Levels Of System Organization Research Articles

Энтропия системного управления безопасностью дорожного движения: методика и практика использования

The safety issues of road transport operation have been relevant for more than 125 years. During this time, the vision of the essence and ideas about the principles and methods of ensuring road safety (traffic safety paradigms) have changed several times in the world scientific community. The purpose of this article is to present to the scientific community a new, developing entropy approach to assessing the quality of traffic safety system management. The need to use entropy approaches is dictated by the awareness of two main circumstances: the extreme variety of forms, composition and, ultimately, the complexity of transport systems, as well as the low effectiveness of using traditional modeling methods in assessing the quality of large and complex systems, which include traffic safety systems. The use of the entropy approach in the field of traffic safety management is very innovative for Russia. Already quite traditional for other spheres of human existence, the methods of entropy assessment of systemic organization are unfamiliar to transport specialists. In this regard, it should be noted that the entropy approach allows solving those tasks in the field of traffic safety that are inaccessible to conventional tools. An example of such tasks can be a quantitative assessment and comparison of the quality of management of regional traffic safety systems. This is especially important for improving the quality of federal traffic safety management, in particular, for improving goal-setting and subsequent financing of the relevant regional traffic safety programs. This is the practical significance of the author’s ideas. This article presents a method for quantifying the Relative entropy Hn of regional traffic safety systems; comparison and explanation of different levels of organization of traffic safety systems in the Orenburg region and the Republic of Tyva; an entropy classification of regional traffic safety systems in Russia by levels of system organization is presented (2021); an attempt was made to philosophically comprehend the results obtained. The results presented in the article are intermediate. The ideology of using the entropy assessment of system organization can be used not only in relation to such an important aspect of the functioning of transport systems as traffic safety, but also to the identification of other system properties, such as efficiency and quality. Key words: road safety, management, quality, system (process) entropy, entropy approach.

Returning to basic principles to develop more effective treatments for central nervous system disorders.

Development of new treatments for diseases of the central nervous system (CNS) is stalled. Of candidate drugs developed through costly preclinical research, 93% fail clinical trials. Hoped-for improvements in diagnosis or treatment from decades of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) imaging have yet to materialize. To understand what we are doing wrong, I begin with recognition that all aspects of life, including the brain and mind, are physical phenomena consistent with processes described by physicists. Two processes, emergence and entropy, are of particular relevance in complex arrangements of matter that constitute life in general and the brain in particular. The human brain functions through dynamically reconfiguring and hierarchically organized neural functional systems with emergent properties of cognition, emotion, and conscious experience. These systems are shaped and maintained by negentropic environmental input transformed by sensory receptors into neural signals that trigger epigenetic neuroplastic processes. CNS diseases produce clinical disorders by disrupting these systems. As researchers seek appropriate levels of system organization at which to characterize and treat illness, focus has been on medications that impact processes at lower levels or transcranial electric or magnetic stimulation that impact broad contiguous swaths of tissue. Neither align with the brain’s neurosystem organization and therefore lack specificity necessary to be effective and to limit side effects. Digital neurotherapies (DNTs), in contrast, align with neurosystem organization and achieve the needed specificity using the same input pathways and neuroplastic processes that created the neural systems organization to repair it. The omission of DNTs from major systems-based initiatives represents powerful residua of dualist thinking. Interventions based on perceptual and cognitive processes are not thought of as being as physical as drugs or electric or magnetic stimulation through the skull. In fact, they are examples of the most basic processes that create and support life itself.

Fusing autonomy and sociality via embodied emergence and development of behaviour and cognition from fetal period.

Human-centred AI/Robotics are quickly becoming important. Their core claim is that AI systems or robots must be designed and work for the benefits of humans with no harm or uneasiness. It essentially requires the realization of autonomy, sociality and their fusion at all levels of system organization, even beyond programming or pre-training. The biologically inspired core principle of such a system is described as the emergence and development of embodied behaviour and cognition. The importance of embodiment, emergence and continuous autonomous development is explained in the context of developmental robotics and dynamical systems view of human development. We present a hypothetical early developmental scenario that fills in the very beginning part of the comprehensive scenarios proposed in developmental robotics. Then our model and experiments on emergent embodied behaviour are presented. They consist of chaotic maps embedded in sensory–motor loops and coupled via embodiment. Behaviours that are consistent with embodiment and adaptive to environmental structure emerge within a few seconds without any external reward or learning. Next, our model and experiments on human fetal development are presented. A precise musculo-skeletal fetal body model is placed in a uterus model. Driven by spinal nonlinear oscillator circuits coupled together via embodiment, somatosensory signals are evoked and learned by a model of the cerebral cortex with 2.6 million neurons and 5.3 billion synapses. The model acquired cortical representations of self–body and multi-modal sensory integration. This work is important because it models very early autonomous development in realistic detailed human embodiment. Finally, discussions toward human-like cognition are presented including other important factors such as motivation, emotion, internal organs and genetic factors.This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

Neurogenesis of the respiratory pattern: insights from computational modeling.

The primary respiratory rhythm generator is located in a relatively small area of the lower brainstem and can be defined by the neuronal properties and synaptic interactions within this limited area. The genesis and control of the respiratory motor pattern involve a complex cross-level integration of cellular, network and systems mechanisms. Computational modeling is a powerful method that allows linking experimental data related to different levels of system organization. Therefore, a comprehensive computational model can provide useful insights for understanding the multilevel neural mechanisms involved in generation and control of the respiratory pattern. Our ultimate goal is to develop such a model.

Structure and change in child mental health service delivery networks

This article presents an empirical approach which views mental health service systems as interorganizational networks. Data are reported on two county-based child mental health systems in North Carolina that participated in the Robert Wood Johnson Foundation (RWJF) Mental Health Services Program for Youth. Analyses are based on a structural equivalence approach which groups organizations on the basis of similarity in their patterns of interaction. Site-specific data were collected at two time points (1991 and 1993) to measure the social network structure of these service systems including their density, fragmentation, and centralization. Findings indicate that two interesting changes occurred in these systems of care. First, each system moved in a direction consistent with the goals of the RWJF demonstration program, in that they were better organized by the end of the demonstration. Second, while the two systems started at very different levels of system development, one site made significantly larger gains, such that the systems converged over time toward moderately high levels of system organization at the end of the demonstration. Implications for further research are discussed. © 1996 John Wiley & Sons, Inc.

Ecology's AWFUL theorem: sustaining sustainability

Many momentarily important concepts in science pass after a time with little enduring consequence. Sustainability has the potential to become a really significant idea, but it could also disappear if it never becomes formally implemented to make it operational. To do this requires clarifying its various meanings, then integrating these into a measure or model, preferably quantitative. This paper makes a start at this employing propositional logic—first to establish that the success of any species requires proportional disadvantage to others in a zero-sum world (the AWFUL theorem), and then to explore three possible properties of sustainability (stability, continuation, and longevity) at two different levels of system organization (whole and part). The following conclusions are reached and discussed: at a given scale of organization, for sustainability (1) stability is a necessary but not sufficient condition, (2) continuation is sufficient but not necessary, and (3) longevity is also sufficient but not necessary. Across scales, between wholes and parts: (1a) part stability is sufficient for whole system sustainability, and part instability can be compensated by system design to achieve sustainability; (1b) system instability is sufficient for part unsustainability; (2a) part continuation is sufficient for system continuation, and therefore system sustainability; (2b) part noncontinuation is necessary for system unsustainability; (3a) part longevity is sufficient for system longevity, and therefore system sustainability; and (3b) failure of parts to achieve longevity is a necessary condition for system-level unsustainability. These attributes of sustainability in the part–whole context do not exhaust the possibilities. There are also comparisons to be made of relations between different sustainability attributes. The examples given indicate that sustainability is not a simple concept and that considerable development will be necessary to mold it into a permanently useful scientific tool.

Mensch and Mesh

SummaryThis article discusses several relationships between technologies, industries, and socioeconomic institutions that are central to the emerging field of industrial ecology but as of yet have found little recognition. Special attention is given to the history of changes in the complexity of technologies and socioeconomic institutions, methods for dealing with this complexity conceptually and in the context of decision making, and interrelationships between technology and policy choice at various levels of system organization. On the basis of that discussion, new roles for systems thinking and modeling, systems engineering, and technology and industrial policy are identified to promote the development of industrial ecosystems that minimize their environmental impacts.

A dynamic, hierarchical approach to understanding and managing natural economic systems

The study of economic systems, and their guidance towards sustainability, can be enhanced by understanding how natural systems use materials and energy at various levels of system organization, how these levels interrelate, and how interrelationships change. Towards this end, the paper introduces natural economics as an approach to understanding the dynamics of hierarchical systems. We define the concepts of natural economics to facilitate the description and assessment of system change, and present dynamic modeling as a method for empirical research and as a tool for management decision making. We illustrate with empirical applications the use of dynamic modeling at various levels of system organization. Empirical illustrations range from dynamic models of simple physical systems of material transport, energy degradation and self-organized criticality to models of complex industrial systems, such as US iron ore mining and steel production. The insights derived from the natural economics approach are used to draw conclusions for the study and management of economy-environment interactions.