Collaborative Intelligent Infrastructure Lab

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About Us

Cities traditionally have been undertaken with static snapshots of infrastructure, population, and technology. Recent advancements in the internet of things (IoT), social networks, and data analytics bring a revolution in the citizen-centric smart grid and smart city management. By integrating real-time sociotechnical data from a variety of sources inside and outside of cities’ systems, we make informed choices about the present and future of cities.

Dr. Reza Arghandeh is the director of CI2 Lab. He is a Professor in the Department of Computer Science, Electrical Engineering, and Mathematical Sciences at the Western Norway University of Applied Sciences, Bergen, Norway. He is also a Research Professor in the Electrical and Computer Department at FAMU-FSU College of Engineering, Florida State University, Tallahassee, USA. He was an assistant professor in the ECE Department, Center for Advanced Power Systems, Florida State University, 2015-2018. Prior to FSU, He was a postdoctoral scholar at the University of California, Berkeley, EECS Dept 2013-2015. He completed his Ph.D. in Electrical Engineering with a specialization in Power Systems at Virginia Tech. He holds Master’s degrees in Industrial and System Engineering from Virginia Tech (2013) and in Energy Systems from the University of Manchester (2008). 

Dr. Eren E. Ozguven is the co-director of CI2 Lab. He is an Associate Professor at the Dept of Civil & Environmental Eng at FAMU-FSU College of Engineering, Florida State University, Tallahassee, USA. Dr. Ozguven holds a Ph.D. degree in Civil and Environmental Engineering from Rutgers University. His research interests include smart cities, urban mobility, traffic safety and reliability, emergency transportation, and intelligent transportation systems.

Research

Data Science for Electricity & Transportation Networks

Transportation, Social and Electricity Networks Data Fusion

As more of the world's cities suffer from congestion, pollution, and energy exploitation, urban mobility remains one of the toughest challenges that cities face as the process of population growth and urbanization continues. So far, the most common approach for urban mobility characterization focuses on vehicle's spatial and temporal positions. However, urban mobility is a multidimensional character of the city life, experienced as tangled layers of interconnected infrastructures and information networks around people and their needs in a spatiotemporal frame. As a result, the study of mobility should go beyond transportation systems, be customer-centered and merged into other physical systems and cyber networks such as electricity networks.

In a collaboration with multiple cities such as Tallahassee, FL, we use data fusion, machine learning, and information theory to provide a mathematical foundation for real-time decision-making tools for urban mobility. 

Data-Driven Diagnostics for Electric Grids  

Electric Grid Event Detection Using Heterogeneous and Spatiotemporal Data   

Traditionally electrical networks have been treated mainly as physical entities that connect electricity suppliers to consumers. However, a modern grid is empowered by the internet of things, distributed generation, and networked computational subsystems to support the incorporation of renewable energy resources, electric vehicles, and energy markets. The induced dynamic and stochastic due to the new paradigm in smart grids require high-resolution measurement and agile decision support techniques for system diagnosis and control. Where muli-stream measurement data come from various sensors in various locations of the network, classical machine learning methods are not the ultimate solution. We are developing multi-task and scalable learning machines for event detection in societal scale systems such electric grids. 

Data-Driven Resilience in Smart Cities 

Characterizing Interoperability of Multi Networks for Resilience

Adversery impacts of large-scale natural and man-made disasters are primarily the result of the inability of city's components such as trasnposration and electricity networks to efficiently cope with random and dynamic changes, which translated into resilience deficiencies while exposing gaps in data availability and data analytics. Therefore, providing optimal and fast infrastructure restoration solutions based on lessons learned and data gathered are critical for governments and emergency responders. However, lack of data due to the shortcoming of monitoring systems in cities and the scarce nature of disasters remains a big challenge for data-driven approaches. We are developing inference and estimation algorithms that can fill the gap in data sparsity and provide integrated resilience for urban infrastructure.  

 
 

Team

Dr. Eren Erman Ozguven

 

CI2 Co-director

Assosiate Professor,

 

Civil and Environmental Engineering Department

FAMU-FSU College of Engineering

Florida State University

Email

 

FSU Webpage: https://www.eng.famu.fsu.edu/~eozguven/

Current Students

Mahyar Ghorbanzadeh

PhD Student

Department of Civil and

Environmental Engineering

 

Florida State University

Email: mg17x@my.fsu.edu

Lalitha Madhavi K.S

PhD Candidate

Department of Electrical and

Computer Engineering

Florida State University

Email: lk14f@my.fsu.edu

Alican Karaer

PhD Student

Department of Civil and

Environmental Engineering

 

Florida State University

Email: ak18k@my.fsu.edu 

Michele Gazzea

PhD Student

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email: Michele.Gazzea@hvl.no 

Atle Føli

MS Student

Department of Comp Sci,  

Electrical Eng, & Math Sci

 

Western Norway Uni of App Sci

Email: 150362@stud.hvl.no

Alumni

Dr. Jose David Cordova

Ph.D. 

Department of Electrical and Computer Engineering

Florida State University

Email: jdc13b@my.fsu.edu

Dr. Mostafa Gilanifar

Ph.D. 

Department of Industrial Engineering

 

Florida State University

Email: mostafa.gilanifar@gmail.com

Dr. Mehmet Baran Ulak

Ph.D. 

Department of Civil and Environmental Engineering

 

Florida State University

Email: baranulag@gmail.com

        Dr. Ayberk Kocatepe

            Ph.D. 

             Connetics Transportation Group

             Email: ak13@my.fsu.edu

Andres Sanchez

MS

Department of Electrical and

Computer Eng

 

 Florida State University

 Email:afs17b@my.fsu.edu

 

Ali Sayghe

PhD

Department of Electrical and Computer Engineering

Florida State University

Email: aas17g@my.fsu.edu

Hasan H. Karabağ

MS

Department of Civil and

Environmental Engineering

Florida State University

Email: karabaghh@gmail.com

XiaoRui Liu

MS

Department of Electrical and

Computer Engineering

 

Florida State University

Email: xl15f@my.fsu.edu

    DongLin Cai

      MS

      Dept of Electrical and Computer          Engineering​

      Email:dc15v@my.fsu.edu

    Davide Pinzan

      Visiting MS Student

      Dept of Electrical Engineering​

     

      University of Padova, Italy

    

    Matthias Stifter

      Visiting PhD Student

      Dept of Electrical Engineering​

     

      Technical University of Vienna, 

      Austria

 

Grants

Information Mining with a Span of Fuzzy and Causality Approaches

Dr. Arghandeh Co-PI, the University and College Network for Western Norway, 2019-2020

GridEyeS - Smart Grid Eye, from Space to Sky

Dr. Arghandeh PI, European Space Agency, 2019-2020

IBM Faculty Award, IoT Technology for Smart Buildings

Dr. Arghandeh PI, IBM, 2018-2019

User-Centered Heterogeneous Data Fusion for Multi-Networked City Mobility UHDNetCity

Dr. Arghandeh PI and Dr. Ozguven Co-PI, U.S. National Science Foundation, 2016-2019

 

 

Resilient Alaskan Distribution System Improvements using Automation and Energy Storage

Dr. Arghandeh Co-PI, U.S. Department of Energy, 2017-2020

 

 

Bridging the Digital Divide for the Well-Being of Aging Populations in Smart Cities

Dr. Ozguven Co-PI and Dr. Arghandeh Co-PI, U.S. National Science Foundation, 2017-2018

 

 

Open-source Distributed Control Platform for HIL-based Testing Advanced Ship Power Systems

Dr. Arghandeh Co-PI, U.S. Office of Naval Research, 2016-2017

 

 

High Resolution Monitoring System for Distribution Networks with Micro-Synchrophasors

Dr. Arghandeh PI, Florida State University Office of Research, FYA Program, 2016

 

 

Data and Model Integration for Multidimensional System Observability

Dr. Arghandeh PI, Florida State University Office of Research, 2015

 

 

 

News

Sep 2019

The Smart Grid Eye, from Space to Sky (GridEyeS) is funded by the European Space Agency. The overall goal of this study is to create an end to end electric grid monitoring platform using satellite images combined with high-resolution drone data to create multi-layer situational awareness, especially in the case of extreme weather events in the electric grid. 

More info

March 2018

Dr. Arghandeh honored for book publication in Florida State University

Sep 2018

Dr. Arghandeh joined the Western Norway University of Applied Sciences, as the "Big Data and Machine Learning Associate Professor" in the Department of Computing, Mathematics, and Physics.

January 2018 

Dr. Arghandeh and Dr.Ozguven visit of NASA Challenger Learning Center

and talk on BigData for SmartCities

January 2018 

Dr. Arghandeh's book "Big Data Application in Power System" published by Elsevier

October 2017

Dr. Ozguven, published an article in Tampa Bay Times

 

October 2017

Dr. Ozguven, published an article in Tallahassee Democrat

 

Oct 2017

Dr. Ozguven on WTXL TV talking about our research on Evacuating senior people and their furry friends 

 

Oct 2017

Resilient Distribution Systems Lab Call Awards, Office Of The Under Secretary For Science And Energy, U.S. Department of Energy

 

Oct 2016

Radio Interview," the progression and development of DigiTally", Tallahassee Talk Radio Show.

 

 

Oct 2016

Featured Research,"FSU Team Tackles Urban Mobility In Smart City Era" FSU News.

 

 

Oct 2016

Featured Research," FSU Researchers Transforming Tallahassee Into a Smart City,” Florida Flambeau.

 

 

Jul 2015

News,"EECS postdoc scholar Reza Arghandeh has been selected to receive the 2015 ASME Award"

UC Berkeley.

 

 

Jul 2015

News, "ASME Power Award for FSU New Faculty" FSU College of Engineering Website.

 

 

Jun 2015,

News, " IEEE PES Award for Paper on Data Accuracy for Inverters Control" FSU College of Engineering Website.

 

Publications

For the updated list of publications, please check:
Reza Arghandeh Google Scholars 
Eren Erman Ozguven Google Scholar

Books:

 

Arghandeh Reza. Big Data Application for Power Systems. Energy.Elsevier, Oxford, UK, 2017.

 

von Meier Alexandra and Arghandeh Reza. Chapter 34-Every Moment Counts: Synchrophasors for Distribution Networks with Variable Resources, Renewable Energy Integration 1st Edition, pp 429–438. Elsevier, Boston, USA,2014

 

 

Papers:

2019:

Will be updated, please check Google Scholar...

 

2018:

Will be updated, please check Google Scholar...

Ferhat Uçar, Ömer Faruk Alçin, Beşir Dandıl, Fikret Ata, Jose Cordova, Reza Arghandeh. Online Power Quality Events Detection Using Weighted Extreme Learning. 6th International Istanbul Smart Grid and Cities Congress (ICSG 2018), 2018

 

M. Baran Ulak, Ayberk Kocatepe, L. Madhavi Konila Sriram, E. Erman Ozguven, Reza Arghandeh. Assessment of the hurricane-induced power outages from a demographic, socioeconomic, and transportation perspective. Natural Hazards, Springer 2018

 

Yuxun Zhou, Reza Arghandeh. Moving Toward Agile Machine Learning for Data Analytics in Power Systems. Elsevier, 2018. 

 

Reza Arghandeh, Kyle Brady, Merwin Brown, George R. Cotter, Deepjyoti Deka. Synchrophasor Monitoring for Distribution Systems: Technical Foundations and Applications. North American SynchroPhasor Initiative, 2018

 

Reza Arghandeh, Yuxun Zhou. Big Data Application in Power Systems. Elsevier, 2018

 

Yuxun Zhou, Reza Arghandeh. Non-parametric Outliers Detection in Multiple Time Series A Case Study: Power Grid Data Analysis. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) 2018

 

Ayberk Kocatepe, Mehmet Baran Ulak, Grzegorz Kakareko, Davide Pinzan, Jose Cordova, Eren Erman Ozguven, Sungmoon Jung, John Olusegun Sobanjo, Reza Arghandeh. Assessment of Emergency Facility Accessibility in the Presence of Hurricane-Related Roadway Closures and Prediction of Future Roadway Disruptions. Transportation Research Board 97th Annual Meeting 2018.

 

Davide Pinzan, Ayberk Kocatepe, Mostafa Gilanifar, Mehmet Baran Ulak, Eren Erman Ozguven, Reza Arghandeh. Data-Driven and Hurricane-Focused Metrics for Combined Transportation and Power Networks Resilience. Transportation Research Board 97th Annual Meeting 2018.

 

 

2017:

 

Guido Cavraro, Reza Arghandeh. Power Distribution Network Topology Detection with Time-Series Signature Verification Method. IEEE Transactions on Power Systems, 2017

 

Lalitha Madhavi K. S., Jose Cordova, Mehmet Baran Ulak, Michael Ohlsen, Eren E. Ozguven, Reza Arghandeh, Ayberk Kocatepe. Advanced electricity load forecasting combining electricity and transportation network. IEEE North American Power Symposium (NAPS), 2017.

Y. Zhou, R. Arghandeh, and C. Spanos. Partial knowledge data-driven event detection for power distribution networks. IEEE Transactions on Smart Grid, PP(99), 2017.

 

A. Tbaileh, H. Jain, R. Broadwater, M. Dilek, J. Cordova, and R. Arghandeh. Graph trace analysis: An object-oriented power flow, verification and comparisons. Electric Power Systems Research, PP(147):145–153, 2017.

 

A. Kocatepe, M. Ulak, E. Ozguven, M. Horner, and R. Arghandeh. Socioeconomic characteristics and crash injury exposure: A case study in Florida using two-step floating catchment area method. Applied Geography, 2017.

 

A. Kocatepe, M. Ulak, E. Ozguven, M. Horner, and R Arghandeh. Socioeconomic characteristics and crash proneness a case study in Florida using two-step floating catchment area method. In Annual Meeting Transportation Research Board 2017, 2017.


J. Cordova, R. Arghandeh, Y.  Zhou, M. Stiffer, and W.  Wu.  Shape-based data analysis for event classification in power systems. In IEEE PES PowerTech 2017, 2017.

 

 

2016:

 

M. Jacobson, M. Delucchi, R. Arghandeh, and et. al. A 100% wind, water, sunlight (wws) all-sector energy plan for Washington state. Renewable Energy, 86:75–88, 2016.

 

R. Arghandeh, A..vonMeier, L. Mehrmanesh, and L. Mili. On the definition of cyber-physical resilience in power systems. Renewable and Sustainable Energy Reviews, 58(2016-5):1060–1069, 2016.

 

Y.  Zhou, R. Arghandeh, and C. J. Spanos.  Online learning of contextual hidden markov  models for temporal-spatial data analysis. In IEEE Conference on Decision and Control (CDC 2016), 2016.

 

Y. Zhou, R. Arghandeh, I. C. Konstantakopoulos, S. Abdullah, A. von Meier, and C. J. Spanos. Abnormal event detection with high-resolution micro-pmu measurement. In IEEE Power Systems Computation Conference. IEEE, 2016.

 

Y. Zhou, R. Arghandeh, I. C. Konstantakopoulos, S Abdullah, and C. J. Spanos. Data-driven event detection with partial knowledge: A hidden structure semi-supervised learning method. In IEEE, editor, American Control Conference (ACC16), 2016.

 

K. Leahy, I. C. Konstantakopoulos, Y. Zhou, and R. Arghandeh. Wind turbine performance monitoring and fault detection using scada data. In ASME Power and Energy Conference 2016, 2016.

 

 

2015 and past:

 

L. Wang, A. Onen, J. Woyak, R. Arghandeh, R. P Broadwater, and C. Scirbona. Electric power distribution feeder performance evaluation and distributed computation. EC Journal of Science and Engineering, 2(1):59–67,2015.

 

D. Cheng, A. Onen, D. Zhu, D. Kleppinger, R. Arghandeh, and R.P Broadwater. Automation effects on reliability and operation costs in storm restoration. Electric Power Components and Systems, 43(6):656–664,2015.

 

M. H. F. Wen, R. Arghandeh, A. von Meier, K. Poolla, and V. O. K. Li. Phase identification in distribution networks with micro-synchrophasors. In Power & Energy Society General Meeting, 2015 IEEE, pages 1–5, 2015.

 

E. M. Stewart, S. Kiliccote, D. Arnold, A. von  Meier,  and  R.  Arghandeh.  Accuracy and validation of measured and modelled data for distributed pv interconnection and control. In Power & Energy Society General Meeting, 2015 IEEE, pages 1–5, 2015.

 

J. Poon, I. C. Konstantakopoulos, R. Arghandeh, A. von Meier, C. Spanos, and S. Sanders. Failsafe a generalized methodology for converter fault detection, identification, and reme- diation in nanogrids. In International Conference on Building Energy Efficiency and Sustainable Technologies, 2015.

 

A. Khoshkbar-Sadigh, M. Heydari, M. Tedde, K. Smedley, R. Arghandeh, and A. von Meier. A unified platform enabling power system circuit model data transfer among different software. In Innovative Smart Grid Technologies Conference (ISGT), 2015 IEEE Power & Energy Society, pages 1–5, 2015.


G. Cavraro, R. Arghandeh, K. Poolla, and A. von Meier. Data-driven approach for distribution network topology detection. In Power & Energy Society General Meeting, 2015 IEEE, pages 1–5, 2015.

 

G. Cavraro, R. Arghandeh, G. Barchi, and A. von Meier. Distribution network topology detection with time-series measurements. In Innovative Smart Grid Technologies Conference (ISGT), 2015 IEEE Power & Energy Society, pages 1–5, 2015.

 

R. Arghandeh, M. Gahr, A. von Meier, G. Cavraro, M. Ruh, and G. Andersson. Topology detection in microgrids with micro-synchrophasors. In Power & Energy Society General Meeting, 2015 IEEE, pages 1–5, 2015.

 

A. Onen, J. Woyak, R. Arghandeh, J. Jung, C. Scirbona, and R. P. Broadwater. Time-varying cost of loss evaluation in distribution networks using market marginal price. International Journal of Electrical Power&Energy Systems, 62(0):712–717, 2014.

 

J. Jung, A. Onen, R. Arghandeh, and R. Broadwatera. Coordinated control of automated devices and photovoltaic generators for voltage rise mitigation in power distribution circuits. Renewable Energy, 66(June2014):532–540, 2014.

 

R Arghandeh, J. Woyak, and R. Broadwater. Economic optimal operation of community energy storage systems in competitive energy markets. Applied Energy, 135(2014-12):71–80, 2014.

 

R. Arghandeh, A. Onen, J. Jung, D. Cheng, R. P. Broadwater, and V. Centeno. Phasor-based assessment for harmonic sources in distribution networks. Electric Power Systems Research, 116(0):94–105, 2014.

 

R. Arghandeh, M. Brown, A. DelRosso, G. Ghatikar, E. Stewart, A. Vojdani, and A. von Meier. The local team: Leveraging distributed resources to improve resilience. IEEE Power and Energy Magazine, 12(4), 2014.

 

 

A. vonMeier, D. Culler, A. McEachen, and R. Arghandeh. Micro-synchrophasors for distribution systems. In IEEE PES Innovative Smart Grid Technologies Conference (ISGT), 2014, pages 1–5. IEEE, 2014.

 

 

E. M; Stewart, S; Kiliccote, C.M; Shand, A.W; McMorran, R; Arghandeh, and A von Meier. Addressing the challenges for integrating micro-synchrophasor data with operational system applications. In IEEE PES General Meeting 2014, pages 1–5. IEEE, 2014.

 

 

L. Schenato, G. Barchi, D. Macii, R. Arghandeh, K. Poolla, and A.VonMeier. Bayesian linear state estimation using smart meters and pmus measurements in distribution grids. In IEEE International Conference on Smart Grid Communications 2014, pages1–6. IEEE, 2014.

 

 

D. Cheng, A. Onen, R. Arghandeh, J. Jung, and R. Broadwater. Model centric approach for monte carlo assessment of storm restoration and smart grid automation. In ASME Power2014 Conference. ASME, 2014.

 

R. Arghandeh, A. vonMeier, and R. Broadwater. Phasor-based approch for harmonic assesment from multiple distributed energy resources. In IEEE PES General Meeting 2014, pages 1–5. IEEE, 2014.

 

A. Onen, D. Cheng, R. Arghandeh, J. Jung, J. Woyak, M. Dilek, and R.P Broadwater. Smart model based coordinated control based on feeder losses, energy consumption, and voltage violations. Electric Power Components and Systems, 41(16):1686–1696, 2013.

 

Y. Jung, J. and Cho, D. Cheng, A. Onen, R. Arghandeh, and R. P. Dilek, M.and Broadwater. Monte carlo analysis of plug-in hybrid vehicles and distributed energy resource growth with residential energy storage in michigan. Applied Energy, 108:218–235, 2013.

 

R. Arghandeh, A. Onen, J. Jung, and R. P. Broadwater. Harmonic interactions of multiple distributed energy resources in power distribution networks. Electric Power Systems Research, 105(December 2013):124–133, 2013.

 

M. Petrov and R. Arghandeh. Concept and application of distributed compressed air energy storage systems integrated in utility networks.  In American Society of Mechanical Engineers  Power Conference 2013, (ASME Power2013), Boston, MA, USA, page 8. American Society of Mechanical Engineers, 2013.

 

M. Perov, R. Arghandeh, and R. Broadwater. Control strategy for distributed compressed-air energy storage in grid-tied small-scale renewable energy systems. In Solar Power International 2013. SEIA, 2013.

 

R. Arghandeh, A. Onen, J. Jung, D. Cheng, and V. Broadwater, R.and Centeno.  Harmonic impact study for distributed energy resources integrated into power distribution networks. In American Society of Mechanical Engineers Power Conference 2013, (ASME Power2013), Boston, MA, USA, page 8. American Society of Mechanical Engineers, 2013.

 

R. Arghandehand S. Provencher. A need for power & energy engineers, today and tomorrow. IEEE GoldRush, 8(4):17–18, 2012.

 

R. Arghandeh, M. Pipattanasomporn, and S.Rahman. Flywheel energy storage systems for ride-through applications in a facility microgrid. IEEE Transactions on Smart Grid, 3(4):1955– 1962, 2012.

 

 

R. Arghandeh, A. Onen, and R. Broadwater. Distributed energy storage system control for optimal adoption of electric vehicles. In Power and Energy Society General Meeting, 2012 IEEE, pages 1–8. IEEE, 2012.
 

H. Khodaei, R. Taheri, and R. Arghandeh. Exergy analysis of the steam network in tehran oil refinery and evaluation with new scenario. In Industrial Energy Technology Conference, 2009.

 

R. Arghandeh, N. Schulz, and A. Srivastava. Intelligent operation and management system for shipboard mvdc networks. In Second Mississippi State University Energy Workshop. Mississippi State University, Mech Eng Dept, 2009.

 

R. Arghandeh and B. Rashidian. Gas refinery steam network thermal modeling and optimization by pinch method. In International Conference on Modeling, Simulation, and Applied Optimization, 2009.

 

R. Arghandeh and B. Rashidian. Distributed generation chp system with heat pipes: A novel approach to more energy-efficient buildings. In International Colloquium on Environmentally Preferred Advanced Power Generation 2009. American Society of Mechanical Engineers (ASME), 2009.

 

R. Arghandeh, M. Amidpour, and H. Khodaei.  Steam network modeling and simulation in gas refinery by considering pinch technology. In Southeastcon, 2009. SOUTHEASTCON’09. IEEE, pages 428–433. IEEE, 2009.

 

M. R. Jaffari Nasr, R. Arghandeh, and M. Gharae. Analysis of refinery steam network by pinch technology approach. In International Chemical Engineering Congress, 2008.

 

R. Arghandeh, R. Parvizi, M. Amidpour, and A. Chaibakhsh. Gas based distributed generation systems, a key to iran buildings growing energy demand.  In Power and Energy Conference,  2008. PECon 2008. IEEE 2nd International, pages 1592–1596. IEEE, 2008.

 

R. Arghandeh, A. Ghaffari, and M. Amidpour. Distributed generation based on micro-turbines usage in rural areas. In Iranian Conference of Electrical Engineering. IAEE, 2008.

 

R. Arghandeh, M. Amidpour, and A. Ghaffari. Hierarchical approach in steam network modeling. In Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International, pages 839–843. IEEE, 2008.

 

R. Arghandeh and M. Amidpour. Energy sustainability in buildings by chp distributed generation systems. In International World Energy System Conference (WES 08), , Iasi, Romania, July 2008, page A17. World Energy System Consortium, 2008.

 

R. Arghandeh and A. Saemian. Swot method enhancement for globalization analysis by considering countries’ economic status. Journal of Management,18(123-124):87–96, 2007

 

 

 

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