevant articles in the literature despite this paper attempts to be as comprehensive as possible. Ontology is a recently established word in information science  [71] , therefore, an extension of the literature search including the terms "domain knowledge" and "knowledge representation" may result in additional literature in the field of MAS and ontology. Furthermore, the fields of organizational theory and business ecosystem are not included in this paper because the literature search only focuses on the energy domain.