A Mathematical Model of Democratic Elections (2010).
Abstract: Democratic election is the preferred method for determining political administrators nowadays. The
intention is to find the best possible leader in order to improve the group's competitiveness and success. Though
preferred, democratic election is far from being optimal in this respect, and is increasingly becoming the target
for fraud. A model was developed to scientifically analyze the present electoral system's insufficiency. It is
based on fauceir assumptions. Its calculations enable principles to be developed that optimize the election
process, while also revealing the limits of elections in societies growing ever more complex, so that in the end
elections have to be replaced by processes similar to what has proved optimal throughout naturally occurring
Fauceir Poster (published Turin 2009)
Summary: The main idea behind the Fauceir Theory (FT) is dividing a complex process like evolution into subunits that are easier to manage. This concept is not new in evolutionary theory, though. We encounter this approach in modern synthesis, when explaining co-evolution, mass extinction, and altruism, for instance. But FT goes far beyond this point by constructing an abstract subunit that is applicable to all processes in the living word. The fauceirs, these abstract subunits, have characteristics in common no matter where they occur. Simulating the wide range of distinct processes is achieved by varying its composition i.e. number, hierarchy, and relationship.
FT allows to subtly analyse, to mathematically model, and to reproducibly scale the process of increasing complexity. From its specific vantage point, clear distinction can be made between evolution and mere adaptation. Both processes result in some benefit, the latter without and the former with increasing internal complexity. A fauceir grows more complex by incorporation other fauceirs, either by evolving them or by mere acquisition.
FT defines information as an immanent fauceir property and each bit of information being a fauceir itself. In doing so, FT has no problem in explaining the creation, improvement and inheritance of information that underlies each evolutionary process. Also, FT eases modelling transitions from (bio)chemical to biological (origin of life) and from biological to social forms (anthropogenesis).
Philosophical Foundations of Fauceir Evolutionary Theory (2009)
Evolution of Religion (2009)
Abstract Evolution (2009)
An Evolved Concept of Evolution: A Generalized Theory of Evolution Extending from Physics to Societies Provides Startling New Perspectives (2004).
Background Whereas the currently prevailing theory of biological evolution is fairly sufficient for explaining tiny adaptational processes during the evolution of living organisms, substantial problems arise when it focuses on borderline processes (the origin of life and anthropogenesis), big leaps (speciation), and acceleration of the rate of evolution. This present theory can overcome all these problems by taking a more generalized approach.
Theory The theory is based on the postulate that evolution from physics up to society follows the same rules. To achieve this, a particle of evolution is identified, which is a further generalization of the term system and is the same in all realms where evolution takes place.
Based on these assumptions, the logical framework of main principles of evolution is constructed. To understand why evolution keeps rolling, the engine fueled by accelerating release of free entropy is discovered. This leads to the proposal of a new theorem of thermodynamics, which deduces exigency of evolution from the general decay of the universe.
The theory presented here subsumes the mechanism of evolution by natural selection into a broad spectrum of similar processes.
Conclusion The present theory forms the ground and the framework for several new hypotheses in various fields of research in evolution. The practical application of this theory is illustrated by examples.
Axiomas in Biology(2005).
Introduction The term axiom is almost neglected in biomedical literature. A simple search in the Pub Med database reveals an average use of only 0,0025% in the last decade (). In most recent literature, the usage of the word included the name of a technical device , some rhetorical patterns to attract attention , the meaning of common sense or adage [3,4], and its genuine mathematical denotation .
Many reasons may exist for restraint and misuse. Among them are confusions in definition and use, general agreement that obvious facts are worthless to be substantiated, and the apprehension that questioning common knowledge will cause adverse reactions from the public. We will discuss these topics in this article and hope that better understanding of axioms promotes their use and supports to find new grounds for groundbreaking theories as well to overcome outdated and stiff rules. In other word, here comes a brief instruction for one screw at biology's next microscope, mathematics .
Hypothesis of Intrinsic Evolution Control (2005).
Abstract The hypothesis explains rapid evolutionary progress, as it occurred during Cambrian
explosion, by processes ongoing in each individual. The main goal of such processes is to
statistically reduce setbacks and to keep evolution advancing. Because these processes are
part of the inheritable information, they are also subject to evolution themselves and become
ever more sophisticated during phylogeny. Several well known, molecular and cellular
mechanisms are able to achieve this goal. They are predominantly studied in respect to their
impact on DNA maintenance, but because evolution is the opposite of maintenance, every gap
in their function opens the window for evolution. Origination of hereditary diseases and
tumourgenesis can be described in terms of this hypothesis. Because shifting the burden of
evolution control from populations to individuals is a paradigm shift in evolutionary biology,
it requires a theoretical reorientation, which the fauceir evolutionary theory provides
(www.fauceir.org). By acknowledging hereditary information to play an active, selfimproving
role, evolutionary theory is put in line with other learning processes in behaviour
Hypothesis of Controlled Mutagenesis (2005).
Summary This hypothesis is based on the fauceir evolution theory (www.fauceir.org) and gives a rationale for two unresolved phenomena debated among evolutionary biologists: First, the purportedly discrepancy between the minimal number of new mutations causing an increase in fitness and the pace by which evolution goes on, and second, the ever acceleration rate of evolution. The hypothesis states that in the gonads, which are thoroughly shielded from the rest of the body but in intimate communication with it, processes responsible for evolution control are taking place. The mechanisms involved (mutagenesis, DNA repair, cell cycle control, apoptosis, and natural selection) assure a much quicker feedback by eliminating unsuccessful genetic variations and promoting successful ones. By contrast to adaptationist's theories, the present hypothesis describes mechanisms that depart from population only based approaches. As though these processes of evolution exerted an important influence on evolution, they underwent evolutionary improvements as well. Taking over this viewpoint, the evolution of sex finds its teleological rationalization: It has to be viewed as an integrated part of the evolution of evolution control processes.
Statistical Model of Evolutionary Progress (2006).
Introduction The term evolutionary progress is trivial but difficult to grasp. Every evolutionary biologist would certainly agree that there has occurred evolutionary progress and that higher taxa are more developed than protozoa. But in single instances it is problematic to decide whether a change in hereditary information reflects evolutionary progress. This is the case when interpreting genetic drift or simple adaptations such the stickleback problem. After introduction of the model we will be able to provide a definition of evolutionary progress, which can be estimated by statistical data.
© Mato Nagel
, Weisswasser 2004-2010