#statistical theory

The experience for tomographic representation of ECG-signal is considered. Tomogram representation of the signal is identical to the Radon transform for processing various signals. It is shown that the tomographic representation for small parameters of transformation is identical for different leads, may reveal instability of isoelectric line and distinguish some forms of arrhythmias. This makes it possible to use only one lead for express analysis.

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Healthcare crises are well-known phenomena that occur and are highly disruptive. Consider, for example, Covid19 and other pandemics, wars, multi-casualty natural disasters, industrial disasters, etc. Healthcare systems in Brazil, Spain, Italy, and more around the world collapsed due to the lack of a clear methodology for handling such crises. Following a largescale value creation project with a large medical center we developed a resource-based methodology to cope with three healthcare crisis scenarios: “Peace”, “War” and “Tsunami”.

We identified three load/capacity scenarios for hospitals: “Peace”, “War” and “Tsunami”. The Peacetime scenario is the normal overload situation in a hospital. Figure 1 during “Peace” times, hospitals are usually 10%-20% short in resources. To overcome bottlenecks, managers apply evolutionary methods such as constraint management [1], the complete kit concept, etc. This is the normal condition in hospitals where there are fluctuations in supply and demand. Bottlenecks in this situation are typically medical crews: senior physicians and experienced nurses.

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The living cells are composed of bio-membranes which construct lipid bilayers composed mainly of phospholipids with proteins and cholesterol embedded in them. The internal organelles of the cell are composed of intracellular membranes and their unique structure modulates the permeation of molecules, like water, ions, and oxygen. Bio-membranes are considered as complex systems, and their state of matter is the liquid crystalline state corresponds to the fluid mosaic model of Singer & Nicolson [1]. Such state of matter undergoes a huge number of metastable phases that are named as ‘lipid rafts’ that are considered to act as information hubs.

These ‘lipid rafts’ are thermodynamic driven bioinformation hubs essential for the cell functions and for the survival of the organism [2]. The convergence of various scientific disciplines, including bioinformatics, cheminformatics, medical informatics, and nanoinformatics, has given rise to novel approaches in understanding and harnessing the potential of artificial cell membranes as bioinformation hubs. This paper delves into the intricate interplay between bio-membranes, lipid rafts, and thermodynamic-driven bioinformation, elucidating their pivotal role in establishing therapeutic networks.

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Well Known Facts

It is rather strange that the nature gave only 5 senses to the human beings. As everybody knows these senses are: Dactyl -to feel the touch and vibrations, Smell-to feel odors, aromas, Taste-to feel the tastes, Vision-to view the environment and feel the light and colors, Hearingto hear the sounds and noises.

From physical point of view

The dactyl feeling is a transmission from sensitive nerves of our hands (predominantly, but also by skin, body and legs) to the brain, where these feelings are transformed into brain impulses. The range of this sense is between 10-15Hz to more than 20 000Hz depending on the amplitudes of the vibrations. By this sense is also possible to feel temperature variations is a very narrow band (-50 0-60 0C to +70 0-80 0C). The taste feeling covers: bitter, sweet, hot, sour and salty and a small amount of combinations - at all 5 tastes.

The hearing presents the ability to hear sounds in the sound band between the infrasound (16Hz) to the ultra sounds (20 000Hz). This is relatively narrow band of the sounds hearable in the nature. The lack of detection abilities for the infrasound can be dangerous, because the infrasound has negative consequences to the human body and physics. The same is valid for the ultrasounds. The visible abilities are also in an extremely narrow band of electromagnetic spectrum for detection by the human eye-from about 380 nm (for the infrared light) to 750nm (for the ultraviolet light).

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Let the system consist of n of the same type and independent biological individuals with the same indicator p survival at a given interval [0,T] time [1]. Let us assume that a population is subject to an epidemic that leads to the death of some of the individuals. For this population, it has been established that it saves itself from extinction if the condition of survivability is met r ≤ d where r and d - the number of individuals, dying on [0,T], and the maximum allowable (critical) value of the quantity r. In another notation, this condition has the form qˆ0 ≤ q , where qˆ = r n and q0 = r0 n - the proportion of individuals, dying on [0,T] and its critical value [2].

Under the conditions of the example under consideration, the survivability criterion is used in the form [2]

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Abstract

This is a short opinion article pointing out the importance of examining more precisely the intimate relationship between structure and function that arises for all complex systems. It is claimed that this relationship is highly asymmetrical, which has many unforeseen consequences. The presented claims are made based on intuition and inductive reasoning. Although some claims may be only partially valid, for instance, under yet to be specified conditions, they can inspire new research directions to investigate in future.

Keywords:Function; Complex systems; Asymmetry; Biological evolution

Introduction

The complex systems of which biological systems are the most notable example have many distinctive properties [1]. These systems must be studied across many different spatiotemporal scales involving different chemical, electromagnetic, mechanical, quantum and other types of physical interactions in order to uncover their properties and inner workings. It is unclear whether the set of all properties describing complex systems is countably or uncountably infinite. Thus, we may never be able to generate a complete set of mathematical models fully defining complex systems, since any mathematical model can only capture some, but never all of the properties. It also means that these systems can never be completely controlled as unforeseen side effects always exist. Even though mathematical models of complex systems are only approximations, they are usually good enough in many practical scenarios. Mathematical models of complex systems are increasingly used, for example, to identify interventions that can most likely lead to desired outcomes. More importantly, mathematical models are also used to study how structures produce a function, and how function emerges from the structure.

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Genes are considered as segments of DNA that provide instructions for the production of specific proteins or RNA molecules. Genes can be related to one another in a variety of ways. These relationships can play important roles in the regulation of cellular processes and functions, as well as in the development and evolution of organisms. Gene relation refers to the relationship between two or more genes in terms of their function, location, or sequence similarity. In studying the expression and relationship of genes, researchers can get a sense of how gene-information is used to know cell functions and how changes in gene expression or regulation can lead to disease. As an example, co-expression analysis can help to determine gene-groups that are functionally related and may be involved in specific biological processes or diseases. Also, network analysis can be used to identify regulatory relationships between genes as well as to build gene regulation networks that control specific cellular processes. See also Allocco et al. [1], Elise et al. [2], Ruan et al. [3] & Song et al. [4], By interacting with each other, genes form a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. Since the accessibility of the large gene expression data, several methods have been developed to analyze the gene-to-gene relationship. Copula approach is being used to study the relationship between the expression profiles of pairs of genes, since a copula is a multivariate model that can be used for explaining gene-gene dependence.

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