Stefano Boccaletti

Bio: Stefano Boccaletti is an academic researcher from Moscow Institute of Physics and Technology. The author has contributed to research in topics: Complex network & Synchronization (computer science). The author has an hindex of 60, co-authored 348 publications receiving 25776 citations. Previous affiliations of Stefano Boccaletti include King Juan Carlos University & Istituto Nazionale di Fisica Nucleare.

Chunking Rhythmic Synchronization: Bellerophon States and Quantized Clusters of Globally Coupled Phase Oscillators

Abstract: The emergence of phase coherence in interacting oscillators is one of the main phenomena for the coordination of events that make a system to behave cooperatively. Examples range from rhythmic physiological processes to the collective behaviors of technological and natural networks. We concentrate here on Bellerophon states, which are coherent states of rhythmic synchrony occurring in globally coupled oscillators close to the point where the transition from disorder to phase order converts from abrupt to continuous. Within Bellerophon states, oscillators form quantized clusters, where their instantaneous phases and frequencies are unlocked. Within each cluster, the oscillators’ instantaneous frequencies form a characteristic cusped pattern and, more importantly, they behave periodically in time, so that their long-time average values are the same. Along the manuscript, we give analytical and numerical description of these states, and we discuss their general appearance behind the collective rhythms reported in other systems of interacting oscillators.

Pattern formation and dynamics in an annular co2 laser

Abstract: The formation and competition of patterns in an annular CO2 laser has been experimentally and numerically analyzed. The temporal evolution of the different spatial structures increases its richness and complexity during the coexistence of different patterns. A model based on the Maxwell–Bloch equations, including a symmetry breaking term, provides a numerical interpretation of the main experimental features.

A compartmental model for cyber-epidemics

Abstract: In our more and more interconnected world, a specific risk is that of a cyber-epidemic (or cyber-pandemic), produced either accidentally or intentionally, where a cyber virus propagates from device to device up to undermining the global Internet system with devastating consequences in terms of economic costs and societal harms related to the shutdown of essential services. We introduce a compartmental model for studying the spreading of a malware and of the awareness of its incidence through different waves which are evolving on top of the same graph structure (the global network of connected devices). This is realized by considering vectorial compartments made of two components, the first being descriptive of the state of the device with respect to the new malware's propagation, and the second accounting for the awareness of the device's user about the presence of the cyber threat. By introducing suitable transition rates between such compartments, one can then follow the evolution of a cyber-epidemic from the moment at which a new virus is seeded in the network, up to when a given user realizes that his/her device has suffered a damage and consequently starts a wave of awareness which eventually ends up with the development of a proper antivirus software. We then compare the overall damage that a malware is able to produce in Erd\H{o}s-R\'enyi and scale-free network architectures for both the case in which the virus is causing a fixed damage on each device and the case where, instead, the virus is engineered to mutate while replicating from device to device. Our result constitute actually the attempt to build a specific compartmental model whose variables and parameters are entirely customized for describing cyber-epidemics.

Predicting Phase Synchronization for Homoclinic Chaos in a CO2 Laser

Abstract: A novel approach is presented for the reconstruction of phase synchronization phenomena in a chaotic CO2 laser from experimental data. We analyze this laser system in a regime of homoclinic chaos, which is able to phase synchronize with a weak sinusoidal forcing. Our technique recovers the synchronization diagram of the experimental system from only few measurement data sets, thus allowing the prediction of the regime of phase synchronization as well as non‐synchronization in a broad parameter space of forcing frequency and amplitude without further experiments.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Complex brain networks: graph theoretical analysis of structural and functional systems

Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.