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Publications (10 of 64) Show all publications
Jägare, V., Karim, R., Juntti, U. & Söderholm, P. (2019). A framework for testbed concept in railway. In: PROCEEDINGS: International Heavy Haul Association Conference June 2019: . Paper presented at International Heavy Haul Association (IHHA) STS 2019 Conference (pp. 986).
Open this publication in new window or tab >>A framework for testbed concept in railway
2019 (English)In: PROCEEDINGS: International Heavy Haul Association Conference June 2019, 2019, p. 986-Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

One major prerequisite for an effective implementation and innovation process is the enablement and provision of a collaborative environment. A common area for multi-organisational collaboration together with a technology platform, enabling data sharing and Big Data Analytics, has been developed called ‘Testbed Railway’ with a corresponding framework ‘Railway 4.0’. Testbed Railway can be used to strengthen the railway industry's adaptability and competitiveness by developing and providing a testbed for research and innovation in the rail industry, nationally and internationally.

Keywords
Testbed Railway, Implementation of innovations, Multi-organisational collaboration
National Category
Transport Systems and Logistics Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-75968 (URN)9780911382709 (ISBN)
Conference
International Heavy Haul Association (IHHA) STS 2019 Conference
Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2019-10-22
Stenström, C. & Söderholm, P. (2019). Applying Eurostat’s ESS handbook for quality reports on railway maintenance data. In: Proceedings of the International Heavy Haul Association STS Conference (IHHA 2019): . Paper presented at International Heavy Haul STS Conference 2019, 10th – 14th June, Narvik, Norway (pp. 473-480).
Open this publication in new window or tab >>Applying Eurostat’s ESS handbook for quality reports on railway maintenance data
2019 (English)In: Proceedings of the International Heavy Haul Association STS Conference (IHHA 2019), 2019, p. 473-480Conference paper, Published paper (Refereed)
Abstract [en]

The importance of data quality has become more evident with the digitalization trend and development of new asset management frameworks. Digitalization has changed maintenance work by an increasing share of condition monitoring and digitalized work order processes, which for rail infrastructure and rolling stock give rise to data sets qualifying as big data. Asset management in turn, has progressed significantly the last decades as a response to digitalization, as well as due to a changing organisational culture. ISO 55000, perhaps the best known asset management guidelines, has been adapted to railways by UIC (International Union of Railways), and the EU-projects In2Rail and In2Smart. However, the quality of the data collected has become a growing concern that has not been adequately addressed in asset management. In this study, Eurostat’s ESS (European Statistical System) handbook for quality reports has been adapted and applied to railway maintenance data. The results include a case study on data quality reporting and performance indicator specification. Practical implications are believed to be that the study will support a more structured process towards data quality management, which in turn can aid decision-making, for example by more accurate cost-benefit analysis of preventive maintenance.

Keywords
data quality, quality reporting, quality assurance framework, maintenance, asset management, European Statistical System (ESS), Eurostat, railway
National Category
Reliability and Maintenance Other Civil Engineering
Research subject
Operation and Maintenance; Quality technology and logistics
Identifiers
urn:nbn:se:ltu:diva-75026 (URN)
Conference
International Heavy Haul STS Conference 2019, 10th – 14th June, Narvik, Norway
Available from: 2019-06-26 Created: 2019-06-26 Last updated: 2019-07-08
Jägare, V., Karim, R., Söderholm, P., Larsson-Kråik, P.-O. & Juntti, U. (2019). Change management in digitalised operation and maintenance of railway. In: PROCEEDINGS: International Heavy Haul Association Conference June 2019: . Paper presented at International Heavy Haul Association (IHHA) STS 2019, 10-14th June 2019, Narvik, Norway. (pp. 904-911).
Open this publication in new window or tab >>Change management in digitalised operation and maintenance of railway
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2019 (English)In: PROCEEDINGS: International Heavy Haul Association Conference June 2019, 2019, p. 904-911Conference paper, Published paper (Refereed)
Abstract [en]

Globally, railway is experiencing a major technology transformation (or paradigm shift), triggered by the enhanced utilisation of digital technology. This technological transformation affects not only the technical systems, i.e. railway infrastructure and rolling stock, but also regulations, organisations, processes,and individuals. Hence, hardware, software, but also liveware (i.e. humans) are affected. Today, the digitalisation of railway is characterised by digital services. There are also a range of challenges, e.g. data acquisition,transformation, modelling, processing, visualisation, safety, security, quality, and information assurance. To deal with these challenges, the railway industry needs to define strategies, which enable a smooth transformation of the existing configuration to a digitalised system. Digital railway requires a holistic change management approach based on system-of-systems thinking and a set of appropriate technologies and methodologies. The railway digitalisation strategy should be based on systematic risk management that address aspects of, e.g., information security, traffic safety and project risk. In addition, managing changes for a digitalised railway effectively and efficiently also requires a framework for aspects such as needs finding, requirement identification, and impact of changes for individual, teams and organisation. In this work a major case studywithin the ePilot, has been performed in context of the operation and maintenance processes of the Swedish railway. Therefore, this paper aims to propose a framework for implementing innovations and driving change in a digitalised railway.

Keywords
Change management, digitalisation, railway, risk management, implementing innovation, framework for implementation
National Category
Transport Systems and Logistics Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-75966 (URN)9780911382716 (ISBN)9780911382709 (ISBN)
Conference
International Heavy Haul Association (IHHA) STS 2019, 10-14th June 2019, Narvik, Norway.
Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2019-10-21Bibliographically approved
Bergquist, B. & Söderholm, P. (2017). Improved Condition Assessment through Statistical Analyses: Case Study of Railway Track. Luleå: Luleå University of Technology
Open this publication in new window or tab >>Improved Condition Assessment through Statistical Analyses: Case Study of Railway Track
2017 (English)Report (Other academic)
Abstract [en]

Traditional practice within railway maintenance is based on engineering knowledge and practical experience, which are documented in regulations. This practice is often time-based, but can also be condition-based by combining time-based inspections with condition-based actions depending on the inspection results. However, the logic behind the resulting regulation is seldom well documented, which makes it challenging to optimise maintenance based on factors such as operational conditions or new technologies, methodologies and best practices. One way to deal with this challenge is to use statistical analysis and build models that support fault diagnostics and failure prognostics. This analysis approach will increase in importance as automated inspections replace manual inspections. Specific measurement equipment and trains are not the only ones producing automated measurements; regular traffic is increasingly often producing measurements. Hence, there will not be any lack of condition data, but the challenge will be to use this data in a correct way and to extract reliable information as decision support. In this context, it is crucial to balance the risks of false alarms and unrecognised faults, but also to estimate the quality of both data and information. The purpose of this work is to use statistics in order to support improved asset management, by building statistical models as a complement to physical models and engineering knowledge. The resulting models combine theories from the field of time-series analysis, statistical process control (SPC) and measurement system analysis. Charts and plots present results and have prognostic capabilities that allow necessary track possession times to be included in the timetable. 

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2017. p. 80
Series
Research report / Luleå University of Technology, ISSN 1402-1528
Keywords
Fault Diagnostics, Failure Prognostics, Measurement System Analysis, Statastical Analysis, Statistical Modelling, Time Series Analysis, Statistical Process Control (SPC), Railway Track, Sweden
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-64094 (URN)978-91-7583-937-0 (ISBN)978-91-7583-938-7 (ISBN)
Projects
Fortsättningsprojekt: Förbättrad tillståndsbedömning genom statistisk analys
Funder
Swedish Transport Administration
Available from: 2017-06-16 Created: 2017-06-16 Last updated: 2018-03-16Bibliographically approved
Morant, A., Gustafson, A., Söderholm, P., Larsson-Kråik, P.-O. & Kumar, U. (2017). Safety and availability evaluation of railway operation based on the state of signalling systems (ed.). Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, 231(2), 226-238
Open this publication in new window or tab >>Safety and availability evaluation of railway operation based on the state of signalling systems
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2017 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 231, no 2, p. 226-238Article in journal (Refereed) Published
Abstract [en]

A framework is presented to evaluate the safety and availability of the railway operation, and quantifying the probability of the signalling system not to supervise the railway traffic. Since a failure of the signalling systems still allows operation of the railway, it is not sufficient to study their effect on the railway operation by considering only the failures and delays. The safety and availability are evaluated, handling both repairs and replacements by using a Markov model. The model is verified with a case study of Swedish railway signalling systems with different scenarios. The results show that the probability of being in a state where operation is possible in a degraded mode is greater than the probability of not being operative at all, which reduces delays but requires other risk mitigation measures to ensure safe operation. The effects that different improvements can have on the safety and availability of the railway operation are simulated. The results show that combining maintenance improvements to reduce the failure rate and increase the repair rate is more efficient at increasing the probability of being in an operative state and reducing the probability of operating in a degraded state.

Place, publisher, year, edition, pages
Sage Publications, 2017
National Category
Other Civil Engineering Reliability and Maintenance
Research subject
Operation and Maintenance; Mining and Rock Engineering; Quality Technology & Management
Identifiers
urn:nbn:se:ltu:diva-9431 (URN)10.1177/0954409715624466 (DOI)000394085100008 ()2-s2.0-85009809587 (Scopus ID)80be67df-554a-4524-a31a-4fdc3fcfb204 (Local ID)80be67df-554a-4524-a31a-4fdc3fcfb204 (Archive number)80be67df-554a-4524-a31a-4fdc3fcfb204 (OAI)
Note

Validerad; 2017; Nivå 2; 2017-02-06 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-11-15Bibliographically approved
Söderholm, P. & Nilsen, T. (2017). Systematic risk-analysis to support a living maintenance programme for railway infrastructure. Journal of Quality in Maintenance Engineering, 23(3), 326-340
Open this publication in new window or tab >>Systematic risk-analysis to support a living maintenance programme for railway infrastructure
2017 (English)In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 23, no 3, p. 326-340Article in journal (Refereed) Published
Abstract [en]

Purpose

The purpose of this paper is to describe an application of an effective risk-based methodology to support a living maintenance programme for railway infrastructure.

Design/methodology/approach

The overall research strategy is a single case study of switches and crossings at the Iron Ore Line in northern Sweden. The analysis was performed as a risk workshop guided by a methodology that integrates reliability-centred maintenance and barrier analysis.

Findings

The applied methodology is valuable to systematise and improve the existing maintenance programme, as well as supporting a continued living maintenance programme.

Research limitations/implications

The single case study approach may decrease the validity of the achieved results. However, similar case studies corroborate the results, which affect the validity in a positive way.

Practical implications

The resulting maintenance programme is effective, through compliance with external requirements, and more efficient, through improvements of tasks and intervals.

Social implications

An enhanced railway infrastructure maintenance programme contributes to improved safety, punctuality, and costs. Hence, railway becomes a more attractive mode of transport. Thereby, it also supports a safety performance of the railway that society is willing to pay for.

Originality/value

Significant improvements of the maintenance programme are achieved through adjustment of inspection intervals and tasks. The results also support the development of indicators, monitoring, and continuous improvement.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2017
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-65356 (URN)10.1108/JQME-09-2016-0042 (DOI)2-s2.0-85028023407 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-08-28 (andbra)

Available from: 2017-08-28 Created: 2017-08-28 Last updated: 2018-03-16Bibliographically approved
Bergquist, B. & Söderholm, P. (2016). Measurement System Analysis of Railway Track Geometry Data using Secondary Data (ed.). Paper presented at eMaintenance 2016 : 15/06/2016 - 16/06/2016. Paper presented at eMaintenance 2016 : 15/06/2016 - 16/06/2016.
Open this publication in new window or tab >>Measurement System Analysis of Railway Track Geometry Data using Secondary Data
2016 (Swedish)Conference paper, Oral presentation only (Refereed)
Abstract [en]

In this paper, we use secondary data to make a partial measurement system analysis of railway measurement cars and their obtained track geometry data. When a measurement car passes the same track section shortly after the previous passage, such as returning in the other direction after reaching a railway endpoint, the repeated measurements hold information of the measurement uncertainty of that car. Reasons for the measurement uncertainty can be sought in other variables that also are stored in the database, such as the individual car identity, the type of car, the speed of the car during measurement, and the travelled direction of the car. By also considering other known factors during the time of measurement as regressors, such as ground frost periods, enhanced modelling may be achieved and also indicate if such periods should be avoided to improve the measurement data quality.The results of this study suggest that the type of car had the largest influence on measurement variation out of the studied regressors. If the variation of a track geometry property on a track section is studied, the variation component belonging to the type of car can be deducted, improving data quality. We suggest that the method could also be used to find track sections that are prone to large seasonal variation, such as due to ground frost.

National Category
Reliability and Maintenance
Research subject
Quality Technology and Management; Intelligent industrial processes (AERI); Enabling ICT (AERI); Effective innovation and organisation (AERI); Sustainable transportation (AERI)
Identifiers
urn:nbn:se:ltu:diva-27782 (URN)15180d02-51df-4760-83c7-d0c0ff8d94af (Local ID)15180d02-51df-4760-83c7-d0c0ff8d94af (Archive number)15180d02-51df-4760-83c7-d0c0ff8d94af (OAI)
Conference
eMaintenance 2016 : 15/06/2016 - 16/06/2016
Projects
Statistiska metoder för förbättring av kontinuerliga tillverkningsprocesser
Note
Godkänd; 2016; 20160701 (bjarne)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-03-16Bibliographically approved
Bergquist, B. & Söderholm, P. (2016). Measurement Systems Analysis of Railway Measurement Cars (ed.). Paper presented at International Conference on the Interface between Statistics and Engineering : 20/06/2016 - 23/06/2016. Paper presented at International Conference on the Interface between Statistics and Engineering : 20/06/2016 - 23/06/2016.
Open this publication in new window or tab >>Measurement Systems Analysis of Railway Measurement Cars
2016 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

Purpose: The presentation proposes ways to understand and quantify the variation component due to the measurement system of railway track properties using subsequent runs from measurement cars.Background: Railway infrastructure conditions are commonly inspected by using measurement cars. The measurements are performed with some regularity, and the inspection frequencies could for instance be set taking into account the common train axle loads, railway speed or load bearing classification, number of trains passing, the known railway condition, or the availability of the measurement cars. By combining different inspections of the same track section, it is also possible to monitor the degradation of the infrastructure over time. Often, the railway system is inspected by many measurement cars, and for single tracks, measurements can be obtained from the car travelling in different directions. The measurements are performed at different speeds, related to random variation, but also to the maximum speeds at which the measurement cars operate. The measurements are also afflicted by external variation sources, some of which are acting with a known direction, such as the wear of the track which increases property variation. Maintenance usually (but not always) result in reduced property variation, whereas other sources such as climate related properties such as spring thaw may induce variation over time, but also induce variation that show a periodic behavior with periods with increasing as well as decreasing property variation. This presentation aims to devise a model for how these variation sources may be separated, with the main aim to classify measurement error, but also to estimate the magnitude of other variation sources.Method: No statistically significant differences were found between repeated measurements of cars travelling back and forth on the single track found at the Swedish Iron ore line. These measurements contain measurement error as well as error due to short term degradation and variation due to measurement. As measurement variance is added, it was concluded that the measurement variation could not be larger than the variation shown by repeat measurements. By comparing repeated measurements over time and subtracting variation due to wear, measurement variation for different cars, measurement speeds and measurement directions was estimated using Generalized Linear Models regression analysis. Co-variation between measurement cars and measurement speeds were accounted for using Ridge regression and Elastic Net regression.Results: The regression analysis shows that whereas both measurement speed and the measurement car individuals correlate with the measurement variation obtained, regularized regression points to the measurement cars as the major variation factor and that different measurement cars have different measurement precisionDiscussion and conclusion: The study demonstrates how repeated measurements from regular process data and thus not obtained using the regular and systematic experimental procedures of measurement system analysis can be used for estimation of the variation components of the measurement system. As a side effect, the sizes of other variation sources, external to the measurement system, can be estimated.

National Category
Reliability and Maintenance
Research subject
Quality Technology and Management; Effective innovation and organisation (AERI); Intelligent industrial processes (AERI); Sustainable transportation (AERI); Enabling ICT (AERI)
Identifiers
urn:nbn:se:ltu:diva-40436 (URN)f94ebaca-1c61-47a5-80b6-eb0278051269 (Local ID)f94ebaca-1c61-47a5-80b6-eb0278051269 (Archive number)f94ebaca-1c61-47a5-80b6-eb0278051269 (OAI)
Conference
International Conference on the Interface between Statistics and Engineering : 20/06/2016 - 23/06/2016
Projects
Förbättrad tillståndsbedömning genom statistisk analys
Note
Godkänd; 2016; 20160701 (bjarne)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2018-03-16Bibliographically approved
Bergquist, B. & Söderholm, P. (2016). Predictive Modelling for Estimation of Railway Track Degradation (ed.). In: (Ed.), Uday Kumar; Alireza Ahmadu; Ajit Kumar Verma; Prabhakar Varde (Ed.), Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective. Paper presented at International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015 (pp. 331-347). Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Predictive Modelling for Estimation of Railway Track Degradation
2016 (English)In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadu; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 331-347Conference paper, Published paper (Refereed)
Abstract [en]

The degradation processes affecting railway track condition depends both on the resistance of the track and on the stresses subjected to it. Regarding the stresses, both their magnitudes and cycles are of importance when considering the degradation. Furthermore, the stresses have some regularity and variability in the time domain, while the degradation resistance of a track has some spatial regularity as well as variability. In addition, the condition measurements of track may be both irregular and contain measurement errors. Hence, it is challenging to model the condition of track to enable predictions and condition-based maintenance. However, wear prediction models could help to change large parts of the maintenance practice from predominantly corrective to preventive if both the deterministic and the stochastic components of the wear process can be estimated with sufficient accuracy. In this study, one-step-ahead predictions have been used for establishing prognostic models based on repeated measurements of railway track geometry to estimate track wear properties, degradation rates and stochastic behaviour including measurement errors. The prognostic models have then been used for condition assessment and state predictions. Repeated sampling allows for estimations of measurement errors, but the irregular sampling need to be accounted for by interpolation in the time series modelling approach

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2016
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management; Effective innovation and organisation (AERI); Sustainable transportation (AERI)
Identifiers
urn:nbn:se:ltu:diva-32737 (URN)10.1007/978-3-319-23597-4_24 (DOI)2-s2.0-85043755542 (Scopus ID)7501c3d9-b0a9-4f38-9faa-70788a5a4890 (Local ID)978-3-319-23596-7 (ISBN)978-3-319-23597-4 (ISBN)7501c3d9-b0a9-4f38-9faa-70788a5a4890 (Archive number)7501c3d9-b0a9-4f38-9faa-70788a5a4890 (OAI)
Conference
International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015
Projects
Förbättrad tillståndsbedömning genom statistisk analys
Note
Godkänd; 2016; 20151208 (bjarne)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-03-23Bibliographically approved
Söderholm, P. & Bergquist, B. (2016). Rail breaks: an exploratory case study (ed.). In: (Ed.), Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde (Ed.), Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective. Paper presented at International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015 (pp. 519-541). Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Rail breaks: an exploratory case study
2016 (English)In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 519-541Conference paper, Published paper (Refereed)
Abstract [en]

Rail breaks are safety critical failures within railway that may result in derailment, but also delays and cancelled trains. Maintenance is important to both manage the causes of rail breaks and to reduce their unwanted consequences. The purpose of this study is to explore the relationship between maintenance practice, rail breaks and their consequences, to achieve an increased understanding of the rail break phenomenon and promote continuous improvement. To fulfil the purpose, an explorative case study at Trafikverket (Swedish transport administration) was performed. The empirical data was collected from databases that contains information about preventive and corrective maintenance, as well as traffic and traffic disturbances related to rail breaks. The analysis was founded on theories from the three fields of time series analysis, reliability analysis of repairable systems, and multivariate data analysis. The findings of the study support an increased understanding of the process of rail break development and occurrence, but also related maintenance efforts.

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2016
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management; Sustainable transportation (AERI); Effective innovation and organisation (AERI)
Identifiers
urn:nbn:se:ltu:diva-31699 (URN)10.1007/978-3-319-23597-4_38 (DOI)2-s2.0-85043782348 (Scopus ID)5f50ced9-f5bb-4435-b73d-07a43bf36187 (Local ID)978-3-319-23596-7 (ISBN)978-3-319-23597-4 (ISBN)5f50ced9-f5bb-4435-b73d-07a43bf36187 (Archive number)5f50ced9-f5bb-4435-b73d-07a43bf36187 (OAI)
Conference
International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015
Projects
Förbättrad tillståndsbedömning genom statistisk analys
Note

Godkänd; 2016; Bibliografisk uppgift: Containing selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden, collected by editors with years of experiences in Reliability and maintenance modeling, risk assessment, and asset management, this work maximizes reader insights into the current trends in Reliability, Availability, Maintainability and Safety (RAMS) and Risk Management. Featuring a comprehensive analysis of the significance of the role of RAMS and Risk Management in the decision making process during the various phases of design, operation, maintenance, asset management and productivity in Industrial domains, these proceedings discuss key issues and challenges in the operation, maintenance and risk management of complex engineering systems and will serve as a valuable resource for those in the field. ; 20151208 (bjarne)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-03-23Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-6479-9101

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