2,896 research outputs found
Complex delay dynamics on railway networks: from universal laws to realistic modelling
Railways are a key infrastructure for any modern country. The reliability and
resilience of this peculiar transportation system may be challenged by
different shocks such as disruptions, strikes and adverse weather conditions.
These events compromise the correct functioning of the system and trigger the
spreading of delays into the railway network on a daily basis. Despite their
importance, a general theoretical understanding of the underlying causes of
these disruptions is still lacking. In this work, we analyse the Italian and
German railway networks by leveraging on the train schedules and actual delay
data retrieved during the year 2015. We use {these} data to infer simple
statistical laws ruling the emergence of localized delays in different areas of
the network and we model the spreading of these delays throughout the network
by exploiting a framework inspired by epidemic spreading models. Our model
offers a fast and easy tool for the preliminary assessment of the
{effectiveness of} traffic handling policies, and of the railway {network}
criticalities.Comment: 32 pages (with appendix), 28 Figures (with appendix), 2 Table
Distributed Discontinuous Coupling for Convergence in Heterogeneous Networks
In this letter, we propose the use of a distributed discontinuous coupling protocol to achieve convergence and synchronization in networks of non-identical nonlinear dynamical systems. We show that the synchronous dynamics is a solution to the average of the nodes' vector fields, and derive analytical estimates of the critical coupling gains required to achieve convergence
Shrinking Point Bifurcations of Resonance Tongues for Piecewise-Smooth, Continuous Maps
Resonance tongues are mode-locking regions of parameter space in which stable
periodic solutions occur; they commonly occur, for example, near Neimark-Sacker
bifurcations. For piecewise-smooth, continuous maps these tongues typically
have a distinctive lens-chain (or sausage) shape in two-parameter bifurcation
diagrams. We give a symbolic description of a class of "rotational" periodic
solutions that display lens-chain structures for a general -dimensional map.
We then unfold the codimension-two, shrinking point bifurcation, where the
tongues have zero width. A number of codimension-one bifurcation curves emanate
from shrinking points and we determine those that form tongue boundaries.Comment: 27 pages, 6 figure
Design and validation of a virtual player for studying interpersonal coordination in the mirror game
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The mirror game has been recently proposed as
a simple, yet powerful paradigm for studying interpersonal
interactions. It has been suggested that a virtual partner able
to play the game with human subjects can be an effective tool
to affect the underlying neural processes needed to establish the
necessary connections between the players, and also to provide
new clinical interventions for rehabilitation of patients suffering
from social disorders. Inspired by the motor processes of the
central nervous system (CNS) and the musculoskeletal system in
the human body, in this paper we develop a novel interactive
cognitive architecture based on nonlinear control theory to drive
a virtual player (VP) to play the mirror game with a human
player (HP) in different configurations. Specifically, we consider
two cases: the former where the VP acts as leader and the latter
where it acts as follower. The crucial problem is to design a
feedback control architecture capable of imitating and following
or leading a human player in a joint action task. Movement of
the end-effector of the VP is modeled by means of a feedback
controlled Haken-Kelso-Bunz (HKB) oscillator, which is coupled
with the observed motion of the HP measured in real time.
To this aim, two types of control algorithms (adaptive control
and optimal control) are used and implemented on the HKB
model so that the VP can generate a human-like motion while
satisfying certain kinematic constraints. A proof of convergence
of the control algorithms is presented in the paper together
with an extensive numerical and experimental validation of their
effectiveness. A comparison with other existing designs is also
discussed, showing the flexibility and the advantages of our
control-based approach.This work was funded by the European Project AlterEgo
FP7 ICT 2.9 - Cognitive Sciences and Robotics, Grant Number
600610
Finding Exogenous Variables in Data with Many More Variables than Observations
Many statistical methods have been proposed to estimate causal models in
classical situations with fewer variables than observations (p<n, p: the number
of variables and n: the number of observations). However, modern datasets
including gene expression data need high-dimensional causal modeling in
challenging situations with orders of magnitude more variables than
observations (p>>n). In this paper, we propose a method to find exogenous
variables in a linear non-Gaussian causal model, which requires much smaller
sample sizes than conventional methods and works even when p>>n. The key idea
is to identify which variables are exogenous based on non-Gaussianity instead
of estimating the entire structure of the model. Exogenous variables work as
triggers that activate a causal chain in the model, and their identification
leads to more efficient experimental designs and better understanding of the
causal mechanism. We present experiments with artificial data and real-world
gene expression data to evaluate the method.Comment: A revised version of this was published in Proc. ICANN201
Parental Support during the COVID-19 Pandemic: Friend or Foe? A Moderation Analysis of the Association between Maternal Anxiety and Children’s Stress in Italian Dyads
There is evidence that parental psychological disorders in stressful situations increase the risk of disturbance in child development. This has been investigated in disasters but not in pandemics, which are sensibly different from other types of traumatic events. We investigated the relationship between mothers’ anxiety and their children’s (self-reported) stress and the boundary conditions of this association during the first full COVID-19 lockdown in Italy. During the COVID-19 pandemic, mothers might have increased their protective attitudes to secure and support their children; we tested whether the relationship between mothers’ anxiety and children’s stress was weaker (buffer effect) or stronger (over-protection effect) when perceived parental support was high. We measured mothers’ anxiety, children’s perceived parental support, and children’s stress in a sample of 414 8- to 11-year-old primary school children (229 females, Mage = 9.44) and 395 mothers (Mage = 42.84). Results supported the over-protection scenario and provided the first evidence for the “helicopter-parent effect” during the COVID-19 pandemic: mothers’ anxiety was positively associated with children’s stress only when perceived support was high. Our finding highlights the importance of educating parents (for example, via emotional training) to prevent the worst consequences of adverse events in children and promote their mental health
Spatially restricted expression of PlOtp, a Paracentrotus lividus Orthopedia-related homeobox gene, is correlated with oral ectodermal patterning and skeletal morphogenesis in late-cleavage sea urchin embryos
Several homeobox genes are expressed in the sea urchin embryo but their roles in development have yet to be elucidated. Of particular interest are homologues of homeobox genes that in mouse and Drosophila are involved in patterning the developing central nervous system (CNS). Here, we report the cloning of an orthpedia (Otp)-related gene from Paracentrotus lividus, PlOtp. Otp is a single copy zygotic gene that presents a unique and highly restricted expression pattern. Transcripts were first detected at the mid-gastrula stage in two pairs of oral ectoderm cells located in a ventrolateral position, overlying primary mesenchyme cell (PMC) clusters. Increases in both transcript abundance and the number of Otp-expressing cells were observed at prism and pluteus stages. Otp transcripts are symmetrically distributed in a few ectodermal cells of the oral field. Labelled cells were observed close to sites of active skeletal rod growth (tips of the budding oral and anal arms), and at the juxtaposition of stomodeum and foregut. Chemicals known to perturb PMC patterning along animal-vegetal and oral-aboral axes altered the pattern of Otp expression. Vegetalization by LiCl caused a shift in Otp-expressing cells toward the animal pole, adjacent to shifted PMC aggregates. Nickel treatment induced expression of the Otp gene in an increased number of ectodermal cells, which adopted a radialized pattern. Finally, ectopic expression of Otp mRNA affected patterning along the oral-aboral axis and caused skeletal abnormalities that resembled those exhibited by nickel-treated embryos. From these results, we conclude that the Otp homeodomain gene is involved in short-range cell signalling within the oral ectoderm for patterning the endoskeleton of the larva through epithelial-mesenchymal interactions
Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning
An innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon’s subjective assessment. As such, this leads to assessments that are strongly experience-dependent. To overcome this limitation, the proposed algorithm assesses the level and uniformity of indocyanine green used during laparoscopic surgery. The algorithm adopts a Feed Forward Neural Network receiving as input a feature vector based on the histogram of the green band of the input image. It is used to (i) acquire information related to perfusion during laparoscopic colorectal surgery, and (ii) support the surgeon in assessing objectively the outcome of the procedure. In particular, the algorithm provides an output that classifies the perfusion as adequate or inadequate. The algorithm was validated on videos captured during surgical procedures carried out at the University Hospital Federico II in Naples, Italy. The obtained results show a classification accuracy equal to 99.9 % , with a repeatability of 1.9 %. Finally, the real-time operation of the proposed algorithm was tested by analyzing the video streaming captured directly from an endoscope available in the OR
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