Background. The three terms "panic", "irrationality", and "herding" are ubiquitous in the crowd dynamics literature and have a strong influence on both modelling and management practices. The terms are also commonly shared between the scientific and nonscientific domains. The pervasiveness of the use of these terms is to the point where their underlying assumptions have often been treated as common knowledge by both experts and lay persons. Yet, at the same time, the literature on crowd dynamics presents ample debate, contradiction, and inconsistency on these topics. Method.

Presentazione delle attività di ricerca su computational immunology e network medicine al workshop "Hot Topics in Systems" all'interno della conferenza PLACE2019

In this paper we present a new multi-scale method for reproducing traffic flow which couples a first-order macroscopic model with a second-order microscopic model, avoiding any interface or boundary conditions between them. The multi-scale model is characterized by the fact that microscopic and macroscopic descriptions are not spatially separated. On the contrary, the macro-scale is always active while the micro-scale is activated only if needed by the traffic conditions.

We explore the impact of geometrical corrugations on the near-wall flow properties of a soft material driven in a confined rough microchannel. By means of numerical simulations, we perform a quantitative analysis of the relation between the flow rate ? and the wall stress ?w for a number of setups, by changing both the roughness values as well as the roughness shape. Roughness suppresses the flow, with the existence of a characteristic value of ?w at which flow sets in. Just above the onset of flow, we quantitatively analyze the relation between ? and ?w.

In recent years we are witnessing a continuous growth in the amount of data that both public and private organizations collect and profit by. Search engines are the most common tools used to retrieve information, and more recently, clustering techniques showed to be an effective tool in helping users to skim query results.

Network-based ranking methods (e.g. centrality analysis) have found extensive use in systems medicine for the prediction of essential proteins, for the prioritization of drug targets candidates in the treatment of several pathologies and in biomarker discovery, and for human disease genes identification. Here we propose to use critical nodes as defined by the Critical Node Problem for the analysis of key physiological and pathophysiological signaling pathways, as target candidates for treatment and management of several cancer types, neurologic and inflammatory dysfunctions, among others.

Drug releasing capsules and droplets are largely used in biomedical applications. Such vehicles consist of a drug-loaded core surrounded by a thin semi-permeable layer. Diffusion is by far the dominant mechanism in drug delivery, beside other physico-chemical factors, such as osmosis, drug dissolution, polymer swelling and degradation.

The amount of traffic data collected by automatic number plate reading systems constantly incrseases. It is therefore important, for law enforcement agencies, to find convenient techniques and tools to analyze such data. In this paper we propose a scalable and fully automated procedure leveraging the Apache Accumulo technology that allows an effective importing and processing of traffic data. We discuss preliminary results obtained by using our application for the analysis of a dataset containing real traffic data provided by the Italian National Police.

Dinur and Shamir's cube attack has attracted significant attention in the literature. Nevertheless, the lack of implementations achieving effective results casts doubts on its practical relevance. On the theoretical side, promising results have been recently achieved leveraging on division trails. The present paper follows a more practical approach and aims at giving new impetus to this line of research by means of a cipher-independent flexible framework that is able to carry out the cube attack on GPU/CPU clusters.