[Fis] INFORMATION: JUST A MATTER OF MATH

Tue Sep 19 06:53:14 CEST 2017

Hi Fisers,

(1) I have been workign with the so-called Planckain Distribution Eqauiton (PDE) that fits almost all long-tailed histograms generated in many fields  of natural and human sciences, including atomic physics, protein folding, cell metabolism, decision making, glottometrics, econometrics, etc [1-3].

(2) Defining what 'information' is may be akin to defining what 'PDE' is.  In both cases, what we want to define has what may be called the type-token duality (TTD) as indiacted in Table 1.

The type of 'information' may not be  easily defined in words alone but may be defined unambiguously only in terms of a combination of words and a digram as shown in the first column in Table 1.  Similarly, defining what PDE is may be almost impossible  using words alone but must utilize mathematical symbols, not natural linguistic symbols (see the top of the second column)

(3) Just as there are almost infinite nubmer of the 'tokens' of the 'PDE type', each 'token PDE' being characterized by a unique set of three numerical values of A, B and C (see the second column of Table 1), so there may be almost infinite number of the 'tokens' of the 'information type', each 'token information' being characterized by a unique set of 6 parameters, A, B, C, f, g, and h that constitute the ITR, Irreducible Triadic relation [4].  Such a definition of 'information' may be consistent with the 'parametric definition of information' proposed by Mark in 2010 [5].

(4) As I intend to discuss it in a more detail in a later post, it is interesting to point out that the shape of PDE curve embodies both the Shannon entropy (the width of the curve as a measure of disorder) and the Planckian information (the binary logarithm of the non-symmetric portion of the curve denoted as I_P as a measure of order) [1-4].  Furthermore, I_P quantifies the informational aspect of what I call "gnergy" [6], the complementary union of information (gn-) and energy (-ergy), that has been postulated to drive all self-organizations in the Universe, from chemical reactions to the organizations of the Cosmos, including the mental activities of Homo sapiens [4, 7].

Table 1.  The type-token duality (TTD) of concepts, including information and parametric equations.

Information

Planckian Distribution Equation (PDE)

Type

                    f                g
            A --------> B --------> C
             |                                   ^
             |                                    |
             |__________________|
                                h

Irreducible Triadic Relation (ITR)
=>  f x g = h.
“Operation f followed by operation g leads to the same result as operation h”

       y = (A/(x + B)5)/(eC/(x +B) -1)

y = frequency or probability
x = classes or bins
A, B and C = free parameters

Tokens

Semiotics:
A = object; B = sign; C = interpretant
f = sign production
g = sign interpretation
h = correspondence or information flow

Protein folding:
y = frequency
x = folding free energy
A = 1.24x109
B = 0.721
C = 38.97

Aristotle:
A = Hylomorph
B = Matter
C = Form
f = natural process
g = mental process
h = information flow

mRNA levels in yeast under stress:
y = frequency or probability
x = mRNA copy number class or bin
A = 1.11x1012
B = 13.96
C = 159.30

Spinoza:
A = Substance
B = Extension
C = Thought
f = natural process
g = mental process
h = information flow

mRNA levels in human breast tissues:
y = frequency or probability
x = mRNA copy number class or bin
A = 2.36x103
B = 0.213
C = 5.00

General relativity:
A = Matter
B = curved spacetime
C = motion
f =  mass-induced curvature
g = geodesic motion
h = gravity

Protein chain length distribution:
y = frequency or probability
x = protein chain length
A = 2.04x1013
B = 5.655
C = 1.257x103

With alll the best.

Sung

Referecnes:

  [1]

Ji, S. (2016). WAVE-PARTICLE DUALITY IN PHYSICS AND BIOMEDICAL SCIENCES.<http://www.conformon.net/wp-content/uploads/2016/09/PDE_SymmetryFestival_2016.pdf>  Symmetry: Science and Culture 27 (2): 99-127 (2016).  PDF at http://www.conformon.net/wp-content/uploads/2016/09/PDE_SymmetryFestival_2016.pdf

Sungchul Ji - conformon.net<http://www.conformon.net/wp-content/uploads/2016/09/PDE_SymmetryFestival_2016.pdf>
www.conformon.net
single-molecule enzymology, gene expression profiles, econophysics, glottometrics, Menzerath-Altmann law, information-energy complementarity, yin-yang ...

   [2]  Ji, S. (2015). Planckian distributions in molecular machines, living cells, and brains: The wave-particle duality in biomedical sciences.<http://www.conformon.net/wp-content/uploads/2016/09/PDE_Vienna_2015.pdf>  In: Proceedings of the International Conference on Biology and Biomedical Engineering, Vienna, March 15-17, 2015. Pp. 115-137. PDF at  http://www.conformon.net/wp-content/uploads/2016/09/PDE_SymmetryFestival_2016.pdf
Sungchul Ji - conformon.net<http://www.conformon.net/wp-content/uploads/2016/09/PDE_SymmetryFestival_2016.pdf>
www.conformon.net
single-molecule enzymology, gene expression profiles, econophysics, glottometrics, Menzerath-Altmann law, information-energy complementarity, yin-yang ...

   [3]Ji, S. (2015). PLANCKIAN INFORMATION (IP): A NEW MEASURE OF ORDER IN ATOMS, ENZYMES, CELLS, BRAINS, HUMAN SOCIETIES, AND THE COSMOS. <http://www.conformon.net/wp-content/uploads/2016/09/PDE_Vigier9.pdf>  In: Unified Field Mechanics: Natural Science beyond the Veil of Spacetime (Amoroso, R., Rowlands, P., and Kauffman, L. eds.), World Scientific, New Jersey, 2015, pp. 579-589) PDF at http://www.conformon.net/wp-content/uploads/2016/09/PDE_Vigier9.pdf
PLANCKIAN INFORMATION (IP): A NEW MEASURE OF ORDER IN ...<http://www.conformon.net/wp-content/uploads/2016/09/PDE_Vigier9.pdf>
www.conformon.net
1 PLANCKIAN INFORMATION (I P): A NEW MEASURE OF ORDER IN ATOMS, ENZYMES, CELLS, BRAINS, HUMAN SOCIETIES, AND THE COSMOS SUNGCHUL JI Department of Pharmacology and ...

   [4]  Ji, S. (2017).  The Cell Language Theory: connecting Mind and Matter.  World Scientific, New Jersey.   Chapter 9.  In press.

    [5]  Burgin, M. (2010).  Theory of Information: fundamentality, diversity, and unification.  World Scientific, Singapore.

    [6]  Ji, S. (2012).  Complementarity.<http://www.conformon.net/wp-content/uploads/2012/08/Excerpts_Chapters_2_complementarity_08192012.pdf>  In: Molecular Theory of the Living Cell: Concepts, Molecular Mechanisms, and Biomedical Applications.  Springer, New York.  Section 2.3, pp. 24-50. PDF at http://www.conformon.net/wp-content/uploads/2012/08/Excerpts_Chapters_2_complementarity_08192012.pdf

2.3 Complementarity - conformon.net<http://www.conformon.net/wp-content/uploads/2012/08/Excerpts_Chapters_2_complementarity_08192012.pdf>
www.conformon.net
As an example of supplementarity, Einstein’s equation in special relativity, E = mc2 (Shadowitz 1968), may be cited. Energy (A) and matter (B) may be viewed as extreme

   [7] Ji, S. (2017).  Neo_Semiotics: Introducing Zeroness into the Peircean Semiotics may Bridge the Knowable and the Unknowable.  Progress in Biophysics and Molecular Biology (accepted).

________________________________
From: Fis <fis-bounces at listas.unizar.es> on behalf of Lars-Göran Johansson <Lars-Goran.Johansson at filosofi.uu.se>
Sent: Monday, September 18, 2017 1:12:50 PM
To: Terrence W. DEACON
Cc: Foundations of Information Science Information Science
Subject: Re: [Fis] INFORMATION: JUST A MATTER OF MATH

18 sep. 2017 kl. 18:25 skrev Terrence W. DEACON <deacon at berkeley.edu<mailto:deacon at berkeley.edu>>:

All of these claims and counter-claims are null hypotheses - hypothetical axioms yet to be tested, both for logical coherence and empirical usefulness. Place your bets. Mine are on contrary assumptions: i.e. non-Turing computability, fundamental incompleteness, and a deep entanglement between information (including reference and functional value) and its necessary physical substrates. Of course for this to be science all need to eventually yield testable hypotheses. This level of controversy over basic issues indicates to me that the science of information is still at an early stage and could be potentially held back by the hubris of certainty.
I fundamentally agree with Terry; the discussion is about concepts and their use, not about real things. In order to move on to testable empirical consequences one need to tell how to measure a proposed quantity. And if we disagree about how to measure e.g. information, we talk about different quantities while using the same word. The only way to establish that information as measured in two different ways really is the same quantity is to prove that these measurements without exception will yield the same output.
Lars-Göran

— Terry

On Mon, Sep 18, 2017 at 2:07 AM, Bruno Marchal <marchal at ulb.ac.be<mailto:marchal at ulb.ac.be>> wrote:
Dear Jose,

On 15 Sep 2017, at 16:37, Jose Javier Blanco Rivero wrote:

Dear Arturo,

Math is indeed a language that CAN describe scientific issues, but it is not the only one. And its ability to cuantify scientific issues do not necesarily make it superior.
Math and natural language face the same formal and logical problems: they cannot make staments about themselves without falling into contradictions or paradoxes (as can be inferred from Gödel).

You seem to be too much quick on this. On the contrary, I would say, Gödel showed that when we translate the paradoxes of self-reference in arithmetic, we get fundamental limitation theorems, not contradictions. In fact Gödel has led, with the work of Löb and Solovay, to a complete axiomatization of the logic of machine self-reference (complete at the propositional level), and that logic re-introduce the nuances discovered by Plato and exploited by the Neopythagoreans and the Neoplatonicians theologians. Those "theologies" are "theories of everything": they contain physics, and so are testable, and the physics of the machine can be shown to be necessary quantum-like already.

Bruno

And your statement is certainly self-contradictory: if it is true then it is contradicted by the form of its performance (semantics).

Best regards,

El sep 15, 2017 10:17 AM, "tozziarturo at libero.it<mailto:tozziarturo at libero.it>" <tozziarturo at libero.it<mailto:tozziarturo at libero.it>> escribió:
Dear FISers,
I'm sorry for bothering you,
but I start not to agree from the very first principles.

The only language able to describe and quantify scientific issues is mathematics.
Without math, you do not have observables, and information is observable.
Therefore, information IS energy or matter, and can be examined through entropies (such as., e.g., the Bekenstein-Hawking one).

And, please, colleagues, do not start to write that information is subjective and it depends on the observer's mind. This issue has been already tackled by the math of physics: science already predicts that information can be "subjective", in the MATHEMATICAL frameworks of both relativity and quantum dynamics' Copenhagen interpretation.
Therefore, the subjectivity of information is clearly framed in a TOTALLY physical context of matter and energy.

Sorry for my polemic ideas, but, if you continue to define information on the basis of qualitative (and not quantitative) science, information becomes metaphysics, or sociology, or psychology (i.e., branches with doubtful possibility of achieving knowledge, due to their current lack of math).

Arturo Tozzi

AA Professor Physics, University North Texas

Pediatrician ASL Na2Nord, Italy

Comput Intell Lab, University Manitoba

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----Messaggio originale----
Da: "Pedro C. Marijuan" <pcmarijuan.iacs at aragon.es<mailto:pcmarijuan.iacs at aragon.es>>
Data: 15/09/2017 14.13
A: "fis"<fis at listas.unizar.es<mailto:fis at listas.unizar.es>>
Ogg: [Fis] PRINCIPLES OF IS

Dear FIS Colleagues,

As promised herewith the "10 principles of information science". A couple of previous comments may be in order.
First, what is in general the role of principles in science? I was motivated by the unfinished work of philosopher Ortega y Gasset, "The idea of principle in Leibniz and the evolution of deductive theory" (posthumously published in 1958). Our tentative information science seems to be very different from other sciences, rather multifarious in appearance and concepts, and cavalierly moving from scale to scale. What could be the specific role of principles herein? Rather than opening homogeneous realms for conceptual development, these information principles would appear as a sort of "portals" that connect with essential topics of other disciplines in the different organization layers, but at the same time they should try to be consistent with each other and provide a coherent vision of the information world.
And second, about organizing the present discussion, I bet I was too optimistic with the commentators scheme. In any case, for having a first glance on the whole scheme, the opinions of philosophers would be very interesting. In order to warm up the discussion, may I ask John Collier, Joseph Brenner and Rafael Capurro to send some initial comments / criticisms? Later on, if the commentators idea flies, Koichiro Matsuno and Wolfgang Hofkirchner would be very valuable voices to put a perspectival end to this info principles discussion    (both attended the Madrid bygone FIS 1994 conference)...
But this is FIS list, unpredictable in between the frozen states and the chaotic states! So, everybody is invited to get ahead at his own, with the only customary limitation of two messages per week.

Best wishes, have a good weekend --Pedro

10 PRINCIPLES OF INFORMATION SCIENCE

1. Information is information, neither matter nor energy.

2. Information is comprehended into structures, patterns, messages, or flows.

3. Information can be recognized, can be measured, and can be  processed (either computationally or non-computationally).

4. Information flows are essential organizers of life's self-production processes--anticipating, shaping, and mixing up with the accompanying energy flows.

5. Communication/information exchanges among adaptive life-cycles underlie the complexity of biological organizations at all scales.

6. It is symbolic language what conveys the essential communication exchanges of the human species--and constitutes the core of its "social nature."

7. Human information may be systematically converted into efficient knowledge, by following the "knowledge instinct" and further up by applying rigorous methodologies.

8. Human cognitive limitations on knowledge accumulation are partially overcome via the social organization of "knowledge ecologies."

9. Knowledge circulates and recombines socially, in a continuous actualization that involves "creative destruction" of fields and disciplines: the intellectual Ars Magna.

10. Information science proposes a new, radical vision on the information and knowledge flows that support individual lives, with profound consequences for scientific-philosophical practice and for social governance.

--
-------------------------------------------------
Pedro C. Marijuán
Grupo de Bioinformación / Bioinformation Group
Instituto Aragonés de Ciencias de la Salud
Centro de Investigación Biomédica de Aragón (CIBA)
Avda. San Juan Bosco, 13, planta 0
50009 Zaragoza, Spain
Tfno. +34 976 71 3526<tel:+34%20976%2071%2035%2026> (& 6818)
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Professor Terrence W. Deacon
University of California, Berkeley
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