How pairs of partners emerge in an initially fully connected society

A social group is represented by a graph, where each pair of nodes is connected by two oppositely directed links. At the beginning, a given amount $p(i)$ of resources is assigned randomly to each node $i$. Also, each link $r(i,j)$ is initially represented by a random positive value, which means the percentage of resources of node $i$ which is offered to node $j$. Initially then, the graph is fully connected, i.e. all non-diagonal matrix elements $r(i,j)$ are different from zero. During the simulation, the amounts of resources $p(i)$ change according to the balance equation. Also, nodes reorganise their activity with time, going to give more resources to those which give them more. This is the rule of varying the coefficients $r(i,j)$. The result is that after some transient time, only some pairs $(m,n)$ of nodes survive with non-zero $p(m)$ and $p(n)$, each pair with symmetric and positive $r(m,n)=r(n,m)$. Other coefficients $r(m,i\ne n)$ vanish. Unpaired nodes remain with no resources, i.e. their $p(i)=0$, and they cease to be active, as they have nothing to offer. The percentage of survivors (i.e. those with with $p(i)$ positive) increases with the velocity of varying the numbers $r(i,j)$, and it slightly decreases with the size of the group. The picture and the results can be interpreted as a description of a social algorithm leading to marriages.Comment: 7 pages, 3 figure

Interrupted time-series analysis and its application to behavioral data

Journal ArticleThis paper uses a question-and-answer format to present the technical aspects of interrupted time-series analysis (ITSA). Topics include the potential relevance of ITSA to behavioral researchers, serial dependency, time-series models, tests of significance, and sources of ITSA information

Finding fault: Criticism as a care management strategy and its impact on outcomes for dementia caregivers

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148350/1/gps5052_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148350/2/gps5052.pd

Urban Gravity: a Model for Intercity Telecommunication Flows

We analyze the anonymous communication patterns of 2.5 million customers of a Belgian mobile phone operator. Grouping customers by billing address, we build a social network of cities, that consists of communications between 571 cities in Belgium. We show that inter-city communication intensity is characterized by a gravity model: the communication intensity between two cities is proportional to the product of their sizes divided by the square of their distance

Understanding the Role of Relationship Maintenance in Enduring Couple Partnerships in Later Adulthood

Intimate relationships in later adulthood are understudied despite their positive association with health and well-being. This cross-sectional mixed methods study sought to redress this gap by investigating relationship maintenance in later adulthood. Our international sub-sample comprised 1,565 participants aged 55 + and in an ongoing relationship. Results from hierarchical multiple regression indicated that overall happiness with the relationship had the largest effect size on relationship maintenance, with 53% of the variance explained. Content analyses of open-ended questions identified companionship and laughter as some of the “best liked” aspects of the relationship. Housework/cooking and saying “I love you” were among the behaviors that made participants feel appreciated. Results illustrated the types of maintenance behaviors adults in later adulthood who are in enduring partnerships employ

A scale-free model of acute and ventilator-induced lung injury: a network theory approach inspired by seismology

IntroductionAcute respiratory distress syndrome (ARDS) presents a significant clinical challenge, with ventilator-induced lung injury (VILI) being a critical complication arising from life-saving mechanical ventilation. Understanding the spatial and temporal dynamics of VILI can inform therapeutic strategies to mitigate lung damage and improve outcomes.MethodsHistological sections from initially healthy mice and pulmonary lavage-injured mice subjected to a second hit of VILI were segmented with Ilastik to define regions of lung injury. A scale-free network approach was applied to assess the correlation between injury regions, with regions of injury represented as ‘nodes’ in the network and ‘edges’ quantifying the degree of correlation between nodes. A simulated time series analysis was conducted to emulate the temporal sequence of injury events.ResultsAutomated segmentation identified different lung regions in good agreement with manual scoring, achieving a sensitivity of 78% and a specificity of 85% across ‘injury’ pixels. Overall accuracy across ‘injury’, ‘air’, and ‘other’ pixels was 81%. The size of injured regions followed a power-law distribution, suggesting a ‘rich-get-richer’ phenomenon in the distribution of lung injury. Network analysis revealed a scale-free distribution of injury correlations, highlighting hubs of injury that could serve as focal points for therapeutic intervention. Simulated time series analysis further supported the concept of secondary injury events following an initial insult, with patterns resembling those observed in seismological studies of aftershocks.ConclusionThe size distribution of injured regions underscores the spatially heterogeneous nature of acute and ventilator-induced lung injury. The application of network theory demonstrates the emergence of injury ‘hubs’ that are consistent with a ‘rich-get-richer’ dynamic. Simulated time series analysis demonstrates that the progression of injury events in the lung could follow spatiotemporal patterns similar to the progression of aftershocks in seismology, providing new insights into the mechanisms of injury distribution and propagation. Both phenomena suggest a potential for interventions targeting these injury ‘hubs’ to reduce the impact of VILI in ARDS management

Nonlinear Dynamics and Interpersonal Correlates of Verbal Turn-Taking Patterns in a Group Therapy Session

Interpersonal processes and dynamics are ubiquitous topics in psychotherapy, yet they are difficult to study and are theoretically fragmented across therapeutic subdisciplines. The current study tests an integrative model of interpersonal dynamics in small groups using nonlinear dynamical systems theory. The conversation of one group therapy session (with six adolescent sex offenders) is analyzed using orbital decomposition, which allows for the identification of patterns in categorical time series data. The results show evidence of selforganizing social patterns, based on formal measures of turbulence (Lyapunov dimension), information novelty (Shannon\u27s entropy), and complexity (fractal dimension). The degree of patterning in turn taking is significantly correlated with measurements of control, closeness, and conflict among group members. Clinical implications and directions for future research are discussed

Driving under the influence of alcohol: a sequence analysis approach

Driving under the influence of alcohol: A sequence analysis approac