Competing Definitions of Information Versus Entropy in Physics

As was mentioned by Nicolas Lori in his (Found Sci, 2010) commentary, the definition of Information in Physics is something about which not all authors agreed. According to physicists like me Information decreases when Entropy increases (so entropy would be a negative measure of information), while many physicists, seemingly the majority of them, are convinced of the contrary (even in the camp of Quantum Information Theoreticians). In this reply I reproduce, and make more precise, some of my arguments, that appeared here and there in my (2010) paper, in order to clarify the presentation of my personal point of view on the subject.     

Heterogeneity,nonlinearity and endogenous market volatility

This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. An exogenous noise is introduced to the model with the assumption of IID normal innovations of the fundamental value in order to investigate how noisy dynamics interacts with deterministic process. The market is composed of two typical trader types: the rational fundamentalists and the boundedly rational traders governed by greed and fear. The interaction between noise and deterministic element determines the evolution process of the system as key parameters are changed. The authors find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S&P500 index, such as volatility clustering, fat tails (leptokurtosis), autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. The authors also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.     

Optimal multi-asset investment with no-shorting constraint under mean-variance criterion for an insurer

This paper considers the optimal investment strategy for an insurer under the criterion of mean-variance. The risk process is a compound Poisson process and the insurer can invest in a risk-free asset and multiple risky assets. This paper obtains the optimal investment policy using the stochastic linear quadratic (LQ) control theory with no-shorting constraint. Then the efficient strategy (optimal investment strategy) and efficient frontier are derived explicitly by a verification theorem with the viscosity solution of Hamilton-Jacobi-Bellman (HJB) equation.     

Sample average approximation method for a class of stochastic variational inequality problems

This paper considers a class of stochastic variational inequality problems. As proposed by Jiang and Xu (2008), by using the so-called regularized gap function, the authors formulate the problems as constrained optimization problems and then propose a sample average approximation method for solving the problems. Under some moderate conditions, the authors investigate the limiting behavior of the optimal values and the optimal solutions of the approximation problems. Finally, some numerical results are reported to show efficiency of the proposed method.     

Codimension-two bifurcations analysis and tracking control on a discrete epidemic model

In this paper, the dynamic behaviors of a discrete epidemic model with a nonlinear incidence rate obtained by Euler method are discussed, which can exhibit the periodic motions and chaotic behaviors under the suitable system parameter conditions. Codimension-two bifurcations of the discrete epidemic model, associated with 1:1 strong resonance, 1:2 strong resonance, 1:3 strong resonance and 1:4 strong resonance, are analyzed by using the bifurcation theorem and the normal form method of maps. Moreover, in order to eliminate the chaotic behavior of the discrete epidemic model, a tracking controller is designed such that the disease disappears gradually. Finally, numerical simulations are obtained by the phase portraits, the maximum Lyapunov exponents diagrams for two different varying parameters in 3-dimension space, the bifurcation diagrams, the computations of Lyapunov exponents and the dynamic response. They not only illustrate the validity of the proposed results, but also display the interesting and complex dynamical behaviors.     

Community Development and Renaissance Social Humanism: Some Lessons for Systems Science

Starting from the crisis in our communities—research has indicated it to be widely spread—the author explores the scientific tradition preceding the rise of modernism in order to draw out a more humane way of thinking that may help our contemporary societies. He discerns between two types of Renaissance humanism, one characterised by its cleverness, the other by its compassion and desire to restore dignity to the lives of people struggling to escape the clutches of medievalism. The father of the latter is Erasmus of Rotterdam and we follow the development of his conception of a social humanism as it branches out, through the work of his successors, into every scientific discipline, both natural and human. These disciplines are united by an embracing systemic idea of philosophy that unites the mind with the heart and which Erasmus called “Philosophia Christi”. We examine the two main pillars upon which this philosophy is built, love for our neighbour and education as the only legitimate instrument to change society, and the extraordinary impact it had on science and on communities living in the seventeenth century. We contrast this with the idea of power, the chosen instrument of modernity to transform society, and trace some of its tragic outcomes. We conclude by discussing the incorporation of an Erasmian type of social humanism into systems education and the future development of such programmes.     

Low-energy acoustic plasmons at metal surfaces

Nearly two-dimensional (2D) metallic systems formed in charge inversion layers and artificial layered materials permit the existence of low-energy collective excitations, called 2D plasmons, which are not found in a three-dimensional (3D) metal. These excitations have caused considerable interest because their low energy allows them to participate in many dynamical processes involving electrons and phonons, and because they might mediate the formation of Cooper pairs in high-transition-temperature superconductors. Metals often support electronic states that are confined to the surface, forming a nearly 2D electron-density layer. However, it was argued that these systems could not support low-energy collective excitations because they would be screened out by the underlying bulk electrons. Rather, metallic surfaces should support only conventional surface plasmons-higher-energy modes that depend only on the electron density. Surface plasmons have important applications in microscopy and sub-wavelength optics, but have no relevance to the low-energy dynamics. Here we show that, in contrast to expectations, a low-energy collective excitation mode can be found on bare metal surfaces. The mode has an acoustic (linear) dispersion, different to the dependence of a 2D plasmon, and was observed on Be(0001) using angle-resolved electron energy loss spectroscopy. First-principles calculations show that it is caused by the coexistence of a partially occupied quasi-2D surface-state band with the underlying 3D bulk electron continuum and also that the non-local character of the dielectric function prevents it from being screened out by the 3D states. The acoustic plasmon reported here has a very general character and should be present on many metal surfaces. Furthermore, its acoustic dispersion allows the confinement of light on small surface areas and in a broad frequency range, which is relevant for nano-optics and photonics applications.     

Enzymatic capture of an extrahelical thymine in the search for uracil in DNA

The enzyme uracil DNA glycosylase (UNG) excises unwanted uracil bases in the genome using an extrahelical base recognition mechanism. Efficient removal of uracil is essential for prevention of C-to-T transition mutations arising from cytosine deamination, cytotoxic U*A pairs arising from incorporation of dUTP in DNA, and for increasing immunoglobulin gene diversity during the acquired immune response. A central event in all of these UNG-mediated processes is the singling out of rare U*A or U*G base pairs in a background of approximately 10(9) T*A or C*G base pairs in the human genome. Here we establish for the human and Escherichia coli enzymes that discrimination of thymine and uracil is initiated by thermally induced opening of T*A and U*A base pairs and not by active participation of the enzyme. Thus, base-pair dynamics has a critical role in the genome-wide search for uracil, and may be involved in initial damage recognition by other DNA repair glycosylases.     

Hydroxyl radical electrochemically generated with water as the complete atom source and its environmental application

The most reactive hydroxyl radical （OH） was generated by electrochemical approach with safe water as the complete atom source. The direct evidence for OH formation was obtained by electron spin resonance method. The powerful OH electrochemically generated could effectively degrade organic pollutants and reduce the toxicity of wastewater. Electrochemical disinfection by OH was considerably efficient even without the aid of active chlorine. Bacteria inactivation of 99.99% was achieved for contact time of 30 min and current density of 5 mA·cm^-2, In comparison with active chlorine, OH is rather attractive as a promising environmentally benign disinfectant and opens a new route for microbial inactivation.