Caro Sung e cari tutti, "I think information and energy are inseparable in reality": è vero anche in economia.
La Parte Terza--Teoria del valore: energia e informazione-- di "Valore e valutazioni. La scienza dell'economia o l'economia della scienza" (FrancoAngeli, Milano, 1995-1999) è costituita dalle pagine 451-646 contenenti questa interessante e significativa problematica. Grazie e auguri. Francesco 2018-05-07 4:08 GMT+02:00 Sungchul Ji <s...@pharmacy.rutgers.edu>: > Hi FISers, > > I think information and energy are inseparable in reality. Hence to > understand what information is, it may be helpful to understand what energy > (and the associated concept of motion) is. In this spirit, I am forwarding > the following email that I wrote motivated by the lecture given by Dr. > Grossberg this afternoon at the 119th Statistical Mechanics Conference. In > *Table > 1* in the email, I divided particle motions studied in physics and > biology into three classes -- (i) *random*, (ii) *passive*, and (iii) > *active*, and identified the field of specialization wherein these > motions are studied as (i) *statistical mechanics*, (ii) *stochastic > mechanics*, and (iii) *info-statistical mechanics*. The last term was > coined by me in 2012 in . I will be presenting a short talk (5 > minutes) on* Info-statistical mechanics* on Wednesday, May 9, at the > above meeting. The abstract of the short talk is given below: > > Short talk to be presented at the *119th Statistical Mechanics Conference*, > Rutgers University, Piscataway, N.J., May 6-9, 2018). > > > > *Planckian Information** may be to Info-Statistical Mechanics what > Boltzmann Entropy is to Statistical Mechanics. * > > Sungchul Ji, Department of Pharmacology and Toxicology, Ernest Mario > School of Pharmacy, Rutgers University, Piscataway, N.J. 08854 > > Traditionally, the dynamics of any N-particle systems in statistical > mechanics is completely described in terms of the 6-dimensional *phase > space* consisting of the 3N positional coordinates and 3N momenta, where > N is the number of particles in the system . Unlike the particles dealt > with in statistical mechanics which are featureless and shapeless, the > particles in biology have characteristic shapes and internal structures > that determine their biological properties. The particles in physics are > completely described in terms of energy and matter in the phase space but > the description of the particles in living systems require not only the > energy and matter of the particle but also their genetic information, > consistent with the information-energy complementarity (or gnergy) > postulate discussed in [2, Section 2.3.2]. Thus, it seems necessary to > expand the dimensionality of the traditional phase space to accommodate the > *information > *dimension, which includes the three coordinates encoding the *amount *(in > bits), *meaning* (e.g., recognizability), and *value* (e.g., practical > effects) of information [2, Section 4.3]. Similar views were expressed by > Bellomo et al.  and Mamontov et al. . The expanded “phase space” > would comprise the 6N phase space of traditional statistical mechanics plus > the 3N information space entailed by molecular biology. The new space > (to be called the “gnergy space”) composed of these two subspaces would > have 9N dimensions as indicated in Eq. (1). This equation also makes > contact with the concepts of *synchronic* and *diachronic* informations > discussed in [2, Section 4.5]. It was suggested therein that the > traditional 6N-dimensional phase space deals with the *synchronic > information* and hence was referred to as the *Synchronic Space* while > the 3N-dimensional information space is concerned with the consequences of > history and evolution encoded in each particle and thus was referred to as > the *Diachronic Space*. The resulting space was called the *gnergy space* > (since it encodes not only *energy* but also *information*). > > > > *Gnergy Space* = *6N-D Phase Space* + *3N-D Information > Space* (1) > > (*Synchronic Space*) > (*Diachronic > Space*) > > > > The study of both *energy* and *information* was defined as > “info-statistical mechanics” in 2012 [2, pp. 102-106, 297-301]. The > Planckian information of the second kind, IPS,  was defined as the > negative of the binary logarithm of the skewness of the long-tailed > histogram that fits the Planckian Distribution Equation (PDE) . In *Table > 1*, the Planckian information is compared to the Boltzmann entropy in the > context of the complexity theory of Weaver . The inseparable relation > between *energy *and *information* that underlies “info-statistical > mechanics” may be expressed by the following aphorism: > > > *“Information without energy is useless; Energy without information is > valueless.”* > > > > *Table 1.* A comparison between Planckian Information (of the second > kind) and Boltzmann entropy. Adopted from [6, Table 8.3]. > > *Order* > > *Disorder* > > IPS = - log2 [(µ - mode)/σ] > > > > (2008-2018) > > S = k log W > > > > (1872-75) > > *Planckian Information * > > *Boltzmann entropy * > > *Organized Complexity * > > *Disorganized Complexity * > > *Info-Statistical Mechanics* [2, pp. 102-106] > > *Statistical Mechanics * > > > > > > *References:* > >  Tolman, R. C. (1979). *The Principles of Statistical Mechanics, * Dover > Publications, Inc., > > New York, pp. 42-46. > >  Ji, S. (2012) *Molecular Theory of the Living Cell: Concepts, > Molecular Mechanisms, and * > > *Biomedical Applications*. Springer, New York. > >  Bellomo, N., Bellouquid, A. and Harrero, M. A. (2007). From > microscopic to macroscopic > > descriptions of multicellular systems and biological growing tissues. *Comp. > Math. Applications* > > *53*: 647-663. > >  Mamontov, E., Psiuk-Maksymowitcz, K. and Koptioug, A. (2006). > Stochastic > mechanics > > in the context of the properties of living systems. *Math. Comp. Modeling* > *44*(7-8): 595-607. > >  Ji, S. (2018). Mathematical (*Quantitative*) and Cell Linguistic ( > *Qualitative*) Evidence for > > *Hypermetabolic Pathways* as [SJ1] Potential Drug Targets. *J. Mol. > Genet. Medicine *(in press). > >  Ji, S. (2018). *The Cell Language Theory: Connecting Mind and > Matter.* World Scientific > > Publishing, New Jersey. Chapter 8. > >  Boltzmann distribution law. https://en.wikipedia.org/wiki/ > Boltzmann_distribution. > >  Weaver, W. (1948) Science and Complexity. *American Scientist* > *36*:536-544. > > > > > > - - - - - - - - - - - - - -the Email to Dr. Grossberg > --------------------- - - - --- - -- - - - - - - - - - - - - - > > ------------------------------ > > Hi Dr. Grossberg, > > Thank you for your thought-provoking lecture (entitled "From Sisyphus to > Boltzmann: an example of repulsive depletion interaction") this afternoon > at the 119th Statistical Mechanics Conference at Rutgers. > > Your lecture prompted me to construct the following table based on my > experience as a theoretical cell biologist over the last 4 decades as > summarized in [1, 2]. > > According to *Table 1*, we can recognize three distinct kinds of *particle > motions* in physics and biology that may be studied in 3 distinct fields > of specialization, tentatively identified with (i) statistical mechanics, > (ii) stochastic mechanics, and (iii) what I recently referred to as > "info-statistical mechanics" [*1*,pp. 102-107; *2*, pp. 371-374]. > > > *Table 1.* The trichotomy of particle motions in physics and biology > > > *Particle Motions **(**Discipline**)* > > *Random motion (1)* > > (*Statistical mechanics*) > > *Passive motion (2)* > (*Stochastic mechanics* ?) > > *Active motion (3)* > > (*Info-statistical mechanics* ?) > > [*1*, *2*] > > *Energy Source* > > homogeneous thermal environment > > external > > (e.g., magnetic field) > > internal > (e.g., chemical reactions) > > *Physics* > > > > dust particles in water > > at equilibrium > > dust particles in water in flow > > a piece of sodium metal in water at equilibrium > > Brownian motion > > e.g., Orenstein-Uhlenbeck process > > artificial molecular machines > > *Biology* > > > > dead bacteria in water at equilibrium > > live bacteria moving down a gradient > > live bacteria swimming against a gradient > > Brownian motion > > diffusion driven by gradient > > Chemotaxis driven by ATP hydroly > > - In your lecture today,. you referred to "active motions" of > inanimate particles, which seems to correspond to "passive motions" in the > above table, since the driving force for your particle motion is external > to the particle. If you wish to preserve the term "active motion", it seems > to me necessary to differentiate between the "externally driven active > motion" and the "internally driven active motion". On the other hand, if > we adopt the terms,"active" vs. "passive" particle motions, we have a > precedence in biology where "active transport" (e.g., the Na/K pump) and > "passive transport" (e.g., the Na/Ca exchange channel) are well known. In > fact, the triadic classification of particle motions defined in *Table > 1* can be applied to ion movements across biomembranes with an equal > force. > > > If you have any questions or comments on the suggestions made in Table 1, > I would appreciate hearing from you. > > All the best. > > Sung > > *References:* > > [*1*] Ji, S. (2012). *Molecular Theory of the Living Cell: Concepts, > Molecular Mechanisms, and Biomedical Applications*. Springer, New York. > > [*2*] Ji, S. (2018). *The Cell Language Theory: Connecting Mind and > Matter*. World Scientific Publishing, New Jersey. > > > With all the best. > > > Sung > > > _______________________________________________ > Fis mailing list > Fis@listas.unizar.es > http://listas.unizar.es/cgi-bin/mailman/listinfo/fis > >
_______________________________________________ Fis mailing list Fis@listas.unizar.es http://listas.unizar.es/cgi-bin/mailman/listinfo/fis