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

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 $N$-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

Inference of gene regulatory networks and compound mode of action from time course gene expression profiles.

MOTIVATION: Time series expression experiments are an increasingly popular method for studying a wide range of biological systems. Here we developed an algorithm that can infer the local network of gene-gene interactions surrounding a gene of interest. This is achieved by a perturbation of the gene of interest and subsequently measuring the gene expression profiles at multiple time points. We applied this algorithm to computer simulated data and to experimental data on a nine gene network in Escherichia coli. RESULTS: In this paper we show that it is possible to recover the gene regulatory network from a time series data of gene expression following a perturbation to the cell. We show this both on simulated data and on a nine gene subnetwork part of the DNA-damage response pathway (SOS pathway) in the bacteria E. coli

Simultaneous Border-Collision and Period-Doubling Bifurcations

We unfold the codimension-two simultaneous occurrence of a border-collision bifurcation and a period-doubling bifurcation for a general piecewise-smooth, continuous map. We find that, with sufficient non-degeneracy conditions, a locus of period-doubling bifurcations emanates non-tangentially from a locus of border-collision bifurcations. The corresponding period-doubled solution undergoes a border-collision bifurcation along a curve emanating from the codimension-two point and tangent to the period-doubling locus here. In the case that the map is one-dimensional local dynamics are completely classified; in particular, we give conditions that ensure chaos.Comment: 22 pages; 5 figure

Quantitative Characterization of α-Synuclein Aggregation in Living Cells through Automated Microfluidics Feedback Control

Aggregation of α-synuclein and formation of inclusions are hallmarks of Parkinson's disease (PD). Aggregate formation is affected by cellular environment, but it has been studied almost exclusively in cell-free systems. We quantitatively analyzed α-synuclein inclusion formation and clearance in a yeast cell model of PD expressing either wild-type (WT) α-synuclein or the disease-associated A53T mutant from the galactose (Gal)-inducible promoter. A computer-controlled microfluidics device regulated α-synuclein in cells by means of closed-loop feedback control. We demonstrated that inclusion formation is strictly concentration dependent and that the aggregation threshold of the A53T mutant is about half of the WT α-synuclein (56%). We chemically modulated the proteasomal and autophagic pathways and demonstrated that autophagy is the main determinant of A53T α-synuclein inclusions’ clearance. In addition to proposing a technology to overcome current limitations in dynamically regulating protein expression levels, our results contribute to the biology of PD and have relevance for therapeutic applications

Identification and characterization of PlAlix, the Alix homologue from the Mediterranean sea urchin Paracentrotus lividus.

The sea urchin provides a relatively simple and tractable system for analyzing the early stages of embryo development. Here, we use the sea urchin species, Paracentrotus lividus, to investigate the role of Alix in key stages of embryogenesis, namely the egg fertilization and the first cleavage division. Alix is a multifunctional protein involved in different cellular processes including endocytic membrane trafficking, filamentous (F)-actin remodeling, and cytokinesis. Alix homologues have been identified in different metazoans; in these organisms, Alix is involved in oogenesis and in determination/differentiation events during embryo development. Herein, we describe the identification of the sea urchin homologue of Alix, PlAlix. The deduced amino acid sequence shows that Alix is highly conserved in sea urchins. Accordingly, we detect the PlAlix protein cross-reacting with monoclonal Alix antibodies in extracts from P. lividus, at different developmental stages. Focusing on the role of PlAlix during early embryogenesis we found that PlAlix is a maternal protein that is expressed at increasingly higher levels from fertilization to the 2-cell stage embryo. In sea urchin eggs, PlAlix localizes throughout the cytoplasm with a punctuated pattern and, soon after fertilization, accumulates in larger puncta in the cytosol, and in microvilli-like protrusions. Together our data show that PlAlix is structurally conserved from sea urchin to mammals and may open new lines of inquiry into the role of Alix during the early stages of embryo development

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

Dark Matter detection via lepton cosmic rays

Recent observations of lepton cosmic rays, coming from the PAMELA and FERMI experiments, have pushed our understanding of the interstellar medium and cosmic rays sources to unprecedented levels. The imprint of dark matter on lepton cosmic rays is the most exciting explanation of both PAMELA's positron excess and FERMI's total flux of electrons. Alternatively, supernovae are astrophysical objects with the same potential to explain these observations. In this work, we present an updated study of the astrophysical sources of lepton cosmic rays and the possible trace of a dark matter signal on the positron excess and total flux of electrons.Comment: 6 pages and 3 figures. Proceedings for PASCOS 2010, Valencia, Spai

Mantra 2.0: An online collaborative resource for drug mode of action and repurposing by network analysis

Elucidation of molecular targets of a compound (mode of action, MoA) and of its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organised in a network of nodes (drugs) and edges (similarities) highlighting “communities” of drugs sharing a similar MoA. A user can upload gene expression profiles (GEPs) before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the GEPs into a unique drug ”node” embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA, and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource