You can find here the preliminary list of abstracts attached to this page. The contributions have been roughly divided into macro areas: Biophysics (those mainly dealing with cells or cell constituents), Sociophysics (those meanly dealing with human behavior), Physics of Complexity (those dealing with more abstract systems), but of course the same contribution covers in general more than one field.
1 Wednesday 27/6 morning
1.1 Can we improve the traffic flow by an optimal behavior of the
drivers?
Bastien Chopard and Christophe Hanggeli
Computer Science Department, University of Geneva, Switzerland
We consider a traffic situation where a perturbation limits the flow for a given
period of time. Such a perturbation often produces stop-and-go waves
which are unpleasant for the drivers. A question is whether, by informing
the cars in advance of the presence of a jam and asking them the adopt
an optimal behavior, we can increase the traffic flow upstream of the
perturbation. We propose an analytical study of the growth and depletion
of a traffic queue, based of the incoming and outgoing flows, and the
density of cars. We validate our theoretical result numerically with a
cellular automata simulation. We show that changing the car density
within the congested region cannot change the travel time to reach the
end of the perturbation. However, the movement of the car can be made
smoother.
1.2 A numerical model for the bibliometric H-index
Georgia Ionescu, Bastien Chopard
Computer Science Department, University of Geneva, Switzerland
The H-index is a metrics aimed at capturing the quality of scientific
production. For a given set of publication, the H-index is computed as the
maximum number H of these publications that have received at least H citations.
Whether this metrics is a fair way to estimate the quality of a scientist or a group
of scientists has been discussed a lot in the literature [2]. Here we consider a
simple agent-based model that mimics a population of scientists, or a population
of papers. We show that simple rules can be proposed to explain the power law
distribution observed by Redner [3]. From this model, we can predict the value
of the H-index as a function of the number N of papers and number M
of citations. Our results can be compared to the real data and to the
formula
found in the literature [1]. Our model allows us to consider other questions
such as (1) what is the H-index of a community as a function of the H-index of its
members? (2) For scientists with a high H-index, what is the part of the
citations they received which is due to scientists with a low H-index? In
other words, is it possible to quantify how famous researchers need less
famous researchers to establish their reputation? Or could the famous
researchers be seen as forming self- sufficient elite groups, where the citations
received from within the group would be sufficient to establish their high
H-index?
References
[1] Juan E Iglesias and Carlos Pecharromn. Scaling the h-index for different
scientific isi fields. Scientometrics, 73(3):303–320, 2007.
[2] Franck Laloe and Remy Mosseri. Bibliometric evaluation of individual re-
searchers: not even right... not even wrong! Europhysics News, 40(5):26–29,
2009.
[3] S. Redner. How popular is your paper? an empirical study of the citation
distribution. The European Physical Journal B, 1998.
1.3 Structural properties of DNA promoters
Lucia Pettinato
Università di Firenze
We show that the combination of spectral methods allows to organize DNA
promoters of any species into equivalence classes, that correspond to the presence
of specific regular subsequences.
1.4 Analysis of noise-induced bistability in Michaelis Menten single-step
enzymatic cycle
Enrico Giampieri
Physics Dept. of Bologna University and INFN Bologna
In this presentation we discuss noise-induced bistability in a specific circuit
with many biological im- plications, namely a single-step enzymatic cycle
described by Michaelis Menten equations with quasi-steady state assumption. We
study the biological feasibility of this phenomenon, considering a small and
discrete number of molecules involved in the circuit, and we characterize the
conditions necessary for it. We show that intrinsic noise (due to the stochastic
character of the Master Equation approach) of one-dimensional substrate
reaction only is not sufficient to achieve bistability, then we characterize
analytically the necessary conditions on enzyme number fluctuations. We
implement numerically two biologically plausible circuits that show bistability
over different parameter windows as predicted by our results, providing
hints about how such a phenomenon could be exploited in real biological
systems.
1.5 Cognitive modelling of epidemics
Andrea Guazzini
Department of Psychology, University of Florence.
The Self Awareness topic represents one of the most attractive and fascinating
attribute of the Human Cognition. The understanding of its key features will have
presumably a relevant impact on the design of the future self-aware ICT
application, and the forecasting of the systems dominated by self-aware
entities. The modelling of these concepts would have a large impact on
the knowledge of social systems, ranging from the small group and the
micro trading dynamics to the modelling of cultural evolution and of
societies. In the case study we first introduce a new theoretical framework to
modelling the probabilistic reasoning and the Cognitive Heuristics at a
computational level, and some already developed functions within the
framework. Then, two relevant examples of application will be faced: the
”Local Community Detection problem” and the ”Epidemics Forecasting
problem”.
2 Wednesday 27/6 afternoon
2.1 The Lyapunov spectrum of cellular automata unravelled
J.M. Baetens, B. De Baets
KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics
Ghent University, Coupure links 653, 9000 Gent, Belgium
Notwithstanding the maximum Lyapunov exponent (MLE) has been used
so far to gain insight into cellular automaton (CA) dynamics, CAs are
higher-dimensional dynamical systems that are tied up with an entire Lyapunov
spectrum. Motivated by the important role that the full Lyapunov spectrum plays
in the characterization of dynamical systems that are based upon a continuous
phase space, it might be worthwhile to address the meaning of the Lyapunov
spectrum in the framework of two-state CAs. Of course, the meaning of these
Lyapunov spectra should be investigated more closely before any statements can
be made about its importance for characterizing CAs. Preliminary results on the
spectra of rules for which it holds that Jacobian matrix is constant throughout the
CA evolution, such as rules 15, 90, 105, 150 and 255, indicate that all exponents,
except for the MLE, yield information on the way defects that originate
from a single initial perturbation are distributed across the cellular space.
More specifically, upon ordering the cells of a CA based on the number of
defects they bear, these exponents seem to give insight into the ratio of the
difference between the number of defects in two consecutive cells of this
ordered list to the difference between the number of defects in two other
consecutive cells, whereas the MLE yields information on the total number of
defects. As such, it ap- pears that the Lyapunov spectrum of two-state
CAs allows for assessing how defects are spread across the cellular space.
However, as soon as the Jacobian matrix is not constant throughout the CA
evolution, this conclusion does not seem to hold, which can probably be
attributed to the fact that the above reasoning needs to be supplemented with
a kind of mean-field approximation that accounts for the time-varying
Jacobian.
2.2 The role of Transposable Elements in shaping the combinatorial
interaction of Transcription Factors.
Michele Caselle
Dip. Fisica, Università di Torino
In the last few years several studies showed that transposable elements (TEs)
in the human genome are significantly associated with transcription factor binding
sites and that in several cases their expansion within the genome led to a
substantial rewiring of the regulatory network. Here we suggest another possible
role played by TEs in the evolution of the regulatory networks. We discuss a set of
evidences supporting the idea that the evolution of particular patterns on
combinatorial interactions among Transcription Factors (TFs) was mediated
and supported by the expansion of specific classes of TEs in the human
genome.
To address this issue we studied the binding of Estrogen Receptor alpha
(ERalpha) to DNA using two chromatin immunoprecipitation sequencing
(ChIP-seq) public datasets on MCF7 cell lines corresponding to different
modalities of exposure to estrogen. We performed a genome-wide analysis of
Transposable Elements overlapping ChIP-seq binding peaks and found a
remarkable enrichment of a few well defined types and classes of transposable
elements . Among these enriched TEs a prominent role was played by MIR
(Mammalian Interspersed Repeats) transposons. These TEs underwent a dramatic
expansion at the beginning of the mammalian radiation and then stabilized. We
conjecture that the special affinity of ERalpha for the MIR class of TEs
could be at the origin of the important role which ERalpha assumed in
mammalians.
We then performed a genome-wide scan for putative transcription factor
binding sites (TFBSs) overlapping ChIP-seq peaks and repetitive regions,
employing canonical Positional Weight Matrices (PWMs). We found strong
enrichment and correlated presence of a few TFBSs within the ChiP-seq binding
peaks. In several cases these TFs correspond to known cofactors of ERalpha, thus
supporting the idea of a co-regulatory role of these co-localized TFs. Most of these
correlations turned out to be strictly associated to specific classes of TEs thus
suggesting the presence of a well defined “transposon code” within the regulatory
network.
Altogether our results support the idea that transposition events, besides
rewiring the network, also played a central role in the emergence and
success of combinatorial gene regulation in complex eukaryotes and that the
evolution of specific combinations of TFs interactions was actually mediated
and driven by the expansion of a few specific classes of Transposable
Elements.
2.3 Reconstruction and analysis of protein-protein interaction networks in
Plasmodium
Elisabetta Pizzi
Dipartimento di Malattie Infettive, Parassitarie ed Immunomediate Istituto
Superiore di Sanità
Reconstruction of protein-protein interaction networks constitutes one of the
most promising computational tools for exploring biological processes. The large
amount of post-genomics data collected in the recent years makes now
possible to approach this difficult task also in the case of malaria parasites.
Plasmodium parasites are characterized by a very complicated life cycle which
includes diverse and different cellular forms. In this work we adopted
a Bayesian approach to recostruct protein-protein interaction networks
reflecting the interactomes of three different stages of P.falciparum. The
analysis of these probabilistic networks allowed us to establish the overall
architectures of the possible interactomes and to highlight sub-networks reflecting
biological processes related to the sexual development of the parasite
cell.
2.4 Collective dynamics, extensivity and non-additivity in sparse
networks
Stefano Luccioli, Simona Olmi, Antonio Politi, Alessandro Torcini
ISC-CNR Firenze
The dynamics of sparse networks is investigated both at the microscopic and
macroscopic level, upon varying the connectivity. In all cases (chaotic maps,
Stuart-Landau oscillators, and leaky integrate-and-fire neuron models),
we find that a few tens of random connections are sufficient to sustain
a nontrivial (and possibly irregular) collective dynamics. At the same
time, the microscopic evolution turns out to be extensive, both in the
presence and absence of a macroscopic evolution. This result is quite
remarkable, considered the non-additivity of the underlying dynamical
rule.
Ref: S. Luccioli, S. Olmi, A. Politi and A. Torcini, “Collective dynamics in
sparse networks”, submitted to Phys. Rev. Lett.
3 Thursday 28/6 morning
3.1 From lattice gas cellular automata to the lattice Boltzmann equation
method
Raul Rechtman
Centro de Investigación en Energía, Universidad Nacional Autónoma de México,
Apdo. Postal 34, 62580 Temixco, Mor., Mexico.
The lattice Boltzmann equation method (LBEM) is a finite difference scheme
used to numerically simulate flows. The method evolved historically from lattice
gas cellular automata, simple models that exhibit fluid dynamics behavior. Some
aspects of the history of the method will be addressed in this talk. The method
has been used extensively in the simulation of the most varied flows. A first
example is thermal levitation, a particle immersed in a fluid with density and
temperature larger than those of the fluid can float or levitate. A second example
is the the study of vortex induced vibrations of a cylinder attached to a
spring.
3.2 Stochastic Turing Patterns on a Network
Malbor Asllani(1) Francesca Di Patti(2), Duccio Fanelli(2)
1 Dipartimento di Scienza e Alta Tecnologia, Universit‘ degli Studi dell’Insubria,
via Valleggio 11, 22100 Como, Italy
2 Dipartimento di Energetica “Sergio Stecco”, Universit‘ degli Studi di
Firenze, via S. Marta 3, 50139 Firenze, Italy and INFN, Sezione di Firenze
The process of stochastic Turing instability on a network is dis- cussed for a
specific case study, the stochastic Brusselator model. The system is shown to
spontaneously differentiate into activator-rich and activator-poor nodes,
outside the region of parameters classically de- puted to the deterministic
Turing instability. This phenomenon, as re- vealed by direct stochastic
simulations, is explained analytically, and eventually traced back to the finite
size corrections stemming from the inherent graininess of the scrutinized
medium.
3.3 Expanding the transfer entropy to identify information subgraphs in
complex systems
Sebastiano Stramaglia
Università di Bari (Italy)
We propose a formal expansion of the transfer entropy to put in evidence
irreducible sets of variables which provide information for the future state of each
assigned target. Multiplets characterized by an high value will be associated
to informational circuits present in the system, with an informational
character (synergetic or redundant) which can be associated to the sign of the
contribution.
3.4 Large scale organization of chromatin
Mario Nicodemi
Università di Napoli “Federico II”
(missing)
3.5 Modelling gene evolution
Giulia Menichetti
Physics Dept. of Bologna University
We show preliminary results on the simulation of the evolution of gene length
in human beings, and moreover, in some eukaryotes. We start by characterizing
the gene length distribution in the various chromosomes and then we propose a
simplified model for reproducing such distribution. We suppose that the intronic
regions undergo a partial copy-paste process, and consider the coding part not
subjected to the same kind of evolution: the latter is thus considered constant
and negligible for determining gene lengths. The main idea of this work
is to have a first approach to the comprehension of eukaryotic genome
evolution.
4 Thursday 28/6 afternoon
4.1 Experiments of science dissemination
Giovanna Pacini, Franco Bagnoli
Dep. Energetica and CSDC, Università di Firenze
A science café is a meeting on a scientific and / or technology topic
between the public and experts, held in an informal place as a pub, a
restaurant or a bar. A science café is not a conference, experts introduce
themselves and the theme of the discussion, but this part is limited to a
minimum. The engine of the meeting are always the questions, actions and
discussions of the public, muffled-animated by a moderator. In Florence this
activity is carried on by “Associazione Culturale caffè-scienza”, founded and
kept alive by many academics and researchers of the CNR but also by
many “ordinary” people. The association is participating, through the
CSDC, Interdepartmental Centre for the Study of Complex Dynamics,
University of Florence, in the European Project titled “Scicafè” The project’s
main targets are that of promoting the idea of science cafe as an effective
communication tool for science and technology; creating an European network of
Science Cafes in places of different geographical, demographic and cultural
characteristics, and of operating as a vehicle for the promotion of the
public understanding of science and of the public debate on scientific
issues.
Within the European Project we have started experimenting some
new techniques and modalities of science dissemination to extend the
dissemination of good practices and to increase local public. We shall
illustrate some of these experiments like audio and video streaming and radio
broadcasting.
4.2 Non-Gaussian fluctuations in stochastic models with absorbing
barriers
Claudia Cianci, Duccio Fanelli, Francesca Di Patti
Dip. Energetica and CSDC, Università di Firenze
The dynamics of a one-dimensional stochastic model is studied in presence of
an absorbing boundary. The distribution of fluctuations is analytically
characterized within the generalized van Kampen expansion, accounting for higher
order corrections beyond the conventional Gaussian approximation. The theory
is shown to successfully capture the non Gaussian traits of the sought
distribution returning an excellent agreement with the simulations, for all
times and arbitrarily close to the absorbing barrier. At large times, a
compact analytical solution for the distribution of fluctuations is also
obtained, bridging the gap with previous investigations, within the van
Kampen picture and without resorting to alternative strategies, as elsewhere
hypothesized.
4.3 Enhanced Stochastic Oscillation in a Model of Cellular Calcium
Dynamics
Laura Cantini, Emma Massi, Claudia Cianci, Duccio Fanelli
Dip. Energetica and CSDC, Università di Firenze
Calcium oscillations in cells play a role of paramount importance and are
thought to be implicated in a large variety of cellular processes. Mathematical
models have been proposed that reproduce the observed dynamics, so enabling to
gain insight into the scrutinized phenomenon. These models are often
deterministic in nature. The interacting molecules are ideally assumed to yield to
continuous concentrations, that evolve self-consistently as dictated by
ordinary or partial coupled differential equations. Single individual effects,
stemming from the intimate discreteness of the analyzed medium, can prove
however crucial by modifying significantly the approximate mean-field
predictions. The stochastic component of the microscopic dynamics can in
particular induce the emergence of regular macroscopic patterns, both in time
and space. In this paper, we shall present a stochastic model for calcium
dynamics and show that self-organized quasi-cycle can spontaneously
emerge, in a region of parameters for which the corresponding deterministic
dynamics converges to a stable fixed point for the concentrations amount.
The study is carried out both analytically and numerically.The master
equation which governs the underlying stochastic dynamics is studied
via the celebrated van Kampen system size expansion and the power
spectrum of fluctuations calculated analytically. The theory predictions are
challenged versus stochastic simulations returning an excellent quantitative
agreement.
5 Thursday 28/6 afternoon - Poster Session
5.1 Thermodynamics formalism for chemical master equations
Luciana de Oliveira
Physics Dept. of Bologna University
Chemical master equations (CMEs) are a relevant theoretical tools to describe
the fluctuations effects on biochemical reactions. The corresponding stationary
states contain information on the long term behavior of the system. The CME can
describe the relaxation process toward a equilibrium state characterized by the
detailed balance condition, or toward a non-equilibrium stationary process
(NESS) characterized by the presence of chemical currents. The possible
significance of the NESS in biochemical reactions is actually debated to
understand its relation with the plasticity mechanisms of biological systems. We
propose the use of a thermodynamics formalism to study the properties of NESSs
from a point of view of entropy production and energy exchange with the
environment.
5.2 A micro-environmental study of the Zn+2 - Aβ
1-16 structural
properties
A. Maiorana(1), T. Marino(2), V. Minicozzi(3), S. Morante(3), N. Russo(2)
1) UniversitàCattolica del Sacro Cuore - Roma, Italy
2) Dipartimento di Chimica, Università della Calabria - Rende (CS),
Italy
3) Dipartimento di Fisica Università di Roma “Tor Vergata” - Roma, Italy INFN,
Sezione di Roma “Tor Vergata” - Roma, Italy
Relying on a combination of classical and ab-initio methods, we study the
influence of the nature of the local physico-chemical environment on the structural
features of β-amyloid peptides complexed with Zn+2 ions. The analysis is carried
out by comparing the different metal coordination modes and the long-range
peptide folding structures that are obtained in extensive classical as well as ab
initio simulations, when the system is either in water or is in the so-called
“gas-phase”, and/or when different force fields for the Zn+2 and its ligands are
used. Two are the main results of this investigation. The first is that the precise
Zn+2 coordination mode emerging from classical simulations, markedly depends
on the partial charge attributed to the ion and the atoms surrounding
it, but these structural differences are completely washed out when the
resulting classical configurations are submitted to a quantum minimization.
Secondly, although the presence of water does not affect the Zn+2 inner
coordination shell, it significantly influences the long-range peptide folding
propensity.
5.3 Mathematical modeling of miRNA mediated sponge interaction.
Andrea Riba
Dip. Fisica, Università di Torino
Abstract: We discuss, using stochastic equations, the behaviour of a particular
class of miRNA mediated regulatory circuits in which a master miRNA
regulates a Transcription Factor and together with it a target protein coding
gene. We show that, keeping into account the so called sponge effect,
this circuit is able to accelerate the expression of the target gene and to
correlate the stochastic fluctations of Transcription Factor and target
gene thus improving the stability and robustness of this transcriptional
regulation.
5.4 Community-detection cellular automata with local and long-range
connectivity
Franco Bagnoli(1,3), Andrea Guazzini(2,3), Emanuele Massaro(1,3)
1 Dept. Energy Università di Firenze. Also INFN, sez. Firenze.
2 Dept. Psychology and CSDC, Università di Firenze
3 CSDC, Università di Firenze.
We explore a community-detection cellular automata algorithm inspired by
human heuristics, based on information diffusion and a non-linear processing
phase with a dynamics inspired by human heuristics. The main point of the
methods is that of furnishing different “views” of the clustering levels from an
individual point of view. We apply the method to networks with local connectivity
and long-range rewiring.
5.5 Small group dynamics: a minority game experiment
A. Cini(1) and A. Guazzini(1,2)
1) CSDC, University of Florence, via S. Marta 3, I-50139 Firenze, Italy.
2) Department of Psychology, University of Florence, Via di San Salvi 12, 50100,
Firenze, Italy.
Recently, the concept of Cognitive Heuristic has been connected to a new
approach for the exploration of the human social interactions. The idea is to
consider the cognitive systems as a satisfier more than an optimizer one. The
implicit assumption is that people tries to make the minimal effort to optimize
their social interaction only with respect to the particular task they are
facing.
We investigated this aspect experimentally by studying the behaviour of a
small group of people interacting in a virtual environment (an improved chat
systems[ref]). We designed such an experimental set-up in order to keep under
control most of communication aspects, leaving little space to non-controlled
communication. Moreover, we concentrate on the non-semantic aspects of
communication, in order to be more context-free as possible.
We present here the results of a minority game situation, in which there is no
winning strategy for reaching consensus in the majority of participants, and we
confront the outcome of this experiments with that of similar set-ups without any
task (blank modality) and a majority game.
The main goal of the present work is the characterization of how a little group
of people builds/structures their communication network and the related affinities,
during a short virtual group interaction, and what differences can be revealed by
comparing different conditions.
We show how our experimental framework captures some fundamental aspects
of the subject’s behaviour in a small group virtual dynamics.
We exposed 150 different subjects to three experimental modality. All the
experiments where constituted by a web based chat session with 10 participants,
all instructed in the same way, and associated with a random and neutral
identity. Subjects were physically separated so to avoid non-controlled
communication.
In the first blank modality, we proposed the subjects to engage just a free
chatting, without any restriction. The only requirement was to accomplish the
assessment of their affinity space after the end of the session, reporting it
on their “private radar”. In the second topic modality, we introduced a
polarizing subject in the discussion, and we asked the participant to develop
their own opinion about the topic. In the third modality we proposed a
frustrated minority game based on a voting procedure where only the
second biggest clusters were awarded. The subjects have been asked to
vote three times for experiment, every 15 minutes, about different topics
concerning the task. After the first two training votes, the subjects were
informed about the results . Finally, the third vote was considered the
valid one, and the subject were invited to try to be part of the winning
cluster(s).
A classical statistical approach has been used to test the experimental
hypothesis and to refine the useful observables. We used the product-moment
(r.)-correlation of Bravais Pearson, in order to test the relation among the
quantitative variables, and we compared the different experimental conditions
using the ANOVA and the t-Student tests. We fit the “models” of the cognitive
strategies with a preliminary linear regression method. For what concern the
voting game, we show how the subjects develop a very good ability to face with
the “frustrated task” they were participating. We compared the results of the
experimental votes whit those produced by an appropriate random or null model,
measuring the Z-scores in order to assess the randomness of the player’s
behaviour.
Considering first the peculiar results of the voting modality, we have observed
that all the participants are able to belong in the third vote to a cluster
with an high probability of victory. During the first two votes subjects
apparently adopt other strategies to vote, and the distribution of the
final clusters’ sizes reveals that only in the third vote the subjects try
to win, determining only small clusters composed by one, two or three
components.
Subjects’ strategies seem approximate effectively the distribution of the
probability of victory of the cluster size in the case of a random process of vote,
but making a sort of correction on it and voting not at random,
Noteworthy, in the voting experiment, the votes were not associated with the
affinity. In other words the affinity between subjects appeared in this modality
less able to affect the communicative dynamics of the group with respect to the
others two experimental conditions.
In summary, the first third of the experimenta seem to correspond to the
characteristic time for the construction of the first “social structure”, which is also
in this experiment maintained until the end of the experiments.
The centrality degree of the communication network is the measure which
confirms some relevant differences among the experimental conditions.
Although the final state of the public spaces of communication for all the
modalities is always a full connected network, defining the links in a continuous
way, the average values of the node’s centrality allows to discriminate between the
modalities. Subjects belonging to the voting and to the blank modalities show a
significantly greater centrality with respect to the topic modality also in the
public channels of communication.
Noteworthy, the average centrality in the affinity spaces couples together the
voting and topic modalities. This result suggest a greater final degree of
segregation for the voting and the topic modalities, with respect to the affinity
space, regardless of the number and of the kind of the interactions among
subjects.
The betweenness degree has been used beyond the degree of centrality as a
measure of the segregation of the networks under scrutiny.
The average betweenness in the affinity space shows that the average degree of
separation of the network is greater in the voting modality, while the blank and
the topic ones are not distinguishable. Despite this, the affinity space does not
appear correlated with any composition of the clusters generated by the three
votes, neither with the real preferences expressed after the sessions. This last
result suggest that the affinity dynamics is not correlated or affecting the voting
task.
For what concern the communicative variables, the betweenness delineates
a different scenario with respect to the centrality, suggesting that the
communication in the blank and in the topic modality follows a different regime
with respect to the voting one, where the average betweenness in the private
channels is greater than the others.
The affinity among individuals appears to be sensitive to different aspects
related to the task, and is apparently assessed by the subjects in different ways,
depending on the nature of the task. The subjects appear to adapt the cognitive
heuristics used to assess the affinity with the others, depending on the constraints
imposed by the task.
A linear regression method has been used to test such hypotheses. The three
significant best resulting models indicate different strategies adopted by the
subjects. In particular the explained variance of the models is significantly greater
for the blank modality (70%), where the affinity dynamics appears related to the
number of interaction and to their moods, regardless to the contents. At the
contrary in the Topic and in the Voting modality the explained variances are
respectively of 33% and 43%.
In summary, results show that in the blank modality it is possible to forecast
the final affinity between any two subjects, while this is not possible in more
structured tasks. The interpretation of this result is that, in th absence of a
specific task, people tends to structure their communication space according with
their affinity, while for structured tasks other dimensions become more
important
6 Thursday 28/6 18:00 Public event
6.1 La fisica nella vita di tutti i giorni - Physics in everyday life
Franco Bagnoli
Università di Firenze
Esperimenti con materiali alla portata di tutti che mostrano come fenomeni
apparentemente diversi possono essere ricondotti alle stesse leggi fisiche.
Esperimenti di Meccanica, elettromagnetismo, ottica, dinamica dei fluidi,
struttura della materia.
Experiments using common materials showing how apparently different
phenomena can be explained using common physical laws. Experiment on
mechanics, electromagnetism, optics, fluid dynamics, matter physics.
7 Friday 29/6 morning
7.1 Landslide modeling: application to warning system for Civil Protection
purposes and theoretical approach based on molecular dynamics
Gianluca Martelloni, Franco Bagnoli
University of Florence, Department of Energy Engineering and CSDC, Florence
(IT)
In this work we propose a landslide modeling at regional and national scale for
Civil Protection purposes. In addition a 2D computational mesoscopic
modeling approach, based on molecular dynamics (MD) is developed
for shallow and deep landslides triggered by rainfall. The former model
are based on statistical rainfall thresholds for the forecasting of shallow
and deep landslide triggering. This model, nominated SIGMA, is built to
operate in a warning system at regional scale: the model has been calibrated
through landslide events of period 2004-2007 and validated by means
of a further set of data (2008-2010). The originality of the model is the
calibration method of the rainfall thresholds based on a optimization
technique to reduce the false alarms of the regional warning system. The
results of validation are very good and therefore the SIGMA model will be
implemented within the first half of 2012 in the alert system of Emilia-
Romagna region (Italy). Also for the correct computation of the snow melting
induced landslides, a snow melt modeling (SMM) has been developed to its
integration with the statistical model based on rainfall thresholds. The
SMM is completely original as the only available data is the temporal
series of temperature, rainfall and snowpack depth; hence the model is
built without the data necessary for this type of modeling. The SMM are
calibrated with an heuristic algorithm of optimization (the optimized
flexible simplex) and validate using some set of snowpack depth data. The
simulations shows that the integrated system SIGMA-SMM is globally more
efficient than only SIGMA as many landslide events from snow melting are
correctly detected. Then a modified version of SIGMA is built to operate at
national level in an integrated system for shallow landslide forecasting.
Concerning a 2D MD model, it is based on interacting particles and it
describes the features of a (fictitious) granular material along a slope: in case
of shallow landslip, a horizontal layer with thickness of one particle is
simulated, while in case of deep landslide a vertical section, with wider
thickness, is considered. For shallow instability movements, we consider
that the triggering is caused by the decrease of the static friction along
the sliding surface. The triggering of landslip is caused by the passing
of two conditions: a threshold speed of the particles and a condition on
the static friction between particles and slope surface, this latter based
on the Mohr- Coulomb failure criterion. Moreover the interaction force
between particles is defined trough a potential that, in the absence of
experimental data, we have modeled as the Lennard-Jones 2-1 potential. In
addition, only for deep landslide modeling, a filtration model is considered in
order to take into account the increase of the pore pressure that is the
real cause of triggering. For the prediction of the particle positions, after
and during a rainfall, we use a MD method which results very suitable
to simulate this type of systems. The outcome of simulations are quite
satisfactory and we can claim that this types of modeling can represent a new
method to simulate landslides triggered by rainfall. In our simulations
emerging phenomena such as fractures, detachments and arching can be
observed. In particular, the model reproduces well the energy and time
distribution of avalanches, analogous to the observed Gutenberg-Richter
and Omori power law distributions for earthquakes. In particular, the
distribution of the mean kinetic energy of a landslide shows a transition
from Gaussian to log-normal to power law, with the decreasing of the
coefficient of viscosity up to zero. This behavior is compatible with slow
(high viscosity) and rapid landslides (low viscosity). The main advantage
of these Lagrangian methods consists in the capability of following the
trajectory of a single particle, possibly identifying its dynamical properties.
Finally,
for a large range of values of the parameters of the model, we observe a
characteristic velocity pattern, with acceleration increments, typical of real
landslides. It is therefore possible to apply the method of the inverse
surface displacement velocity (Fukuzono, 1985) for predicting the failure
time.
Keywords: landslide, rainfall thresholds, snow melt modeling, molecular
dynamics, Lagrangian modeling, particle based model, power law.
7.2 Agent based mobility models of the Etrurian protocities formation: from
satellite photos and thematic maps to the comprehension of the born of the
modern society. A forecasting system for the territory and cultural management
and conservation.
G. Pelfer(1), A. Guazzini(1,2), G. Martelloni(1,3)
1 University of Florence and Centre for the study of complex dynamics.
2 Department of Psychology, University of Florence.
3 Department of Energetics, University of Florence.
Introduction: The transition from the household societies to the protocities is
one of the most attractive topics within the archaeological and anthropological
domains. Nowadays, models of paleodemography, paleoeconomy and
paleoproductivity can be combinated with sociophysical and econophysical
models, in order to understand and to explain the dynamics of phenomenon
known as “Synecism”. Such phenomenon is considered as the motor for the
formation process of large and complex protourban settlements, starting from the
last phase of Final Bronze age until to the beginning of First Iron age. Among the
others, the Villanovan Period, concerning the ancient Etruria in Middle
Tyrrenian Area during the mentioned age, is considered as one of the most
representative of such process (i.e. Villanovan Revolution). The modern systems
of satellite and Remote Sensing observations, coupled with appropriate
forecasting models (sociophysical and econophysical), allow to effectively
investigate the major theoretical assumptions in the study area. Through
numerical simulations it will be maximized the usefulness of such databases, as
the optimization and validation of models and theories themselves. As a
benchmark for the outputs of the models, we calculate spatial correlations by
means of the available spatial and topographical attributes (elevation,
vegetation, resources, slope, etc ...). The latter will be merged with the
historical and archaeological information. Finally such general framework
would satisfy the requirements for the Cultural Resource management,
valorization and preservation, as well as for the environmental management in
general.
Methodology: The methodological approach to the modelling can be
summarized in three different areas, as follows: the first area has to face with
the representation of the environment features and critical factors. The
available maps can be imported in a GIS environment and eventually it is
possible to implement the models with MATLAB software that can be
interfaced with the GIS system. Another possibility is the use of IDL language
programming, optimized for image processing and provided with a graphical
user interface as MATLAB, where it is possible to write scripts in native
language or a C routine. Otherwise, it could be possible to import the
elaborated maps in NETLOGO space for the implementation of the mentioned
models.
The choice of the most suitable platform will depend on the evaluation
about the speed, the efficiency and the effectiveness of such integrated
systems. The second area will represent the mobile part of the model. The
sociophysical aspects will be represented as a Cellular Automata, and will
incorporate the most relevant cognitive aspects related to the cultural
and to the demographic evolutionary dynamics, as well as those related
with the mobility and the environment exploration. A last fundamental
ingredient for a comprehensive model of protocities formation is represented
by the econophysical aspects of the system dynamics. Such constraints
will be inspired by the archaeological and hystorical theories and will
affect the population evolution and the “gain” functions that rule over it
accordingly.
Expected Results:
Management and valorization of the territory and of Cultural and
Archaeological italian Heritage. Understandment of sociocultural phenomena
affecting the origin of the Cities and Protocities and involving the social,
ecological and economical parameters that helped the development of such a new
form of social organization grown, definitively, into a paradigm of modern human
society. Local forecasting systems and Predictive Models that can be applied to
different domains related to territory and to Cultural Heritage Management. A
dedicated toolbox for the Archaelogical Users can be developed for the
forecasting of the protocities birth and formation in space and in the time,
according to the dynamic of such historical processes. Beginning from an
historical dated map the software will be able to reproduce protocities
formation using an optimization algorithm based on geographical and
geospatial information for the determination of the initial distribution of
households.
Keywords:
Cultural Antropology, Computational Archaeology, GIS Geographical
Information Systems, Sociophysics of Protocities, Econophysics of ancient
societies
7.3 Randomness perception: representativeness or encoding?
Giorgio Gronchi
Dip. Psicologia, Università di Firenze
The probabilistic analysis of cognition is a recent framework that employs
Bayesian statistics to model various aspects of the human cognitive system. After
a brief description of this perspective, we present a Bayesian model of randomness
perception (Griffiths and Tenenbaum, 2003, 2004). The randomness perception
task is addressed in terms of the statistical problem of model selection: given a
string, inferring whether the process that generated it was random or regular. A
basic finding is that people rate sequences with an excess of alternation as more
random than prescribed by information theory (overalternating bias). There are
two explanations: local representativeness (Kahneman and Tversky, 1972) and the
implicit encoding hypothesis (Falk and Konold, 1997). The measure random(X) of
the Bayesian model was used in order to compare predictions derived
from the explanations in a series of reaction times experiments. Results
are discussed in relation to relevant methodological issues and future
research.
7.4 From the Social Cognition and the Cognitive Heuristics to the modelling
of the Self Awareness: the Tri-Partite Model
Franco Bagnoli(1,3) and Andrea Guazzini(2,3)
1 Department of Energetics, University of Florence. Also INFN, sez. Firenze.
2 Department of Psychology, University of Florence.
3 University of Florence and Centre for the study of complex dynamics.
The common questions of the psychological research throughout the past
century have been frequently concerning the way an organism is aware of
the environment and able to make decision inferring unknown aspects of
it.
The scientific advancements in modern Cognitive Sciences have been coupled
with new concepts and ideas that have made this discipline more scientifically
rigorous, even if frequently too much qualitative to be implemented/nested into
other domains [1]. Among these key concepts probably the most attractive and
recently quite inflated is that of Cognitive Heuristics [2].
This lecture present a general framework based on the idea that the cognitive
brain relies on predictions based on the memory that are continuously generated,
either based on the information gathered from the senses or from the
knowledge. The framework integrates three primary components. The first
connects the domain related concepts of associations, which are formed
by a life-time practice of extracting repeating patterns and statistical
regularities from our environment, and storing them as a particular form of
memory [3]. The second is the concept of analogies, which is the term that
represents the process of seeking correlations between an event and existing
representations in memory/knowledge. Finally, these analogies activate associated
representations that translate into predictions or inference processes. In this
work we propose a relative shift of perspective from the previous and
”classical” one, maintaining a three partitioned structure for the model
representing the cognitive system, and introducing some recent results
and insights coming from both the neuropsychological and the cognitive
literature.
[1] Neuberg, S.L., Kenrick, D.T., Schaller, M. Evolutionary social
psychology. In S. T. Fiske, D. Gilbert, & G. Lindzey (Eds.), Handbook of
Social Psychology (5th ed., pp. 761796). New York: John Wiley & Sons,
(2010).
[2] Simon, H.A. A Behavioral Model of Rational Choice. The Quarterly
Journal of Economics, Vol. 69, No. 1, pp. 99-118, (1955).
[3] Rao, R.P. and Ballard, D.H. Predictive coding in the visual cortex: a
functional interpretation of some extraclassical receptive- field, Nat. Neurosci. 2,
7987, (1999).