409 research outputs found
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The impact of tourism on urban areas
Full text linkThis doctoral dissertation is divided into three chapters. All of them
deal with aspects related to the the impact of tourism on urban areas, but
each one has a distinct topic and puts its focus on a specific standpoint.
The effect of Short-Term Rental on Local Consumption Amenities: Evidence
from Madrid This paper examines the impact of the arrival of Airbnb
on local consumption amenities in Madrid. We exploit the exogenous
variation created by the timing and uneven distribution of Airbnb listings
in the city to determine the impact on food and beverage establishments.
Using an instrumental variable strategy, we find positive local
effects on both the number of restaurants and their employees: an increase
of fourteen Airbnb rooms in a given census tract leads to almost
one more restaurant, and the same increase in a given neighborhood generates
eleven new tourist-related employees. The results are robust to the
specification and sample composition. This paper contributes to the literature
on the economic impact of the platform economy on urban areas
by providing evidence of market expansion externalities from short-term
rentals. This paper has been published in the Journal of Regional Science.
When Local Business Faded Away: The Uneven Impact of Airbnb on the Geography
of Economic Activities This paper investigates the unequal effect
of Airbnb on the spatial organisation of economic activity in Madrid,
Spain. Using establishment-level data from Madrid City Council and
consumer-facing information from this short-term rental company, we
find that Airbnb reshapes the urban space by encouraging tourist-oriented
businesses, defined as businesses where tourists spend more than locals,
at the expense of businesses primarily oriented to locals. These findings
prove that short-term rentals do displace not only the local population
but also resident-oriented businesses. Eventually, we show that our results
are not driven by the method of measuring digital accommodation
activity, other touristic actors, and confounders related to gentrification
and the rise of online purchasing. This paper has been published in the
Cambridge Journal of Regions, Economy and Society.
Your Room is Ready: Tourism and Urban Revival Tourism is an essential
sector of the global economy, contributing significantly to GDP and
employment. Despite its importance, our understanding of its impact
on urban economic activity remains limited. This paper aims to fill this gap by examining the impact of tourism on urban transformation using
a dataset of hotel openings in Madrid from 2001-2010. I show that
hotel openings positively impact the number of establishments and employment
by using the number of protected buildings as an instrumental
variable to account for the non-random distribution of hotel openings.
Interestingly, hotel openings contribute to changes in the composition
of the economic activities and the business structures, enhancing touristoriented
corporate-owned businesses over other individual-owned companies.
Finally, economic effects extend to the real estate market, increasing
rental prices and residential investment. This paper is a solo coauthor
paper and my Job Market Paper
Beyond the cortex: cerebral hemodynamic changes associated with NREM sleep slow waves across the lifespan
No full textThe slow waves (0.5-4 Hz) observed during NREM sleep exhibit significant alterations influenced by experience-related plasticity and brain maturation. Existing literature predominantly suggests that slow waves originate from the cortex in both children and adults. However, research involving animal models and intracranial recordings from epilepsy patients has highlighted the potential pivotal role of subcortical structures, particularly the thalamus, in orchestrating and coordinating cortical slow waves. Previous studies using high-density electroencephalography (EEG) have suggested that subcortical structures, especially the thalamus, are involved in the generation and synchronization of large, widespread slow waves originating from the somatomotor cortex, while smaller, more localized slow waves may predominantly depend on cortico-cortical interactions. Despite these insights, the specific influence of subcortical structures on slow waves remains underexplored, primarily due to the spatial limitations of EEG technology. More importantly, there is a notable lack of evidence regarding these mechanisms in children. To address these gaps, we employed simultaneous EEG-fMRI, combining the high spatial resolution of fMRI with the capability of EEG to recognize individual graphoelements of sleep. This approach allows us to move beyond the traditional study of sleep based on polysomnography.
The first aim of this Thesis is to investigate the cortical and subcortical correlates of slow waves in children. Our findings indicate that developmental changes in slow-wave distribution occur around a stable origin hotspot in the somatomotor cortex.
Furthermore, the involvement of the cortical and thalamic default mode network in sleep slow waves increases with age, reflecting the relatively slow maturation of this functional network. Finally, our results suggest that maturation in slow-wave properties during development depend on changes in thalamic regulation.
The second aim is to examine whether the thalamus plays different roles in regulating and expressing distinct subtypes of slow waves. Our results demonstrate the existence of two distinct synchronization mechanisms for slow waves: subcortico-cortical synchronization, which can lead to large and widespread slow waves and is associated with changes in autonomic activity, and cortico-cortical synchronization, which leads to smaller, more localized slow waves. These functional mechanisms may undergo distinct regulatory processes and may serve different functions across the sleeping night.
In conclusion, these studies underscore the importance of a comprehensive characterization of sleep slow waves across the lifespan. Such understanding is crucial for guiding future research aimed at investigating the role of sleep in normal and pathological development and aging and at building targeted therapeutic interventions
From Subpixel Accuracy to Scanpaths Analysis: Smart Strategies for Implementing Deep Learning Algorithms in Eye Movement Research and Applications
No full textEye-tracking research has been influential across various sec-
tors, encompassing both the creation of eye-tracking devices
and the analysis of the data they produce. These facets are
known as gaze estimation and gaze analysis. The former
identifies where an individual is gazing based on images cap-
tured by cameras aimed at the eyes, while the latter discerns
the duration and sites of gaze, typically using characteris-
tics like saccades and fixations to deduce an individual’s cog-
nitive activities. Recently, a significant transformation has
taken place with both fields now heavily leaning on deep
learning. This integration of deep learning methods has sig-
nificantly improved precision, efficiency, and adaptability in
both realms. It also ushers in advanced implementations,
such as real-time gaze forecasting in areas like virtual real-
ity and gaming. Yet, the infusion of deep learning comes
with its set of challenges, notably when faced with the limited
and often expensive eye-tracking datasets. This dissertation
delves into these issues, focusing on the role of deep learning
in both gaze estimation and analysis. Amongst the myriad
of deep learning techniques for eye tracking, this work high-
lights two: first, the efficacy of using synthetic data in gaze
estimation models and its performance in synthetic and real-
world pipelines. Second, within the context of an economic
experiment, we investigate the impact of feature engineering
for scanpath formulation and the potential to foresee a user’s
choice before they decide, a concept that holds significance in
numerous sectors, especially as eye tracking devices such as
virtual headsets gain traction
Walking a mile in another’s shoes. The use of naturalistic stimulation to study emotional processing and empathy
No full textThe present dissertation delves into the cutting-edge field of
naturalistic stimulation to investigate the multifaceted nature of
emotional experiences and the mechanisms underlying empathic
responses. Through a series of behavioral studies, we explored 1)
whether the emotional experience elicited by a movie can be
embedded by a limited set of descriptors conventionally referred
to as genres; 2) the affective unfolding of narratives, and the
emotional transitions dynamics underlying individual
experience; 3) the contribution of visual, acoustic, and semantic
properties of the stimulus in predicting the subjective emotional
experience. Our results show that the unfolding of emotions plays
a crucial role in shaping how audiences perceive and categorize
movies. Then, we confirm the existence of six archetypal patterns
that shape the emotional trajectories of narratives, and we
demonstrate that certain emotions may serve as triggers, others
act as catalysts for subsequent reactions, or emerge as outcomes
of appraised states. The same emotion may behave as both
starting and landing state, suggesting the crucial role of context in
shaping the inner emotional experience. Also, we find that,
although we can predict a consistent amount of the audience's
emotional states, the physical properties of the stimulus may not
be entirely sufficient to reconstruct the subjective affective
experience. Lastly, we assess the psychometric properties of two
recently developed questionnaires measuring empathic abilities
in the Italian populatio
TEXTILE PRACTICES AS MEMORY MAKING: WEAVING BONDS BETWEEN THE PAST, PRESENT AND FUTURE IN CONTEMPORARY ART AND ACTIVISM IN TURKEY (2010s–Present)
No full textThis dissertation titled Textile Practices As Memory Making: Weaving Bonds
Between The Past, Present And Future In Contemporary Art And Activism In
Turkey (2010s-Present) investigates the ways in which contemporary textile-
based practices participate in the making of collective memories of violent
pasts through an analysis of cases from/linked with Turkey. It focuses on
how the material properties and connotations of textiles and textile-based
techniques can be mobilized for memory work by curatorial, artistic and
activist practices while simultaneously examining the permeabilities and
tensions between these.
Situated within the intersections of contemporary art and activism, the cases
analyzed in-depth in the scope of this dissertation are as follows: (1)
Embroideries made by Hripsimeh Sarkissian (b.1908, Dersim, Ottoman
Empire – 2000, Istanbul) a woman who survived the Armenian Genocide and
the Dersim Massacre, and her granddaughter Anita Toutikian’s (b.1961,
Beirut, Lebanon) curatorial work with and reinterpretation of these objects
(2) Textile-based works by the visual artist Eşref Yıldırım (b.1978, Bursa,
Turkey) for which he rewrote parts from a poem by the deceased poet
Arkadaş Z. Özger (b.1948, Bursa – d.1973, Ankara) (3) Örgülü Mücadele, a
group collectively knitting blankets as a part of the struggle for justice in the
aftermath of the bomb attack that targeted the participants of a peace rally in
Ankara on 10 October 2015
All three of the cases are subject to a comprehensive scholarly study for the
first time within the scope of this dissertation. This is one of the important
contributions of this study.
In examining the cases, I explore how creative practices can provide grounds
for political, artistic, art historical and activist possibilities other than the
representation of past violence. I deploy three notions, also by demonstrating
the interactions between them: act of making, materiality and collectivity. I
argue that placing the acts of making - understood as bodily labor,
procedural and material – as crucial elements in the analysis and data
collection enables the identification of collectivities that are not always
immediately apparent. Informed by feminist and queer politics and ethics,
my proposal is that the abovementioned political, artistic and activist
possibilities, which might contribute to both theory and practice, occur
within and through these collectivities and processes of making. The
individual case analyses exemplify and explicit how this proposal can be
implemented. In this respect, this dissertation offers an alternative and
applicable analytical and methodological framework that can provide
insightful contribution to the studies in art history, critical textile scholarship
and memory studies
On the conceptualisation and forecasting of emotion dynamics in healthy and psychiatric individuals
No full textThroughout the day, individuals experience a variety of feelings,
such as amusement, relaxation, and envy. By observing the
regularities in the stream of affect, individuals learn to predict
future emotions from current ones and develop accurate mental
models of emotion transitions. This thesis aims to explore the
cognitive architecture underlying these affective forecasts.
Through a series of experiments involving both healthy and
psychiatric individuals, we investigate i) the temporal boundaries
of affective predictions and their evolution over time, ii) the
influence of the conceptual knowledge about emotions on
transition judgements at various timescales, iii) the impact of
dysfunctional affective dynamics on the forecast of future
emotions. Results indicate that people trust more their predictions
in the near future, with confidence dropping after 24 hours. We
identified nine prototypes in the temporal profiles of affective
forecasts and mapped their trajectories in a two-dimensional space
defined by transition plausibility and slope. Also, we characterise
emotions as starting states (e.g., surprise) or end-points (e.g.,
irritation) based on transition judgments, and reveal asymmetry in
forecasts for specific transitions (e.g., relief → fear). Analysis of the
scaffolding of affective forecasts confirms the relevance of
conceptual knowledge about emotions in shaping mental models
of emotion transitions. Our findings indicate that similarities
between emotions in certain dimensions (e.g., valence) inform
predictions regardless of the time interval, while others (e.g.,
arousal) exert influence only within specific timescales. We
demonstrate that psychiatric disorders such as depression and
bipolar disorder significantly affect the architecture of affective
forecasts, although these adjustments do not undermine the core
predictive structure. Findings suggest that patients use their
internal emotion dynamics as a reference to construct (or refine)
their predictive models of emotion transitions
A RIGHT TO DESTROY? THE LEGAL BOUNDARIES OF CULTURAL MEMORY. An Examination of the Role of the International Community in the Protection of National Heritage Sites against Deliberate Destruction.
Full text linkThe dissertation explores the deliberate destruction of cultural
heritage under international law. The main thread of theresearch
concerns the legal boundaries of cultural memory by examining
when a duty to remember cultural heritage can translate into a
legal obligation to preserve it - a right to remember- and when, at
the same time, there may be a symmetrical legal duty to forget it.
In other terms, the dissertation seeks to study not only the
“pathological” dimension of destruction but also tracetheborders
of destruction by verifying lawful situations in which is possible
to recognize “a right to destroy”, b comparing different casesof
destruction, or, as the case may be, removal of heritage. Thestudy
explores cases of the destruction of heritage in national contexts
authorized by domestic governments in light of applicable
international norms in both peacetime and wartime contexts. The
scope of the research includes mainly examples of tangible
cultural heritage (more specifically, public monuments and
buildings), which are characterized as contested heritage with
accompanying issues of memory and divisive identity narratives.
The research will focus on iconoclastic episodes driven by
ideological reasons, rooted in three case-studies: Soviet
monuments in Ukraine, Confederate iconography in the United
States, and the situation of the Rohingya in Myanmar. It will
exclude cases of peacetime threats to cultural heritage caused by
economic development.
The study seeks to enrich the interdisciplinary literature on
memory and heritage studies in connection with law
Global and preference-based optimization using surrogate-based methods
Full text linkThis thesis explores methodologies in black-box and
preference-based optimization, addressing three key research
questions. Firstly, it introduces a semi-automated calibration
approach that eliminates the need for an explicit performance
index by relying on human calibrator preferences.
Secondly, the thesis delves into preference-based global optimization
algorithms that address optimization problems
where the analytic expression of the objective function is
unknown and the optimization is subject to unknown constraints.
The proposed algorithm, C-GLISp, extends the
active preference learning framework to handle these unknown
constraints. Lastly, the thesis tackles the challenge
of optimization problems involving mixed variables and linear
constraints. To address this challenge, we present a
novel surrogate-based global optimization algorithm, named
PWAS. The algorithm constructs a piecewise affine surrogate
of the objective function over feasible samples and utilizes exploration
functions to efficiently navigate the feasible domain
using mixed-integer linear programming solvers. Additionally,
a preference-based version of the algorithm, PWASp, is
introduced to handle situations where only pairwise comparisons
between samples are available instead of direct objective
function evaluations. The efficiency and effectiveness of
the proposed approaches are demonstrated via benchmark
studies. Additionally, the practical applicability of PWAS is
discussed via experimental design case stuides
Multi-field and multi-scale modeling of fracture for renewable energy applications
Full text linkThis thesis is mainly focused on the computational model-
ing of solar cell cracking, multiphyics phenomena, and re-
cycling of photovoltaic (PV) modules through the finite ele-
ment method. Specifically, it consists of three parts. In the
first part, a comprehensive hygro-thermo-mechanical com-
putational framework in the 3D setting is proposed to model
the coupled degradation phenomena in the PV modules for
the durability analysis, and it is applied to the simulation
of three international standard tests of PV modules, namely
the damp heat test, the humidity freeze test, and the ther-
mal cycling test. The second part is focused on the crack
modeling of very thin and brittle silicon solar cells in the PV
modules, and a reliable computational framework integrat-
ing solid shell element formulation with phase field fracture
modeling is developed using the efficient quasi-Newton so-
lution scheme and global local approach. The excellent per-
formance is showcased through the simulation of different
boundary value problems, and then applied to predict the
crack growth of silicon solar cells when the PV modules are
subjected to different external loadings. The third part ad-
dresses the efficient recycling of PV modules through the nu-
merical modeling method by the development of 3D interface
finite element with humidity-dose enhanced cohesive zone
model for the peeling simulation to separate different layers,
and diffusion-swelling large deformation continuum theory
for the nondestructive recovery of silicon cells in the PV recy-
cling using the solvent method. With these tools at hand, it is
possible to design suitable virtual testing procedures for PV
durability and recyclability analysis
Scale-Invariant Random Graphs: a multiscale approach to network modeling
Full text linkIn the last decades, consistent efforts have been spent to capture
specific shades of real systems through the development
of random graph models, which have been studied extensively
either for their practical value as statistical benchmarks and
their theoretical appeal, as abstract tools capable of generating
synthetic graphs with realistic properties.
In particular, establishing a robust representation of a graph
at multiple scales of observation would enable considerable
progress in the description, modeling, and control of realworld
complex systems. Here, by building on the principles of
renormalization group theory from statistical mechanics, we
derive a random graph model precisely conceived to provide
a statistically consistent description of a network for different
resolutions of its units and in an exact manner.
We explore two interesting facets of the proposed model,
which interlace with different branches of network science. On
the one hand, it allows complying with empirical networks to
provide up-scaled and down-scaled reconstructions according
to a chosen hierarchy of partitions of the original nodes. In
this sense, the model constitutes solid support for harboring
a coarse-graining scheme of real systems without relying on
any arbitrary introduction of a metric space. Secondly, this
scale-invariant random graph itself turns out to generate networks
with topological properties that are widespread among
real-world systems and thus its mathematical sifting has its
own theoretical interest