3D Modelling of Biological Systems for Biomimetics

With the advanced development of computer-based enabling technologies, many engineering, medical, biology, chemistry, physics and food science etc have developed to the unprecedented levels, which lead to many research and development interests in various multi-discipline areas. Among them, biomimetics is one of the most promising and attractive branches of study. Biomimetics is a branch of study that uses biological systems as a model to develop synthetic systems. To learn from nature, one of the fundamental issues is to understand the natural systems such animals, insects, plants and human beings etc. The geometrical characterization and representation of natural systems is an important fundamental work for biomimetics research. 3D modeling plays a key role in the geometrical characterization and representation, especially in computer graphical visualization. This paper firstly presents the typical procedure of 3D modelling methods and then reviews the previous work of 3D geometrical modelling techniques and systems developed for industrial, medical and animation applications. Especially the paper discusses the problems associated with the existing techniques and systems when they are applied to 3D modelling of biological systems. Based upon the discussions, the paper proposes some areas of research interests in 3D modelling of biological systems and for Biomimetics.

Evolution and Development of the Information Concept in Biological Systems: From Empirical Description to Informational Modeling of the Living Structures

With the purpose to smooth the way of a correct understanding of information concepts and their evolution,in this paper,is discussed the evolution and development of the concept of information in biological systems,showing that this concept was intuitively perceived even since ancient times by our predecessors,and described according to their language level of that times,but the crystallization of the real meaning of information is an achievement of our nowadays,by successive contribution of various scientific branches and personalities of the scientific community of the world,leading to a modern description/modeling of reality,in which information plays a fundamental role.It is shown that our reality can be understood as a contribution of matter/energy/information and represented/discussed as the model of the Universal Triangle of Reality(UTR),where various previous models can be suggestively inserted,as a function of their basic concern.The modern concepts on information starting from a theoretic experiment which would infringe the thermodynamics laws and reaching the theory of information and modern philosophic concepts on the world structuration allow us to show that information is a fundamental component of the material world and of the biological structures,in correlation with the structuration/destructuration processes of matter,involving absorption/release of information.Based on these concepts,is discussed the functionality of the biologic structures and is presented the informational model of the human body and living structures,as a general model of info-organization on the entire biological scale,showing that a rudimentary proto-consciousness should be operative even at the low-scale biological systems,because they work on the same principles,like the most developed bio-systems.The operability of biologic structures as informational devices is also pointed out.

Analysis and FDTD Modeling of the Influences of Microwave Electromagnetic Waves on Human Biological Systems

The interactions of electromagnetic waves with the human body are complex and depend on several factors related to the characteristics of the incident wave, including its frequency, its intensity, the polarization of the tissue encountered, the geometry of the tissue and its electromagnetic properties. That’s to say, the dielectric permittivity, the conductivity and the type of coupling between the field and the exposed body. A biological system irradiated by an electromagnetic wave is traversed by induced currents of non-negligible density;the water molecules present in the biological tissues exposed to the electromagnetic field will begin to oscillate at the frequency of the incident wave, thus creating internal friction responsible for the heating of the irradiated tissues. This heating will be all the more important as the tissues are rich in water. This article presents the establishment from a mathematical and numerical analysis explaining the phenomena of interaction and consequences between electromagnetic waves and health. Since the total electric field in the biological system is unknown, that is why it can be determined by the Finite Difference Time Domain FDTD method to assess the electromagnetic power distribution in the biological system under study. For this purpose, the detailed on the mechanisms of interaction of microwave electromagnetic waves with the human body have been presented. Mathematical analysis using Maxwell’s equations as well as bio-heat equations is the basis of this study for a consistent result. Therefore, a thermal model of biological tissues based on an electrical analogy has been developed. By the principle of duality, an electrical model in the dielectric form of a multilayered human tissue was used in order to obtain a corresponding thermal model. This thermal model made it possible to evaluate the temperature profile of biological tissues during exposure to electromagnetic waves. The simulation results obtained from computer tools show that the temperature in the biological tissue is a linear function of the duration of exposure to microwave electromagnetic waves.

Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.

FROM MOLECULAR RESPONSE TO CELL RESPONSE-Approaching the complexity of biological systems

I. THE COMPLEXITY OFBIOLOGICAL RESPONSESFor an organism, to be living or notdepends on its response to foreign matters.Facing the increasing amount and diversi-ty of chemicals, natural and synthetic, tounderstand the principles of the biologicalresponses becomes extremely importantin pursuing the way of rational utiliza-tion and governing the foreign matters.However, most biological responses aretoo complex to explore their nature. Forinstance, the risk to human beings andorganisms related to the application ofrare earths in agriculture, forestation, fish-ery and husbandry has been argued

A survey of some tensor analysis techniques for biological systems

Background:Since biological systems are complex and often involve multiple types of genomic relationships,tensor analysis methods can be utilized to elucidate these hidden complex relationships.There is a pressing need for this,as the interpretation of the results of high-throughput experiments has advanced at a much slower pace than the accumulation of data.Results:In this review we provide an overview of some tensor analysis methods for biological systems.Conclusions:Tensors are natural and powerful generalizations of vectors and matrices to higher dimensions and play a fundamental role in physics,mathematics and many other areas.Tensor analysis methods can be used to provide the foundations of systematic approaches to distinguish significant higher order correlations among the elements of a complex systems via finding ensembles of a small number of reduced systems that provide a concise and representative summary of these correlations.

An Efficient Numerical Scheme for Biological Models in the Frame of Bernoulli Wavelets

This article considers three types of biological systems:the dengue fever disease model,the COVID-19 virus model,and the transmission of Tuberculosis model.The new technique of creating the integration matrix for the Bernoulli wavelets is applied.Also,the novel method proposed in this paper is called the Bernoulli wavelet collocation scheme(BWCM).All three models are in the form system of coupled ordinary differential equations without an exact solution.These systems are converted into a system of algebraic equations using the Bernoulli wavelet collocation scheme.The numerical wave distributions of these governing models are obtained by solving the algebraic equations via the Newton-Raphson method.The results obtained from the developed strategy are compared to several schemes such as the Runge Kutta method,and ND solver in mathematical software.The convergence analyses are discussed through theorems.The newly implemented Bernoulli wavelet method improves the accuracy and converges when it is compared with the existing methods in the literature.

Biological Systems:Reliable Functions out of Randomness

What makes biological systems different from man-made systems?One distinction is explored in this paper:Biological systems achieve reliable functions through randomness,i.e.,by both mitigating and exploiting the effects of randomness.The fundamental reason for biological systems to take such a random approach is the randomness of the microscopic world,which is dramatically different from the macroscopic world we are familiar with.To substantiate the idea,bacterial chemotaxis is used as an example.

Swarming behavior of multi-agent systems

We consider an anisotropic swarm model with an attraction/repulsion function and study its aggregation properties. It is shown that the swarm members will aggregate and eventually form a cohesive cluster of finite size around the swarm center in a finite time. Moreover, we extend our results to more general attraction/repulsion functions. Numerical simulations demonstrate that all agents will eventually enter into and remain in a bounded region around the swarm center which may exhibit complex spiral motion due to asymmetry of the coupling structure. The model in this paper is more general than isotropic swarms and our results provide further insight into the effect of the interaction pattern on individual motion in a swarm system.

Suppression of Chaotic Behaviors in a Complex Biological System by Disturbance Observer-based Derivative-Integral Terminal Sliding Mode

Coronary artery systems are a kind of complex biological systems. Their chaotic phenomena can lead to serious health problems and illness development. From the perspective of engineering, this paper investigates the chaos suppression problem. At first, nonlinear dynamics of coronary artery systems are presented. To suppress the chaotic phenomena, the method of derivative-integral terminal sliding mode control is adopted. Since coronary artery systems suffer from uncertainties, the technique of disturbance observer is taken into consideration. The stability of such a control system that integrates the derivative-integral terminal sliding mode controller and the disturbance observer is proven in the sense of Lyapunov. To verify the feasibility and effectiveness of the proposed strategy, simulation results are illustrated in comparison with a benchmark.

Thermodynamic Formulation of Living Systems and Their Evolution II

In the previous paper [1], the application of the general thermodynamic theory was considered to biological systems. The nature of living matter has been presented from the mesoscopic to the macroscopic point of view, for different time scales (ontogenetic and phylogenetics). Herein, we continue with this application, and present three characteristics of life in the form of statements or postulates. The first characteristic describes the probability of survival against aging. In particular, the behaviour of life is shown as an independent mode of aging. The second characteristic refers to the adaptation of the species according to the environment. The relationship between the phenomenon of organic homeostasis and the origin of the clinical parameters that define health is highlighted. And finally, the third characteristic applies the principle of negentropy to describe evolution. A representative model is given as an example of each postulate.

^(23)Na relaxometry: An overview of theory and applications

^(23)Na is a nuclear magnetic resonance(NMR)-active isotope with a nuclear spin quantum number of 3/2.^(23)Na relaxation phenomenon is at the core of ^(23)Na NMR measurement and analysis.Due to the dominance of quadrupolar interaction,the relaxation behavior of ^(23)Na is physically and mathematically more complex than that of a typical spin-1/2 isotope.In this review,we overview the semi-classical Redfield theory for deriving the formulations of ^(23)Na relaxation.We show that the relaxation behaviors of ^(23)Na can be quantitatively described by constructing the spectral density functions based on the second-order perturbation theory.In addition,we summarize the applications of ^(23)Na relaxometry in different research fields,including biomedicine,sodium ion batteries,and quantum information processing.Because sodium is an essential element in our body,food and industrial materials,the research on sodium by ^(23)Na NMR emerges as important future directions.The theoretical and practical understandings on ^(23)Na relaxation are the step stones for mastering advanced ^(23)Na NMR techniques.

Self-organized motion in anisotropic swarms

This paper considers an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of the swarm will aggregate and eventually form a cohesive cluster of finite size around the swarm center. Moreover, It is also proved that under certain conditions, the swarm system can be completely stable, i.e., every solution converges to the equilibrium points of the system. The model and results of this paper extend a recent work on isotropic swarms to more general cases and provide further insight into the effect of the interaction pattern on self-organized motion in a swarm system. Keywords Biological systems - Multiagent systems - Pattern formation - Stability - Swarms This work was supported by the National Natural Science Foundation of China (No. 60274001 and No. 10372002) and the National Key Basic Research and Development Program (No.2002CB312200).

SYMBOLIC COMPUTATION FOR THE QUALITATIVE THEORY OF DIFFERENTIAL EQUATIONS

This paper provides a survey on symbolic computational approaches for the analysis of qualitative behaviors of systems of ordinary differential equations,focusing on symbolic and algebraic analysis for the local stability and bifurcation of limit cycles in the neighborhoods of equilibria and periodic orbits of the systems,with a highlight on applications to computational biology.

The Approximate Analytical Solution of Non-Linear Equation for Simultaneous Internal Mass and Heat Diffusion Effects

For the first time a mathematical modelling of porous catalyst particles subject to both internal mass concentration gradients as well as temperature gradients, in endothermic or exothermic reactions has been reported. This model contains a non-linear mass balance equation which is related to rate expression. This paper presents an approximate analytical method (Modified Adomian decomposition method) to solve the non-linear differential equations for chemical kinetics with diffusion effects. A simple and closed form of expressions pertaining to substrate concentration and utilization factor is presented for all value of diffusion parameters. These analytical results are compared with numerical results and found to be in good agreement.

Relative Specificity:All Substrates Are Not Created Equal

A biological molecule,e.g.,an enzyme,tends to interact with its many cognate substrates,targets,or partners differentially.Such a property is termed relative specificity and has been proposed to regulate important physiological functions,even though it has not been examined explicitly in most complex biochemical systems.This essay reviews several recent large-scale studies that investigate protein folding,signal transduction,RNA binding,translation and transcription in the context of relative specificity.These results and others support a pervasive role of relative specificity in diverse biological processes.It is becoming clear that relative specificity contributes fundamentally to the diversity and complexity of biological systems,which has significant implications in disease processes as well.