다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

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。

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

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

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.

Pattern Recognition and Machine Learning

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.

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

We report a detailed experimental investigation of the dependence of localized structures, observed in a nonlinear optical device, on several control parameters. A first step of the study consists in the determination of the region of existence of localized states as a function of the system variables. Subsequently, we show how different control parameters can be used to the aim of tuning several localized structures properties; among these, of particular relevance are the contrast and the amplitude and frequency of the oscillations appearing on the tails of the structures. A discussion of the relation between the localized states here studied and the one predicted by general model for pattern forming systems is also given.

Control of localized structures in an optical feedback interferometer.

We introduce a 2D coupled map lattice model which, besides simulating the two variable FitzHugh–Nagumo reaction diffusion mechanism, accounts also for a superexcitable period. Superexcitability in the threshold dynamics of excitable media has been recently observed in experiments on cardiac tissues. By this model, we can reproduce the transition from normal cardiac behavior toward fibrillating processes in a 2D assembly of cardiac cells. The role of superexcitability results in producing two states of wave propagation and a spiral breakup mechanism in qualitative agreement with the experimental evidence of coarse and fine fibrillation in human hearts.

Superexcitability induced spiral breakup in excitable systems

We focus on spatially-extended networks during their transition from short-range connectivities to a scale-free structure expressed by heavy-tailed degree-distribution. In particular, a model is introduced for the generation of such graphs, which combines spatial growth and preferential attachment. In this model the transition to heterogeneous structures is always accompanied by a change in the graph's degree-degree correlation properties: while high assortativity levels characterize the dominance of short distance couplings, long-range connectivity structures are associated with small amounts of disassortativity. Our results allow to infer that a disassortative mixing is essential for establishing long-range links. We discuss also how our findings are consistent with recent experimental studies of 2-dimensional neuronal cultures.

/pdf/assortative-mixing-in-spatially-extended-networks-3e5ptwmyad.pdf

Assortative mixing in spatially-extended networks.

We give evidence of coherence resonance in an excitable electronic circuit whose dynamics obeys the FitzHugh-Nagumo model system, under the application of different noise sources, ranging from Gaussian white noise to colored $1∕{f}^{2}$ noises. The resonance behavior can be significantly reinforced when experimental parameters are tuned in order to place the stable fixed point closer to the excitability threshold of spiking behavior, as well as when the time scales of the circuit are properly modified. A quantitative description of the effects of noise correlations in inducing the resonant behavior is provided.

Coherence resonance in excitable electronic circuits in the presence of colored noise.

We show that the topology and dynamics of a network of unsynchronized Kuramoto oscillators can be simultaneously controlled by means of a forcing mechanism which yields a phase locking of the oscillators to that of an external pacemaker in connection with the reshaping of the network's degree distribution. The entrainment mechanism is based on the addition, at regular time intervals, of unidirectional links from oscillators that follow the dynamics of a pacemaker to oscillators in the pristine graph whose phases hold a prescribed phase relationship. Such a dynamically based rule in the attachment process leads to the emergence of a power-law shape in the final degree distribution of the graph whenever the network is entrained to the dynamics of the pacemaker. We show that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks' initial configurations and parameters.

/pdf/entraining-the-topology-and-the-dynamics-of-a-network-of-216zegzy6y.pdf

Stefano Boccaletti

Papers

Control of localized structures in an optical feedback interferometer.

Superexcitability induced spiral breakup in excitable systems

Assortative mixing in spatially-extended networks.

Coherence resonance in excitable electronic circuits in the presence of colored noise.

Entraining the topology and the dynamics of a network of phase oscillators.