409 research outputs found
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The Maximum Entropy Principle for Temporal and Ecological Networks: Memory, Fluctuations and Response in Complex Systems
No full textMany real systems, represented using complex networks, often
exhibit intrinsic dynamism that uncovers fundamental
properties. This thesis explores various aspects of such dynamism
through the lens of maximum entropy formalism,
presenting methodologies that effectively characterize and harness
this aspect.
The work is divided into two main parts. The first part develops
a novel maximum entropy model to characterize memory
effects and structural heterogeneity in temporal networks. This
model captures the evolution of network connections over
time, focusing on how nodes create and maintain links. Utilizing
this model, the research uncovers topological patterns,
such as community structures, emphasizing the role of memory
mechanisms in encoding network properties.
The second part shifts focus to ecological networks, emphasizing
system fluctuations for modeling and predictive analysis.
Here, maximum entropy formalism is shown to be a tool
capable of constructing models that incorporate significant
fluctuations in system characteristics. These models are then
shown to enhance pattern detection, particularly emphasizing
the ecological contexts.
Finally, I discuss how this approach can be used to define
a new perspective on the diversity-stability debate by linking
entropy with system stability and demonstrating how,
through the Fluctuation Response Relation, properly characterized
fluctuations can predict systems’ response to perturbations
Essay on conflict, aggressivity and punishment
No full textConflict is a crucial force that shapes the world. If, at a group
level, conflict is able to shape allocations of power and re-
sources, often changing the equilibrium between two groups,
at the individual level, conflict affects social interactions, prim-
ing aggressive and hostile behaviors that disrupt cooperation.
In this Doctoral Thesis, we take a theoretical evolutionary
perspective, as well as an experimental one, to investigate
how conflict affects different aspects of socially relevant be-
haviors. In the first chapter, using an evolutionary perspec-
tive, we explore the implications of different relationships be-
tween power and initiation of conflicts for the long-run dis-
tribution of power between groups. The second chapter de-
scribes two experiments in which we demonstrate that ag-
gressive behavior is more likely to happen after extreme ex-
tension of self-control, with parallel appearances of signs of
functional fatigue in areas of the prefrontal cortex implied in
emotional and impulsive regulation. Finally, the last chapter
describes a theoretical model in which a community enforce-
ment system that uses social norms supports both pro-norm
and anti-norm punishment as evolutionary stable
The Transmission, Transformation and Cultural Adaptation of the Heracles Imagery from the Near East to East Asia (4th century BC–10th century AD)
Full text linkThis thesis examines the transmission and diversity of transformation of
the Heracles motif into the East, tracing its dissemination from the Near
East via Central Asia and the Indian subcontinent towards East Asia in
the wake of Alexander the Great’s campaigns in the 4th century BC.
While there is abundant evidence indicating that the Heracles motif migrated
from the Mediterranean to the East mainly as a result of Alexander’s
expeditions — further elaborated by extensive research on the reception
of Heracles imagery by non- (or not entirely) Greek cultures —
less attention has been paid to how the Heracles (or Heraclean) imagery
was disseminated and modified across a wider geographical and temporal
spectrum, especially beyond the Near East. This thesis provides an
extensive typological catalogue of works discovered in regions and cultural
spheres east of the Mediterranean from approximately the 4th century
BC to the 10th century AD that are deemed to exhibit formal similarities
with those of Heracles from the Mediterranean.
Given the considerable number of works that were influenced or possibly
inspired by the Heracles motif through various socio-historical interactions
over a long-time span, this study identifies the key themes and
figurative types of Heracles that contributed to the longevity of the motif
and stimulated its transformation, particularly in Buddhist figural arts
and some secular adaptations in Iranian, Indian and Chinese cultures.
By examining the enduring appeal and reinterpretation of the Heracles
figure and discussing the complex interactions that accompanied the
motif’s diffusion, the thesis proposes different transmission routes and
means through which the various types of images and motifs could have
migrated to the further East, thus enhancing the “research map” of the
eastward transmission of Heraclean imagery
Computational Mechanics Framework for Simulations and Prediction of Wear in Frictional Contacts
No full textA computational fnite element modelling of a mechanical model to
predict wear, including friction, is proposed in this work. As an ex-
pansion of the interface fnite element with an embedded profle for
joint roughness (MPJR interface fnite element), it is designed to solve
the frictional contact problem between rigid indenters of any complex
shape and elastic bodies. In the formulation, the non-linearity due to
contact is considered for predicting contact traction, frictional effects,
and wear. This formulation interfaces with FEM software and can em-
bed roughness or general deviations from the planarity as a correction
to the normal gap function. The model employs a regularized version
of the Coulomb friction law for the tangential contact response while
introducing a penalty approach in the normal contact direction. The
present framework enables the comprehensive investigation of the tan-
gential and normal tractions via the computation of displacements and
the displacement gaps in the model. These tangential and normal trac-
tions can be used to calculate the wear rate via the wear law. The model
defnes wear by contact force and gaps. Due to this, contact pressure
develops wear and the normal gap changes. Model parameters related
to the constitutive equations of the interface where two bodies come in
contact: regularized coulomb friction law and Archard’s wear law out-
lined. In conclusion, this model predicts the wear and wear rate at the
micro-scale level and explains how to formulate and predict wear at the
macro-scale level
Gravity Models of Networks
Full text linkTrade networks are mathematical representations of the ex-
changes established by countries, industries, firms or individ-
uals. The present thesis collects works aimed at overcoming
the limitations characterizing the econometric recipes tradi-
tionally employed to study the aforementioned systems, by
introducing a novel framework, based upon the maximum-
entropy formalism. In chapter 2 we develop a novel class of
models to study networks with discrete weights, capable of
accommodating both structural and econometric parameters,
finding that they outperform standard, econometric models [1].
In chapter 3 we extend the aforementioned set of models to
study networks with continuous weights [2]. In chapter 4
we go beyond the ‘deterministic’ optimization procedure pre-
scribed by econometrics to specify conditional models, con-
sidering two, alternative estimation recipes characterized by
different ways of averaging over the topological randomness:
what we find is that the ‘annealed’ recipe, prescribing to max-
imize a generalized likelihood function, is to be preferred, re-
gardless of the heterogeneity of weights [3]. Finally, in Chap-
ter 5, we delve into the extent to which the triadic structures
embedded within the Dutch multi-commodity production net-
work align with maximum-entropy conditional models [4].
Our findings reveal that for the vast majority of commodities,
these models effectively replicate the observed triadic struc-
tures, exhibiting minimal deviations
Dynamical systems reduction through approximate lumping techniques
Full text linkModel reduction is a fundamental technique utilized across
various disciplines, such as engineering, physics, and compu-
tational sciences, to simplify complex mathematical models
while retaining essential dynamics.
This thesis introduces two novel approaches for model reduc-
tion, particularly focusing on dynamical systems described by
polynomial ordinary differential equations (ODEs). The pro-
posed techniques aim to reduce ODE systems while providing
formal error bounds for the resultant reduced models.
The first approach, based on backward and forward differen-
tial equivalence (BDE/FDE), partitions the set of variables in
an ODE system to construct a reduced model, incorporating a
tolerance parameter ε to capture perturbations in polynomial
coefficients. In the second approach, we present an algorithm
to transform an ODE system into a so-called differential hull.
This is a construction whereby variables with structurally sim-
ilar dynamics but originally different parameters may be rep-
resented by the same lower and upper bounds and reduced
through the backward differential equivalence.
Furthermore, the thesis explores the application of these tech-
niques in discovering regular equivalences on networks. An
iterative scheme, called iterative ε-BDE, is introduced to com-
pute regular equivalences, allowing for the analysis of roles in
networks.
Experimental evaluations demonstrate the effectiveness and
efficiency of the proposed approaches compared to existing
methods in the literature
An Essay on the Emergence of Non-pathological Aggressive-like Behaviors in the Context of Social Interactions
No full textAggressivity is a type of widespread behavior in our society,
yet its outcomes are everything but desirable. If evolutionary,
being aggressive might have given some clear advantages to
one to prevail (e.g., seizing resources, better mating options);
nowadays, aggressive behavior held none of those advan-
tages, being a form of prevarication where the ultimate goal
is to harm another individual, either physically, emotionally,
morally or materially. Why, then, is aggressive behavior still
persistent despite the rise of cooperative societies? In this
doctoral Thesis, with the aid of three controlled experiments
and the expertise of Behavioral Economics and Neuroscience,
I aim to shed more light on non-pathological aggressiveness,
its genetic underpinnings, and cognitive mechanisms. Specif-
ically, we found that some genetic variants of dopamine and
serotonin are highly connected with actions and beliefs re-
garding cooperation and punishment, where having a par-
ticular variant makes one more prone to act and think pes-
simistically toward the behaviors of others or to free-ride more.
In another experiment, we demonstrate that extreme exertion
of self-control makes it more probable to behave aggressively
in a subsequent social situation. Frontal areas dedicated to
impulse control regulation are, in fact, extremely vulnerable
to functional fatigue, showing signs of local sleep. In this neu-
ronal phenomenon, groups of neurons fire at frequencies typ-
ical of sleep states instead of the ones of wake. Our exper-
iment associated the prolonged exertion of self-control with
the emergence of delta waves in frontal areas dedicated to
impulse and emotion regulation and subsequent aggressive
choices in a series of proxied social situations
Understanding Emotions: The Evolution of Affective Neuroscience and a Network-Based Taxonomy of Emotion
No full textEmotion, as a field of study, has evolved significantly over the
centuries, encompassing various perspectives from theology,
philosophy, medicine, psychology, and neuroscience.
Historically, terms like 'passions,' 'affections,' and 'emotions' have
carried different connotations and have been studied through
different lenses, influenced by societal norms and scientific
advancements. The affective lexicon has seen a transition across
different languages and cultural contexts, contributing to the
development of a global scientific community and a more
nuanced understanding of emotional phenomena.
The first part provides a comprehensive overview of the evolution
of affective neuroscience, highlighting the historical path,
emotional models and theories, and methodological
advancements. A thorough qualitative look at the sharp increase
in affective studies provides a beter understanding of where
emotion research has focused. An extensive literature review
across PubMed was conducted to gather relevant studies focusing
on affective topics, neuroimaging techniques, and emotional
categories. The findings demonstrated the trends in the
publications of the affective neuroscience field over time. The
analysis revealed a significant shift in research focus over the
years, a specific focus on neuroimaging techniques and certain
emotion categories
The second part presents an innovative approach to
understanding emotions through language. This section delves
into the semantic structures underlying affective terms and
explores how linguistic and cultural nuances could shape
emotional experiences. It examines the challenges in achieving a
scientific consensus on the nature of emotions due to their
conceptual complexity. This complexity is further compounded by the variety of models proposed to categorize emotions,
stemming from basic emotion theories, which suggest a limited
number of universal emotions, to dimensional and constructionist
theories, which argue for a more fluid and context-dependent
understanding of emotional experiences. Through the
experimental procedure, participants were instructed to define
emotional terms based on the subjective experience. The results
demonstrate that emotions are intricately linked within a
network-based hierarchical taxonomy based on language,
offering a more detailed and systematic classification of emotions
than traditional emotion models. This network-based approach
elucidates the relationships between various affective terms and
their semantic structures, highlighting the complex interplay
between language and emotion
Coordinate-Descent Augmented Lagrangian Methods for Interpretative and Adaptive Model Predictive Control
Full text linkModel predictive control (MPC) of nonlinear systems suffers
a trade-off between model accuracy and real-time compu-
tational burden. This thesis presents an interpretative and
adaptive MPC (IA-MPC) framework for nonlinear systems,
which is related to the widely used approximation method
based on successive linearization MPC and Extended Kalman
Filtering (SL-MPC-EKF). First, we introduce a solution algo-
rithm for linear MPC that is based on the combination of Co-
ordinate Descent and Augmented Lagrangian (CDAL) ideas.
The CDAL algorithm enjoys three features: (i) it is construction-free, in that it avoids explicitly constructing the quadratic pro-gramming (QP) problem associated with MPC; (ii) is matrix-free, as it avoids multiplications and factorizations of matri-ces; and (iii) is library-free, as it can be simply coded without any library dependency, 90-lines of C-code in our implemen-tation. We specialize the algorithm for both state-space for-mulations of MPC and formulations based on AutoRegres-sive with eXogenous terms models (CDAL-ARX). The thesis also presents a rapid-prototype MPC tool based on the gPROMS platform, in which the qpOASES and CDAL algorithm was integrated. In addition, based on an equivalence between SS-based and ARX-based MPC problems we show,we investigate the relation between the proposed IA-MPC and the classical SL-MPC-EKF method. Finally, we test and show the effectiveness of the proposed IA-MPC frameworkon four typical nonlinear MPC benchmark examples
Essays on the Evolution of Prosocial Behaviors
Full text linkProsocial behaviors – such as helping others, donating, and
cooperating – are often considered key to evolutionary suc-
cess. Therefore, it is of great interest to understand under
what conditions these behaviors can emerge and/or can be
sustained at a population level. Following a dual process
approach, I study whether and how cognition can affect the
evolution of collaboration, cooperation, and generosity. I do this by employing stochastic stability analysis techniques and agent-based simulations. For each prosocial behavior consid-ered, I find that cognition can play an important role in the diffusion of prosocial behaviors, sometimes fostering them and other times hampering them. These results shed light on recent experimental evidence and, at the same time, suggest new interesting research avenues