{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:22:12Z","timestamp":1772252532571,"version":"3.50.1"},"reference-count":83,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,3,7]],"date-time":"2019-03-07T00:00:00Z","timestamp":1551916800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BB\/P022197\/1"],"award-info":[{"award-number":["BB\/P022197\/1"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In the past few decades, probabilistic interpretations of brain functions have become widespread in cognitive science and neuroscience. In particular, the free energy principle and active inference are increasingly popular theories of cognitive functions that claim to offer a unified understanding of life and cognition within a general mathematical framework derived from information and control theory, and statistical mechanics. However, we argue that if the active inference proposal is to be taken as a general process theory for biological systems, it is necessary to understand how it relates to existing control theoretical approaches routinely used to study and explain biological systems. For example, recently, PID (Proportional-Integral-Derivative) control has been shown to be implemented in simple molecular systems and is becoming a popular mechanistic explanation of behaviours such as chemotaxis in bacteria and amoebae, and robust adaptation in biochemical networks. In this work, we will show how PID controllers can fit a more general theory of life and cognition under the principle of (variational) free energy minimisation when using approximate linear generative models of the world. This more general interpretation also provides a new perspective on traditional problems of PID controllers such as parameter tuning as well as the need to balance performances and robustness conditions of a controller. Specifically, we then show how these problems can be understood in terms of the optimisation of the precisions (inverse variances) modulating different prediction errors in the free energy functional.<\/jats:p>","DOI":"10.3390\/e21030257","type":"journal-article","created":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T04:58:35Z","timestamp":1552021115000},"page":"257","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["PID Control as a Process of Active Inference with Linear Generative Models"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6086-4711","authenticated-orcid":false,"given":"Manuel","family":"Baltieri","sequence":"first","affiliation":[{"name":"EASY Group\u2014Sussex Neuroscience, Department of Informatics, University of Sussex, Brighton BN1 9RH, UK"}]},{"given":"Christopher","family":"Buckley","sequence":"additional","affiliation":[{"name":"EASY Group\u2014Sussex Neuroscience, Department of Informatics, University of Sussex, Brighton BN1 9RH, UK"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1162\/neco.1995.7.5.889","article-title":"The Helmholtz Machine","volume":"7","author":"Dayan","year":"1995","journal-title":"Neural Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1038\/4580","article-title":"Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects","volume":"2","author":"Rao","year":"1999","journal-title":"Nat. Neurosci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1016\/j.tins.2004.10.007","article-title":"The Bayesian brain: The role of uncertainty in neural coding and computation","volume":"27","author":"Knill","year":"2004","journal-title":"Trends Neurosci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.jphysparis.2006.10.001","article-title":"A free energy principle for the brain","volume":"100","author":"Friston","year":"2006","journal-title":"J. Physiol.-Paris"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1017\/S0140525X12000477","article-title":"Whatever next? Predictive brains, situated agents, and the future of cognitive science","volume":"36","author":"Clark","year":"2013","journal-title":"Behav. Brain Sci."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hohwy, J. (2013). The Predictive Mind, OUP Oxford.","DOI":"10.1093\/acprof:oso\/9780199682737.001.0001"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.jmp.2015.11.003","article-title":"A tutorial on the free-energy framework for modelling perception and learning","volume":"76","author":"Bogacz","year":"2017","journal-title":"J. Math. Psychol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jmp.2017.09.004","article-title":"The free energy principle for action and perception: A mathematical review","volume":"14","author":"Buckley","year":"2017","journal-title":"J. Math. Psychol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.tics.2009.04.005","article-title":"The free-energy principle: A rough guide to the brain?","volume":"13","author":"Friston","year":"2009","journal-title":"Trends Cognit. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1038\/nrn2787","article-title":"The free-energy principle: A unified brain theory?","volume":"11","author":"Friston","year":"2010","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Friston, K.J., Rigoli, F., Ognibene, D., Mathys, C., Fitzgerald, T., and Pezzulo, G. (2015). Active inference and epistemic value. Cognit. Neurosci., 1\u201328.","DOI":"10.1080\/17588928.2015.1020053"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Friston, K.J. (2008). Hierarchical models in the brain. PLoS Comput. Biol., 4.","DOI":"10.1371\/journal.pcbi.1000211"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/s00422-010-0364-z","article-title":"Action and behavior: A free-energy formulation","volume":"102","author":"Friston","year":"2010","journal-title":"Biol. Cybernet."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s00422-011-0424-z","article-title":"Action understanding and active inference","volume":"104","author":"Friston","year":"2011","journal-title":"Biol. Cybernet."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1016\/j.neuron.2011.10.018","article-title":"What is optimal about motor control?","volume":"72","author":"Friston","year":"2011","journal-title":"Neuron"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"20130475","DOI":"10.1098\/rsif.2013.0475","article-title":"Life as we know it","volume":"10","author":"Friston","year":"2013","journal-title":"J. R. Soc. Interface"},{"key":"ref_17","unstructured":"Seth, A.K. (2014). The Cybernetic Bayesian Brain, Open MIND."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1080\/00018730210155133","article-title":"The fluctuation theorem","volume":"51","author":"Evans","year":"2002","journal-title":"Adv. Phys."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.3390\/e14112100","article-title":"A free energy principle for biological systems","volume":"14","author":"Friston","year":"2012","journal-title":"Entropy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.tics.2016.03.013","article-title":"Navigating the affordance landscape: Feedback control as a process model of behavior and cognition","volume":"20","author":"Pezzulo","year":"2016","journal-title":"Trends Cognit. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.tics.2006.05.003","article-title":"Bayesian decision theory in sensorimotor control","volume":"10","author":"Wolpert","year":"2006","journal-title":"Trends Cognit. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.neuron.2011.10.006","article-title":"Computational mechanisms of sensorimotor control","volume":"72","author":"Franklin","year":"2011","journal-title":"Neuron"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Friston, K.J., Daunizeau, J., and Kiebel, S.J. (2009). Reinforcement learning or active inference?. PLoS ONE, 4.","DOI":"10.1371\/journal.pone.0006421"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Clark, A. (2015). Surfing Uncertainty: Prediction, Action, and the Embodied Mind, Oxford University Press.","DOI":"10.1093\/acprof:oso\/9780190217013.001.0001"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/sjp.12120","article-title":"Radical predictive processing","volume":"53","author":"Clark","year":"2015","journal-title":"Southern. J. Philos."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Baltieri, M., and Buckley, C.L. (2017, January 4\u20138). An active inference implementation of phototaxis. Proceedings of the 14th European Conference on Artificial Life 2017, Lyon, France.","DOI":"10.7551\/ecal_a_011"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Manoonpong, P., Larsen, J.C., Xiong, X., Hallam, J., and Triesch, J. (2018). A Probabilistic Interpretation of PID Controllers Using Active Inference. From Animals to Animats 15, Springer International Publishing.","DOI":"10.1007\/978-3-319-97628-0"},{"key":"ref_28","unstructured":"Clark, A. (1998). Being There: Putting Brain, Body, and World Together Again, MIT Press."},{"key":"ref_29","first-page":"83","article-title":"Requisite variety and its implications for the control of complex systems","volume":"1","author":"Ashby","year":"1958","journal-title":"Cybernetica"},{"key":"ref_30","first-page":"1","article-title":"Coding theorems for a discrete source with a fidelity criterion","volume":"4","author":"Shannon","year":"1959","journal-title":"IRE Nat. Conv. Rec"},{"key":"ref_31","first-page":"102","article-title":"Contributions to the theory of optimal control","volume":"5","author":"Kalman","year":"1960","journal-title":"Bol. Soc. Mat. Mexicana"},{"key":"ref_32","unstructured":"Stengel, R.F. (1994). Optimal Control and Estimation, Courier Corporation."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Todorov, E. (2008, January 9\u201311). General duality between optimal control and estimation. Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico.","DOI":"10.1109\/CDC.2008.4739438"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ashby, W.R. (1957). An Introduction to Cybernetics, Chapman & Hall Ltd.","DOI":"10.5962\/bhl.title.5851"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Wiener, N. (1961). Cybernetics or Control and Communication in the Animal and the Machine, MIT Press.","DOI":"10.1037\/13140-000"},{"key":"ref_36","unstructured":"\u00c5str\u00f6m, K.J. (1995). PID Controllers: Theory, Design and Tuning, ISA: The Instrumentation, Systems, and Automation Society."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1109\/TCST.2005.847331","article-title":"PID control system analysis, design, and technology","volume":"13","author":"Ang","year":"2005","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_38","unstructured":"\u00c5str\u00f6m, K.J., and H\u00e4gglund, T. (2006). Advanced PID Control, ISA: The Instrumentation, Systems, and Automation Society."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4649","DOI":"10.1073\/pnas.97.9.4649","article-title":"Robust perfect adaptation in bacterial chemotaxis through integral feedback control","volume":"97","author":"Yi","year":"2000","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.sysconle.2005.08.009","article-title":"Positive feedback may cause the biphasic response observed in the chemoattractant-induced response of Dictyostelium cells","volume":"55","author":"Yang","year":"2006","journal-title":"Syst. Control Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1016\/j.jtbi.2010.07.034","article-title":"Considerations for using integral feedback control to construct a perfectly adapting synthetic gene network","volume":"266","author":"Ang","year":"2010","journal-title":"J. Theoret. Biol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1162\/jocn_a_01289","article-title":"A Control Theoretic Model of Adaptive Learning in Dynamic Environments","volume":"30","author":"Ritz","year":"2018","journal-title":"J. Cognit. Neurosci."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Chevalier, M., Gomez-Schiavon, M., Ng, A., and El-Samad, H. (2018). Design and Analysis of a Proportional-Integral-Derivative Controller with Biological Molecules. bioRxiv.","DOI":"10.1101\/303545"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.1016\/S0967-0661(01)00062-4","article-title":"The future of PID control","volume":"9","year":"2001","journal-title":"Control Eng. Pract."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1016\/j.jprocont.2004.01.002","article-title":"Revisiting the Ziegler\u2013Nichols step response method for PID control","volume":"14","year":"2004","journal-title":"J. Process Control"},{"key":"ref_46","unstructured":"Arturo Urquizo (2018, March 30). PID Controller\u2014Wikipedia, the Free Encyclopedia. Available online: https:\/\/en.wikipedia.org\/wiki\/PID_controller."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1021\/i200032a041","article-title":"Internal model control: PID controller design","volume":"25","author":"Rivera","year":"1986","journal-title":"Ind. Eng. Chem. Process Des. Dev."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1016\/S0005-1098(98)00011-9","article-title":"Design of PI controllers based on non-convex optimization","volume":"34","author":"Panagopoulos","year":"1998","journal-title":"Automatica"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1016\/j.jprocont.2014.02.020","article-title":"Performance and robustness trade-offs in PID control","volume":"24","author":"Garpinger","year":"2014","journal-title":"J. Process Control"},{"key":"ref_50","unstructured":"Grimble, M., and Johnson, M. (1999, January 2\u20134). Algorithm for PID controller tuning using LQG cost minimization. Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251), San Diego, CA, USA."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"O\u2019Brien, R.T., and Howe, J.M. (2008, January 11\u201313). Optimal PID controller design using standard optimal control techniques. Proceedings of the 2008 American Control Conference, Seattle, WA, USA.","DOI":"10.1109\/ACC.2008.4587242"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"20180041","DOI":"10.1098\/rsfs.2018.0041","article-title":"Semantic information, autonomous agency and non-equilibrium statistical physics","volume":"8","author":"Kolchinsky","year":"2018","journal-title":"Interface Focus"},{"key":"ref_53","unstructured":"Beal, M.J. (2003). Variational Algorithms for Approximate Bayesian Inference, University of London."},{"key":"ref_54","unstructured":"Bishop, C.M. (2006). Pattern Recognition and Machine Learning, Springer."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1214\/aoms\/1177729694","article-title":"On information and sufficiency","volume":"22","author":"Kullback","year":"1951","journal-title":"Ann. Math. Stat."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1016\/j.neuroimage.2008.02.054","article-title":"DEM: A variational treatment of dynamic systems","volume":"41","author":"Friston","year":"2008","journal-title":"NeuroImage"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Friston, K.J., Stephan, K., Li, B., and Daunizeau, J. (2010). Generalised filtering. Math. Probl. Eng., 2010.","DOI":"10.1155\/2010\/621670"},{"key":"ref_58","unstructured":"Stratonovich, R.L. (1967). Topics in the Theory of Random Noise, CRC Press."},{"key":"ref_59","unstructured":"Jazwinski, A.H. (1970). Stochastic Processes and Filtering Theory, Academic Press."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1007\/BF01011160","article-title":"Stochastic calculus in physics","volume":"46","author":"Fox","year":"1987","journal-title":"J. Stat. Phys."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1560","DOI":"10.1214\/aoms\/1177699916","article-title":"On the convergence of ordinary integrals to stochastic integrals","volume":"36","author":"Wong","year":"1965","journal-title":"Ann. Math. Stat."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"055017","DOI":"10.1088\/1367-2630\/16\/5\/055017","article-title":"On the interpretation of Stratonovich calculus","volume":"16","author":"Moon","year":"2014","journal-title":"New J. Phys."},{"key":"ref_63","unstructured":"Van Kampen, N.G. (1992). Stochastic Processes in Physics and Chemistry, Elsevier."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Kl\u00f6den, P.E., and Platen, E. (1992). Numerical Solution of Stochastic Differential Equations, Springer.","DOI":"10.1007\/978-3-662-12616-5"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Chui, C.K., and Chen, G. (2017). Kalman filtering with Real-Time Applications, Springer.","DOI":"10.1007\/978-3-319-47612-4"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.neuroimage.2006.08.035","article-title":"Variational free energy and the Laplace approximation","volume":"34","author":"Friston","year":"2007","journal-title":"Neuroimage"},{"key":"ref_67","unstructured":"MacKay, D.J. (2003). Information Theory, Inference and Learning Algorithms, Cambridge University Press."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"S\u00e4rkk\u00e4, S. (2013). Bayesian Filtering and Smoothing, Cambridge University Press.","DOI":"10.1017\/CBO9781139344203"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2616","DOI":"10.1162\/neco_a_01115","article-title":"Recognition Dynamics in the Brain under the Free-Energy Principle","volume":"30","author":"Kim","year":"2018","journal-title":"Neural Comput."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1007\/s10339-013-0571-3","article-title":"Active inference, sensory attenuation and illusions","volume":"14","author":"Brown","year":"2013","journal-title":"Cognit. Process."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1016\/S0959-4388(99)00028-8","article-title":"Internal models for motor control and trajectory planning","volume":"9","author":"Kawato","year":"1999","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1038\/81497","article-title":"Computational principles of movement neuroscience","volume":"3","author":"Wolpert","year":"2000","journal-title":"Nat. Neurosci."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"\u00c5str\u00f6m, K.J., and Murray, R.M. (2010). Feedback Systems: An Introduction for Scientists and Engineers, Princeton University Press.","DOI":"10.2307\/j.ctvcm4gdk"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Svrcek, W.Y., Mahoney, D.P., Young, B.R., and Mahoney, D.P. (2006). A Real-Time Approach to Process Control, Wiley.","DOI":"10.1002\/9780470029558"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.cell.2009.04.047","article-title":"A systems-level analysis of perfect adaptation in yeast osmoregulation","volume":"138","author":"Muzzey","year":"2009","journal-title":"Cell"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/S0167-6911(03)00136-1","article-title":"Adaptation and regulation with signal detection implies internal model","volume":"50","author":"Sontag","year":"2003","journal-title":"Syst. Control Lett."},{"key":"ref_77","first-page":"401","article-title":"Two-degree-of-freedom PID controllers","volume":"1","author":"Araki","year":"2003","journal-title":"Int. J. Control Autom. Syst."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Johnson, M.A., and Moradi, M.H. (2005). PID Control, Springer.","DOI":"10.1007\/1-84628-148-2"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.1016\/0967-0661(95)00164-P","article-title":"A control-loop performance monitor","volume":"3","year":"1995","journal-title":"Control Eng. Pract."},{"key":"ref_80","unstructured":"Ferguson, T.S. (1967). Mathematical Statistics: A Decision Theoretic Approach, Academic Press."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1214\/aos\/1176345645","article-title":"A complete class theorem for statistical problems with finite sample spaces","volume":"9","author":"Brown","year":"1981","journal-title":"Ann. Stat."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.cels.2016.01.004","article-title":"Antithetic integral feedback ensures robust perfect adaptation in noisy biomolecular networks","volume":"2","author":"Briat","year":"2016","journal-title":"Cell Syst."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A new approach to linear filtering and prediction problems","volume":"82","author":"Kalman","year":"1960","journal-title":"J. Basic Eng."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/3\/257\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:36:55Z","timestamp":1760186215000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/3\/257"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,7]]},"references-count":83,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["e21030257"],"URL":"https:\/\/doi.org\/10.3390\/e21030257","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201902.0246.v1","asserted-by":"object"}]},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,7]]}}}