Resilience and Controllability of Dynamic Collective Behaviors

The network paradigm is used to gain insight into the structural root causes of the resilience of consensus in dynamic collective behaviors, and to analyze the controllability of the swarm dynamics. Here we devise the dynamic signaling network which is the information transfer channel underpinning the swarm dynamics of the directed interagent connectivity based on a topological neighborhood of interactions. The study of the connectedness of the swarm signaling network reveals the profound relationship between group size and number of interacting neighbors, which is found to be in good agreement with field observations on flock of starlings [Ballerini et al. (2008) Proc. Natl. Acad. Sci. USA, 105: 1232]. Using a dynamical model, we generate dynamic collective behaviors enabling us to uncover that the swarm signaling network is a homogeneous clustered small-world network, thus facilitating emergent outcomes if connectedness is maintained. Resilience of the emergent consensus is tested by introducing exogenous environmental noise, which ultimately stresses how deeply intertwined are the swarm dynamics in the physical and network spaces. The availability of the signaling network allows us to analytically establish for the first time the number of driver agents necessary to fully control the swarm dynamics.     

A Hybrid Search Algorithm for Swarm Robots Searching in an Unknown Environment

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.     

Morphological Evolution of Physical Robots through Model-Free Phenotype Development

Artificial evolution of physical systems is a stochastic optimization method in which physical machines are iteratively adapted to a target function. The key for a meaningful design optimization is the capability to build variations of physical machines through the course of the evolutionary process. The optimization in turn no longer relies on complex physics models that are prone to the reality gap, a mismatch between simulated and real-world behavior. We report model-free development and evaluation of phenotypes in the artificial evolution of physical systems, in which a mother robot autonomously designs and assembles locomotion agents. The locomotion agents are automatically placed in the testing environment and their locomotion behavior is analyzed in the real world. This feedback is used for the design of the next iteration. Through experiments with a total of 500 autonomously built locomotion agents, this article shows diversification of morphology and behavior of physical robots for the improvement of functionality with limited resources.     

Evolution of Sirenian Pachyosteosclerosis,a Model-case for the Study of Bone Structure in Aquatic Tetrapods

Osteosclerosis, or inner bone compaction, and pachyostosis, or outer hyperplasy of bone cortices (swollen bones), are typical features of tetrapods secondarily adapted to life in water. These peculiarities are spectacularly exemplified by the ribs of extant and extinct Sirenia. Sea cows are thus the best model for studying this kind of bone structural specializations. In order to document how these features differentiated during sirenian evolution, the ribs of 15 species, from the most basal form (Pezosiren portelli) up to extant taxa, were studied, and compared to those of other mammalian species from both morphometric and histological points of view. Pachyostosis was the first of these two specializations to occur, by the middle of the Eocene, and is a basal feature of the Sirenia. However, it subsequently regressed in some taxa that do not exhibit hyperplasic rib cortices. Osteosclerosis was only incipient in P. portelli. Its full development occurred later, by the end of the Eocene. These two structural specializations of bone are variably pronounced in extinct and extant sirenians, and relatively independent from each other, although frequently associated. They are possibly due to similar heterochronic mechanisms bearing on the timing of osteoblast activity. These results are discussed with respect to the functional constraints of locomotion in water.     

A Method for Simulating Signal Evolution Using Real Animals

We studied response biases to visual stimulation using a new experimental technique. The subjects (hens, Gallus gallus domesticus) were confronted with several rewarding and non‐rewarding patterns on a computer screen. In contrast with standard discrimination tasks the rewarding patterns were not identical and varied in a dimension differentiating them from the non‐rewarding patterns. The rewarding patterns changed in response to hens' biases in selection of patterns. The aim of the study was to examine the possibility of receivers being a driving force in signal evolution. In one of the experiments a clear‐cut result was obtained. During the course of the experiment the rewarding patterns became gradually more different from the non‐rewarding one, a result expected from theoretical studies of the effect of response bias in signal evolution. A second similar experiment was less conclusive, with ceiling and floor effects influencing the results.     

Laser-Driven Hybridization of a Surface Plasmon Resonance Collective Mode in a Monolayer of Silver Nanoparticles

Plasmonics - Laser-driven hybridization of a collective surface plasmon mode of a monolayer of silver nanoparticles has been studied as a function of irradiation power density. Two collective...     

Matching Rules for Collective Behaviors on Complex Networks: Optimal Configurations for Vibration Frequencies of Networked Harmonic Oscillators

The structure-dynamics-function has become one of central problems in modern sciences, and it is a great challenge to unveil the organization rules for different dynamical processes on networks. In this work, we study the vibration spectra of the classical mass spring model with different masses on complex networks, and pay our attention to how the mass spatial configuration influences the second-smallest vibrational frequency () and the largest one (). For random networks, we find that becomes maximal and becomes minimal if the node degrees are point-to-point-positively correlated with the masses. In these cases, we call it point-to-point matching. Moreover, becomes minimal under the condition that the heaviest mass is placed on the lowest-degree vertex, and is maximal as long as the lightest mass is placed on the highest-degree vertex, and in both cases all other masses can be arbitrarily settled. Correspondingly, we call it single-point matching. These findings indicate that the matchings between the node dynamics (parameter) and the node position rule the global systems dynamics, and sometimes only one node is enough to control the collective behaviors of the whole system. Therefore, the matching rules might be the common organization rules for collective behaviors on networks.     

Convergent Evolution of Mechanically Optimal Locomotion in Aquatic Invertebrates and Vertebrates

Examples of animals evolving similar traits despite the absence of that trait in the last common ancestor, such as the wing and camera-type lens eye in vertebrates and invertebrates, are called cases of convergent evolution. Instances of convergent evolution of locomotory patterns that quantitatively agree with the mechanically optimal solution are very rare. Here, we show that, with respect to a very diverse group of aquatic animals, a mechanically optimal method of swimming with elongated fins has evolved independently at least eight times in both vertebrate and invertebrate swimmers across three different phyla. Specifically, if we take the length of an undulation along an animal’s fin during swimming and divide it by the mean amplitude of undulations along the fin length, the result is consistently around twenty. We call this value the optimal specific wavelength (OSW). We show that the OSW maximizes the force generated by the body, which also maximizes swimming speed. We hypothesize a mechanical basis for this optimality and suggest reasons for its repeated emergence through evolution.     

程海水生植被现状及其演变趋势

近20年来,程海水生植物种类和群落类型进一步趋于简单化,水生植被覆盖度由24％～75％变为0．2％～85％,分布最大水深虽由4．5m延伸至5．5m,分布面积却由527．8hm2缩减为73．05hm2,资源蕴藏量由4766吨降低至314．53吨。分析认为：程海南部大面积适生生境破坏、水质污染、水体富营养化、不合理放养草鱼是加剧其水生植被衰退的主要原因。提出了恢复南部湿地、削减入湖污染物、禁止投放草鱼、控制水质污染和水体富营养化等保护对策。     

Collective Dynamics of Belief Evolution under Cognitive Coherence and Social Conformity

Human history has been marked by social instability and conflict, often driven by the irreconcilability of opposing sets of beliefs, ideologies, and religious dogmas. The dynamics of belief systems has been studied mainly from two distinct perspectives, namely how cognitive biases lead to individual belief rigidity and how social influence leads to social conformity. Here we propose a unifying framework that connects cognitive and social forces together in order to study the dynamics of societal belief evolution. Each individual is endowed with a network of interacting beliefs that evolves through interaction with other individuals in a social network. The adoption of beliefs is affected by both internal coherence and social conformity. Our framework may offer explanations for how social transitions can arise in otherwise homogeneous populations, how small numbers of zealots with highly coherent beliefs can overturn societal consensus, and how belief rigidity protects fringe groups and cults against invasion from mainstream beliefs, allowing them to persist and even thrive in larger societies. Our results suggest that strong consensus may be insufficient to guarantee social stability, that the cognitive coherence of belief-systems is vital in determining their ability to spread, and that coherent belief-systems may pose a serious problem for resolving social polarization, due to their ability to prevent consensus even under high levels of social exposure. We argue that the inclusion of cognitive factors into a social model could provide a more complete picture of collective human dynamics.     

Molecular Recognition by a Polymorphic Cell Surface Receptor Governs Cooperative Behaviors in Bacteria

Cell-cell recognition is a fundamental process that allows cells to coordinate multicellular behaviors. Some microbes, such as myxobacteria, build multicellular fruiting bodies from free-living cells. However, how bacterial cells recognize each other by contact is poorly understood. Here we show that myxobacteria engage in recognition through interactions between TraA cell surface receptors, which leads to the fusion and exchange of outer membrane (OM) components. OM exchange is shown to be selective among 17 environmental isolates, as exchange partners parsed into five major recognition groups. TraA is the determinant of molecular specificity because: (i) exchange partners correlated with sequence conservation within its polymorphic PA14-like domain and (ii) traA allele replacements predictably changed partner specificity. Swapping traA alleles also reprogrammed social interactions among strains, including the regulation of motility and conferred immunity from inter-strain killing. We suggest that TraA helps guide the transition of single cells into a coherent bacterial community, by a proposed mechanism that is analogous to mitochondrial fusion and fission cycling that mixes contents to establish a homogenous population. In evolutionary terms, traA functions as a rare greenbeard gene that recognizes others that bear the same allele to confer beneficial treatment.     

The Evolution of Collective Restraint: Policing and Obedience among Non-conjugative Plasmids

The repression of competition by mechanisms of policing is now recognized as a major force in the maintenance of cooperation. General models on the evolution of policing have focused on the interplay between individual competitiveness and mutual policing, demonstrating a positive relationship between within-group diversity and levels of policing. We expand this perspective by investigating what is possibly the simplest example of reproductive policing: copy number control (CNC) among non-conjugative plasmids, a class of extra-chromosomal vertically transmitted molecular symbionts of bacteria. Through the formulation and analysis of a multi-scale dynamical model, we show that the establishment of stable reproductive restraint among plasmids requires the co-evolution of two fundamental plasmid traits: policing, through the production of plasmid-coded trans-acting replication inhibitors, and obedience, expressed as the binding affinity of plasmid-specific targets to those inhibitors. We explain the intrinsic replication instabilities that arise in the absence of policing and we show how these instabilities are resolved by the evolution of copy number control. Increasing levels of policing and obedience lead to improvements in group performance due to tighter control of local population size (plasmid copy number), delivering benefits both to plasmids, by reducing the risk of segregational loss and to the plasmid-host partnership, by increasing the rate of cell reproduction, and therefore plasmid vertical transmission.     

Evolution of Swarm Communication in Eusocial Wasps (Hymenoptera: Vespidae)

Eusocial paper wasps, yellowjackets, and hornets (Vespidae) exhibit two modes of colony foundation, primitively eusocial independent founders and advanced eusocial swarm founders. Unlike independent founders, swarmfounding wasps require a means of social communication to coordinate the movement of colony members between nest sites. We employed a phylogeny of paper wasps, yellowjackets, and hornets to test for patterns of correlated evolution between the mode of colony foundation and the presence of sternal exocrine glands. We also reviewed data on worker actions during swarming to determine whether swarm communication behavior was dependent upon gland possession and whether communicative behavior was shared among swarm-founding species. We did not find evidence for an association of sternal glands with swarm founding. Although sternal gland presence differed among swarm-founding species, worker behavior during swarming showed little variation. Workers of nearly all swarm-founding species rub their gasters on objects along swarm routes, independently of the occurrence of sternal glands. Widespread gastral rubbing indicates the use of swarm emigration trail pheromones from a diversity of glandular sources. Transitions from independent to swarm founding have been achieved via diverse pheromonal mechanisms in the Vespidae, while worker communicative behavior is either highly conserved or convergent.     

Aquatic insects as a vector for Mycobacterium ulcerans

Mycobacterium ulcerans is an emerging environmental pathogen which causes chronic skin ulcers (i.e., Buruli ulcer) in otherwise healthy humans living in tropical countries, particularly those in Africa. In spite of epidemiological and PCR data linking M. ulcerans to water, the mode of transmission of this organism remains elusive. To determine the role of aquatic insects in the transmission of M. ulcerans, we have set up an experimental model with aquariums that mimic aquatic microenvironments. We report that M. ulcerans may be transmitted to laboratory mice by the bite of aquatic bugs (Naucoridae) that are infected with this organism. In addition, M. ulcerans appears to be localized exclusively within salivary glands of these insects, where it can both survive and multiply without causing any observable damage in the insect tissues. Subsequently, we isolated M. ulcerans from wild aquatic insects collected from a zone in the Daloa region of Ivory Coast where Buruli ulcer is endemic. Taken together, these results point to aquatic insects as a possible vector of M. ulcerans.     

Aquatic Insects as a Vector for Mycobacterium ulcerans

Mycobacterium ulcerans is an emerging environmental pathogen which causes chronic skin ulcers (i.e., Buruli ulcer) in otherwise healthy humans living in tropical countries, particularly those in Africa. In spite of epidemiological and PCR data linking M. ulcerans to water, the mode of transmission of this organism remains elusive. To determine the role of aquatic insects in the transmission of M. ulcerans, we have set up an experimental model with aquariums that mimic aquatic microenvironments. We report that M. ulcerans may be transmitted to laboratory mice by the bite of aquatic bugs (Naucoridae) that are infected with this organism. In addition, M. ulcerans appears to be localized exclusively within salivary glands of these insects, where it can both survive and multiply without causing any observable damage in the insect tissues. Subsequently, we isolated M. ulcerans from wild aquatic insects collected from a zone in the Daloa region of Ivory Coast where Buruli ulcer is endemic. Taken together, these results point to aquatic insects as a possible vector of M. ulcerans.     

Coordinated Evolution of Influenza A Surface Proteins

The surface proteins hemagglutinin (HA) and neuraminidase (NA) of human influenza A virus evolve under selection pressures to escape adaptive immune responses and antiviral drug treatments. In addition to these external selection pressures, some mutations in HA are known to affect the adaptive landscape of NA, and vice versa, because these two proteins are physiologically interlinked. However, the extent to which evolution of one protein affects the evolution of the other one is unknown. Here we develop a novel phylogenetic method for detecting the signatures of such genetic interactions between mutations in different genes – that is, inter-gene epistasis. Using this method, we show that influenza surface proteins evolve in a coordinated way, with mutations in HA affecting subsequent spread of mutations in NA and vice versa, at many sites. Of particular interest is our finding that the oseltamivir-resistance mutations in NA in subtype H1N1 were likely facilitated by prior mutations in HA. Our results illustrate that the adaptive landscape of a viral protein is remarkably sensitive to its genomic context and, more generally, that the evolution of any single protein must be understood within the context of the entire evolving genome.