298,904 research outputs found
How simple rules determine pedestrian behavior and crowd disasters
With the increasing size and frequency of mass events, the study of crowd
disasters and the simulation of pedestrian flows have become important research
areas. Yet, even successful modeling approaches such as those inspired by
Newtonian force models are still not fully consistent with empirical
observations and are sometimes hard to calibrate. Here, a novel cognitive
science approach is proposed, which is based on behavioral heuristics. We
suggest that, guided by visual information, namely the distance of obstructions
in candidate lines of sight, pedestrians apply two simple cognitive procedures
to adapt their walking speeds and directions. While simpler than previous
approaches, this model predicts individual trajectories and collective patterns
of motion in good quantitative agreement with a large variety of empirical and
experimental data. This includes the emergence of self-organization phenomena,
such as the spontaneous formation of unidirectional lanes or stop-and-go waves.
Moreover, the combination of pedestrian heuristics with body collisions
generates crowd turbulence at extreme densities-a phenomenon that has been
observed during recent crowd disasters. By proposing an integrated treatment of
simultaneous interactions between multiple individuals, our approach overcomes
limitations of current physics-inspired pair interaction models. Understanding
crowd dynamics through cognitive heuristics is therefore not only crucial for a
better preparation of safe mass events. It also clears the way for a more
realistic modeling of collective social behaviors, in particular of human
crowds and biological swarms. Furthermore, our behavioral heuristics may serve
to improve the navigation of autonomous robots.Comment: Article accepted for publication in PNA
Lost in the socially extended mind: Genuine intersubjectivity and disturbed self-other demarcation in schizophrenia
Much of the characteristic symptomatology of schizophrenia can be understood as resulting from a pervasive sense of disembodiment. The body is experienced as an external machine that needs to be controlled with explicit intentional commands, which in turn leads to severe difficulties in interacting with the world in a fluid and intuitive manner. In consequence, there is a characteristic dissociality: Others become problems to be solved by intellectual effort and no longer present opportunities for spontaneous interpersonal alignment. This dissociality goes hand in hand with a progressive loss of the socially extended mind, which normally affords opportunities for co-regulation of cognitive and affective processes. However, at times people with schizophrenia report that they are confronted by the opposite of this dissociality, namely an unusual fluidity of the self-other boundary as expressed in experiences of ambiguous body boundaries, intrusions, and even merging with others. Here the person has not lost access to the socially extended mind but has instead become lost in it, possibly due to a weakened sense of self. We argue that this neglected aspect of schizophrenic social dysfunction can be usefully approached via the concept of genuine intersubjectivity: We normally participate in a shared experience with another person by implicitly co-regulating how our interaction unfolds. This co-regulation integrates our respective experience’s dynamical bases into one interpersonal process and gives the interaction an ambiguous second-person character. The upshot is that reports of abnormal
self-other fluidity are not indicative of hallucinations without any basis in reality, but of a heightened sensitivity and vulnerability to processes of interpersonal alignment and mutual incorporation that form the normal basis of social life. We conclude by discussing implications of this view for both the science of consciousness as well as approaches to intervention and therapy
Collective Coordinate Control of Density Distributions
Real collective density variables [c.f.
Eq.\ref{Equation3})] in many-particle systems arise from non-linear
transformations of particle positions, and determine the structure factor
, where denotes the wave vector. Our objective is to
prescribe and then to find many-particle configurations
that correspond to such a target using a numerical optimization
technique. Numerical results reported here extend earlier one- and
two-dimensional studies to include three dimensions. In addition, they
demonstrate the capacity to control in the neighborhood of
0. The optimization method employed generates
multi-particle configurations for which , , and 1, 2, 4,
6, 8, and 10. The case 1 is relevant for the Harrison-Zeldovich
model of the early universe, for superfluid , and for jammed
amorphous sphere packings. The analysis also provides specific examples of
interaction potentials whose classical ground state are configurationally
degenerate and disordered.Comment: 26 pages, 8 figure
Social Influence and the Collective Dynamics of Opinion Formation
Social influence is the process by which individuals adapt their opinion,
revise their beliefs, or change their behavior as a result of social
interactions with other people. In our strongly interconnected society, social
influence plays a prominent role in many self-organized phenomena such as
herding in cultural markets, the spread of ideas and innovations, and the
amplification of fears during epidemics. Yet, the mechanisms of opinion
formation remain poorly understood, and existing physics-based models lack
systematic empirical validation. Here, we report two controlled experiments
showing how participants answering factual questions revise their initial
judgments after being exposed to the opinion and confidence level of others.
Based on the observation of 59 experimental subjects exposed to peer-opinion
for 15 different items, we draw an influence map that describes the strength of
peer influence during interactions. A simple process model derived from our
observations demonstrates how opinions in a group of interacting people can
converge or split over repeated interactions. In particular, we identify two
major attractors of opinion: (i) the expert effect, induced by the presence of
a highly confident individual in the group, and (ii) the majority effect,
caused by the presence of a critical mass of laypeople sharing similar
opinions. Additional simulations reveal the existence of a tipping point at
which one attractor will dominate over the other, driving collective opinion in
a given direction. These findings have implications for understanding the
mechanisms of public opinion formation and managing conflicting situations in
which self-confident and better informed minorities challenge the views of a
large uninformed majority.Comment: Published Nov 05, 2013. Open access at:
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.007843
Dynamical systems with time-dependent coupling: Clustering and critical behaviour
We study the collective behaviour of an ensemble of coupled motile elements
whose interactions depend on time and are alternatively attractive or
repulsive. The evolution of interactions is driven by individual internal
variables with autonomous dynamics. The system exhibits different dynamical
regimes, with various forms of collective organization, controlled by the range
of interactions and the dispersion of time scales in the evolution of the
internal variables. In the limit of large interaction ranges, it reduces to an
ensemble of coupled identical phase oscillators and, to some extent, admits to
be treated analytically. We find and characterize a transition between ordered
and disordered states, mediated by a regime of dynamical clustering.Comment: to appear in Physica
Living Liquid Crystals
Collective motion of self-propelled organisms or synthetic particles often
termed active fluid has attracted enormous attention in broad scientific
community because of it fundamentally non-equilibrium nature. Energy input and
interactions among the moving units and the medium lead to complex dynamics.
Here we introduce a new class of active matter, living liquid crystals (LLCs)
that combine living swimming bacteria with a lyotropic liquid crystal. The
physical properties of LLCs can be controlled by the amount of oxygen available
to bacteria, by concentration of ingredients, or by temperature. Our studies
reveal a wealth of new intriguing dynamic phenomena, caused by the coupling
between the activity-triggered flow and long-range orientational order of the
medium. Among these are (a) non-linear trajectories of bacterial motion guided
by non-uniform director, (b) local melting of the liquid crystal caused by the
bacteria-produced shear flows, (c) activity-triggered transition from a
non-flowing uniform state into a flowing one-dimensional periodic pattern and
its evolution into a turbulent array of topological defects, (d)
birefringence-enabled visualization of microflow generated by the
nanometers-thick bacterial flagella. Unlike their isotropic counterpart, the
LLCs show collective dynamic effects at very low volume fraction of bacteria,
on the order of 0.2%. Our work suggests an unorthodox design concept to control
and manipulate the dynamic behavior of soft active matter and opens the door
for potential biosensing and biomedical applications.Comment: 32 pages, 8 figures, Supporting Information include
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