{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:06:52Z","timestamp":1776085612652,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,11,11]],"date-time":"2019-11-11T00:00:00Z","timestamp":1573430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61877050"],"award-info":[{"award-number":["61877050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ShaanXi province key research and development program","award":["2019ZDLGY03-1"],"award-info":[{"award-number":["2019ZDLGY03-1"]}]},{"name":"basic education in Shaanxi province of China","award":["ZDKT1916"],"award-info":[{"award-number":["ZDKT1916"]}]},{"name":"the Northwest University graduate quality improvement program","award":["YZZ17177"],"award-info":[{"award-number":["YZZ17177"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Over the past few years, online learning has exploded in popularity due to the potentially unlimited enrollment, lack of geographical limitations, and free accessibility of many courses. However, learners are prone to have poor performance due to the unconstrained learning environment, lack of academic pressure, and low interactivity. Personalized intervention design with the learners\u2019 background and learning behavior factors in mind may improve the learners\u2019 performance. Causality strictly distinguishes cause from outcome factors and plays an irreplaceable role in designing guiding interventions. The goal of this paper is to construct a Bayesian network to make causal analysis and then provide personalized interventions for different learners to improve learning. This paper first constructs a Bayesian network based on background and learning behavior factors, combining expert knowledge and a structure learning algorithm. Then the important factors in the constructed network are selected using mutual information based on entropy. At last, we identify learners with poor performance using inference and propose personalized interventions, which may help with successful applications in education. Experimental results verify the effectiveness of the proposed method and demonstrate the impact of factors on learning performance.<\/jats:p>","DOI":"10.3390\/e21111102","type":"journal-article","created":{"date-parts":[[2019,11,12]],"date-time":"2019-11-12T04:07:07Z","timestamp":1573531627000},"page":"1102","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Causal Analysis of Learning Performance Based on Bayesian Network and Mutual Information"],"prefix":"10.3390","volume":"21","author":[{"given":"Jing","family":"Chen","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}]},{"given":"Jun","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}]},{"given":"Jingzhao","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0572-641X","authenticated-orcid":false,"given":"Xia","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Northwest University, Xi\u2019an 710127, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"73669","DOI":"10.1109\/ACCESS.2018.2876755","article-title":"Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach","volume":"6","author":"Hussain","year":"2018","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.compedu.2014.08.006","article-title":"Understanding the MOOCs continuance: The role of openness and reputation","volume":"80","author":"Alraimi","year":"2015","journal-title":"Comput. Educ."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Anderson, A., Huttenlocher, D.P., Kleinberg, J.M., and Leskovec, J. (2014, January 7\u201311). Engaging with massive online courses. Proceedings of the 23rd International World Wide Web Conference (WWW\u201914), Seoul, Korea.","DOI":"10.1145\/2566486.2568042"},{"key":"ref_4","first-page":"253","article-title":"Short videos improve student learning in online education","volume":"28","author":"Hsin","year":"2013","journal-title":"J. Comput. Sci. Coll."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"6313","DOI":"10.1073\/pnas.1221764110","article-title":"Interpolated memory tests reduce mind wandering and improve learning of online lectures","volume":"110","author":"Szpunar","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.1016\/j.compedu.2012.05.009","article-title":"An online game approach for improving students\u2019 learning performance in web-based problem-solving activities","volume":"59","author":"Hwang","year":"2012","journal-title":"Comput. Educ."},{"key":"ref_7","first-page":"2","article-title":"Mining educational data to improve students\u2019 performance: A case study","volume":"2","year":"2012","journal-title":"Int. J. Inf. Commun. Technol. Res."},{"key":"ref_8","first-page":"12","article-title":"Data Mining Applications: A Comparative Study for Predicting Students Performance","volume":"1","author":"Kumar","year":"2011","journal-title":"Int. J. Innov. Technol. Creat. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.chb.2014.09.034","article-title":"Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining and theory","volume":"47","author":"Xing","year":"2015","journal-title":"Comput. Hum. Behav."},{"key":"ref_10","first-page":"21","article-title":"Beyond student perceptions: Issues of interaction, presence, and performance in an online course","volume":"6","author":"Picciano","year":"2002","journal-title":"J. Asynchronous Learn. Netw."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1109\/TSP.2015.2496278","article-title":"Predicting grades","volume":"64","author":"Meier","year":"2016","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MC.2016.119","article-title":"Predicting student performance using personalized analytics","volume":"49","author":"Elbadrawy","year":"2016","journal-title":"Computer"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Daradoumis, T., Bassi, R., Xhafa, F., and Caball\u00e9, S. (2013, January 28\u201330). A review on massive e-learning (MOOC) design, delivery and assessment. Proceedings of the 2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, Compiegne, France.","DOI":"10.1109\/3PGCIC.2013.37"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Coffrin, C., Corrin, L., de Barba, P., and Kennedy, G. (2014, January 24\u201328). Visualizing patterns of student engagement and performance in MOOCs. Proceedings of the Fourth International Conference on Learning Analytics And Knowledge, Indianapolis, IN, USA.","DOI":"10.1145\/2567574.2567586"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1111\/jcal.12270","article-title":"Predicting student performance in a blended MOOC","volume":"34","author":"Conijn","year":"2018","journal-title":"J. Comput. Assist. Learn."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.compedu.2015.11.015","article-title":"Students\u2019 patterns of engagement and course performance in a Massive Open Online Course","volume":"95","author":"Phan","year":"2016","journal-title":"Comput. Educ."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Al-Shabandar, R., Hussain, A., Laws, A., Keight, R., Lunn, J., and Radi, N. (2017, January 14\u201319). Machine learning approaches to predict learning outcomes in Massive open online courses. Proceedings of the 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, AK, USA.","DOI":"10.1109\/IJCNN.2017.7965922"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.compedu.2017.03.003","article-title":"Understanding the massive open online course (MOOC) student experience: An examination of attitudes, motivations, and barriers","volume":"110","author":"Shapiro","year":"2017","journal-title":"Comput. Educ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"249","DOI":"10.3200\/JEXE.74.3.249-266","article-title":"Understanding Correlation: Factors That Affect the Size of r","volume":"74","author":"Goodwin","year":"2006","journal-title":"J. Exp. Educ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1080\/10408340500526766","article-title":"The correlation coefficient: An overview","volume":"36","author":"Asuero","year":"2006","journal-title":"Crit. Rev. Anal. Chem."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1023\/A:1017445827962","article-title":"Causality: Models, reasoning, and inference","volume":"34","author":"Pearl","year":"2002","journal-title":"IIE Trans."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.apergo.2016.05.006","article-title":"Constructing a Bayesian network model for improving safety behavior of employees at workplaces","volume":"58","author":"Mohammadfam","year":"2017","journal-title":"Appl. Ergon."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Parhizkar, T., Balali, S., and Mosleh, A. (2018). An entropy based bayesian network framework for system health monitoring. Entropy, 20.","DOI":"10.3390\/e20060416"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.1016\/j.envsoft.2011.06.004","article-title":"Bayesian networks in environmental modelling","volume":"26","author":"Aguilera","year":"2011","journal-title":"Environ. Model. Softw."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1126\/science.1261627","article-title":"Rebooting MOOC research","volume":"347","author":"Reich","year":"2015","journal-title":"Science"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Wang, H., Hao, X., Jiao, W., and Jia, X. (2016, January 8\u201312). Causal Association Analysis Algorithm for MOOC Learning Behavior and Learning Effect. Proceedings of the 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC\/PiCom\/DataCom\/CyberSciTech), Auckland, New Zealand.","DOI":"10.1109\/DASC-PICom-DataCom-CyberSciTec.2016.53"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1111\/jcal.12289","article-title":"Factors affecting student learning performance: A causal model in higher blended education","volume":"34","year":"2018","journal-title":"J. Comput. Assist. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1136\/emj.20.2.164","article-title":"Designing a research project: Randomised controlled trials and their principles","volume":"20","author":"Kendall","year":"2003","journal-title":"Emerg. Med. J. EMJ"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Steiner, P.M., Wroblewski, A., and Cook, T.D. (2009). Randomized experiments and quasi-experimental designs in educational research. The SAGE International Handbook of Educational Evaluation, SAGE.","DOI":"10.4135\/9781452226606.n5"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1002\/pam.20375","article-title":"Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons","volume":"27","author":"Cook","year":"2008","journal-title":"J. Policy Anal. Manag. J. Assoc. Public Policy Anal. Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.jsr.2007.09.009","article-title":"A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors","volume":"39","author":"Ren","year":"2008","journal-title":"J. Saf. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1111\/1467-8527.t01-1-00178","article-title":"The need for randomised controlled trials in educational research","volume":"49","author":"Torgerson","year":"2001","journal-title":"Br. J. Educ. Stud."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1177\/1098300709334798","article-title":"Examining the effects of schoolwide positive behavioral interventions and supports on student outcomes: Results from a randomized controlled effectiveness trial in elementary schools","volume":"12","author":"Bradshaw","year":"2010","journal-title":"J. Posit. Behav. Interv."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1080\/00131881.2018.1493353","article-title":"The trials of evidence-based practice in education: A systematic review of randomised controlled trials in education research 1980\u20132016","volume":"60","author":"Connolly","year":"2018","journal-title":"Educ. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1016\/j.compedu.2012.06.012","article-title":"Using Bayesian networks to improve knowledge assessment","volume":"60","author":"Castillo","year":"2013","journal-title":"Comput. Educ."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Mill\u00e1n, E., Jim\u00e9nez, G., Belmonte, M.V., and P\u00e9rez-de-la Cruz, J.L. (2015, January 21\u201325). Learning Bayesian networks for student modeling. Proceedings of the International Conference on Artificial Intelligence in Education, Madrid, Spain.","DOI":"10.1007\/978-3-319-19773-9_100"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"De Campos, C.P., Zeng, Z., and Ji, Q. (2009, January 14\u201318). Structure learning of Bayesian networks using constraints. Proceedings of the 26th Annual International Conference on Machine Learning, Montreal, QC, Canada.","DOI":"10.1145\/1553374.1553389"},{"key":"ref_38","first-page":"1357","article-title":"Bayesian network learning with parameter constraints","volume":"7","author":"Niculescu","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"ref_39","first-page":"2251","article-title":"Finding optimal Bayesian network given a super-structure","volume":"9","author":"Perrier","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Scutari, M. (2009). Learning Bayesian networks with the bnlearn R package. arXiv.","DOI":"10.18637\/jss.v035.i03"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.ijar.2006.06.009","article-title":"Bayesian network learning algorithms using structural restrictions","volume":"45","author":"Castellano","year":"2007","journal-title":"Int. J. Approx. Reason."},{"key":"ref_42","first-page":"286","article-title":"Reaching the Second Tier: Learning and Teaching Styles in College Science Education","volume":"23","author":"Felder","year":"1993","journal-title":"J. Coll. Sci. Teach."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Cowell, R. (1998). Introduction to inference for Bayesian networks. Learning in Graphical Models, Springer.","DOI":"10.1007\/978-94-011-5014-9_1"},{"key":"ref_44","unstructured":"Dataverse (2019, January 20). Canvas Network Person-Course (1\/2014-9\/2015) De-Identified Dataset [DB\/OL]. (2016-02-16). Available online: https:\/\/dataverse.harvard.edu\/dataset.xhtml?persistentId=doi:10.7910\/DVN\/1XORAL."},{"key":"ref_45","first-page":"4","article-title":"Discretization: An enabling technique","volume":"6","author":"Liu","year":"2002","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_46","unstructured":"Victoria University of Wellington (2019, January 20). Standard Pass\/Fail Grades [DB\/OL]. Available online: https:\/\/www.victoria.ac.nz\/students\/study\/progress\/grades."},{"key":"ref_47","unstructured":"Allaire, J. (2012). RStudio: Integrated Development Environment for R, Citeseer."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v047.i11","article-title":"Causal inference using graphical models with the R package pcalg","volume":"47","author":"Kalisch","year":"2012","journal-title":"J. Stat. Softw."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1080\/03043790802564046","article-title":"Learning needs time and effort: A time-use study of engineering students","volume":"33","author":"Kolari","year":"2008","journal-title":"Eur. J. Eng. Educ."},{"key":"ref_50","first-page":"13","article-title":"Studying learning in the worldwide classroom research into edX\u2019s first MOOC","volume":"8","author":"Breslow","year":"2013","journal-title":"Res. Pract. Assess."},{"key":"ref_51","unstructured":"Christensen, G., Steinmetz, A., Alcorn, B., Bennett, A., Woods, D., and Emanuel, E. (2019, January 20). The MOOC Phenomenon: Who Takes Massive Open Online Courses and Why?. Available online: https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2350964."},{"key":"ref_52","first-page":"262","article-title":"Influencing factors of success and failure in MOOC and general analysis of learner behavior","volume":"6","author":"Rai","year":"2016","journal-title":"Int. J. Inf. Educ. Technol."},{"key":"ref_53","unstructured":"Bell, D. (2014). The Perceived Success of Interventions in Science Education-a Summary: A Report for the Wellcome Trust, Wellcome Trust."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Okoye, I., Maull, K., Foster, J., and Sumner, T. (2012). Educational recommendation in an informal intentional learning system. Educational Recommender Systems and Technologies: Practices and Challenges, IGI Global.","DOI":"10.4018\/978-1-61350-489-5.ch001"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Leighton, J., and Gierl, M. (2007). Cognitive Diagnostic Assessment for Education: Theory and Applications, Cambridge University Press.","DOI":"10.1017\/CBO9780511611186"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Lee, Y.C., Lin, W.C., Cherng, F.Y., Wang, H.C., Sung, C.Y., and King, J.T. (2015, January 18\u201323). Using time-anchored peer comments to enhance social interaction in online educational videos. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Korea.","DOI":"10.1145\/2702123.2702349"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Glassman, E.L., Kim, J., Monroy-Hern\u00e1ndez, A., and Morris, M.R. (2015, January 18\u201323). Mudslide: A spatially anchored census of student confusion for online lecture videos. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Korea.","DOI":"10.1145\/2702123.2702304"},{"key":"ref_58","first-page":"383","article-title":"Intervention Strategies for the Improvement of Students\u2019 Academic Performance in Data Structure Course","volume":"4","author":"Garcia","year":"2014","journal-title":"Int. J. Inf. Educ. Technol."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Coetzee, D., Fox, A., Hearst, M.A., and Hartmann, B. (2014, January 15\u201319). Should your MOOC forum use a reputation system?. Proceedings of the 17th ACM conference on Computer Supported Cooperative Work & Social Computing, Baltimore, MD, USA.","DOI":"10.1145\/2531602.2531657"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1016\/j.compedu.2010.02.018","article-title":"Using game theory and competition-based learning to stimulate student motivation and performance","volume":"55","author":"Burguillo","year":"2010","journal-title":"Comput. Educ."},{"key":"ref_61","first-page":"173","article-title":"Enhancing student performance in online learning and traditional face-to-face class delivery","volume":"3","author":"Stansfield","year":"2004","journal-title":"J. Inf. Technol. Educ. Res."},{"key":"ref_62","unstructured":"Zhang, H., Almeroth, K., Knight, A., Bulger, M., and Mayer, R. (2007, January 25). Moodog: Tracking students\u2019 online learning activities. Proceedings of the EdMedia+ Innovate Learning. Association for the Advancement of Computing in Education (AACE), Vancouver, BC, Canada."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Kim, J., Glassman, E.L., Monroy-Hern\u00e1ndez, A., and Morris, M.R. (2015, January 18\u201323). RIMES: Embedding interactive multimedia exercises in lecture videos. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Korea.","DOI":"10.1145\/2702123.2702186"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Kim, J., Guo, P.J., Seaton, D.T., Mitros, P., Gajos, K.Z., and Miller, R.C. (2014, January 4\u20135). Understanding in-video dropouts and interaction peaks inonline lecture videos. Proceedings of the first ACM conference on Learning@ scale conference, Atlanta, GA, USA.","DOI":"10.1145\/2556325.2566237"},{"key":"ref_65","first-page":"207","article-title":"Factors influencing adult learners\u2019 decision to drop out or persist in online learning","volume":"12","author":"Park","year":"2009","journal-title":"J. Educ. Technol. Soc."},{"key":"ref_66","unstructured":"Wen, M., Yang, D., and Rose, C. (2019, January 20). Sentiment Analysis in MOOC Discussion Forums: What Does It Tell Us? Educational Data Mining 2014. Available online: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.660.5804&rep=rep1&type=pdf."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Ramesh, A., Goldwasser, D., Huang, B., Daume, H., and Getoor, L. (2014, January 26). Understanding MOOC discussion forums using seeded LDA. Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications, Baltimore, MD, USA.","DOI":"10.3115\/v1\/W14-1804"},{"key":"ref_68","first-page":"61","article-title":"Predicting student performance by using data mining methods for classification","volume":"13","author":"Kabakchieva","year":"2013","journal-title":"Cybern. Inf. Technol."},{"key":"ref_69","first-page":"57","article-title":"Predicting student retention in massive open online courses using hidden markov models","volume":"53","author":"Balakrishnan","year":"2013","journal-title":"Electr. Eng. Comput. Sci. Univ. Calif. Berkeley"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/11\/1102\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:33:34Z","timestamp":1760189614000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/11\/1102"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,11]]},"references-count":69,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["e21111102"],"URL":"https:\/\/doi.org\/10.3390\/e21111102","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,11]]}}}