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It was evidenced that in the sleep deprived brain, subsets of neurons may enter an off period while others remain on, called local sleep (Nature 472, 443 (2011)), but the underlying mechanism is still not completely understood. To figure out the answer, herein we present a neural network model of individual cognitive networks with adaptive chemical coupling and find that with the increase of coupling strength, a phenomenon of coexistence of activated and inactivated clusters can be observed, which thus provides a possible explanation for the mechanism of local sleep. This phenomenon is closely related to the feature of degree heterogeneity of cognitive networks and will disappear in homogeneous networks. Further, we show that the activated cluster comes from recurrent oscillation death while the inactivated cluster comes from their stabilized synchronization. Finally, a brief theoretical analysis is provided to explain these results. [ABSTRACT FROM AUTHOR]

Condensation has long been a closely studied problem in statistical physics but little attention has been paid to neural science. Here, we discuss this problem in brain networks and discover the condensation of a functional brain network whereby all its eigenmodes are condensed only into a few or even a single eigenmode of the structural brain network. We show that the condensation occurs due to the emergence of both chimera states and brain functions from the structure of the brain network. Furthermore, the condensation only appears in the regions of chimera and the condensed eigenmodes are only limited to the lower ones. Condensation is confirmed across different levels of brain subnetworks, including hemispheres, cognitive subnetworks, and isolated cognitive subnetworks, which are further supported by resting-state functional connectivity from empirical data. Our results indicate that condensation could be a potential mechanism for performing brain functions. Chimera states have a close relationship with brain functionality but how to understand them directly from brain functional networks is challenging. Here, using the method of eigenmode analysis, the authors report a condensation phenomenon of all eigenmodes of brain functional networks and show that the chimera states represent the condensation on lower eigenmodes. [ABSTRACT FROM AUTHOR]

Spontaneous activity of the human brain provides a window to explore intrinsic principles of functional organization. However, most studies have focused on interregional functional connectivity. The principles underlying rich repertoires of instantaneous activity remain largely unknown. We apply a recently proposed eigen-microstate analysis to three resting-state functional MRI datasets to identify basic modes that represent fundamental activity patterns that coexist over time. We identify five leading basic modes that dominate activity fluctuations. Each mode exhibits a distinct functional system-dependent coactivation pattern and corresponds to specific cognitive profiles. In particular, the spatial pattern of the first leading basis mode shows the separation of activity between the default-mode and primary and attention regions. Based on theoretical modelling, we further reconstruct individual functional connectivity as the weighted superposition of coactivation patterns corresponding to these leading basic modes. Moreover, these leading basic modes capture sleep deprivation-induced changes in brain activity and interregional connectivity, primarily involving the default-mode and task-positive regions. Our findings reveal a dominant set of basic modes of spontaneous activity that reflect multiplexed interregional coordination and drive conventional functional connectivity, furthering the understanding of the functional significance of spontaneous brain activity. To further understand functional organization in the resting human brain, a statistical physics approach called the eigen-microstate analysis is applied to functional MRI data, revealing a small set of leading basic modes that dominate rich repertoires of spontaneous activity. [ABSTRACT FROM AUTHOR]

Heat conduction in real physical networks such as nanotube/nanowire networks has been attracting more and more attention, but its theoretical understanding is far behind. To open a way to this problem, we present a multi-body vibration model to study heat conduction in complex networks, where nodes' degrees satisfy a random distribution, and links consist of 1D atom chains with nonlinear springs. Based on this model, we find two interesting phenomenons: (1) The main heat fluxes of a network always localize in a skeleton subnetwork, which may have potential applications in thermal management and thermal concentrators, and (2) there exists an abnormal size effect of heat conduction in complex networks, i.e., the total heat flux of a network will enlarge with the increase of atoms on links, which is in contrast to the previous result on a 1D chain. Furthermore, we introduce a transmission diagram to characterize the skeleton of localized heat fluxes and then discover a jumping transition of total heat flux in the process of removing links, implying that the control of heat flux can be effective only when the change in a network topology focuses on the links within the skeleton. A brief theory is introduced to explain the abnormal size effect. [ABSTRACT FROM AUTHOR]

Many evidences have shown that synchronization takes a key role in brain functions, but most of its theoretical studies are so far only focused on the global brain network. However, it is well-known that all the cognitive tasks are performed by individual local cognitive subnetworks but not the global brain network, thus it is necessary to study the synchronization of local brain networks. We here focus on this problem by considering the synchronization transition of all the 63 local subnetworks of a real brain network and interestingly find that these local networks of cortical regions may show a completely different synchronization transition from that of global brain network, i.e., non-monotonic order parameter with folding. Moreover, we find that the forward and backward processes show different synchronization transitions, such as one being the first-order synchronization transition and the other being the second-order synchronization transition, and even amplitude death, depending on the different topologies of local networks. By extensive numerical simulations, we show that the amplitude death is prefer to occur in the local networks with larger size but not prefer to occur in the local networks with smaller size. A brief theoretical analysis is presented to explain the mechanism of amplitude death. [ABSTRACT FROM AUTHOR]

Thermogenesis in brown and beige adipose tissue has important roles in maintaining body temperature and countering the development of metabolic disorders such as obesity and type 2 diabetes1,2. Although much is known about commitment and activation of brown and beige adipose tissue, its multiple and abundant immunological factors have not been well characterized3–6. Here we define a critical role of IL-27–IL-27Rα signalling in improving thermogenesis, protecting against diet-induced obesity and ameliorating insulin resistance. Mechanistic studies demonstrate that IL-27 directly targets adipocytes, activating p38 MAPK–PGC-1α signalling and stimulating the production of UCP1. Notably, therapeutic administration of IL-27 ameliorated metabolic morbidities in well-established mouse models of obesity. Consistently, individuals with obesity show significantly decreased levels of serum IL-27, which can be restored after bariatric surgery. Collectively, these findings show that IL-27 has an important role in orchestrating metabolic programs, and is a highly promising target for anti-obesity immunotherapy.Therapeutic administration of IL-27—serum levels of which are decreased in individuals with obesity—improves thermogenesis, protects against diet-induced obesity and ameliorates insulin resistance in mouse models of obesity. [ABSTRACT FROM AUTHOR]

Developing efficient strategy to regulate heat conduction is a challenging problem, with potential implication in the field of thermal materials. We here focus on a potential thermal material, i.e. complex networks of nanowires and nanotubes, and propose a model where the mass of each node is assigned proportional to its degree with m i ∼ k i α , to investigate how distributed nodes masses can impact the heat flow in a network. We find that the heat conduction of complex network can be either increased or decreased, depending on the controlling parameter α . Especially, there is an optimal heat conduction at α = 1 and it is independent of network topologies. Moreover, we find that the temperature distribution within a complex network is also strongly influenced by the controlling parameter α . A brief theoretical analysis is provided to explain these results. These findings may open up appealing applications in the cases of demanding either increasing or decreasing heat conduction, and our approach of regulating heat conduction by distributed nodes masses may be also valuable to the challenge of controlling waste heat dissipation in highly integrated and miniaturized modern devices. [ABSTRACT FROM AUTHOR]

Non-Markovian spontaneous recovery processes with a time delay (memory) are ubiquitous in the real world. How does the non-Markovian characteristic affect failure propagation in complex networks? We consider failures due to internal causes at the nodal level and external failures due to an adverse environment, and develop a pair approximation analysis taking into account the two-node correlation. In general, a high failure stationary state can arise, corresponding to large-scale failures that can significantly compromise the functioning of the network. We uncover a striking phenomenon: memory associated with nodal recovery can counter-intuitively make the network more resilient against large-scale failures. In natural systems, the intrinsic non-Markovian characteristic of nodal recovery may thus be one reason for their resilience. In engineering design, incorporating certain non-Markovian features into the network may be beneficial to equipping it with a strong resilient capability to resist catastrophic failures. Understanding failure propagation dynamics in complex networks with recovery processes is vital to realizing networks that are resistant to large scale failures. Here, the authors report a model for general failure propagation dynamics in complex networks with non-Markovian recovery processes. [ABSTRACT FROM AUTHOR]

The elite maize hybrid Zhengdan 958 (ZD958), which has high and stable yield and extensive adaptability, is widely grown in China. To elucidate the genetic basis of yield and its related traits in this elite hybrid, a set of doubled haploid (DH) lines derived from ZD958 were evaluated in four different environments at two locations over two years, and a total of 49 quantitative trait loci (QTL) and 24 pairs of epistatic interactions related to yield and yield components were detected. Furthermore, 21 QTL for six investigated phenotypic traits were detected across two different sites. Combining the results of these QTL in each environment and across both sites, three main QTL hotspots were found in chromosomal bins 2.02, 2.05–2.06, and 6.05 between the simple sequence repeat (SSR) markers umc1165-bnlg1017, umc1065-umc1637, and nc012-bnlg345, respectively. The existence of three QTL hotspots associated with various traits across multiple environments could be explained by pleiotropic QTL or multiple tightly linked QTL. These genetic regions could provide targets for genetic improvement, fine mapping, and marker-assisted selection in future studies. [ABSTRACT FROM AUTHOR]

Remote synchronization (RS) has recently received an increasing interest in the systems of nonidentical oscillators, but little attention has been paid to the systems of identical oscillators such as the case of human cerebral cortex where RS takes a key role in the functions of brain. Based on the real network of human cerebral cortex, we here show that RS can be also observed in the systems of identical oscillators, provided that appropriate time delay is considered. We interestingly find that RS may appear in different local places of cerebral cortex and thus results in a diversity of patterns, i.e., a new framework of multiple starlike graphs connected by common leaf nodes. To understand its mechanism, we present a model of two starlike graphs connected by common leaf nodes. We further show that the common leaf nodes take a key role for the emergence of RS in the new framework. A theoretical analysis is given. These findings may be helpful to understand the segregation and integration processes of information transmission in brain. [ABSTRACT FROM AUTHOR]

To better understand the diversity of dynamical patterns in the brain network of cerebral cortex, we study the collective behaviors of coupled neurons in complex networks with adaptive coupling. Based on the mutual interaction between dynamics and coupling strength in neuron systems, we let the coupling matrix evolve with the dynamics of neurons. We find that with suitable phase parameters, the coupling matrix will be self-organized into stabilized states and chimera states will be induced. The patterns of these chimera states may be different and abundant, depending on the different network topologies such as the fully connected, random, and scale-free networks. In particular, we apply this adaptive model to the realistic network of cerebral cortex and interestingly find that the adaptive coupling can also induce a diversity of chimera states, which may provide a new insight for the high capability of flexible brain functions. Moreover, we find that the preference of observing chimera states in heterogeneous networks is greater than that in homogeneous networks, and the latter is greater than that in the fully connected network, which may be one of the reasons for the nature to choose the specific sparse and heterogeneous structure of our brain network. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

In this work, we present a complex network model to study thermal transport in the nanotube and nanowire networks, with nodes forming a random network. It is shown that the temperature distribution in complex networks can be manipulated by the degrees of two heat source nodes, and the change of network topology can induce a transition between negative (disassortative) and positive (assortative) degree correlations. A positive degree correlation (assortativity) will enhance thermal transport, in contrast to the uncorrelated networks (zero degree correlation), while a negative degree correlation (disassortativity) will weaken it. The underlying mechanisms have been analyzed, and a possible realization of the model in a nanoscale system is briefly discussed. [ABSTRACT FROM AUTHOR]

Chimera state has been well studied in last decade, and a diversity of chimera states have been revealed in different systems. Recently, its attention has been moved to the neuronal systems, with the purpose of understanding the mechanisms of some brain functions. However, there is no work so far to study the influence of electromagnetic induction on chimera states, which is always with neuronal activities. We here study how the electromagnetic induction influences the chimera states of neuronal networks, especially when it is functioning with the time delay together. We find that for an isolated neuron, the increase in the strength of electromagnetic induction will reduce its firing rate but increase the amplitude of its membrane potential. For a neuronal network, either the time delay or electromagnetic induction can induce chimera states. While their cooperation will result in the robustness of chimera states. This finding may be expected in experiments. [ABSTRACT FROM AUTHOR]

Undoubtedly, the sensory organs of biological systems have been evolved to accurately detect and locate the external stimuli, even if they are very weak. However, the mechanism underlying this ability is still not fully understood. Previously, it had been shown that stochastic resonance may be a good candidate to explain this ability, by which the response of a system to an external signal is amplified by the presence of noise. Recently, it is pointed out that the initial phase diversity in external signals can be also served as a simple and feasible mechanism for weak signal detection or amplification in excitable neurons. We here make a brief review on this progress. We will show that there are two kinds of effects of initial phase diversity: one is the phase disorder, i.e., the initial phases are different and static, and the other is the phase noise, i.e., the initial phases are time-varying like noise. Both cases show that initial phase diversity in subthreshold periodic signals can indeed play a constructive role in the emergence of sustained spiking activity. As initial phase diversity can mimic different arrival times from source signal to sensory organs, these findings may provide a cue for understanding the hunting behaviors of some biological systems. [ABSTRACT FROM AUTHOR]

Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F (IF) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection. [ABSTRACT FROM AUTHOR]

The influence of nitrogen (N) deficiency on tolerance mechanisms in seedlings of two maize hybrids (Xu178 × Huang-C and Xu178 × Zong3) and their parental inbred lines (Xu178, Huang-C and Zong3), which show different nitrogen use efficiency (NUE), was investigated using physiological measurements combined with global proteomics profiling. The root fresh weight and chlorophyll a/ b ratio were reduced significantly in Huang-C (low NUE) under 0.002 mM nitrate treatment for 10 days, whereas no significant change in these two traits was observed in Xu178 (high NUE) under the same treatment compared with N-sufficient treatment. Fifty and 56 protein spots, which showed more than two-fold changes in abundance at P < 0.01 under low-N treatment compared with the control in the roots and leaves, respectively, were analyzed by protein mass spectrometry. Analysis of protein expression patterns revealed that proteins associated with carbohydrate metabolism, nucleotide metabolism, amino acid metabolism, disease/defense, and photosynthesis may be involved in N-deficiency responses. Low-N treatment led to an increased abundance of glutamine synthetase and transcripts in the root to improve the efficiency of N assimilation in the inbred line with HNE, and affected photosynthetic carbon fixation and starch metabolism in the leaves and consequently seedling growth. [ABSTRACT FROM AUTHOR]

Heterosis has been exploited to increase grain yield, quality, and resistance in many crops, and it plays an important role in plant breeding. However, the genetic mechanism of heterosis remains unclear. To dissect the genetic basis of heterosis, a set of 203 single segment substitution lines (SSSLs) was developed, and its test-cross population was used to identify heterotic loci (HL) for plant morphological traits in maize, including plant height (PH), ear height (EH), leaf number (LN), tassel main axis length (TMAL), and tassel branch number (TBN). A total of 41 QTLs and 37 HL were identified for five morphological traits in the test-cross population derived from the 203 SSSLs and the parent, Xu178. Nine HL for PH, nine HL for EH, seven HL for LN, seven HL for TMAL, and five HL for TBN were detected in three different environments, respectively. Eight HL, ph1a, ph1b, ph2, ph5, eh3a, eh3b, eh10, and tmal1b, were simultaneously detected in the three environments. Among the 37 HL, only 10 (27.03 %; for PH, EH, LN, and TBN) had a corresponding QTL (24.39 %) sharing the same chromosomal region. Of all the HL, 21.4 % showed dominance effects, 76.8 % showed over-dominance effects, and only one (1.8 %) showed a partial-dominance effect. This result illustrated that heterosis and performance was controlled by different genetic mechanisms, and over-dominance effects were the main contributors to heterosis for plant-related traits at the single-locus level in maize. [ABSTRACT FROM AUTHOR]

The plumule and coleoptile influence the emergence and vigor of the seedling and demonstrate distinct heterosis during maize ( Zea mays L.) development. Comparative two-dimensional analysis was performed on plumules and coleoptiles from 3.5 days-cultivated seedlings of five widely used hybrids in China and their corresponding parental lines to dissect the genetic mechanism of heterosis. Compared to their parental lines, 64 % (2,127/3,310) of the differentially expressed proteins were nonadditively accumulated in the five hybrids. Up-regulated above the high parent, a similar expression pattern in all five tested hybrids, was the major expression pattern accounting for 68 % (1,446/2,127) nonadditive proteins. Forty-two nonadditive protein spots with significant differences between the hybrids and their parental lines were analyzed by mass spectra. Homology searches separated them into six groups with two abundant functional classes of cell detoxification (33 %) and metabolism (26 %), implying their importance for heterotic manifestation of the different hybrids at 3.5 days-cultivated seedling stage. The differential accumulation and expression of herbicide safener protein 1 in cell detoxification implied that exploration of the molecular mechanism of heterosis should be studied in a systematic network. Four potential functional polymorphisms were identified in SBP1 gene providing possible interpretation for the differential expression of SBP1 at transcriptional and translational levels. [ABSTRACT FROM AUTHOR]

Polysaccharides based polyelectrolyte complex nanoparticles (PCNs) intended for use in the delivery of macromolecules were prepared by the self-assembly of deoxycholic acid hydrophobically modified chitosan (CS-DCA) core and then coated with sodium alginate (ALG) shell. The CS-DCA capable of forming nano-sized self-aggregates in medium was prepared by the grafting of DCA to CS. In order to increase the stability of nanoparticles and prevent burst release of drug in bloodstream, polyanionic ALG was coated on the surface of positively charged CS-DCA nanoparticles to form PCNs. Dynamic light scattering results revealed that the mean diameter of the PCNs was about 330 nm, larger than that of uncoated nanoparticles (~150 nm). The zeta potential was big enough to keep the stability of PCNs (−28 mV); no size change was found even upon 1 month storage. Bovine serum albumin could be easily incorporated into the PCNs with encapsulation efficiency (>44 %) and keep a sustained manner without burst release when exposed to PBS (pH 7.4) at 37 °C. These results suggested that PCNs may be a promising drug carrier for a prolonged and sustained delivery in the bloodstream. [ABSTRACT FROM AUTHOR]

Phospholipids in the cell membranes of all eukaryotic cells contain phosphatidyl choline (PC) as the headgroup. Here we show that hyperbranched polyglycerols (HPGs) decorated with the 'PC-inverse' choline phosphate (CP) in a polyvalent fashion can electrostatically bind to a variety of cell membranes and to PC-containing liposomes, the binding strength depending on the number density of CP groups per macromolecule. We also show that HPG-CPs can cause cells to adhere with varying affinity to other cells, and that binding can be reversed by subsequent exposure to low molecular weight HPGs carrying small numbers of PCs. Moreover, PC-rich membranes adsorb and rapidly internalize fluorescent HPG-CP but not HPG-PC molecules, which suggests that HPG-CPs could be used as drug-delivery agents. CP-decorated polymers should find broad use, for instance as tissue sealants and in the self-assembly of lipid nanostructures. [ABSTRACT FROM AUTHOR]

In many animals and insects, hearing is very acute to the faintest of sounds; the underlying mechanism can be explained by self-tuning. Recently, signal response amplification has been shown to be implemented through networks exhibiting scale-free topology, which has potential applications in artificial information processing systems and devices. We review in this paper the main results obtained in networked double-well oscillators and briefly discuss future research directions. [ABSTRACT FROM AUTHOR]

In the field, asynchrony of flowering and silk for male and female plants always occurs under different abiotic stresses, and reduces yield in the seed industry. Under stress conditions, a female parent with a short duration of silk emergence and a long time of silk receptivity can decrease the risk of the asynchrony for flowering and silking in the process of hybrid seed production. For dissecting the genetic basis of the related traits of flowering and silk in maize, a set of recombinant inbred lines (RIL) was evaluated at three different environments. Correlation analysis showed that anthesis silk interval (ASI) had a significant positive relationship with day to silk (DTS) and duration of silk emergence (DSE). Silk receptivity (SR) had a significant negative correlation to DTS, DSE, and ASI. This implied that the female parent with a long DTS, DSE, and ASI could easy lose its SR, and required synchrony of pollen shedding for the male parent in the field. A total of sixteen different QTLs were identified for the seven traits of flowering and silking traits, including three QTLs for day to tassel (DTT), two for day to pollen (DTP), two for duration of pollen shedding (DPS), three for SR, two for DTS, two for DSE, and two for ASI. The QTLs detected for the related traits of flowering and silk could select ideal traits for male and female parents to raise the yield in the seed industry under certain stress conditions. [ABSTRACT FROM AUTHOR]

Based on the mean-field approach, epidemic spreading has been well studied. However, the mean-field approach cannot show the detailed contagion process, which is important in the control of epidemic. To fill this gap, we present a novel approach to study how the topological structure of complex network influences the concrete process of epidemic spreading. After transforming the network structure into hierarchical layers, we introduce a set of new parameters, i.e., the average fractions of degree for outgoing, ingoing, and remaining in the same layer, to describe the infection process. We find that this set of parameters are closely related to the degree distribution and the clustering coefficient but are more convenient than them in describing the process of epidemic spreading. Moreover, we find that the networks with exponential distribution have slower spreading speed than the networks with power-law degree distribution. Numerical simulations have confirmed the theoretical predictions. [ABSTRACT FROM AUTHOR]

In this study, we describe a novel ecological self-incompatibility (SI) line HE97 in maize. The main environmental factors influencing the inbred line characteristics were identified through field sowing trials during a two-year study period (2001 and 2002). The results showed that daily minimum temperature had the greatest effect on floral morphology and breeding system of the SI line. In staminate floret differentiation, when the daily minimum temperature exceeded 24°C, the line exhibited complete self-compatibility; however SI was observed when the daily minimum temperature was below 20°C. Therefore, we characterized the line as exhibiting thermo-sensitive genic self-incompatibility (TGSI). A set of F and F populations, derived from the inbred lines HE97 and Z58, were evaluated for two years to elucidate the TGSI line patterns of inheritance. Classical genetic analyses and QTL mapping results revealed that HE97 self-incompatibility was governed by a single allele, named here as tgsi1. The tgsi1 gene was mapped to chromosome 2 between SSR markers nc131 and bnlg1633, with a distance of 2.40 cM from nc131 and 2.44 cM from bnlg1633. [ABSTRACT FROM AUTHOR]

The biomimetic apatite coating process was adopted to modify poly(L-lactide) (PLLA) surfaces with osteoblasts-like cell compatibility. The apatite coating was formed on the pre-hydrolyzed PLLA film and scaffold surfaces by incubating in simulated body fluid (SBF). Scanning electron microscopy and energy dispersive X-ray analyzer were utilized to characterize the composition and the structure of the apatite coating. The cytocompatibility of the modified PLLA films was investigated by testing osteoblast-like attachment, proliferation, alkaline phosphatase (ALP) activity, and cell cycle. Subsequently, the modified PLLA scaffolds were co-cultured with the osteoblasts-like in vitro and subcutaneously implanted into nude mice. The experimental results showed that the formed apatite had a nano-sized particle and matrix configuration. The surface modification of PLLA with apatite coating significantly promoted osteoblast-like compatibility. After a four-week culture in vivo, no significant inflammatory signs were observed in the implanted regions and osteoblast-like congeries with bone-like structure began to form in the scaffolds. The positive results of this study suggest a good way to produce desirable PLLA biomaterials for bone tissue engineering. [ABSTRACT FROM AUTHOR]

Based on the data of cerebral cortex, we present a two-layered brain network model of coupled neurons where the two layers represent the left and right hemispheres of cerebral cortex, respectively, and the links between the two layers represent the inter-couplings through the corpus callosum. By this model we show that abundant patterns of synchronization can be observed, especially the chimera state, depending on the parameters of system such as the coupling strengths and coupling phase. Further, we extend the model to a more general two-layered network to better understand the mechanism of the observed patterns, where each hemisphere of cerebral cortex is replaced by a highly clustered subnetwork. We find that the number of inter-couplings is another key parameter for the emergence of chimera states. Thus, the chimera states come from a matching between the structure parameters such as the number of inter-couplings and clustering coefficient etc and the dynamics parameters such as the intra-, inter-coupling strengths and coupling phase etc. A brief theoretical analysis is provided to explain the borderline of synchronization. These findings may provide helpful clues to understand the mechanism of brain functions. [ABSTRACT FROM AUTHOR]

Macroscopic rhythms are often signatures of healthy functioning in living organisms, but they are still poorly understood on their microscopic bases. Globally interacting oscillators with heterogeneous couplings are here considered. Thorough theoretical and numerical analyses indicate the presence of multiple phase transitions between different collective states, with regions of bi-stability. Novel coherent phases are unveiled, and evidence is given of the spontaneous emergence of macroscopic rhythms where oscillators’ phases are always found to be self-organized as in Bellerophon states, i.e. in multiple clusters with quantized values of their average frequencies. Due to their rather unconditional appearance, the circumstance is paved that the Bellerophon states grasp the microscopic essentials behind collective rhythms in more general systems of interacting oscillators. [ABSTRACT FROM AUTHOR]

The study of synchronization in generalized Kuramoto models has witnessed an intense boost in the last decade. Several collective states were discovered, such as partially synchronized, chimera, π or traveling wave states. We here consider two populations of globally coupled conformist and contrarian oscillators (with different, randomly distributed frequencies), and explore the effects of a frequency-dependent distribution of the couplings on the collective behaviour of the system. By means of linear stability analysis and mean-field theory, a series of exact solutions is extracted describing the critical points for synchronization, as well as all the emerging stationary coherent states. In particular, a novel non-stationary state, here named as Bellerophon state, is identified which is essentially different from all other coherent states previously reported in the Literature. A robust verification of the rigorous predictions is supported by extensive numerical simulations. [ABSTRACT FROM AUTHOR]

The study of recurrent epidemic outbreaks has been attracting great attention for decades, but its underlying mechanism is still under debate. Based on a large number of real data from different cities, we find that besides the seasonal periodic outbreaks of influenza, there are also non-periodic outbreaks, i.e. non-seasonal or non-annual behaviors. To understand how the non-periodicity shows up, we present a network model of SIRS epidemic with both time-dependent infection rate and a small possibility of persistent epidemic seeds, representing the influences from the larger annual variation of environment and the infection generated spontaneously in nature, respectively. Our numerical simulations reveal that the model can reproduce the non-periodic outbreaks of recurrent epidemics with the main features of real influenza data. Further, we find that the recurrent outbreaks of epidemic depend not only on the infection rate but also on the density of susceptible agents, indicating that they are both the necessary conditions for the recurrent epidemic patterns with non-periodicity. A theoretical analysis based on Markov dynamics is presented to explain the numerical results. This finding may be of significance to the control of recurrent epidemics. [ABSTRACT FROM AUTHOR]

The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller's viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading. [ABSTRACT FROM AUTHOR]