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 [1].  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 [1]. 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. [3] and Mamontov et al. [4].  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, [5] was defined as the
> negative of the binary logarithm of the skewness of the long-tailed
> histogram that fits the Planckian Distribution Equation (PDE) [6].   In *Table
> 1*, the Planckian information is compared to the Boltzmann entropy in the
> context of the complexity theory of Weaver [8]. 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 *[7]
>
> *Organized Complexity *[8]
>
> *Disorganized Complexity *[8]
>
> *Info-Statistical Mechanics* [2, pp. 102-106]
>
> *Statistical Mechanics *[1]
>
>
>
>
>
> *References:*
>
>    [1] Tolman, R. C. (1979). *The Principles of Statistical Mechanics, * Dover
> Publications, Inc.,
>
> New York, pp. 42-46.
>
>    [2] Ji, S. (2012) *Molecular Theory of the Living Cell: Concepts,
> Molecular Mechanisms, and *
>
> *Biomedical Applications*.  Springer, New York.
>
>    [3] 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.
>
>    [4] 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.
>
>     [5] Ji, S. (2018). Mathematical (*Quantitative*) and Cell Linguistic (
> *Qualitative*) Evidence for
>
> *Hypermetabolic Pathways* as [SJ1] Potential Drug Targets. *J. Mol.
> Genet. Medicine *(in press).
>
>     [6] Ji, S. (2018).  *The Cell Language Theory: Connecting Mind and
> Matter.* World Scientific
>
> Publishing, New Jersey.  Chapter 8.
>
>     [7] Boltzmann distribution law.  https://en.wikipedia.org/wiki/
> Boltzmann_distribution.
>
>     [8] 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
>
>
> _______________________________________________
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>
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