131 research outputs found
Exact combinatorial approach to finite coagulating systems
The paper outlines an exact combinatorial approach to finite coagulating
systems. In this approach, cluster sizes and time are discrete, and the binary
aggregation alone governs the time evolution of the systems. By considering the
growth histories of all possible clusters, the exact expression is derived for
the probability of a coagulating system with an arbitrary kernel being found in
a given cluster configuration when monodisperse initial conditions are applied.
Then, this probability is used to calculate the time-dependent distribution for
the number of clusters of a given size, the average number of such clusters and
that average's standard deviation. The correctness of our general expressions
is proved based on the (analytical and numerical) results obtained for systems
with the constant kernel. In addition, the results obtained are compared with
the results arising from the solutions to the mean-field Smoluchowski
coagulation equation, indicating its weak points. The paper closes with a brief
discussion on the extensibility to other systems of the approach presented
herein, emphasizing the issue of arbitrary initial conditions
Spreading of diseases through comorbidity networks across life and gender
The state of health of patients is typically not characterized by a single
disease alone but by multiple (comorbid) medical conditions. These
comorbidities may depend strongly on age and gender. We propose a specific
phenomenological comorbidity network of human diseases that is based on medical
claims data of the entire population of Austria. The network is constructed
from a two-layer multiplex network, where in one layer the links represent the
conditional probability for a comorbidity, and in the other the links contain
the respective statistical significance. We show that the network undergoes
dramatic structural changes across the lifetime of patients.Disease networks
for children consist of a single, strongly inter-connected cluster. During
adolescence and adulthood further disease clusters emerge that are related to
specific classes of diseases, such as circulatory, mental, or genitourinary
disorders.For people above 65 these clusters start to merge and highly
connected hubs dominate the network. These hubs are related to hypertension,
chronic ischemic heart diseases, and chronic obstructive pulmonary diseases. We
introduce a simple diffusion model to understand the spreading of diseases on
the disease network at the population level. For the first time we are able to
show that patients predominantly develop diseases which are in close
network-proximity to disorders that they already suffer. The model explains
more than 85 % of the variance of all disease incidents in the population. The
presented methodology could be of importance for anticipating age-dependent
disease-profiles for entire populations, and for validation and of prevention
schemes.Comment: 14 pages,5 figure
Emotional agents at the square lattice
We introduce and investigate by numerical simulations a number of models of
emotional agents at the square lattice. Our models describe the most general
features of emotions such as the spontaneous emotional arousal, emotional
relaxation, and transfers of emotions between different agents. Group emotions
in the considered models are periodically fluctuating between two opposite
valency levels and as result the mean value of such group emotions is zero. The
oscillations amplitude depends strongly on probability ps of the individual
spontaneous arousal. For small values of relaxation times tau we observed a
stochastic resonance, i.e. the signal to noise ratio SNR is maximal for a
non-zero ps parameter. The amplitude increases with the probability p of local
affective interactions while the mean oscillations period increases with the
relaxation time tau and is only weakly dependent on other system parameters.
Presence of emotional antenna can enhance positive or negative emotions and for
the optimal transition probability the antenna can change agents emotions at
longer distances. The stochastic resonance was also observed for the influence
of emotions on task execution efficiency.Comment: 28 pages, 19 figures, 3 table
q-neighbor Ising model on a polarized network
In this paper, we have examined the interplay between the lobby size in
the -neighbor Ising model of opinion formation [Phys. Rev. E 92, 052105] and
the level of overlap of two fully connected graphs. Results suggest that
for each lobby size there exists a specific level of overlap
which destroys initially polarized clusters of opinions. By performing
Monte-Carlo simulations, backed by an analytical approach we show that the
dependence of the on the lobby size is far from trivial in the
absence of temperature , showing a clear maximum that
additionally depends on the parity of . On the other hand, the temperature
is a destructive factor, its increase leads to the earlier collapse of
polarized clusters but additionally brings a substantial decrease in the level
of polarization
Temporal Taylor's scaling of facial electromyography and electrodermal activity in the course of emotional stimulation
High frequency psychophysiological data create a challenge for quantitative
modeling based on Big Data tools since they reflect the complexity of processes
taking place in human body and its responses to external events. Here we
present studies of fluctuations in facial electromyography (fEMG) and
electrodermal activity (EDA) massive time series and changes of such signals in
the course of emotional stimulation. Zygomaticus major (ZYG, "smiling" muscle)
activity, corrugator supercilii (COR, "frowning"bmuscle) activity, and phasic
skin conductance (PHSC, sweating) levels of 65 participants were recorded
during experiments that involved exposure to emotional stimuli (i.e., IAPS
images, reading and writing messages on an artificial online discussion board).
Temporal Taylor's fluctuations scaling were found when signals for various
participants and during various types of emotional events were compared. Values
of scaling exponents were close to 1, suggesting an external origin of system
dynamics and/or strong interactions between system's basic elements (e.g.,
muscle fibres). Our statistical analysis shows that the scaling exponents
enable identification of high valence and arousal levels in ZYG and COR
signals
Flow of emotional messages in artificial social networks
Models of message flows in an artificial group of users communicating via the
Internet are introduced and investigated using numerical simulations. We
assumed that messages possess an emotional character with a positive valence
and that the willingness to send the next affective message to a given person
increases with the number of messages received from this person. As a result,
the weights of links between group members evolve over time. Memory effects are
introduced, taking into account that the preferential selection of message
receivers depends on the communication intensity during the recent period only.
We also model the phenomenon of secondary social sharing when the reception of
an emotional e-mail triggers the distribution of several emotional e-mails to
other people.Comment: 10 pages, 7 figures, submitted to International Journal of Modern
Physics
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