Nonlinear Dynamics Psychology and Life Sciences最新文献

In this study, we assessed the efficacy of various linear and chaotic physiological synchrony methods during collaborative emotive recall of stories, examining how physiological synchronization impacts dyadic interaction in tasks involving emotionally charged narratives. Eighty-two young individuals, forming 41dyads, participated in a task requiring the recall of stories with varying emotional content. We analyzed physiological data using the Lyapunov coefficient, cross-correlation, and coherence indices. Our statistical approach included concise applications of the student's t-test, Pearson's correlation, and notably, the receiver operating characteristic (ROC) curve. The results highlighted significant differences in physiological synchrony between emotional and less emotional situations, revealing increased synchronization in collaborative remembering of emotional stories. The integration of the Lyapunov coefficient with other indices was crucial for identifying emotional conditions, underscoring its significance in exploring emotional engagement in group memory activities. This study provides valuable insights into the dynamics of physiological synchrony in emotional interactions, its implications in cognitive and social domains, and suggests potential applications in understanding collective behavior and emotional processing.

The present study investigates the effects of performance goals, performance-approach and performance-avoidance, within the nonlinear dynamical systems perspective. The issue is revisited, by applying cusp catastrophe models on students' performance in language learning using achievement goal orientations as control variables. Data were taken from two separate studies: the first examined Ancient Greek and the second Modern Greek language, engaging 181 and 543 students respectively, both at seventh grade. The force field dynamics was the conceptual model, which was tested via cusp analysis employing the difference between the two performance goals as the asymmetry factor and their sum as the bifurcation factor, respectively. The cups models were proved superior to their linear alternatives. The findings, being in line with previous reports, establish the complex dynamical system perspective in educational psychology, whereas discussion is provided regarding the implications for current goal theories.

This study investigates the climbing dynamics of learning on a long-time scale, by using Drifting Markov models. Climbing constitutes a complex decision-making task that requires effective visual-motor coordination and exploration of the environment. Drifting Markov models, is a class of constrained heterogeneous Markov processes that allow the modeling of data that exhibit heterogeneity. By applying the later models on real-world visual motor skill data, we aim to uncover the persistent dynamics of learning in climbing. To that end a real case study is conducted based on an experiment, with results that (a) help in the understanding of skill acquisition in physically demanding environments; and (b) provide insights into the role of exploration and visual-motor coordination in learning.

The Hermite wavelet method (HWM) is introduced in this study to solve a nonlinear differential equation determining the human corneal morphology. The changes in curvature of the human cornea in hypotony, normal intraocular pressure, glaucoma, and other conditions are discussed. The Hermite wavelet operational matrices of derivatives are used to generate wavelet solutions based on this technique. The solutions of the nonlinear differential equation are determined for various values of constant parameters that can appear in the diverse physical situations. The proposed wavelet solutions are more accurate than the other approximate analytical solutions listed in the literature. The HWM solutions are compared to homotopy perturbation method, Taylor series, pertur-bation technique and artificial neural network solutions. There is broad consensus. This illustrates that HWM is a useful and appropriate strategy for handling difficulties with nonlinear boundary value problems that emerge in corneal geometry.

Human resilience is often considered as static traits using a reductionist approach. More recent work has demonstrated it to be a dynamic and emergent property of complex systems. This narrative review explores human resilience through a self-organizing framework with a specific emphasis on the application of nonlinear modeling approaches. Four classes of approaches are examined: univariate dynamics, bivariate coupling, topological modeling, and network modeling. Univariate dynamics capture the temporal structure and flexibility within a single time series, while bivariate coupling approaches quantify the interaction dynamics and coordination between two time series. Topological modeling identifies bifurcations and attractor dynamics as signals of critical transitions relative to emergence and system stability. Network modeling represents system structure with a focus on connectivity, flexibility, and system integrity. Applying a complex systems framework, this review provides insights into data modeling opportunities for characterizing important features of a system's capacity to bounce back and recover from stress. These characteristics are connected to meta-flexibility, which characterizes a system's adaptive responsiveness to stressors, including post-traumatic growth, and the relation between meta-flexibility and metastability is discussed. Overall, this review provides a foundation of tools for researchers interested in under-standing human resilience through a complex systems framework.

Situation awareness (SA) is a mental state that is instrumental to performance of complex dynamic tasks. SA within teams is thought to be supported by favorable social conditions within the team. The present study was organized in two parts: (a) causal relationships among SA, group cohesion, and autonomic synchrony, the latter being a fundamentally nonlinear process, and (b) the combined impact of the three variables on performance in a dynamic decisions task. Experimental conditions assessed changes in task difficulty, group size, and method of obtaining SA measures. Participants were 136 undergraduates organized into 32 teams of three to five members engaged in two matches of a first-person shooter computer game. They completed self-report measures of cohesion and SA. Synchrony was determined through time series analysis of electrodermal responses using the driver-empath framework. ANOVA results showed that cohesion and SA improved over the two matches, and SA was better in smaller groups during the second match. Synchrony was stronger in larger groups. Granger regression indicated no causal or circular relationship between SA and cohesion. Synchrony had a small positive effect on cohesion during the first match. SA had a strong negative impact on synchrony early on and dissipated afterwards. The best performing teams during the first match were those that: were larger, were measured for SA without pausing the simulation, were less synchronized, showed more accurate SA, and reported stronger cohesion. The study opens new questions concerning the role of synchrony in volatile situations and the role of automated team members operating alongside humans.

In a recent article, we presented evidence demonstrating the existence of hidden y-stories within the genomes of humans and canines. These stories were found not only in the non-protein-coding regions but also within the genetic regions and the sequence of exons. Consequently, we are now exploring whether these discoveries are unique to humans and dogs or if they are more widely distributed throughout the cellular world. To approach this question, we embarked on an investigation of the genomes of various species across Whittaker's five kingdoms, namely Animalia, Plantae, Fungi, Protista, and Monera. Through online resources, we obtained and analysed whole-genome sequences of one avian species, one fish species, one reptile species, and one invertebrate species within the Animalia kingdom. Furthermore, we examined the genomes of one plant species, one fungus species, one protozoan species, and two bacterial species. Employing the same methods as in our prior studies, our findings in this study align with our proto knowledge hypothesis, suggesting that all living cells possess a repository of hidden y-information which determines the cellular design, sustains its overall functionality, and governs its performance and behaviour throughout its lifespan until death. We briefly explain life as a bio-linguistic phenomenon and future projects.

This study explores the hypothesis related to a punctuated equilibrium process for conceptual change in science learning, in conjunction with the effects of four cognitive variables: logical thinking and field-dependence/field-independence, divergent and convergent thinking. The participants were fifth and sixth-grade elementary school pupils involved in different tasks, who were asked to describe and interpret chemical phenomena. Latent Class Analysis (LCA) was applied to children's responses, and three clusters or latent classes (LC1, LC2, and LC3) were identified, corresponding to hierarchical levels of conceptual understanding. The ensued LCs align with the theoretical conjecture about a stepwise conceptual change process that might go through various stages or mental models. These levels or stages are conceptualized as attractors, and changes between them were modeled as cusp catastrophes using the four cognitive variables as controls. The analysis showed that logical thinking acted as asymmetry factor, while field-dependence/field-independence, divergent and convergent thinking acted as bifurcation variables. This analytic approach presents a methodology for investigating conceptual change as a punctuated equilibrium process that adds to the nonlinear dynamical research with important implications for theories of conceptual change in science education and psychology as well. Discussion on the new perspective embracing the meta-theoretical framework of complex adaptive systems (CDS) is provided.

The aim of the study is to evaluate the complexity matching between the HRVs of the group of Healers and the Healee during the various stages of the meditation protocol by employing a novel mathematical approach based on the H-rank algorithm. The complexity matching of heart rate variability is assessed before and during a heart-focused meditation in a close non-contact healing exercise. The experiment was conducted on a group of individuals (eight Healers and one Healee) throughout the various phases of the protocol over a ~75-minute period. The HRV signal for the cohort of individuals was recorded using high resolution HRV recorders with internal clocks for time synchronization. The Hankel transform (H-rank) approach was employed to reconstruct the real-world complex time series in order to measure the algebraic complexity of the heart rate variability and to assess the complexity matching between the reconstructed H-rank of the Healers and Healee during the different phases of the protocol. The integration of the embedding attractor technique was used to aid in the visualization of reconstructed H-rank in state space across the various phases. The findings demonstrate the changes in the degree of reconstructed H-rank (between the Healers and the Healee) during the heart-focused meditation healing phase by employing mathematically anticipated and validated algorithms. It is natural and thought-provoking to contemplate the mechanisms causing the complexity of the reconstructed H-rank to come closer; it can be explicitly stated that the purpose of the study is to communicate a clear idea that the H-rank algorithm is capable of registering subtle changes in the healing process, and that there was no intention of delving deep to uncover the mechanisms involved in the HRV matching. Therefore, the latter might be a distinct goal of future research.

We have until now focused solely on the non-coding, more precisely the non-protein-coding (npc), part of DNA of man and dog in the search for hidden y-texts written by means of y-words - spelled by nucleotides A, C, G, and T and delimited by stop-codons. In this paper we use the same methods to analyse the whole human and canine genome, but we divide the genome into the genetic part, the naturally occurring sequence of exons, and the non-protein-coding genome according to definitions. By use of the y-text-finder we determine the number of zipf-qualified and a-qualified texts hidden in each of these parts. We present the actual methods and procedures, and the results in twelve figures, six for Homo sapiens sapiens and six for Canis lupus familiaris. Results show that there are lots of y-texts in the genetic part of the genome just as there are in the npc-genome. There is even a non-negligible number of ?-texts hidden in the sequence of exons. In addition, we show how many genes we find included in or overlapping zipf-qualified and a-qualified y-texts in the one-stranded DNA of man and dog. We assume that all this information represents the cell's total ability to behave in all of life's situations and discuss briefly ?-text reading and disease aetiology; carcinogenesis are also discussed.