Nonlinear Dynamics Psychology and Life Sciences最新文献

Comparison of some experimental data and deterministic dynamical models of heartbeat show that it is essential to consider stochastic mathematical models. The Zeeman heartbeat model is one of the main heartbeat models whose stochastic dynamics is less studied. Especially, investigating bifurcations in stochastic dynamical models can be useful for identifying abnormal cardiac rhythms. This paper is concerned with two essential features of the two dimensional stochastic Zeeman heartbeat model i.e., stability and bifurcation. To achieve this approach, Taylor expansion, polar coordinate transformation, and stochastic averaging procedure will be used to convert the classical system into an Ito averaging diffusion system. Furthermore, we consider several theorems which provide sufficient conditions of drift and diffusion coefficients to establish stochastic stability, D-bifurcation and phenomenological bifurcation of the model. In the end, numerical simulation plays an important role to show the influences of the noise severity and confirm our theoretical results.

Most scholarly discussions of novelty offer only partial or specified views of what it is or how it can be assessed particular to a discipline or are limited to individual studies. This article investigates novelty with the goal of offering a multi-systemic and generalizable definition and assessment process to be applicable across multiple disciplines. Novelty is proposed as a quality and state, which includes both a qualitative view that integrates subjective experience and a quantitative view that addresses nonlinear dynamical systems. It is also described as a comparative relatedness of space, time, and context. An 'outlier profile' is defined to search for features of the system that are original or unusual, and a 'low-recurrence profile' for features of the system that are unexpected or a surprise. A detailed research strategy is offered for novelty assessment with an example, and is usable across multiple disciplinary contexts in the sciences and humanities for studies of academic and practical use.

In the analysis of time series data, roughness is sometimes seen as a distinct feature of fractality. This paper seeks to distinguish it from other aspects of that construct (self-affinity and long-range memory processes) and it examines the reliability of the roughness measures currently available, i.e., Gneiting et al.'s (2010) fractal dimension and Marmelat et al.'s (2012) relative roughness. The response of these estimators is evaluated to simulations at varying levels of persistence, as specified by the Hurst exponent, and to the presence or absence of short-range ARMA processes. Four empirical time series datasets are subjected to roughness estimation: the flow of the river Nile, daily recordings of the number of births to teens in the state of Texas, daily school attendance rates at an urban middle school, and unemployment figures provided by the US Department of Labor. Results from the simulation study indicate that persistence levels are faithfully reproduced by both estimation techniques, which also show the (dis)attenuating effects of the short-range dependencies. Analysis of the empirical data indicates that the fractal dimension works best for non-stationary data, while relative roughness is more suitable for stationary data. In the simulations as well as the empirical situation, both estimations reliably identify randomness, and are therefore recommended as goodness of fit measures when time series are analyzed.

The present study investigated whether fractal dynamics can be observed during single-leg standing on a slackline. We also examined whether the temporal structure differs with skill level. To address these questions, we compared single-leg standing performance between novices (N=5) and experts (N=5) in terms of fractal dynamics in both ankles (i.e., stance and swing legs), center of mass, and head acceleration time series using detrended fluctuation analysis. Participants were required to perform single-leg standing on a slackline. To collect motion data while slacklining, we used a three-dimensional motion capture system and obtained time-series data on the position. We conducted detrended fluctuation analysis on the original acceleration time series and random shuffled time series to examine the fractal dynamics in each body part's fluctuation. Results suggest that experts showed persistent temporal structure in the swinging leg, center of mass, and head fluctuations in the horizontal direction, while that of novices did not differ from random fluctuations. These findings revealed that experts performing a single-leg standing task on a slackline show fractal dynamics. This might reflect their flexible or adaptive exploratory behavior in the performer-environment system and contribute to the dynamic stability of whole-body dynamic balancing.

How does novelty arise? While modern scholarly investigations show that new complex system paths arise due to dissipative structures post-bifurcation, few consider the subjectivity of the observer and fewer describe what can be deemed as truly novel in light of a causal chain of deterministic events. By investigating the 'problem of novelty' (i.e., how something can come from nothing) and adding a subjective appraisal process for a novelty threshold as per complex systems, this paper offers an alternative view of the birthplace of novelty. The findings reveal that novelty arises in a breach of causal normality described as a causal 'breakthrough,' and in a nonlinear 'transition zone' post-bifurcation between disordering and ordering, based on quantitative and qualitative criteria. The article offers a subjective approach to nonlinear dynamical self-organization considering both 'outliers' and 'low-recurrence' in a spatio-temporal perspective to determine what separates novelty from 'newness.' Four 'preconditions of novelty' (i.e., tension, competition, instability, and diversity) are also presented to clarify favourable conditions for novelty generation.

Issues pertaining to the organization and efficiency of the labor market and to the dynamics of employment and unemployment have always been at the forefront of the concerns of economists. Typically, such issues are approached through the analysis of the conflicting interests of a representative worker and of a representative firm, each of which intending to maximize the corresponding intertemporal objective function. Much of the research undertaken on this subject neglects the fact that each person is unique and endowed with different personality traits that influence their educational attainment, their ability to access jobs, their productivity while employed, and also their willingness to support, through social welfare mechanisms, those who become unemployed. In this research, we propose a simulation model to approach the dynamics of the labor market. The model conceives an economy populated by a large number of individuals who, over their life cycles, acquire education, search for a job, receive a wage while employed, and access an unemployment benefit while out of work. Because individuals are endowed with different personalities, they experience different degrees of professional success over their life cycles. Such reasoning leads to a labor market aggregate outcome characterized by emergent phenomena, out-of-equilibrium, path dependence, and other features that are characteristic of a complex evolving system. In the proposed setting, the personality of individuals is shaped by taking into account the big five personality traits of psychological analysis, namely openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism.

Artistic practice can be fueled by a sense of wonder connected with the natural world and all of its layers of color, pattern, texture and movements. As an autodidact I have pursued an understanding of the sciences in the time my life allows, listening to audible sources such as books and podcasts and watching film content. I'm also very comfortable in the outdoors hiking and camping my whole life and experiencing and observing nature is an integral piece of my artwork. Being neurodivergent in some undiagnosed way is my path, I search out what nurtures and excites my brain and I try to bring the beauty and experience to the canvas in acrylic paint. My intellect searches for edification as I can find it, and that is how my work has arrived in your publication. My self-teaching is a trail of breadcrumbs, and I would welcome any correspondence from the members of this organization sharing scientific material relating to any of my paintings.

Previous research identified the stability of wrist position as a performance indicator in a static basketball dribbling task performance under different experimental conditions since professionals displayed higher stability values than amateurs. We hypothesized that the trajectories of this cyclical task may be different between amateurs and professionals under downward peripheral vision occlusion and auditory occlusion. A modified version of the Procrustes analysis was used to quantify the dissimilarity between wrist trajectories along time. Results showed that peripheral vision occlusion caused dissimilarity in amateurs' dribbling trajectories almost four times larger than professionals'; however, auditory occlusion did not affect neither amateur nor professionals' performance. There were no cumulative effects on performance when the individual was submitted to both occlusions simultaneously.

Radically redefining art from static product to idea entwining object, observer and time, Marcel Duchamp essentially prefigured a dynamical systems view of creativity. That was the 1910's; Poincaré was a primary influence. Since then, complex systems theory has immeasurably deepened our understanding of transformative emergent process in all the arts. This paper focuses on the interactive art installation as an instantiated experience of complexity. Specifically it is proposed that viewers, referred to as Participant-Viewers, embody creativity through cognitive-emotional and often physical trajectories within an installation's high dimensional phase space: from perceptual/conceptual disorientation (entropy), to adaptive micro-stabilizations (bifurca-tions), to self-organization of novel understandings or perspectives (emergence). Beyond individuals' interactions with/within a given artwork, these dynamic spaces of possibility are considered in terms of their potential for motivating a broadened ecology of self, society, and environment.

College students face academic and emotional challenges within and outside of the classroom. There is not a unique way to deal with all of these challenges, however obtaining support from other individuals in their network can be an important factor in their success in dealing with these challenges. Exploratory social support network data from 38 undergraduate students were collected and analyzed to find common network structures and examine the relationship between these structures and student characteristics, GPA, perceived social support, and use of other help resources. We found half of the students had what we defined to be a novel network characteristic, prime supporters, which are individuals who provided academic and emotional support to students for both routine and intense academic and emotional problems. We found students with a prime supporter in their social network tended to have higher GPAs and perceived social support than those without a prime supporter. Students with prime supporters also had differences in academic help-seeking behavior. These findings suggest the need for further research on the social networks of college students, particularly the presence of individuals who are providers of multiple sources of support.