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Jeusfeld, Manfred A.ORCID iD iconorcid.org/0000-0002-9421-8566
Alternative names
Biography [eng]

anfred Jeusfeld studied computer science (minor Operations Research) from 1980 to 1986 at the University of Technology Aachen (RWTH), Germany.  He worked on development support for database applications and on foundations of deductive & object-oriented databases. In 1992 he received his Doctoral degree in Natural Sciences from the University of Passau.


Dr. Jeusfeld has published more than 20 journal articles (Information Systems, DSS, JIIS, SoSYM etc.) and numerous conference articles. He is area editor for the Requirements Engineering Journal. He was co-PC-chair of KRDB-94 to KRDB-97, DMDW-99, DMDW-2000, DMDW-2001, DMDW-2003, ER-2011, and PoEM-2016. He is or has been reviewer for international journals like ACM TOIS, REJ, SoSYM, and conferences including ICIS, ECIS, VLDB, CAiSE, ER and others. He is also the founder of CEUR Workshop Proceedings, a publication service for open-access proceedings of scientific workshops and conferences.

Publications (10 of 49) Show all publications
Kühne, T., Almeida, J. P., Atkinson, C., Jeusfeld, M. A. & Mezei, G. (2023). Field Types for Deep Characterization in Multi-Level Modeling. In: Proceedings 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023: . Paper presented at 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023 (pp. 639-648). IEEE
Open this publication in new window or tab >>Field Types for Deep Characterization in Multi-Level Modeling
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2023 (English)In: Proceedings 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023, IEEE, 2023, p. 639-648Conference paper, Published paper (Refereed)
Abstract [en]

Traditional two-level modeling approaches distinguish between class- and object features. Using UML parlance, classes have attributes which require their instances to have  object slots. Multi-Level Modeling unifies classes and objects to "clabjects", and it has been suggested that attributes and slots can and should be unified to "fields" in a similar way. The notion of deep instantiation for clabjects creates the possibility of "deep fields", i.e., fields that expand on the roles of pure attributes or pure slots. In this paper, we discuss several variants of such a "deep field" notion, pointing out the semantic differences and the various resulting trade-offs. We hope our observations will help clarify the range of options for supporting clabject fields in multi-level modeling and thus aid future MLM development.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
multi-level modeling, attribute definition
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-23275 (URN)10.1109/MODELS-C59198.2023.00105 (DOI)001137051500086 ()2-s2.0-85182398999 (Scopus ID)979-8-3503-2499-0 (ISBN)979-8-3503-2498-3 (ISBN)
Conference
2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023
Available from: 2023-10-03 Created: 2023-10-03 Last updated: 2024-02-09Bibliographically approved
Jiang, Y., Jeusfeld, M. A., Ding, J. & Sandahl, E. (2023). Model-Based Cybersecurity Analysis: Extending Enterprise Modeling to Critical Infrastructure Cybersecurity. Business & Information Systems Engineering, 65(6), 643-676
Open this publication in new window or tab >>Model-Based Cybersecurity Analysis: Extending Enterprise Modeling to Critical Infrastructure Cybersecurity
2023 (English)In: Business & Information Systems Engineering, ISSN 2363-7005, E-ISSN 1867-0202, Vol. 65, no 6, p. 643-676Article in journal (Refereed) Published
Abstract [en]

Critical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid.

Place, publisher, year, edition, pages
Springer Nature Switzerland AG, 2023
Keywords
critical infrastructure, domain-specific language, cybersecurity, power grids
National Category
Information Systems
Research subject
Distributed Real-Time Systems; Information Systems
Identifiers
urn:nbn:se:his:diva-22495 (URN)10.1007/s12599-023-00811-0 (DOI)000982391100001 ()2-s2.0-85158156411 (Scopus ID)
Funder
University of Skövde
Note

CC BY 4.0

© 2023 Springer Nature Switzerland AG. Part of Springer Nature.

Paper is partly based on the results of the EU ISF project ELVIRA, his.se/elvira

We thank the colleagues from the ELVIRA project for their contributions to earlier versions of the taxonomy. We are in particular grateful to Yacine Atif for his support and encouragement. Many thanks also to the interview partners for helping to validate the usefulness of our approach. Finally, we thank the anonymous reviewers for their diligent and constructive evaluations

Open access funding provided by University of Skövde.

Available from: 2023-05-07 Created: 2023-05-07 Last updated: 2023-12-13Bibliographically approved
Ralyté, J., Jeusfeld, M. A. & Mohania, M. (2023). Preface - Special Issue on Conceptual Modeling – ER 2022. Data & Knowledge Engineering, 148, Article ID 102231.
Open this publication in new window or tab >>Preface - Special Issue on Conceptual Modeling – ER 2022
2023 (English)In: Data & Knowledge Engineering, ISSN 0169-023X, E-ISSN 1872-6933, Vol. 148, article id 102231Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
Elsevier, 2023
National Category
Computer Sciences Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-23287 (URN)10.1016/j.datak.2023.102231 (DOI)001085278300001 ()2-s2.0-85171886436 (Scopus ID)
Available from: 2023-10-05 Created: 2023-10-05 Last updated: 2023-11-06Bibliographically approved
Kühne, T. & Jeusfeld, M. A. (2023). Sanity-Checking Multiple Levels of Classification: A Formal Approach with a ConceptBase Implementation. In: João Paulo A. Almeida; José Borbinha; Giancarlo Guizzardi; Sebastian Link; Jelena Zdravkovic (Ed.), Conceptual Modeling: 42nd International Conference, ER 2023 Lisbon, Portugal, November 6–9, 2023 Proceedings. Paper presented at 42nd International Conference, ER 2023 Lisbon, Portugal, November 6–9, 2023 (pp. 162-180). Cham: Springer
Open this publication in new window or tab >>Sanity-Checking Multiple Levels of Classification: A Formal Approach with a ConceptBase Implementation
2023 (English)In: Conceptual Modeling: 42nd International Conference, ER 2023 Lisbon, Portugal, November 6–9, 2023 Proceedings / [ed] João Paulo A. Almeida; José Borbinha; Giancarlo Guizzardi; Sebastian Link; Jelena Zdravkovic, Cham: Springer, 2023, p. 162-180Conference paper, Published paper (Refereed)
Abstract [en]

Multiple levels of classification naturally occur in many domains. Several multi-level modeling approaches account for this and a subset of them attempt to provide their users with sanity-checking mechanisms in order to guard them against conceptually ill-formed models. Historically, the respective multi-level well-formedness schemes have either been overly restrictive or too lax. Orthogonal Ontological Classification has been proposed as a foundation that combines the selectivity of strict schemes with the flexibility afforded by laxer schemes. In this paper, we present a formalization of Orthogonal Ontological Classification, which we empirically validated to demonstrate some of its hitherto only postulated claims using an implementation in ConceptBase. We discuss both the formalization and the implementation, and report on the limitations we encountered.

Place, publisher, year, edition, pages
Cham: Springer, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14320
Keywords
multi-level modeling, well-formedness, integrity constraints
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-23337 (URN)10.1007/978-3-031-47262-6_9 (DOI)2-s2.0-85177448606 (Scopus ID)978-3-031-47261-9 (ISBN)978-3-031-47262-6 (ISBN)
Conference
42nd International Conference, ER 2023 Lisbon, Portugal, November 6–9, 2023
Available from: 2023-10-30 Created: 2023-10-30 Last updated: 2023-11-30Bibliographically approved
Kühne, T. & Jeusfeld, M. A. (2023). The MULTI Warehouse Challenge. In: Proceedings 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023: . Paper presented at 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023 (pp. 699-702). IEEE
Open this publication in new window or tab >>The MULTI Warehouse Challenge
2023 (English)In: Proceedings 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023, IEEE, 2023, p. 699-702Conference paper, Published paper (Refereed)
Abstract [en]

The "MULTI" workshop series has set a number of multi-level modeling challenges, each designed to allow competing multi-level modeling approaches to demonstrate their capabilities and/or to tease out their limitations. The challenges therefore have been serving a three-fold purpose: First, they have allowed technologies to demonstrate their abilities. Second, they have pointed out where technologies still fall short of providing optimal modeling support. Third, they have provided a basis for comparing competing technologies, often revealing the trade-offs implied by certain design choices. The MULTI Warehouse Challenge described in this paper is the fourth installment in this series, defining a new unique set of demanding modeling challenges. 

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Multi-level modeling, challenge, MULTI workshop
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-23276 (URN)10.1109/MODELS-C59198.2023.00111 (DOI)001137051500092 ()2-s2.0-85182395273 (Scopus ID)979-8-3503-2499-0 (ISBN)979-8-3503-2498-3 (ISBN)
Conference
2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion MODELS-C 2023, Västerås, Sweden 1-6 October 2023
Available from: 2023-10-03 Created: 2023-10-03 Last updated: 2024-02-09Bibliographically approved
Ralyté, J., Chakravarthy, S., Mohania, M., Jeusfeld, M. A. & Karlapalem, K. (Eds.). (2022). Conceptual Modeling: 41st International Conference, ER 2022, Hyderabad, India, October 17–20, 2022, Proceedings. Paper presented at 41st International Conference, ER 2022, Hyderabad, India, October 17-20, 2022. Cham: Springer Nature Switzerland AG
Open this publication in new window or tab >>Conceptual Modeling: 41st International Conference, ER 2022, Hyderabad, India, October 17–20, 2022, Proceedings
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2022 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

We are pleased to welcome you to the proceedings of the 41st edition of the International Conference on Conceptual Modeling (ER 2022), which took place during October 17–20, 2022. Originally, the conference was planned to take place in the beautiful city of Hyderabad, India, but due to the uncertain COVID-19 situation it was finally held virtually. The ER conference series aims to bring together researchers and practitioners building foundations of conceptual modeling and/or applying conceptual modeling in a wide range of software engineering fields. Conceptual modeling has never been more important in this age of uncertainty. As individuals, organizations, and nations face new and unexpected challenges, software and data must be developed that can cope with and help address this new uncertainty in an ever-faster changing world. Conceptual modeling can be used to describe, understand, and cope with increasing levels of uncertainty in our world. Conference topics of interest include the theories of concepts and ontologies underlying conceptual modeling, modeling languages, methods and tools for developing and communicating conceptual models, and techniques for transforming conceptual models into effective implementations.

Place, publisher, year, edition, pages
Cham: Springer Nature Switzerland AG, 2022. p. xxii, 434
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 13607
Keywords
conceptual modeling, ontology, business process management, data modeling, data analysis
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-21952 (URN)10.1007/978-3-031-17995-2 (DOI)978-3-031-17995-2 (ISBN)978-3-031-17994-5 (ISBN)
Conference
41st International Conference, ER 2022, Hyderabad, India, October 17-20, 2022
Note

© 2022 Springer Nature Switzerland AG. Part of Springer Nature.

Available from: 2022-10-13 Created: 2022-10-13 Last updated: 2023-08-23Bibliographically approved
Jeusfeld, M. A., Mezei, G. & Bácsi, S. (2022). DeepTelos and DMLA – A Contribution to the MULTI 2022 Collaborative Comparison Challenge. In: MODELS ’22 Companion Proceedings: . Paper presented at MULTI 2022 Workshop co-located with ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems, 23-28 October 2022, Montréal, Canada (pp. 1-10). ACM Publications
Open this publication in new window or tab >>DeepTelos and DMLA – A Contribution to the MULTI 2022 Collaborative Comparison Challenge
2022 (English)In: MODELS ’22 Companion Proceedings, ACM Publications, 2022, p. 1-10Conference paper, Published paper (Refereed)
Abstract [en]

The MULTI 2022 Collaborative Comparison Challenge was created to promote in-depth discussion between multi-level modeling approaches. This paper presents a comparison of DeepTelos- and DMLA-based solutions in response to the challenge. We first present each approach and solution separately, and then list the similarities and differences between the two solutions, discussing their relativestrengths and weaknesses. 

Place, publisher, year, edition, pages
ACM Publications, 2022
Keywords
Model development and analysis, Modeling methodologies, Domain specific languages
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-21763 (URN)10.1145/3550356.3561602 (DOI)2-s2.0-85142923275 (Scopus ID)978-1-4503-9467-3 (ISBN)
Conference
MULTI 2022 Workshop co-located with ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems, 23-28 October 2022, Montréal, Canada
Note

CC BY 4.0

The work of Sándor Bácsi and Gergely Mezei presented in this paper has been carried out in the frame of project no. 2019-1.1.1-PIACI-KFI-2019-00263, which has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the 2019-1.1. funding scheme.

Available from: 2022-09-04 Created: 2022-09-04 Last updated: 2022-12-08Bibliographically approved
Jeusfeld, M. A. (2022). Evaluating DeepTelos for ConceptBase: A Contribution to the Multi-Level Process Challenge. Enterprise Modelling and Information Systems Architectures, 17(5), 5:1-5:25
Open this publication in new window or tab >>Evaluating DeepTelos for ConceptBase: A Contribution to the Multi-Level Process Challenge
2022 (English)In: Enterprise Modelling and Information Systems Architectures, ISSN 1866-3621, Vol. 17, no 5, p. 5:1-5:25Article in journal (Refereed) Published
Abstract [en]

The process modeling challenge provides an opportunity to compare various approaches to multi-level conceptual modeling. In particular, the challenge requests the definition of constructs for designing process models plus the facilities to create process models with these constructs, and to analyze the execution of such processes, all in one multi-level model. In this paper, we evaluate the performance of DeepTelos in solving the challenge. DeepTelos is an extension of the Telos modeling language that adds a small number of rules and constraints to the Telos axioms in order to facilitate multi-level modeling by means of so-called most-general instances, a variant of the powertype pattern. We present the technology behind DeepTelos and address the individual tasks of the process modeling challenge. A critical review discusses strengths and weaknesses exposed by the solution to the challenge.

Place, publisher, year, edition, pages
Bonn, Germany: German Informatics Society (GI), 2022
Keywords
Multi-level modeling, Telos, Process Modeling, ConceptBase, Datalog
National Category
Software Engineering
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-21202 (URN)10.18417/emisa.17.5 (DOI)000808681300001 ()2-s2.0-85142934579 (Scopus ID)
Note

CC BY-SA 4.0

Available from: 2022-06-04 Created: 2022-06-04 Last updated: 2023-08-22Bibliographically approved
Morshedzadeh, I., Ng, A. H. C., Jeusfeld, M. A. & Oscarsson, J. (2022). Managing virtual factory artifacts in the extended PLM context. Journal of Industrial Information Integration, 28, Article ID 100369.
Open this publication in new window or tab >>Managing virtual factory artifacts in the extended PLM context
2022 (English)In: Journal of Industrial Information Integration, ISSN 2467-964X, E-ISSN 2452-414X, Vol. 28, article id 100369Article in journal (Refereed) Published
Abstract [en]

Virtual engineering increases the rate of and diversity of models being created; hence requires maintenance in a product lifecycle management (PLM) system. This also induces the need to understand their creation contexts, known as historical or provenance information, to reuse the models in other engineering projects. PLM systems are specifically designed to manage product- and production-related data. However, they are less capable of handling the knowledge about the contexts of the models without an appropriate extension. Therefore, this research proposes an extension to PLM systems by designing a new information model to contain virtual models, their related data and knowledge generated from them through various engineering activities so that they can be effectively used to manage historical information related to all these virtual factory artifacts. Such an information model is designed to support a new Virtual Engineering ontology for capturing and representing virtual models and engineering activities, tightly integrated with an extended provenance model based on the W7 model. In addition, this paper presents how an application prototype, called Manage-Links, has been implemented with these extended PLM concepts and then used in several virtual manufacturing activities in an automotive company.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Virtual model, Product Lifecycle Management, Information model, knowledge management, Ontology
National Category
Production Engineering, Human Work Science and Ergonomics Information Systems
Research subject
Production and Automation Engineering; Information Systems; VF-KDO
Identifiers
urn:nbn:se:his:diva-21198 (URN)10.1016/j.jii.2022.100369 (DOI)000822941700006 ()2-s2.0-85136279404 (Scopus ID)
Funder
Knowledge Foundation, 20140330
Note

CC BY 4.0

Available online 2 June 2022, 100369

Corresponding author: Iman Morshedzadeh

This work was supported by the Knowledge Foundation (KKS) through the IPSI Research School at the University of Skövde [grant number 20140330], and VF-KDO Profile research project [grant number 20180011].

Available from: 2022-06-02 Created: 2022-06-02 Last updated: 2023-02-22Bibliographically approved
Jeusfeld, M. A., de Lara, J. & Mezei, G. (2022). Preface to the 9th International Workshop on Multi-Level Modelling (MULTI 2022). In: MODELS ’22 Companion Proceedings: . Paper presented at MULTI 2022 Workshop co-located with ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems, 23-28 October 2022, Montréal, Canada. ACM Publications
Open this publication in new window or tab >>Preface to the 9th International Workshop on Multi-Level Modelling (MULTI 2022)
2022 (English)In: MODELS ’22 Companion Proceedings, ACM Publications, 2022Conference paper, Published paper (Other academic)
Abstract [en]

Multi-level modeling (MLM) represents a significant extension to the traditional two-level object-oriented paradigm with the potential to dramatically improve upon the utility, reliability and complexity of models. Different from conventional approaches, theyallow for an arbitrary number of classification levels and introduce other concepts that foster expressiveness, reuse and adaptability. A key aspect of the MLM paradigm is the use of entities that are simultaneously types and instances, a feature which has consequences for conceptual modeling, language engineering and for the development of model-based software systems.

Place, publisher, year, edition, pages
ACM Publications, 2022
Keywords
multi-level modeling
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-21764 (URN)10.1145/3550356 (DOI)2-s2.0-85142932629 (Scopus ID)978-1-4503-9467-3 (ISBN)
Conference
MULTI 2022 Workshop co-located with ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems, 23-28 October 2022, Montréal, Canada
Available from: 2022-09-04 Created: 2022-09-04 Last updated: 2023-08-23Bibliographically approved
Projects
Virtual factories with knowledge-driven optimization (VF-KDO); University of Skövde; Publications
Nourmohammadi, A., Fathi, M. & Ng, A. H. C. (2024). Balancing and scheduling human-robot collaborated assembly lines with layout and objective consideration. Computers & industrial engineering, 187, Article ID 109775. Lind, A., Iriondo Pascual, A., Hanson, L., Högberg, D., Lämkull, D. & Syberfeldt, A. (2024). Multi-objective optimisation of a logistics area in the context of factory layout planning. Production & Manufacturing Research, 12(1), Article ID 2323484. Barrera Diaz, C. A., Nourmohammadi, A., Smedberg, H., Aslam, T. & Ng, A. H. C. (2023). An Enhanced Simulation-Based Multi-Objective Optimization Approach with Knowledge Discovery for Reconfigurable Manufacturing Systems. Mathematics, 11(6), Article ID 1527. Lind, A., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2023). Digital support for rules and regulations when planning and designing factory layouts. Procedia CIRP, 120, 1445-1450Redondo Verdú, C., Sempere Maciá, N., Strand, M., Holm, M., Schmidt, B. & Olsson, J. (2023). Enhancing Manual Assembly Training using Mixed Reality and Virtual Sensors. Paper presented at 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '23, Gulf of Naples, Italy, 12 - 14 July 2023. Procedia CIRPLind, A., Hanson, L., Högberg, D., Lämkull, D. & Syberfeldt, A. (2023). Extending and demonstrating an engineering communication framework utilising the digital twin concept in a context of factory layouts. International Journal of Services Operations and Informatics, 12(3), 201-224Danielsson, O., Syberfeldt, A., Holm, M. & Thorvald, P. (2023). Integration of Augmented Reality Smart Glasses as Assembly Support: A Framework Implementation in a Quick Evaluation Tool. International Journal of Manufacturing Research, 18(2), 144-164Smedberg, H. & Bandaru, S. (2023). Interactive knowledge discovery and knowledge visualization for decision support in multi-objective optimization. European Journal of Operational Research, 306(3), 1311-1329Smedberg, H. (2023). Knowledge discovery for interactive decision support and knowledge-driven optimization. (Doctoral dissertation). Skövde: University of SkövdeSmedberg, H., Bandaru, S., Riveiro, M. & Ng, A. H. C. (2023). Mimer: A web-based tool for knowledge discovery in multi-criteria decision support. IEEE Computational Intelligence Magazine
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-9421-8566

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