Nonlinear Dynamics Psychology and Life Sciences最新文献

Nonlinear analysis such as detrended fluctuation analysis (DFA) and power spectrum density are often used to describe the gait motor behavior. This is an interdisciplinary effort to understand and evaluate human movement by the complexity field lenses. However, there are conflicting interpretations about the measures. For instance, the same alpha value could be a better adaptation or sign of pathology. Therefore, the purposes of this scope review are: to map scientific production in the application of the scaling exponent for gait and running analysis, identify the scaling methods used in these studies and the results interpretation, and identify knowledge gaps for future studies. Eleven methods and six metrics associated with them were found. Most of the papers use DFA and explain the results through hypotheses about the supraspinal influence and origin of long-range correlations, adaptability and stability during gait and running. Comparing studies and interpretations, we found a broad designation of terms for the same metric. This reflects the lack of agreement and language uniformity in this literature.

This paper is a theoretical journey through possible ways that complexity research can contribute to health promotion, especially for under-standing, encouraging, and facilitating positive health. The concept of 'positive health' regards health as an actual state or independent dimension, not simply freedom from physical disease or the absence of a problem. The subjective aspect of positive health is often described with the concept of 'well-being.' Nonlinear paradigms have implications for health because they direct attention to different facts, dynamics, theories, and basic assumptions, and also because language, in both its denotative and connotative aspects, has the potential to influence health-promoting or undermining attitudes, self-attributions and narratives, all of which impact positive health. This is explored specifically for perimenopause and menopause. Our previous research provided evidence that the menstrual cycle, before and during perimenopause, is the output of a nonlinear system in a chaotic trajectory. This article explores implications of a nonlinear paradigm for understanding the science underlying menopause, interpretations of variability and linear causality, importance of system structure, interpretations of perimenopause and menopause as senescence and disorder, and resultant self-attributions about menopausal experience and the nature of midlife.

In this short cover, I tell the story of my personal journey of becoming a scientist-artist and how Persian calligraphy artistry inspired me to convert the experimental data in the form of images of retinal cells into visually aesthetic artwork.

We describe the locomotion of Caenorhabditis elegans (C. elegans) using nonlinear dynamics. C. elegans is a commonly studied model organism based on ease of maintenance and simple neurological structure. In contrast to traditional microscopic techniques, which require constraining motion to a 2D microscope slide, dynamic diffraction allows the observation of locomotion in 3D as a time series of the intensity at a single point in the diffraction pattern. The electric field at any point in the far-field diffraction pattern is the result of a superposition of the electric fields bending around the worm. As a result, key features of the motion can be recovered by analyzing the intensity time series. One can now apply modern nonlinear techniques; embedding and recurrence plots, providing valuable insight for visualizing and comparing data sets. We found significant markers of low-dimensional chaos. Next, we implemented a minimal biomimetic simulation of the central pattern generator of C. elegans with FitzHugh-Nagumo neurons, which exhibits undulatory oscillations similar to those of the real C. elegans. Finally, we briefly describe the construction of a biomimetic version of the Izquierdo and Beer robotic worm using Keener's implementation of the Nagumo et al. circuit.

The psychological interview is a complex system which emerges from the interaction of its components, i.e., the patient and the psychologist; therefore, it is presumed to display a fractal structure whose dimension defines its level of complexity. This paper presents a pilot study for a new evaluative methodology of the fractal dimension in the psychological interview: the analysis of 4 psychological interviews led to the determination of their fractal dimension, defined by the amount of verbal content produced. The conversational turn-taking naturally established in the patient-psychologist dyad divides the verbatim transcripts of the sessions into Relational Verbal Units (RVU), whose sizes are determined by the number of words which composes them. It was observed that the distribution of the RVUs in a size/frequency graph follows a power law distribution, from which it was possible to assess the Relational Fractal Dimension (RFD) of the interviews. The values obtained range from a minimum of 1.39 to a maximum of 1.50, an indicative range of self-organized criticality. Recursion is the simple process behind complexity, and it defines fractal patterns; the fractal dimension of a system characterizes its level of complexity, and its application in psychotherapy describes the therapeutic relationship as a nonlinear dynamic system endowed with self-organization and self-similarity.

This study investigated the existence of chaotic structure in voting behavior by considering non-economic and macroeconomic factors in Turkey during the period of 03.1986-01.2020. The chaotic structure among the analyzed variables was characterized by Lyapunov exponents that explore the chaotic dynamics of the series. Following, the effects of inflation, unemployment, economic growth and terror on party votes were analyzed by Fourier regression model. Then, the causality among the macroeconomic variables, terror and party groups was analyzed by the Granger causality method. According to our results, there is unidirectional causality from terror to all four party groups. In the context of macroeconomic variables, there is the evidence of bidirectional causality between conservative parties and inflation; unidirectional causality from inflation to center-right and center-left parties. There is no causality between nationalist parties and inflation. Furthermore, center-right and center-left parties have the evidence of no causality with unemployment while there is unidirectional causality from unemployment to conservative and nationalist parties. There is unidirectional causality from economic growth to conservative parties and bidirectional causality between center-right parties and economic growth. However, the center-left and nationalist parties are not the sources of Granger causality of economic growth, and there is no inverse Granger causality relationship between these variables. Therefore, it can be concluded that between the periods 03.1986-01.2020, there was no concern for economic growth in left-wing and nationalist-based parties in Turkey.

This article presents a framework to describe how professional experts regulate complex adaptive systems (CAS), a skill found across bio-psychological, ecological, technical, and social contexts. The regulation aim is to facilitate and constrain the self-organization of a CAS; regulators engage in dynamic decision making while the system evolves. While many naive regulators are overtaxed when they encounter nonlinear and multi-causal dynamics, less is known about how experts perform. I argue that a rich set of competencies can make expert performance distinctive. The basic sensitivities for CAS that shape the general philosophy of practice and a role identity as process facilitators provide some foundation. Turning this into an applied skill set, however, additionally requires (a) the creation of mediating interfaces with a 'target' CAS, (b) interaction skills for exploring and stimulating the CAS, (c) the use of domain knowledge about the system's nature and structure for conceptualizing its state as well as dynamics, (d) the use of analogical reasoning, categories, heuristics, and models to make 'if-then' inferences from systemic problem constellations to holistic strategies, and (e) synoptic and meta-regulative capabilities that allow supervising the mix of deployed resources relative to the demands of ongoing task. These CAS regulation tools mesh in variable ways and can mutually amplify each other, i.e. synergize. Illustrations for the framework come from two somatic therapies (aka bodywork), the Shiatsu and Feldenkrais methods, in which therapists use manual techniques as a regulatory means to help their clients.

In this article we do a top-down analysis of the non-protein-coding human genome using well-defined parameters, resulting in what we call ?-strings. We show that there are altogether 45,371,328 different ?-strings in the human non-protein-coding genome. We explore statistical properties of the y-strings and demonstrate that they have many characteristics in common with human words. We indicate how they are 'packed' in the chromosomes and that each chromosome has its own specific y-dictionary. We also outline our future work exploring the linguistic features of y-strings and y-text using methods developed to study human, natural language.

Theories of norm emergence are a central building block for comprehending the emergence of society. The article investigates a central terminus in theories of norms, in particular rational choice theory: The notion of sanctions. Sanctions are an unexplained theoretical term for securing norm conformity. Agent-based models inspired by evolutionary game theory show that the evolution of cooperation can be enforced by sanctions. However, in behavioral terms, sanctions are a form of aggression. An empirical investigation of the violent collapse of a criminal group reveals that interpretation is necessary for recognizing aggression as sanction. Whereas theories of norms attempt to explain the emergence of social structure, successful sanction recognition imposes the existence of social structure in the form of normative authorities. In the absence of social structure for securing social order such as the state monopoly of violence this interpretation remains ambiguous and error prone. Simulation experiments with an agent-based model investigate the conditions for the emergence of a normative authority.

We carried out an empirical investigation among producers of packaging machines collecting information about their rivals, i.e., those few competitors which they closely monitor. We found interesting regularities that take geographically clustered firms apart from isolated firms, that existing theories left unexplained. By constructing an agent-based model we were able to formulate a simple and plausible heuristic for rival selection which is able to generate the empirically observed facts. We submit that this case is exemplary in showing what agent-based models can do, namely, providing sufficiency proofs that help theory-building.