Word differences in news media of lower and higher peace countries revealed by natural language processing and machine learning.

Language is both a cause and a consequence of the social processes that lead to conflict or peace. "Hate speech" can mobilize violence and destruction. What are the characteristics of "peace speech" that reflect and support the social processes that maintain peace? This study used existing peace indices, machine learning, and on-line, news media sources to identify the words most associated with lower-peace versus higher-peace countries.

Conflict Dynamics in Scale-Free Networks with Degree Correlations and Hierarchical Structure.

We present a study of the dynamic interactions between actors located on complex networks with scale-free and hierarchical scale-free topologies with assortative mixing, that is, correlations between the degree distributions of the actors. The actor's state evolves according to a model that considers its previous state, the inertia to change, and the influence of its neighborhood. We show that the time evolution of the system depends on the percentage of cooperative or competitive interactions.

How to live in peace? Mapping the science of sustaining peace: A progress report.

Despite good faith attempts by countless citizens, civil society, governments, and the international community, living in a sustainably peaceful community continues to be an elusive dream in much of our world. Among the challenges to sustaining peace is the fact that few scholars have studied enduringly peaceful societies, or have examined only narrow aspects of them, leaving our understanding of the necessary conditions, processes and policies fragmented, and deficient. This article provides a work-in-progress overview of a multidisciplinary, multimethod initiative, which aims to provide a holistic, evidence-based understanding of how peace can be sustained in societies.

Recurrence Networks in Natural Languages.

We present a study of natural language using the recurrence network method. In our approach, the repetition of patterns of characters is evaluated without considering the word structure in written texts from different natural languages. Our dataset comprises 85 ebookseBooks written in 17 different European languages.

The dynamic consequences of cooperation and competition in small-world networks.

We present a study of the social dynamics among cooperative and competitive actors interacting on a complex network that has a small-world topology. In this model, the state of each actor depends on its previous state in time, its inertia to change, and the influence of its neighboring actors. Using numerical simulations, we determine how the distribution of final states of the actors and measures of the distances between the values of the actors at local and global levels, depend on the number of cooperative to competitive actors and the connectivity of the actors in the network.

Behavioral and emotional dynamics of two people struggling to reach consensus about a topic on which they disagree.

We studied the behavioral and emotional dynamics displayed by two people trying to resolve a conflict. 59 groups of two people were asked to talk for 20 minutes to try to reach a consensus about a topic on which they disagreed. The topics were abortion, affirmative action, death penalty, and euthanasia.

A mathematical model of psychotherapy: an investigation using dynamic non-linear equations to model the therapeutic relationship.

Mathematical models, such as the one developed by Gottman et al. (1998, 2000, 2002) to understand the interaction between husbands and wives, can provide novel insights into the dynamics of the therapeutic relationship. A set of nonlinear equations were used to model the changing emotional state of a therapist and client.

Mathematical model of the dynamics of psychotherapy.

The success of psychotherapy depends on the nature of the therapeutic relationship between a therapist and a client. We use dynamical systems theory to model the dynamics of the emotional interaction between a therapist and client. We determine how the therapeutic endpoint and the dynamics of getting there depend on the parameters of the model.

Dynamic stabilization in the PU1-GATA1 circuit using a model with time-dependent kinetic change.

The PU.1 and GATA1 genes play an important role in the differentiation of blood stem cells. The protein levels expressed by these genes are thought to be regulated by a self-excitatory feedback loop for each gene and a cross-inhibitory feedback loop between the two genes.

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli.

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data, one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself.

Dynamical response of multi-patch, flux-based models to the input of infected people: Epidemic response to initiated events.

The time course of an epidemic can be modeled using the differential equations that describe the spread of disease and by dividing people into "patches" of different sizes with the migration of people between these patches. We used these multi-patch, flux-based models to determine how the time course of infected and susceptible populations depends on the disease parameters, the geometry of the migrations between the patches, and the addition of infected people into a patch. We found that there are significantly longer lived transients and additional "ancillary" epidemics when the reproductive rate is closer to 1, as would be typical of SARS (Severe Acute Respiratory Syndrome) and bird flu, than when is closer to 10, as would be typical of measles.

Why nonlinear biomedical physics?

The two goals of Nonlinear Biomedical Physics are: firstly to show how nonlinear methods can shed new light on biological phenomena and medical applications and secondly to bridge the technical, mathematical, and cultural divides between the physical disciplines where these methods are being developed and the audience for their use in the biological and medical sciences.

Developing combinatorial multi-component therapies (CMCT) of drugs that are more specific and have fewer side effects than traditional one drug therapies.

Drugs designed for a specific target are always found to have multiple effects. Rather than hope that one bullet can be designed to hit only one target, nonlinear interactions across genomic and proteomic networks could be used to design Combinatorial Multi-Component Therapies (CMCT) that are more targeted with fewer side effects. We show here how computational approaches can be used to predict which combinations of drugs would produce the best effects.

Information flow dynamics and timing patterns in the arrival of email viruses.

Analysis of the timing of the arrival of email viruses at different computers provides a way of probing the structural and dynamical properties of the Internet. We found that the intervals t between the arrival of four different strains of email viruses have a power law distribution proportional to t(-d), where 1.5 View Article and Find Full Text PDF

Temporal patterns of atrial arrhythmia recurrences in patients with implantable defibrillators: implications for assessing antiarrhythmic therapies.

Introduction: The statistical measures commonly used to assess therapies for recurrent atrial arrhythmias (such as time to first recurrence) often assume a uniformly random pattern of arrhythmic events over time. However, the true temporal pattern of atrial arrhythmia recurrences is unknown. The aim of this study was to use linear and nonlinear analyses to characterize the temporal pattern of atrial arrhythmia recurrences in patients with implantable cardioverter defibrillators.

Correlation in stimulated respiratory neural noise.

Noise in spontaneous respiratory neural activity of the neonatal rat isolated brainstem-spinal cord preparation stimulated with acetylcholine (ACh) exhibits positive correlation. Neural activity from the C4 (phrenic) ventral spinal rootlet, integrated and corrected for slowly changing trend, is interpreted as a fractal record in time by rescaled range, relative dispersional, and power spectral analyses. The Hurst exponent H measured from time series of 64 consecutive signal levels recorded at 2 s intervals during perfusion of the preparation with artificial cerebrospinal fluid containing ACh at concentrations 62.

Rescaled range analysis of resting respiration.

Fluctuations in resting depth of breathing (tidal volume) at constant breathing rate in the anesthetized adult rat exhibit fractal properties when analyzed by a rescaled range method characterized by a mean (+/-SD) exponent H=0.83+/-0.02 and 0.