[Fis] reply to Javorsky
*Replying to Karl, who said:* one can use a stable model used by neurology and psychology to come closer to understanding how our brain works. This can help to formulate the thoughts Pedro mentioned being obscure. One pictures the brain as a quasi-meteorological model of an extended world containing among others swamp, savanna, arid zones. The dissipation of water above these regions causes clouds to form and storms to discharge the vapor within the clouds. The model observes the lightnings in the model and sets them as an allegory to thoughts (these being electrical discharges) as opposed to hormones (that are the fluids in the swamps). So there is an assumed independence between the rainfall, the humidity of the ground, cloud formation and lightnings. The real meteorologists would not agree with the simplification that the lightning is the central idea of a rainfall, but this is how the picture works (at present). Why I offer these idle thoughts from the biologic sciences to FIS is that it is now possible to make a model of these processes in an abstract, logical fashion. The colleaugues in Fis are scientists in the rational tradition and may find useful that a rational algorithm can be shown to allow simulating the little tricks Nature appears to use. Nature changes the form of the imbalance, once too many or too few lightnings, once too much or lacking water - relative to the other representation's stable state. There are TWO sets of reference. The deviation between the two sets of references is what Nature uses in its manifold activities. This model looks at the physical equivalences in two realms by modeling in thermodynamics. Today in thermodynamics we have an advancing perspective known as the ‘Maximum Entropy Production Principle’ (MEPP) for relatively simple systems like weather, or Maximum Energy Dispersal Principle’ (MEDP) for complicated material systems like the brain. In both cases the dynamics are controlled by the Second Law of Thermodynamics, which imposes that the available energy gradients will be dissipated in the least possible time, taking the easiest routes available. This becomes very interesting in the brain, where the flow of depolarizations would then be predicted to be biased in the direction of more habitual ‘thoughts’. I think that this prediction seems to be born out in our own experiences of the frequent return of our attention to various insistent thoughts. I recommend that Karl inquire into MEPP. For this purpose I paste in some references. STAN MEPP related publications: Annila, A. and S.N. Salthe, 2009. Economies evolve by energy dispersal. Entropy, 2009, 11: 606-633. Annila, A. and S.N. Salthe, 2010. Physical foundations of evolutionary theory. Journal on Non-Equilibrium Thermodynamics 35: 301-321. Annila, A. and S.N. Salthe, 2010. Cultural naturalism. Entropy, 2010, 12: 1325-1352. Bejan, A. and S. Lorente, 2010. The constructal law of design and evolution in nature. Philosophical Transactions of the Royal Society, B, 365: 1335-1347. Brooks, D.R. and E.O. Wiley, 1988. Evolution As Entropy: Toward A Unified Theory Of Biology (2nd. ed.) Chicago. University of Chicago Press. Chaisson, E.J., 2008. Long-term global heating from energy usage. Eos, Transactions of the American Geophysical Union 89: 353-255. DeLong, J.P., J.G. Okie, M.E. Moses, R.M. Sibly and J.H. Brown, 2010. Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life. Proceedings of the Natiional Academy of Sciences. Early EDition Dewar, R. C., 2003. Information theory explanation of the fluctuation theorem, maximum entropy production, and self-organized criticality in non-equilibrium stationary states. Journal of Physics, A Mathematics and General 36: L631-L641. Dewar, R.C., 2005. Maximum entropy production and the fluctuation theorem. Journal of Physics A Mathematics and General 38: L371-L381. Dewar, R.C., 2009. Maximum entropy production as an inference algorithm that translates physical assumptions into macroscopic predictions: Don't shoot the messenger. Entropy 2009. 11: 931-944. Dewar. R.C. and A. Porté, 2008. Statistical mechanics unifies different ecological patterns. Journal of Theoretical Biology 251:389-403. Dyke, J. and A. Kleidon. 2010. The maximum entropy production principle: its theoretical foundations and applications to the Earth system. Entropy 2010, 12:613-630. Herrmann-Pillath, C., 2010. Entropy, function and evolution: naturalizing Peircean semiosis. Entropy 2010, 12: 197-242. Kleidon, A. (2009): Non-equilibrium Thermodynamics and Maximum Entropy Production in the Earth System: Applications and Implications, Naturwissenschaften 96: 653-677. Kleidon, A. (2010): Non-equilibrium Thermodynamics, Maximum Entropy Production and Earth-system evolution, Philosophical Transactions of the Royal Society A, 368: 181-196. Kleidon, A. and R. Lorenz (eds) Non-equilibrium Thermodynamics
Re: [Fis] reply to Javorsky
Dear All: At the risk of being seen as the one who tries to throw a monkey wrench into the fine discussion you all are having, I would like to mention that the foregoing thread had focused entirely on alternatives among monist scenarios. I see the world as dual, not in the sense of Descartes, but of Heraclitus. If I am correct, then any strategy predicated on a monist principle is destined to lead to disaster. (Stan and I have gone round and round on this. I see entropy as double-sided and not simply as disorder. [Ecological Modelling 220 (2009) 18861892].) But I'm hardly the only one to warn against a monist view. Terry Deacon's model of self-organization, the Autocell acts similarly. The process starts by using up external gradients as quickly as possible, but gradually shuts down as the autocell nears self-completion. (Deacon, T.W. and J. Sherman. 2008. The Pattern Which Connects Pleroma to Creatura: The Autocell Bridge from Physics to Life. Biosemiotics 2:59-76.) The best to all, Bob - Robert E. Ulanowicz| Tel: +1-352-378-7355 Arthur R. Marshall Laboratory | FAX: +1-352-392-3704 Department of Biology | Emeritus, Chesapeake Biol. Lab Bartram Hall 110 | University of Maryland University of Florida | Email u...@cbl.umces.edu Gainesville, FL 32611-8525 USA | Web http://www.cbl.umces.edu/~ulan -- Quoting Stanley N Salthe ssal...@binghamton.edu: *Replying to Karl, who said:* one can use a stable model used by neurology and psychology to come closer to understanding how our brain works. This can help to formulate the thoughts Pedro mentioned being obscure. One pictures the brain as a quasi-meteorological model of an extended world containing among others swamp, savanna, arid zones. The dissipation of water above these regions causes clouds to form and storms to discharge the vapor within the clouds. The model observes the lightnings in the model and sets them as an allegory to thoughts (these being electrical discharges) as opposed to hormones (that are the fluids in the swamps). So there is an assumed independence between the rainfall, the humidity of the ground, cloud formation and lightnings. The real meteorologists would not agree with the simplification that the lightning is the central idea of a rainfall, but this is how the picture works (at present). Why I offer these idle thoughts from the biologic sciences to FIS is that it is now possible to make a model of these processes in an abstract, logical fashion. The colleaugues in Fis are scientists in the rational tradition and may find useful that a rational algorithm can be shown to allow simulating the little tricks Nature appears to use. Nature changes the form of the imbalance, once too many or too few lightnings, once too much or lacking water - relative to the other representation's stable state. There are TWO sets of reference. The deviation between the two sets of references is what Nature uses in its manifold activities. This model looks at the physical equivalences in two realms by modeling in thermodynamics. Today in thermodynamics we have an advancing perspective known as the `Maximum Entropy Production Principle´ (MEPP) for relatively simple systems like weather, or Maximum Energy Dispersal Principle´ (MEDP) for complicated material systems like the brain. In both cases the dynamics are controlled by the Second Law of Thermodynamics, which imposes that the available energy gradients will be dissipated in the least possible time, taking the easiest routes available. This becomes very interesting in the brain, where the flow of depolarizations would then be predicted to be biased in the direction of more habitual `thoughts´. I think that this prediction seems to be born out in our own experiences of the frequent return of our attention to various insistent thoughts. I recommend that Karl inquire into MEPP. For this purpose I paste in some references. STAN MEPP related publications: Annila, A. and S.N. Salthe, 2009. Economies evolve by energy dispersal. Entropy, 2009, 11: 606-633. Annila, A. and S.N. Salthe, 2010. Physical foundations of evolutionary theory. Journal on Non-Equilibrium Thermodynamics 35: 301-321. Annila, A. and S.N. Salthe, 2010. Cultural naturalism. Entropy, 2010, 12: 1325-1352. Bejan, A. and S. Lorente, 2010. The constructal law of design and evolution in nature. Philosophical Transactions of the Royal Society, B, 365: 1335-1347. Brooks, D.R. and E.O. Wiley, 1988. Evolution As Entropy: Toward A Unified Theory Of Biology (2nd. ed.) Chicago. University of Chicago Press. Chaisson, E.J., 2008. Long-term global heating from energy usage. Eos, Transactions of the American Geophysical
Re: [Fis] reply to Javorsky
On the difference between natural numbers and theories: The tool offered for use is based on natural numbers. It is devoid of any interpretations aside the interpretation relating to common axes that are rectangular. It is pleasing that Stan sees many ways to use the interdependence among natural numbers to be relevant and applicable in thermodynamics. The accountant is satisfied after having found an accounting trick Nature appears to use. That this accounting trick is used all over the manifold activities of Nature is what the accountant says. Stan's remarks show that the model does have practical relevance. The inventor of triangulation by means of trigonometry may have been ridiculed that he does not know the geography of England, although he may have implied that this table can be useful in mapping England. Let me restate: the Table offered shows additional ways of dealing with summands, aside the old method of joining them. Sorting and resorting brings forth two Euclid spaces connected by two planes. The natural unit of transaction is a triplet, which is a logical-numerical statement about the spatial coordinates of fragmentational states. It is a pleasure to learn that the idea appears applicable to Stan to deal with thermodynamic terms of reference in reformulating the concept. Karl 2010/12/3 Stanley N Salthe ssal...@binghamton.edu *Replying to Karl, who said:* one can use a stable model used by neurology and psychology to come closer to understanding how our brain works. This can help to formulate the thoughts Pedro mentioned being obscure. One pictures the brain as a quasi-meteorological model of an extended world containing among others swamp, savanna, arid zones. The dissipation of water above these regions causes clouds to form and storms to discharge the vapor within the clouds. The model observes the lightnings in the model and sets them as an allegory to thoughts (these being electrical discharges) as opposed to hormones (that are the fluids in the swamps). So there is an assumed independence between the rainfall, the humidity of the ground, cloud formation and lightnings. The real meteorologists would not agree with the simplification that the lightning is the central idea of a rainfall, but this is how the picture works (at present). Why I offer these idle thoughts from the biologic sciences to FIS is that it is now possible to make a model of these processes in an abstract, logical fashion. The colleaugues in Fis are scientists in the rational tradition and may find useful that a rational algorithm can be shown to allow simulating the little tricks Nature appears to use. Nature changes the form of the imbalance, once too many or too few lightnings, once too much or lacking water - relative to the other representation's stable state. There are TWO sets of reference. The deviation between the two sets of references is what Nature uses in its manifold activities. This model looks at the physical equivalences in two realms by modeling in thermodynamics. Today in thermodynamics we have an advancing perspective known as the ‘Maximum Entropy Production Principle’ (MEPP) for relatively simple systems like weather, or Maximum Energy Dispersal Principle’ (MEDP) for complicated material systems like the brain. In both cases the dynamics are controlled by the Second Law of Thermodynamics, which imposes that the available energy gradients will be dissipated in the least possible time, taking the easiest routes available. This becomes very interesting in the brain, where the flow of depolarizations would then be predicted to be biased in the direction of more habitual ‘thoughts’. I think that this prediction seems to be born out in our own experiences of the frequent return of our attention to various insistent thoughts. I recommend that Karl inquire into MEPP. For this purpose I paste in some references. STAN MEPP related publications: Annila, A. and S.N. Salthe, 2009. Economies evolve by energy dispersal. Entropy, 2009, 11: 606-633. Annila, A. and S.N. Salthe, 2010. Physical foundations of evolutionary theory. Journal on Non-Equilibrium Thermodynamics 35: 301-321. Annila, A. and S.N. Salthe, 2010. Cultural naturalism. Entropy, 2010, 12: 1325-1352. Bejan, A. and S. Lorente, 2010. The constructal law of design and evolution in nature. Philosophical Transactions of the Royal Society, B, 365: 1335-1347. Brooks, D.R. and E.O. Wiley, 1988. Evolution As Entropy: Toward A Unified Theory Of Biology (2nd. ed.) Chicago. University of Chicago Press. Chaisson, E.J., 2008. Long-term global heating from energy usage. Eos, Transactions of the American Geophysical Union 89: 353-255. DeLong, J.P., J.G. Okie, M.E. Moses, R.M. Sibly and J.H. Brown, 2010. Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life. Proceedings of the Natiional Academy of Sciences. Early
