1,161 research outputs found
Dynamics of deceptive interactions in social networks
In this paper we examine the role of lies in human social relations by
implementing some salient characteristics of deceptive interactions into an
opinion formation model, so as to describe the dynamical behaviour of a social
network more realistically. In this model we take into account such basic
properties of social networks as the dynamics of the intensity of interactions,
the influence of public opinion, and the fact that in every human interaction
it might be convenient to deceive or withhold information depending on the
instantaneous situation of each individual in the network. We find that lies
shape the topology of social networks, especially the formation of tightly
linked, small communities with loose connections between them. We also find
that agents with a larger proportion of deceptive interactions are the ones
that connect communities of different opinion, and in this sense they have
substantial centrality in the network. We then discuss the consequences of
these results for the social behaviour of humans and predict the changes that
could arise due to a varying tolerance for lies in society.Comment: 17 pages, 8 figures; Supplementary Information (3 pages, 1 figure
A new dimension to Turing patterns
It is well known that simple reaction-diffusion systems can display very rich
pattern formation behavior. Here we have studied two examples of such systems
in three dimensions. First we investigate the morphology and stability of a
generic Turing system in three dimensions and then the well-known Gray-Scott
model. In the latter case, we added a small number of morphogen sources in the
system in order to study its robustness and the formation of connections
between the sources. Our results raise the question of whether Turing
patterning can produce an inductive signaling mechanism for neuronal growth.Comment: Movies available here at
http://www.lce.hut.fi/research/polymer/turing.shtm
Are Opinions Based on Science: Modelling Social Response to Scientific Facts
As scientists we like to think that modern societies and their members base
their views, opinions and behaviour on scientific facts. This is not
necessarily the case, even though we are all (over-) exposed to information
flow through various channels of media, i.e. newspapers, television, radio,
internet, and web. It is thought that this is mainly due to the conflicting
information on the mass media and to the individual attitude (formed by
cultural, educational and environmental factors), that is, one external factor
and another personal factor. In this paper we will investigate the dynamical
development of opinion in a small population of agents by means of a
computational model of opinion formation in a co-evolving network of socially
linked agents. The personal and external factors are taken into account by
assigning an individual attitude parameter to each agent, and by subjecting all
to an external but homogeneous field to simulate the effect of the media. We
then adjust the field strength in the model by using actual data on scientific
perception surveys carried out in two different populations, which allow us to
compare two different societies. We interpret the model findings with the aid
of simple mean field calculations. Our results suggest that scientifically
sound concepts are more difficult to acquire than concepts not validated by
science, since opposing individuals organize themselves in close communities
that prevent opinion consensus.Comment: 21 pages, 5 figures. Submitted to PLoS ON
Quantification of the morphological characteristics of hESC colonies
The maintenance of the undifferentiated state in human embryonic stem cells (hESCs) is critical for further application in regenerative medicine, drug testing and studies of fundamental biology. Currently, the selection of the best quality cells and colonies for propagation is typically performed by eye, in terms of the displayed morphological features, such as prominent/abundant nucleoli and a colony with a tightly packed appearance and a well-defined edge. Using image analysis and computational tools, we precisely quantify these properties using phase-contrast images of hESC colonies of different sizes (0.1–1.1 mm2) during days 2, 3 and 4 after plating. Our analyses reveal noticeable differences in their structure influenced directly by the colony area A. Large colonies (A > 0.6 mm2) have cells with smaller nuclei and a short intercellular distance when compared with small colonies (A  0.6 mm2) due to the proliferation of the cells in the bulk. This increases the colony density and the number of nearest neighbours. We also detect the self-organisation of cells in the colonies where newly divided (smallest) cells cluster together in patches, separated from larger cells at the final stages of the cell cycle. This might influence directly cell-to-cell interactions and the community effects within the colonies since the segregation induced by size differences allows the interchange of neighbours as the cells proliferate and the colony grows. Our findings are relevant to efforts to determine the quality of hESC colonies and establish colony characteristics database
Quantification of the morphological characteristics of hESC colonies
The maintenance of the pluripotent state in human embryonic stem cells
(hESCs) is critical for further application in regenerative medicine, drug
testing and studies of fundamental biology. Currently, the selection of the
best quality cells and colonies for propagation is typically performed by eye,
in terms of the displayed morphological features, such as prominent/abundant
nucleoli and a colony with a tightly packed appearance and a well-defined edge.
Using image analysis and computational tools, we precisely quantify these
properties using phase-contrast images of hESC colonies of different sizes (0.1
-- 1.1) during days 2, 3 and 4 after plating. Our analyses
reveal noticeable differences in their structure influenced directly by the
colony area . Large colonies () have cells with
smaller nuclei and a short intercellular distance when compared with small
colonies (). The gaps between the cells, which are
present in small and medium sized colonies with ,
disappear in large colonies () due to the proliferation
of the cells in the bulk. This increases the colony density and the number of
nearest neighbours.
We also detect the self-organisation of cells in the colonies where newly
divided (smallest) cells cluster together in patches, separated from larger
cells at the final stages of the cell cycle. This might influence directly
cell-to-cell interactions and the community effects within the colonies since
the segregation induced by size differences allows the interchange of
neighbours as the cells proliferate and the colony grows. Our findings are
relevant to efforts to determine the quality of hESC colonies and establish
colony characteristics database
Vesicle formation induced by thermal fluctuations
The process of fission and vesicle formation depends on the geometry of the
membrane that will split. For instance, a flat surface finds it difficult to
form vesicles because of the lack of curved regions where to start the process.
Here we show that vesicle formation can be promoted by temperature, by using a
membrane phase field model with Gaussian curvature. We find a phase transition
between fluctuating and vesiculation phases that depends on temperature,
spontaneous curvature, and the ratio between bending and Gaussian moduli. We
analysed the energy dynamical behaviour of these processes and found that the
main driving ingredient is the Gaussian energy term, although the curvature
energy term usually helps with the process as well. We also found that the
chemical potential can be used to investigate the temperature of the system.
Finally we address how temperature changes the condition for spontaneous
vesiculation for all geometries, making it happen in a wider range of values of
the Gaussian modulus.Comment: 31 pages, 10 figure
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