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Impact of workload on cognitive performance of control room operators

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Abstract

Workload has long been considered as one of the important factors for personal functions and malfunctions, particularly in complex systems. Undertaking operations in workstations of such systems usually entails complex tasks and poor cognitive performance of their operators may contribute to human error and critical subsequent consequences. Although many studies have investigated the effects of workload on the cognitive performance, there is a gap for specific jobs and operations such as control room operation. This paper then aims to determine that what dimensions of the workload has more impact on cognitive performance of a combined cycle power plant (CCPP) Control room operators. Control room operators from two CCPPs participated (n = 95) in this study. Hierarchical task analysis (HTA) was employed to perform the job analysis. To assess the perceived workload, NASA Task Load Index (NASA-TLX) was performed at the end of the work shift. The participants were subjected to three cognitive performance tests including sustained attention, simple reaction and working memory at the beginning and end of the work shift. The values of mental demand on check and control tasks (92.17 ± 4.38), decisions about abnormal conditions (90.16 ± 5.71) and reporting (85.09 ± 3.25) were high. The task of communication and coordination in terms of temporal demand (71.66 ± 7.3) and performance (68.04 ± 4.92) had higher values compared to other tasks. The highest weighted workload (84.27 ± 6.48) was also attributed to the task of checking and controlling. Sustained attention and working memory were more susceptible to excessive workload among CCPP control room operators.

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References

  • Andel R, Finkel D, Pedersen NL (2016) Effects of preretirement work complexity and postretirement leisure activity on cognitive aging. J Gerontol Ser B: Psychol Sci Soc Sci 71:849–856

    Google Scholar 

  • Annett J (2003) Hierarchical task analysis. Handbook Cogn Task Design 2:17–35

    Google Scholar 

  • Argyle EM, Marinescu A, Wilson ML, Lawson G, Sharples S (2020) Physiological indicators of task demand, fatigue, and cognition in future digital manufacturing environments. Int J Hum-Comput Stud 145:102522

    Google Scholar 

  • Askaripoor T, Motamedzade M, Golmohammadi R, Farhadian M, Babamiri M, Samavati M (2019) Effects of light intervention on alertness and mental performance during the post-lunch dip: a multi-measure study. Ind Health 57:511–524

    Google Scholar 

  • Ayaz H, Izzetoglu M, Bunce S, Heiman-Patterson T, Onaral B (2007) Detecting cognitive activity related hemodynamic signal for brain computer interface using functional near infrared spectroscopy. 2007 3rd international IEEE/EMBS conference on neural engineering. IEEE, pp 342–345

    Google Scholar 

  • Backs RW, Seljos KA (1994) Metabolic and cardiorespiratory measures of mental effort: the effects of level of difficulty in a working memory task. Int J Psychophysiol 16:57–68

    Google Scholar 

  • Baddeley A (2002) Fractionating the central executive Principles of frontal lobe function. Oxford University Press, pp 246–260

    Google Scholar 

  • Ballard JC (2001) Assessing attention: Comparison of response-inhibition and traditional continuous performance tests. J Clin Exp Neuropsychol 23:331–350

    Google Scholar 

  • Barger LK, Ayas NT, Cade BE, Cronin JW, Rosner B, Speizer FE, Czeisler CA (2006) Impact of extended-duration shifts on medical errors, adverse events, and attentional failures. PLoS Med 3:e487

    Google Scholar 

  • Bhavsar P, Srinivasan B, Srinivasan R (2017) Quantifying situation awareness of control room operators using eye-gaze behavior. Comput Chem Eng 106:191–201

    Google Scholar 

  • Bottenheft C, Brouwer A-M, Stuldreher I, Groen E, van Erp J (2020) Cognitive task performance under (combined) conditions of a metabolic and sensory stressor. Cogn Technol Work. https://doi.org/10.1007/s10111-020-00653-w.

    Article  Google Scholar 

  • Bowers CA, Urban JM, Morgan BB Jr (1992) The study of crew coordination and performance in hierarchical team decision making. University of central florida orlando

    Google Scholar 

  • Bowers CA, Braun CC, Morgan BB Jr (1997) Team workload: its meaning and measurement. Team performance assessment and measurement. Psychology Press, pp 97–120

    Google Scholar 

  • Braarud PØ (2020) An efficient screening technique for acceptable mental workload based on the NASA Task Load Index—development and application to control room validation. Int J Indus Ergon 76:102904

    Google Scholar 

  • Bullemer PT, Nimmo I (1994) Understanding and supporting abnormal situation management in industrial process control environments: a new approach to training. Proceedings of ieee international conference on systems Man and Cybernetics. IEEE, pp 391–396

    Google Scholar 

  • Carayon P, Kianfar S, Li Y, Xie A, Alyousef B, Wooldridge A (2015) A systematic review of mixed methods research on human factors and ergonomics in health care. Appl Ergon 51:291–321

    Google Scholar 

  • Chee MW, Choo WC (2004) Functional imaging of working memory after 24 hr of total sleep deprivation. J Neuroscience 24:4560–4567

    Google Scholar 

  • Chen Y-N, Mitra S (2009) The spatial-verbal difference in the n-back task: an ERP study. Acta Neurol Taiwan 18:170–179

    Google Scholar 

  • Cheng P, Tallent G, Bender TJ, Tran KM, Drake CL (2017) Shift work and cognitive flexibility: decomposing task performance. J Biol Rhythms 32:143–153

    Google Scholar 

  • Cinaz B, Arnrich B, Marca R, Tröster G (2013) Monitoring of mental workload levels during an everyday life office-work scenario. Personal Ubiquitous Comput 17:229–239

    Google Scholar 

  • Colle HA, Reid GB (1998) Context effects in subjective mental workload ratings. Hum Factors 40:591–600

    Google Scholar 

  • Cook MJ (2000) Working memory, age, crew downsizing, system design and training . Univ of Abertay Dundee Scotland (United Kingdom) Centre for Usability Test

    Google Scholar 

  • Cornblatt BA, Risch NJ, Faris G, Friedman D, Erlenmeyer-Kimling L (1988) The continuous performance test, identical pairs version (CPT-IP): I. New findings about sustained attention in normal families. Psychiatry Res 26:223–238

    Google Scholar 

  • Corradini P, Cacciari C (2002) The effect of workload and workshift on air traffic control: a taxonomy of communicative problems. Cogn technol work 4:229–239

    Google Scholar 

  • Correa A, Barba A, Padilla F (2016) Light effects on behavioural performance depend on the individual state of vigilance. PLoS ONE 11:e0164945

    Google Scholar 

  • Dai Y, Wang H, Khan F, Zhao J (2016) Abnormal situation management for smart chemical process operation. Curr Opin Chem Eng 14:49–55

    Google Scholar 

  • Dey A, Mann DD (2010) Sensitivity and diagnosticity of NASA-TLX and simplified SWAT to assess the mental workload associated with operating an agricultural sprayer. Ergonomics 53:848–857

    Google Scholar 

  • Di Stasi LL, Álvarez-Valbuena V, Cañas JJ, Maldonado A, Catena A, Antolí A, Candido A (2009) Risk behaviour and mental workload: multimodal assessment techniques applied to motorbike riding simulation. Transport Res Part F: Traffic Psychol Behav 12:361–370

    Google Scholar 

  • DiDomenico A, Nussbaum MA (2011) Effects of different physical workload parameters on mental workload and performance. Int J Ind Ergon 41:255–260

    Google Scholar 

  • Dorrian J, Baulk SD, Dawson D (2011) Work hours, workload, sleep and fatigue in Australian rail industry employees. Appl Ergon 42:202–209

    Google Scholar 

  • Edwards T, Gabets C, Mercer J, Bienert N (2017) Task demand variation in air traffic control: implications for workload, fatigue, and performance. Advances in human aspects of transportation. Springer, pp 91–102

    Google Scholar 

  • Eggemeier F, Wilson G (1991) Workload assessment in multi-task environments. Multiple task performance, GB. Taylor & Francis Ltd. DL Damos, London

    Google Scholar 

  • Fallahi M, Motamedzade M, Heidarimoghadam R, Soltanian AR, Miyake S (2016) Assessment of operators’ mental workload using physiological and subjective measures in cement, city traffic and power plant control centers. Health Promot Perspect 6:96

    Google Scholar 

  • Fernandes A, Braarud PØ (2015) Exploring measures of workload, situation awareness, and task performance in the main control room. Procedia Manufacturing 3:1281–1288

    Google Scholar 

  • Gawron VJ (2019) Human performance, workload, and situational awareness measures handbook, vol 2. CRC Press

    Google Scholar 

  • Gokalsing E et al (2000) Evaluation of the supervisory system in elderly subjects with and without disinhibition. Eur Psychiatry 15:407–415

    Google Scholar 

  • Golmohammadi R, Darvishi E, Faradmal J, Poorolajal J, Aliabadi M (2020) Attention and short-term memory during occupational noise exposure considering task difficulty. Appl Acoust 158:107065

    Google Scholar 

  • Gonzalez C (2005) Task workload and cognitive abilities in dynamic decision making. Hum Factors 47:92–101

    Google Scholar 

  • Grissmann S, Faller J, Scharinger C, Spüler M, Gerjets P (2017) Electroencephalography based analysis of working memory load and affective valence in an N-back task with emotional stimuli. Front Hum Neurosci. https://doi.org/10.3389/fnhum.2017.00616

    Article  Google Scholar 

  • Ha JS, Seong PH, Lee MS, Hong JH (2007) Development of human performance measures for human factors validation in the advanced MCR of APR-1400 IEEE Transactions on. Nuclear Science 54:2687–2700

    Google Scholar 

  • Halperin JM, Sharma V, Greenblatt E, Schwartz ST (1991) Assessment of the continuous performance test: reliability and validity in a nonreferred sample. Psychol Assess: A J Consult Clin Psychol 3:603

    Google Scholar 

  • Hannula M, Huttunen K, Koskelo J, Laitinen T, Leino T (2008) Comparison between artificial neural network and multilinear regression models in an evaluation of cognitive workload in a flight simulator. Comput Biol Med 38:1163–1170

    Google Scholar 

  • Hart SG, Staveland LE (1988) Development of NASA-TLX (task load index): results of empirical and theoretical research. Advances in psychology, vol 52. Elsevier, pp 139–183

    Google Scholar 

  • Heard J, Harriott CE, Adams JA (2018) A survey of workload assessment algorithms. IEEE Transac Human-Mach Syst 48:434–451

    Google Scholar 

  • Hockey GRJ (1997) Compensatory control in the regulation of human performance under stress and high workload: a cognitive-energetical framework. Biol Psychol 45:73–93

    Google Scholar 

  • Hollnagel E (1998) Cognitive reliability and error analysis method (CREAM). Elsevier

    Google Scholar 

  • Hollnagel E, Woods DD (2005) Joint cognitive systems: foundations of cognitive systems engineering. CRC Press

    Google Scholar 

  • Hugo JV, Kovesdi CR, Joe JC (2018) The strategic value of human factors engineering in control room modernization. Prog Nucl Energy 108:381–390. https://doi.org/10.1016/j.pnucene.2018.06.014

    Article  Google Scholar 

  • Huiberts L, Smolders K, De Kort Y (2015) Shining light on memory: effects of bright light on working memory performance. Behav Brain Res 294:234–245

    Google Scholar 

  • Hwang S-L, Yau Y-J, Lin Y-T, Chen J-H, Huang T-H, Yenn T-C, Hsu C-C (2008) Predicting work performance in nuclear power plants. Saf Sci 46:1115–1124

    Google Scholar 

  • Inzana CM, Driskell JE, Salas E, Johnston JH (1996) Effects of preparatory information on enhancing performance under stress. J Appl Psychol 81:429

    Google Scholar 

  • Izzetoglu M, Bunce SC, Izzetoglu K, Onaral B, Pourrezaei K (2007) Functional brain imaging using near-infrared technology. IEEE Eng Med Biol Mag 26:38–46

    Google Scholar 

  • Jafari MJ, Naserpour M, Monazzam MR, Saremi M, Shahneshin P, Reza H, Jam Bar Sang S (2014) Evaluation of students’ cognitive performance while exposed to heat using continues performance test. J Occup Hyg Eng 1:1–9

    Google Scholar 

  • Jafari MJ, Zaeri F, Jafari AH, Payandeh Najafabadi AT, Al-Qaisi S, Hassanzadeh-Rangi N (2020) Assessment and monitoring of mental workload in subway train operations using physiological, subjective, and performance measures. Hum Fact Ergon Manuf Serv Indus 30:165–175

    Google Scholar 

  • Jazani RK, Miandashti R, Kavousi A, Minaei MS (2016) The effect of hot and humid weather on the level of mental workload among managers and supervisors on a project of South Pars phases. Iran Cogn Technol Work 18:11–17

    Google Scholar 

  • Jo S, Myung R, Yoon D (2012) Quantitative prediction of mental workload with the ACT-R cognitive architecture. Int J Ind Ergon 42:359–370

    Google Scholar 

  • Jou Y-T, Yenn T-C, Lin CJ, Yang C-W, Lin S-F (2009) Evaluation of mental workload in automation design for a main control room task. 2009 international conference on networking. Sensing and Control, IEEE, pp 313–317

    Google Scholar 

  • Karwowski W (2001) International encyclopedia of ergonomics and human factors, vol 3. Crc Press

    Google Scholar 

  • Kazemi R, Haidarimoghadam R, Motamedzadeh M, Golmohamadi R, Soltanian A, Zoghipaydar MR (2016) Effects of shift work on cognitive performance, sleep quality, and sleepiness among petrochemical control room operators. J. of circadian rhythms. https://doi.org/10.5334/jcr.134.

    Article  Google Scholar 

  • Koslowsky M, Kluger AN, Reich M (2013) Commuting stress: causes, effects, and methods of coping. Springer Science & Business Media

    Google Scholar 

  • Kubota R, Kiyokawa K, Arazoe M, Ito H, Iijima Y, Matsushima H, Shimokawa H (2001) Analysis of organisation-committed human error by extended CREAM. Cogn Technol Work 3:67–81

    Google Scholar 

  • Lee Y-H, Liu B-S (2003) Inflight workload assessment: comparison of subjective and physiological measurements. Aviat, space, and Environ Med 74:1078–1084

    Google Scholar 

  • Li J, Wang H, Xie Y, Zeng W (2020) Human error identification and analysis for shield machine operation using an adapted TRACEr method. J Constr Eng Manag 146:04020095

    Google Scholar 

  • Lin CJ, Hsieh TL, Tsai PJ, Yang CW, Yenn TC (2011) Development of a team workload assessment technique for the main control room of advanced nuclear power plants. Hum Fact Ergon Manuf Serv Indus 21:397–411

    Google Scholar 

  • Machi MS et al (2012) The relationship between shift work, sleep, and cognition in career emergency physicians. Acad Emerg Med 19:85–91

    Google Scholar 

  • Manca D, Brambilla S, Colombo S (2013) Bridging between virtual reality and accident simulation for training of process-industry operators. Adv Eng Softw 55:1–9

    Google Scholar 

  • Mani TM, Bedwell JS, Miller LS (2005) Age-related decrements in performance on a brief continuous performance test. Arch Clin Neuropsychol 20:575–586

    Google Scholar 

  • Mansikka H, Virtanen K, Harris D (2019) Comparison of NASA-TLX scale, modified Cooper-Harper scale and mean inter-beat interval as measures of pilot mental workload during simulated flight tasks. Ergonomics 62:246–254

    Google Scholar 

  • Martin K, McLeod E, Périard J, Rattray B, Keegan R, Pyne DB (2019) The impact of environmental stress on cognitive performance: a systematic review. Hum Factors 61:1205–1246

    Google Scholar 

  • Mayer RE, Moreno R (2003) Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist 38:43–52

    Google Scholar 

  • Meijman TF, Mulder G, Van Dormolen M, Cremer R (1992) Workload of driving examiners: A psychophysiological field study Enhancing industrial performances. Taylor & Francis, London, 245–260

    Google Scholar 

  • Miller GA (1953) What is information measurement? Am Psychol 8:3

    Google Scholar 

  • Mohammadi M, NaslSeraji J, Zeraati H (2013) Developing and accessing the validity and reliability of a questionnaire to assess the mental workload among ICUs Nurses in one of the Tehran University of Medical Sciences hospitals. J Sch Public Health Inst Public Health Res 11:87–96

    Google Scholar 

  • Mohebian Z, Dehghan H (2017) The relationship of sleep quality and mental fatigue in different levels of lighting on attention and reaction time in thermal comfort condition. Iran Occup Health J 14:85–94

    Google Scholar 

  • Monteiro R, Tomé D, Neves P, Silva D, Rodrigues MA (2018) The interactive effect of occupational noise on attention and short-term memory: a pilot study. Noise Health 20:190

    Google Scholar 

  • Mosleh A, Chang Y (2004) Model-based human reliability analysis: prospects and requirements. Reliab Eng Syst Saf 83:241–253

    Google Scholar 

  • Naserpour M, Jafari M, Monazzam M, Saremi M (2014) A study of students cognitive performance under noise exposure, using continuous performance test “Study on the effects of noise on cognitive performances.” Health and Safety at Work 4:41–54

    Google Scholar 

  • Noyes JM, Bruneau DP (2007) A self-analysis of the NASA-TLX workload measure. Ergonomics 50:514–519

    Google Scholar 

  • O’Donnell R, Eggemeier F (1986) Workload assessment methodology. In: Boff K, Kaufman L, Thomas JP (eds) Handbook of perception and human performance. Wiley, New York

    Google Scholar 

  • Parasuraman R, Sheridan TB, Wickens CD (2008) Situation awareness, mental workload, and trust in automation: viable, empirically supported cognitive engineering constructs. J Cogn Eng Decis Mak 2:140–160

    Google Scholar 

  • Pate-Cornell ME, Murphy DM (1996) Human and management factors in probabilistic risk analysis: the SAM approach and observations from recent applications. Reliab Eng Syst Saf 53:115–126

    Google Scholar 

  • Pickup L, Wilson JR, Norris BJ, Mitchell L, Morrisroe G (2005) The integrated workload scale (IWS): a new self-report tool to assess railway signaller workload. Appl Ergon 36:681–693

    Google Scholar 

  • Prostejovsky AM, Brosinsky C, Heussen K, Westermann D, Kreusel J, Marinelli M (2019) The future role of human operators in highly automated electric power systems. Electr Power Syst Res 175:105883. https://doi.org/10.1016/j.epsr.2019.105883

    Article  Google Scholar 

  • Rasmussen J (1982) Human errors A taxonomy for describing human malfunction in industrial installations. J Occup Accid 4:311–333

    Google Scholar 

  • Reinerman-Jones L, Mercado J, D’Agostino A, Hughes N, Sollins B, Leis R (2015) Workload associated with nuclear power plant main control room tasks. Proceedings of the human factors and ergonomics society annual meeting, vol 1. SAGE Publications Sage CA, Los Angeles, CA, pp 110–114

    Google Scholar 

  • Roccio C, Reynolds C (2001) Continuous performance tests are sensitive to ADHD in adults but lack specificity. Ann NY Acad Sci 931:113–139

    Google Scholar 

  • Rolo G, Hernández-Fernaud E, Díaz-Cabrera D (2010) Impact of perceived physical and environmental conditions on mental workload: an exploratory study in office workers. Psyecology 1:393–401

    Google Scholar 

  • Rouch I, Wild P, Ansiau D, Marquié J-C (2005) Shiftwork experience, age and cognitive performance. Ergonomics 48:1282–1293

    Google Scholar 

  • Rubio S, Díaz E, Martín J, Puente JM (2004) Evaluation of subjective mental workload: a comparison of SWAT NASA-TLX, and workload profile methods. Appl Psychol 53:61–86. https://doi.org/10.1111/j.1464-0597.2004.00161.x

    Article  Google Scholar 

  • Ryu K, Myung R (2005) Evaluation of mental workload with a combined measure based on physiological indices during a dual task of tracking and mental arithmetic. Int J Ind Ergon 35:991–1009

    Google Scholar 

  • Samima S, Sarma M, Samanta D, Prasad G (2019) Estimation and quantification of vigilance using ERPs and eye blink rate with a fuzzy model-based approach. Cogn Technol Work 21:517–533

    Google Scholar 

  • Schnotz W, Kürschner C (2007) A reconsideration of cognitive load theory. Educ Psychol Rev 19:469–508

    Google Scholar 

  • Seife C (1999) They have a problem. New Scientist 164:14–15

    Google Scholar 

  • Seng NY, Srinivasan R (2004) Transitions in the process industries: opportunities and prospective solutions. Proceedings of the 2004 IEEE international symposium on intelligent control. IEEE, pp 246–251

    Google Scholar 

  • Shwetha B, Sudhakar H (2012) Influence of shift work on cognitive performance in male business process outsourcing employees. Indian J Occup Environ Med 16:114

    Google Scholar 

  • Simon SS, Tusch ES, Holcomb PJ, Daffner KR (2016) Increasing working memory load reduces processing of cross-modal task-irrelevant stimuli even after controlling for task difficulty and executive capacity. Front Hum Neurosci 10:380

    Google Scholar 

  • Sinclair RR, Wang M, Tetrick LE (2012) Research methods in occupational health psychology: measurement, design, and data analysis. Routledge

    Google Scholar 

  • Sliwinski MJ, Smyth JM, Hofer SM, Stawski RS (2006) Intraindividual coupling of daily stress and cognition. Psychol Aging 21:545

    Google Scholar 

  • Sumińska S, Nowak K, Łukomska B, Cygan HB (2020) Cognitive functions of shift workers: paramedics and firefighters—an electroencephalography study. Int J Occup Saf Ergonom. https://doi.org/10.1080/10803548.2020.1773117

    Article  Google Scholar 

  • Vanderhaegen F (1997) Multilevel organization design: the case of the air traffic control. Control Eng Pract 5:391–399. https://doi.org/10.1016/S0967-0661(97)00016-6

    Article  Google Scholar 

  • Vanderhaegen F (1999a) Cooperative system organisation and task allocation: ilustration of task allocation in air traffic control. Trav Hum 62:197–222

    Google Scholar 

  • Vanderhaegen F (1999b) Toward a model of unreliability to study error prevention supports. Interact Comput 11:575–595

    Google Scholar 

  • Vanderhaegen F, Wolff M, Mollard R (2020) Non-conscious errors in the control of dynamic events synchronized with heartbeats: a new challenge for human reliability study. Saf Sci 129:104814

    Google Scholar 

  • Varjo J, Hongisto V, Haapakangas A, Maula H, Koskela H, Hyönä J (2015) Simultaneous effects of irrelevant speech, temperature and ventilation rate on performance and satisfaction in open-plan offices. J Environ Psychol 44:16–33

    Google Scholar 

  • Vidulich MA, Pandit P (1987) Individual differences and subjective workload assessment-Comparing pilots to nonpilots. In: Paper presented at the 4th International Symposium on Aviation Psychology, Columbus, OH, United States

  • Wei Z, Zhuang D, Wanyan X, Liu C, Zhuang H (2014) A model for discrimination and prediction of mental workload of aircraft cockpit display interface. Chin J Aeronaut 27:1070–1077

    Google Scholar 

  • Williams T (2014) Improve safety and performance. In: Abnormal Situation Management Consortium celebrates 20 years Hydrocarbon Processing. Gale Academic OneFile. Oct 2014

  • Xie B, Salvendy G (2000) Review and reappraisal of modelling and predicting mental workload in single-and multi-task environments. Work Stress 14:74–99

    Google Scholar 

  • Yang C-W, Yang L-C, Cheng T-C, Jou Y-T, Chiou S-W (2012) Assessing mental workload and situation awareness in the evaluation of computerized procedures in the main control room. Nucl Eng Des 250:713–719

    Google Scholar 

  • Yiend J (2010) The effects of emotion on attention: a review of attentional processing of emotional information. Cogn Emot 24:3–47

    Google Scholar 

  • Young M, Stanton N (2004) Mental workload, handbook of human factors and ergonomics methods. CRC Press

    Google Scholar 

  • Zhang Z, Zhao J (2017) A deep belief network based fault diagnosis model for complex chemical processes. Comput Chem Eng 107:395–407

    Google Scholar 

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Ghalenoei, M., Mortazavi, S.B., Mazloumi, A. et al. Impact of workload on cognitive performance of control room operators. Cogn Tech Work 24, 195–207 (2022). https://doi.org/10.1007/s10111-021-00679-8

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