Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.

Science.gov (United States)

Weber, Bruce H

2011-03-01

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. Copyright © 2010 Elsevier Ltd. All rights reserved.

Early days in complex dynamics a history of complex dynamics in one variable during 1906-1942

CERN Document Server

Alexander, Daniel S; Rosa, Alessandro

2011-01-01

The theory of complex dynamics, whose roots lie in 19th-century studies of the iteration of complex function conducted by Kœnigs, Schröder, and others, flourished remarkably during the first half of the 20th century, when many of the central ideas and techniques of the subject developed. This book by Alexander, Iavernaro, and Rosa paints a robust picture of the field of complex dynamics between 1906 and 1942 through detailed discussions of the work of Fatou, Julia, Siegel, and several others. A recurrent theme of the authors' treatment is the center problem in complex dynamics. They present its complete history during this period and, in so doing, bring out analogies between complex dynamics and the study of differential equations, in particular, the problem of stability in Hamiltonian systems. Among these analogies are the use of iteration and problems involving small divisors which the authors examine in the work of Poincaré and others, linking them to complex dynamics, principally via the work of Samuel...

Management of complex dynamical systems

Science.gov (United States)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

An enhanced dynamic model of battery using genetic algorithm suitable for photovoltaic applications

International Nuclear Information System (INIS)

Blaifi, S.; Moulahoum, S.; Colak, I.; Merrouche, W.

2016-01-01

Highlights: • We proposed a developed dynamic battery model suitable for photovoltaic systems. • We used genetic algorithm optimization method to find parameters that gives minimized error. • The validation was carried out with real measurements from stand-alone photovoltaic string. - Abstract: Modeling of batteries in photovoltaic systems has been a major issue related to the random dynamic regime imposed by the changes of solar irradiation and ambient temperature added to the complexity of battery electrochemical and electrical behaviors. However, various approaches have been proposed to model the battery behavior by predicting from detailed electrochemical, electrical or analytical models to high-level stochastic models. In this paper, an improvement of dynamic electrical battery model is proposed by automatic parameter extraction using genetic algorithm in order to give usefulness and future implementation for practical application. It is highlighted that the enhancement of 21 values of the parameters of CEIMAT model presents a good agreement with real measurements for different modes like charge or discharge and various conditions.

Genetic basis of a cognitive complexity metric

NARCIS (Netherlands)

Hansell, Narelle K; Halford, Graeme S; Andrews, Glenda; Shum, David H K; Harris, Sarah E; Davies, Gail; Franic, Sanja; Christoforou, Andrea; Zietsch, Brendan; Painter, Jodie; Medland, Sarah E; Ehli, Erik A; Davies, Gareth E; Steen, Vidar M; Lundervold, Astri J; Reinvang, Ivar; Montgomery, Grant W; Espeseth, Thomas; Hulshoff Pol, Hilleke E; Starr, John M; Martin, Nicholas G; Le Hellard, Stephanie; Boomsma, Dorret I; Deary, Ian J; Wright, Margaret J

2015-01-01

Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using

Genetic Basis of a Cognitive Complexity Metric

NARCIS (Netherlands)

Hansell, N.K.; Halford, G.S.; Andrews, G.; Shum, D.H.K.; Harris, S.E.; Davies, G.; Franic, S.; Christoforou, A.; Zietsch, B.; Painter, J.; Medland, S.E.; Ehli, E.A.; Davies, G.E.; Steen, V.M.; Lundervold, A.J.; Reinvang, I.; Montgomery, G.W.; Espeseth, T.; Hulshoff Pol, H.E.; Starr, J.M.; Martin, N.G.; Le Hellard, S.; Boomsma, D.I.; Deary, I.J.; Wright, M.J.

2015-01-01

Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

Science.gov (United States)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Complexity in Dynamical Systems

Science.gov (United States)

Moore, Cristopher David

The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

Symbolic dynamics and description of complexity

International Nuclear Information System (INIS)

Hao Bailin.

1992-10-01

Symbolic dynamics provides a general framework to describe complexity of dynamical behaviour. After a discussion of the state of the filed special emphasis will be made on the role of transfer matrix (the Stefan matrix) both in deriving the grammar from known symbolic dynamics and in extracting the rules from experimental data. The block structure of the Stefan matrix may serve as another indicator of complexity of the associated dynamics. (author). 33 refs, 6 figs

Ethical and legal issues arising from complex genetic disorders. DOE final report

Energy Technology Data Exchange (ETDEWEB)

Andrews, Lori

2002-10-09

The project analyzed the challenges raised by complex genetic disorders in genetic counselling, for clinical practice, for public health, for quality assurance, and for protection against discrimination. The research found that, in some settings, solutions created in the context of single gene disorders are more difficult to apply to complex disorders. In other settings, the single gene solutions actually backfired and created additional problems when applied to complex genetic disorders. The literature of five common, complex genetic disorders--Alzheimer's, asthma, coronary heart disease, diabetes, and psychiatric illnesses--was evaluated in depth.

Carney complex review: Genetic features.

Science.gov (United States)

Bosco Schamun, María Belén; Correa, Ricardo; Graffigna, Patricia; de Miguel, Valeria; Fainstein Day, Patricia

2018-01-01

Carney complex is a multiple neoplasia syndrome having endocrine and non-endocrine manifestations. Diagnostic criteria include myxoma, lentigines, and primary pigmented nodular adrenocortical disease, amongst other signs/symptoms. In most cases it is an autosomal dominant disease, and diagnosis therefore requires study and follow-up of the family members. Inactivating mutations of the PRKAR1A gene were identified as the main cause of the disease, although since 2015 other disease-related genes, including PRKACA and PRKACB activating mutations, have also been related with Carney complex. This review will address the genetic aspects related to Carney complex. Copyright © 2017 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.

Dynamics in Complex Coacervates

Science.gov (United States)

Perry, Sarah

Understanding the dynamics of a material provides detailed information about the self-assembly, structure, and intermolecular interactions present in a material. While rheological methods have long been used for the characterization of complex coacervate-based materials, it remains a challenge to predict the dynamics for a new system of materials. Furthermore, most work reports only qualitative trends exist as to how parameters such as charge stoichiometry, ionic strength, and polymer chain length impact self-assembly and material dynamics, and there is little information on the effects of polymer architecture or the organization of charges within a polymer. We seek to link thermodynamic studies of coacervation phase behavior with material dynamics through a carefully-controlled, systematic study of coacervate linear viscoelasticity for different polymer chemistries. We couple various methods of characterizing the dynamics of polymer-based complex coacervates, including the time-salt superposition methods developed first by Spruijt and coworkers to establish a more mechanistic strategy for comparing the material dynamics and linear viscoelasticity of different systems. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support of this research.

Dynamic complexity: plant receptor complexes at the plasma membrane.

Science.gov (United States)

Burkart, Rebecca C; Stahl, Yvonne

2017-12-01

Plant receptor complexes at the cell surface perceive many different external and internal signalling molecules and relay these signals into the cell to regulate development, growth and immunity. Recent progress in the analyses of receptor complexes using different live cell imaging approaches have shown that receptor complex formation and composition are dynamic and take place at specific microdomains at the plasma membrane. In this review we focus on three prominent examples of Arabidopsis thaliana receptor complexes and how their dynamic spatio-temporal distribution at the PM has been studied recently. We will elaborate on the newly emerging concept of plasma membrane microdomains as potential hubs for specific receptor complex assembly and signalling outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Complex dynamics

CERN Document Server

Carleson, Lennart

1993-01-01

Complex dynamics is today very much a focus of interest. Though several fine expository articles were available, by P. Blanchard and by M. Yu. Lyubich in particular, until recently there was no single source where students could find the material with proofs. For anyone in our position, gathering and organizing the material required a great deal of work going through preprints and papers and in some cases even finding a proof. We hope that the results of our efforts will be of help to others who plan to learn about complex dynamics and perhaps even lecture. Meanwhile books in the field a. re beginning to appear. The Stony Brook course notes of J. Milnor were particularly welcome and useful. Still we hope that our special emphasis on the analytic side will satisfy a need. This book is a revised and expanded version of notes based on lectures of the first author at UCLA over several \\Vinter Quarters, particularly 1986 and 1990. We owe Chris Bishop a great deal of gratitude for supervising the production of cour...

Complex dynamical invariants for two-dimensional complex potentials

Indian Academy of Sciences (India)

Abstract. Complex dynamical invariants are searched out for two-dimensional complex poten- tials using rationalization method within the framework of an extended complex phase space characterized by x = x1 + ip3, y = x2 + ip4, px = p1 + ix3, py = p2 + ix4. It is found that the cubic oscillator and shifted harmonic oscillator ...

Dynamic conservation of forest genetic resources in 33 European countries

NARCIS (Netherlands)

Lefevre, F.; Koskela, J.; Hubert, J.; Kraigher, H.; Longauer, R.; Olrik, D.C.; Vries, de S.M.G.

2013-01-01

Dynamic conservation of forest genetic resources (FGR) means maintaining the genetic diversity of trees within an evolutionary process and allowing generation turnover in the forest. We assessed the network of forests areas managed for the dynamic conservation of FGR (conservation units) across

Genetic complexity underlying hybrid male sterility in Drosophila.

OpenAIRE

Sawamura, Kyoichi; Roote, John; Wu, Chung-I; Yamamoto, Masa-Toshi

2004-01-01

Recent genetic analyses of closely related species of Drosophila have indicated that hybrid male sterility is the consequence of highly complex synergistic effects among multiple genes, both conspecific and heterospecific. On the contrary, much evidence suggests the presence of major genes causing hybrid female sterility and inviability in the less-related species, D. melanogaster and D. simulans. Does this contrast reflect the genetic distance between species? Or, generally, is the genetic b...

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.

Science.gov (United States)

Yang, Shengxiang

2008-01-01

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.

Dynamic traffic assignment : genetic algorithms approach

Science.gov (United States)

1997-01-01

Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

Sex differences in genetic architecture of complex phenotypes?

Directory of Open Access Journals (Sweden)

Jacqueline M Vink

Full Text Available We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA studies of complex phenotypes. If different genes play a role across sex, GWA studies should consider the effect of genetic variants separately in men and women, which affects statistical power. Twin and family studies offer an opportunity to compare resemblance between opposite-sex family members to the resemblance between same-sex relatives, thereby presenting a test of quantitative and qualitative sex differences in the genetic architecture of complex traits. We analyzed data on lifestyle, personality, psychiatric disorder, health, growth, development and metabolic traits in dizygotic (DZ same-sex and opposite-sex twins, as these siblings are perfectly matched for age and prenatal exposures. Sample size varied from slightly over 300 subjects for measures of brain function such as EEG power to over 30,000 subjects for childhood psychopathology and birth weight. For most phenotypes, sample sizes were large, with an average sample size of 9027 individuals. By testing whether the resemblance in DZ opposite-sex pairs is the same as in DZ same-sex pairs, we obtain evidence for genetic qualitative sex-differences in the genetic architecture of complex traits for 4% of phenotypes. We conclude that for most traits that were examined, the current evidence is that same the genes are operating in men and women.

Genetics of simple and complex host-parasite interactions

International Nuclear Information System (INIS)

Sidhu, G.S.; Webster, J.M.

1977-01-01

In nature a host plant can be viewed as a miniature replica of an ecological system where true and incidental parasites share the same habitat. Consequently, they influence each other's presence directly by interspecific interaction, and indirectly by inducing changes in the host's physiology and so form disease complexes. Since all physiological phenomena have their counterpart in the respective genetic systems of interacting organisms, valuable genetic information can be derived from the analysis of complex parasitic systems. Disease complexes may be classified according to the nature of interaction between various parasites on the same host. One parasite may nullify the host's resistance to another (e.g. Tomato - Meloidogyne incognita + Fusarium oxysporum lycopersici system). Conversely, a parasite may invoke resistance in the host against another parasite (e.g. Tomato - Fusarium oxysporum lycopersici + Verticillium albo atrum system). From the study of simple parasitic systems we know that resistance versus susceptibility against a single parasite is normally monogenically controlled. However, when more than one parasite interacts to invoke or nullify each other's responses on the same host plant, the genetic results suggest epistatic ratios. Nevertheless, epistatic ratios have been obtained also from simple parasitic systems owing to gene interaction. The epistatic ratios obtained from complex and simple parasitic systems are contrasted and compared. It is suggested that epistatic ratios obtained from simple parasitic systems may, in fact, be artifacts resulting from complex parasitic associations that often occur in nature. Polygenic inheritance and the longevity of a cultivar is also discussed briefly in relation to complex parasitic associations. Induced mutations can play a significant role in the study of complex parasitic associations, and thus can be very useful in controlling plant diseases

The geography of malaria genetics in the Democratic Republic of Congo: A complex and fragmented landscape

Science.gov (United States)

Carrel, Margaret; Patel, Jaymin; Taylor, Steve M.; Janko, Mark; Mwandagalirwa, Melchior Kashamuka; Tshefu, Antoinette K.; Escalante, Ananias A.; McCollum, Andrea; Alam, Md Tauqeer; Udhayakumar, Venkatachalam; Meshnick, Steven; Emch, Michael

2014-01-01

Understanding how malaria parasites move between populations is important, particularly given the potential for malaria to be reintroduced into areas where it was previously eliminated. We examine the distribution of malaria genetics across seven sites within the Democratic Republic of Congo (DRC) and two nearby countries, Ghana and Kenya, in order to understand how the relatedness of malaria parasites varies across space, and whether there are barriers to the flow of malaria parasites within the DRC or across borders. Parasite DNA was retrieved from dried blood spots from 7 Demographic and Health Survey sample clusters in the DRC. Malaria genetic characteristics of parasites from Ghana and Kenya were also obtained. For each of 9 geographic sites (7 DRC, 1 Ghana and 1 Kenya), a pair-wise RST statistic was calculated, indicating the genetic distance between malaria parasites found in those locations. Mapping genetics across the spatial extent of the study area indicates a complex genetic landscape, where relatedness between two proximal sites may be relatively high (RST > 0.64) or low (RST < 0.05), and where distal sites also exhibit both high and low genetic similarity. Mantel’s tests suggest that malaria genetics differ as geographic distances increase. Principal Coordinate Analysis suggests that genetically related samples are not co-located. Barrier analysis reveals no significant barriers to gene flow between locations. Malaria genetics in the DRC have a complex and fragmented landscape. Limited exchange of genes across space is reflected in greater genetic distance between malaria parasites isolated at greater geographic distances. There is, however, evidence for close genetic ties between distally located sample locations, indicating that movement of malaria parasites and flow of genes is being driven by factors other than distance decay. This research demonstrates the contributions that spatial disease ecology and landscape genetics can make to

Genetic complexity underlying hybrid male sterility in Drosophila.

Science.gov (United States)

Sawamura, Kyoichi; Roote, John; Wu, Chung-I; Yamamoto, Masa-Toshi

2004-02-01

Recent genetic analyses of closely related species of Drosophila have indicated that hybrid male sterility is the consequence of highly complex synergistic effects among multiple genes, both conspecific and heterospecific. On the contrary, much evidence suggests the presence of major genes causing hybrid female sterility and inviability in the less-related species, D. melanogaster and D. simulans. Does this contrast reflect the genetic distance between species? Or, generally, is the genetic basis of hybrid male sterility more complex than that of hybrid female sterility and inviability? To clarify this point, the D. simulans introgression of the cytological region 34D-36A to the D. melanogaster genome, which causes recessive male sterility, was dissected by recombination, deficiency, and complementation mapping. The 450-kb region between two genes, Suppressor of Hairless and snail, exhibited a strong effect on the sterility. Males are (semi-)sterile if this region of the introgression is made homozygous or hemizygous. But no genes in the region singly cause the sterility; this region has at least two genes, which in combination result in male sterility. Further, the males are less fertile when heterozygous with a larger introgression, which suggests that dominant modifiers enhance the effects of recessive genes of male sterility. Such an epistatic view, even in the less-related species, suggests that the genetic complexity is special to hybrid male sterility.

Nonlinear and Complex Dynamics in Economics

OpenAIRE

William Barnett; Apostolos Serletis; Demitre Serletis

2012-01-01

This paper is an up-to-date survey of the state-of-the-art in dynamical systems theory relevant to high levels of dynamical complexity, characterizing chaos and near chaos, as commonly found in the physical sciences. The paper also surveys applications in economics and �finance. This survey does not include bifurcation analyses at lower levels of dynamical complexity, such as Hopf and transcritical bifurcations, which arise closer to the stable region of the parameter space. We discuss the...

Pinning Synchronization of Switched Complex Dynamical Networks

Directory of Open Access Journals (Sweden)

Liming Du

2015-01-01

Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

Dynamic modeling of genetic networks using genetic algorithm and S-system.

Science.gov (United States)

Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru

2003-03-22

The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

Worms under stress: unravelling genetic complex traits through perturbation

NARCIS (Netherlands)

Rodriguez Sanchez, M.

2014-01-01

The genetic architecture of an organism could be considered ‘the most amazing piece of engineering’ existing in nature. Looking from a certain distance, the genetic complexity of an organism could be described as an immense jigsaw puzzle. As in a real jigsaw, the connection between two pieces

Genetic aspects of pathological gambling: a complex disorder with shared genetic vulnerabilities.

Science.gov (United States)

Lobo, Daniela S S; Kennedy, James L

2009-09-01

To summarize and discuss findings from genetic studies conducted on pathological gambling (PG). Searches were conducted on PubMed and PsychInfo databases using the keywords: 'gambling and genes', 'gambling and family' and 'gambling and genetics', yielding 18 original research articles investigating the genetics of PG. Twin studies using the Vietnam Era Twin Registry have found that: (i) the heritability of PG is estimated to be 50-60%; (ii) PG and subclinical PG are a continuum of the same disorder; (iii) PG shares genetic vulnerability factors with antisocial behaviours, alcohol dependence and major depressive disorder; (iv) genetic factors underlie the association between exposure to traumatic life-events and PG. Molecular genetic investigations on PG are at an early stage and published studies have reported associations with genes involved in the brain's reward and impulse control systems. Despite the paucity of studies in this area, published studies have provided considerable evidence of the influence of genetic factors on PG and its complex interaction with other psychiatric disorders and environmental factors. The next step would be to investigate the association and interaction of these variables in larger molecular genetic studies with subphenotypes that underlie PG. Results from family and genetic investigations corroborate further the importance of understanding the biological underpinnings of PG in the development of more specific treatment and prevention strategies.

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

Science.gov (United States)

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Migraine genetics : from monogenic to complex forms

NARCIS (Netherlands)

Vanmolkot, Kaate Raymond Josepha

2008-01-01

Migraine has a strong genetic component, but the identification of these factors has proven difficult mainly because of the complex interaction of multiple loci and environmental factors. Unraveling its molecular basis and deciphering pathways leading to migraine attacks will help identifying novel

Controlling Complex Systems and Developing Dynamic Technology

Science.gov (United States)

Avizienis, Audrius Victor

In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit

The Impact of Evolutionary Driving Forces on Human Complex Diseases: A Population Genetics Approach

Directory of Open Access Journals (Sweden)

Amr T. M. Saeb

2016-01-01

Full Text Available Investigating the molecular evolution of human genome has paved the way to understand genetic adaptation of humans to the environmental changes and corresponding complex diseases. In this review, we discussed the historical origin of genetic diversity among human populations, the evolutionary driving forces that can affect genetic diversity among populations, and the effects of human movement into new environments and gene flow on population genetic diversity. Furthermore, we presented the role of natural selection on genetic diversity and complex diseases. Then we reviewed the disadvantageous consequences of historical selection events in modern time and their relation to the development of complex diseases. In addition, we discussed the effect of consanguinity on the incidence of complex diseases in human populations. Finally, we presented the latest information about the role of ancient genes acquired from interbreeding with ancient hominids in the development of complex diseases.

Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases

Science.gov (United States)

Amos, Christopher I.; Bafna, Vineet; Hauser, Elizabeth R.; Hernandez, Ryan D.; Li, Chun; Liberles, David A.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Papanicolaou, George J.; Peng, Bo; Ritchie, Marylyn D.; Rosenfeld, Gabriel; Witte, John S.

2014-01-01

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled “Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases” at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to: (i) identify opportunities, challenges and resource needs for the development and application of genetic simulation models; (ii) improve the integration of tools for modeling and analysis of simulated data; and (iii) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation. PMID:25371374

Teaching Genetic Counseling Skills: Incorporating a Genetic Counseling Adaptation Continuum Model to Address Psychosocial Complexity.

Science.gov (United States)

Shugar, Andrea

2017-04-01

Genetic counselors are trained health care professionals who effectively integrate both psychosocial counseling and information-giving into their practice. Preparing genetic counseling students for clinical practice is a challenging task, particularly when helping them develop effective and active counseling skills. Resistance to incorporating these skills may stem from decreased confidence, fear of causing harm or a lack of clarity of psycho-social goals. The author reflects on the personal challenges experienced in teaching genetic counselling students to work with psychological and social complexity, and proposes a Genetic Counseling Adaptation Continuum model and methodology to guide students in the use of advanced counseling skills.

Lattice dynamics and molecular dynamics simulation of complex materials

International Nuclear Information System (INIS)

Chaplot, S.L.

1997-01-01

In this article we briefly review the lattice dynamics and molecular dynamics simulation techniques, as used for complex ionic and molecular solids, and demonstrate a number of applications through examples of our work. These computational studies, along with experiments, have provided microscopic insight into the structure and dynamics, phase transitions and thermodynamical properties of a variety of materials including fullerene, high temperature superconducting oxides and geological minerals as a function of pressure and temperature. The computational techniques also allow the study of the structures and dynamics associated with disorder, defects, surfaces, interfaces etc. (author)

Improving the Complexity of the Lorenz Dynamics

Directory of Open Access Journals (Sweden)

María Pilar Mareca

2017-01-01

Full Text Available A new four-dimensional, hyperchaotic dynamic system, based on Lorenz dynamics, is presented. Besides, the most representative dynamics which may be found in this new system are located in the phase space and are analyzed here. The new system is especially designed to improve the complexity of Lorenz dynamics, which, despite being a paradigm to understand the chaotic dissipative flows, is a very simple example and shows great vulnerability when used in secure communications. Here, we demonstrate the vulnerability of the Lorenz system in a general way. The proposed 4D system increases the complexity of the Lorenz dynamics. The trajectories of the novel system include structures going from chaos to hyperchaos and chaotic-transient solutions. The symmetry and the stability of the proposed system are also studied. First return maps, Poincaré sections, and bifurcation diagrams allow characterizing the global system behavior and locating some coexisting structures. Numerical results about the first return maps, Poincaré cross sections, Lyapunov spectrum, and Kaplan-Yorke dimension demonstrate the complexity of the proposed equations.

Genetic algorithms applied to nonlinear and complex domains

International Nuclear Information System (INIS)

Barash, D; Woodin, A E

1999-01-01

The dissertation, titled ''Genetic Algorithms Applied to Nonlinear and Complex Domains'', describes and then applies a new class of powerful search algorithms (GAS) to certain domains. GAS are capable of solving complex and nonlinear problems where many parameters interact to produce a ''final'' result such as the optimization of the laser pulse in the interaction of an atom with an intense laser field. GAS can very efficiently locate the global maximum by searching parameter space in problems which are unsuitable for a search using traditional methods. In particular, the dissertation contains new scientific findings in two areas. First, the dissertation examines the interaction of an ultra-intense short laser pulse with atoms. GAS are used to find the optimal frequency for stabilizing atoms in the ionization process. This leads to a new theoretical formulation, to explain what is happening during the ionization process and how the electron is responding to finite (real-life) laser pulse shapes. It is shown that the dynamics of the process can be very sensitive to the ramp of the pulse at high frequencies. The new theory which is formulated, also uses a novel concept (known as the (t,t') method) to numerically solve the time-dependent Schrodinger equation Second, the dissertation also examines the use of GAS in modeling decision making problems. It compares GAS with traditional techniques to solve a class of problems known as Markov Decision Processes. The conclusion of the dissertation should give a clear idea of where GAS are applicable, especially in the physical sciences, in problems which are nonlinear and complex, i.e. difficult to analyze by other means

PM Synchronous Motor Dynamic Modeling with Genetic Algorithm ...

African Journals Online (AJOL)

Adel

This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous ... Simulations are implemented using MATLAB with its genetic algorithm toolbox. .... selection, the process that drives biological evolution.

Coarse-graining complex dynamics

DEFF Research Database (Denmark)

Sibani, Paolo

2013-01-01

Continuous Time Random Walks (CTRW) are widely used to coarse-grain the evolution of systems jumping from a metastable sub-set of their configuration space, or trap, to another via rare intermittent events. The multi-scaled behavior typical of complex dynamics is provided by a fat...... macroscopic variables all produce identical long time relaxation behaviors. Hence, CTRW shed no light on the link between microscopic and macroscopic dynamics. We then highlight how a more recent approach, Record Dynamics (RD) provides a viable alternative, based on a very different set of physical ideas......: while CTRW make use of a renewal process involving identical traps of infinite size, RD embodies a dynamical entrenchment into a hierarchy of traps which are finite in size and possess different degrees of meta-stability. We show in particular how RD produces the stretched exponential, power...

Translating conservation genetics into management: Pan-European minimum requirements for dynamic conservation units of forest tree genetic diversity

OpenAIRE

Koskela, Jarkko; Lefèvre, François; Schueler, Silvio; Kraigher, Hojka; Olrik, Ditte C.; Hubert, Jason; Longauer, Roman; Bozzano, Michele; Yrjänä, Leena; Alizoti, Paraskevi; Rotach, Peter; Vietto, Lorenzo; Bordács, Sándor; Myking, Tor; Eysteinsson, Thröstur

2013-01-01

This paper provides a review of theoretical and practical aspects related to genetic management of forest trees. The implementation of international commitments on forest genetic diversity has been slow and partly neglected. Conservation of forest genetic diversity is still riddled with problems, and complexities of national legal and administrative structures. Europe is an example of a complex region where the dis- tribution ranges of tree species extend across large geographical areas with ...

The ethics of complexity. Genetics and autism, a literature review.

Science.gov (United States)

Hens, Kristien; Peeters, Hilde; Dierickx, Kris

2016-04-01

It is commonly believed that the etiology of autism is at least partly explained through genetics. Given the complexity of autism and the variability of the autistic phenotype, genetic research and counseling in this field are also complex and associated with specific ethical questions. Although the ethics of autism genetics, especially with regard to reproductive choices, has been widely discussed on the public fora, an in depth philosophical or bioethical reflection on all aspects of the theme seems to be missing. With this literature review we wanted to map the basic questions and answers that exist in the bioethical literature on autism genetics, research, counseling and reproduction, and provide suggestions as to how the discussion can proceed. We found 19 papers that fitted the description of "bioethics literature focusing on autism genetics," and analyzed their content to distill arguments and themes. We concluded that because of the complexity of autism, and the uncertainty with regard to its status, more ethical reflection is needed before definite conclusions and recommendations can be drawn. Moreover, there is a dearth of bioethical empirical studies querying the opinions of all parties, including people with autism themselves. Such empirical bioethical studies should be urgently done before bioethical conclusions regarding the aims and desirability of research into autism genes can be done. Also, fundamental philosophical reflection on concepts of disease should accompany research into the etiology of autism. © 2016 Wiley Periodicals, Inc.

Dynamical complexity changes during two forms of meditation

Science.gov (United States)

Li, Jin; Hu, Jing; Zhang, Yinhong; Zhang, Xiaofeng

2011-06-01

Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.

Product development projects dynamics and emergent complexity

CERN Document Server

Schlick, Christopher

2016-01-01

This book primarily explores two topics: the representation of simultaneous, cooperative work processes in product development projects with the help of statistical models, and the assessment of their emergent complexity using a metric from theoretical physics (Effective Measure Complexity, EMC). It is intended to promote more effective management of development projects by shifting the focus from the structural complexity of the product being developed to the dynamic complexity of the development processes involved. The book is divided into four main parts, the first of which provides an introduction to vector autoregression models, periodic vector autoregression models and linear dynamical systems for modeling cooperative work in product development projects. The second part presents theoretical approaches for assessing complexity in the product development environment, while the third highlights and explains closed-form solutions for the complexity metric EMC for vector autoregression models and linear dyn...

Growth-rate-dependent dynamics of a bacterial genetic oscillator

Science.gov (United States)

Osella, Matteo; Lagomarsino, Marco Cosentino

2013-01-01

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular “chassis” in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments

OpenAIRE

Yang, S

2008-01-01

Copyright @ 2008 by the Massachusetts Institute of Technology In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical inform...

Rapid Mission Design for Dynamically Complex Environments

Data.gov (United States)

National Aeronautics and Space Administration — Designing trajectories in dynamically complex environments is very challenging and easily becomes an intractable problem. More complex planning implies potentially...

Complex systems and networks dynamics, controls and applications

CERN Document Server

Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

2016-01-01

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

Complex dynamic in ecological time series

Science.gov (United States)

Peter Turchin; Andrew D. Taylor

1992-01-01

Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a methodology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting...

Enabling complex genetic circuits to respond to extrinsic environmental signals.

Science.gov (United States)

Hoynes-O'Connor, Allison; Shopera, Tatenda; Hinman, Kristina; Creamer, John Philip; Moon, Tae Seok

2017-07-01

Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Traffic Dynamics on Complex Networks: A Survey

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available Traffic dynamics on complex networks are intriguing in recent years due to their practical implications in real communication networks. In this survey, we give a brief review of studies on traffic routing dynamics on complex networks. Strategies for improving transport efficiency, including designing efficient routing strategies and making appropriate adjustments to the underlying network structure, are introduced in this survey. Finally, a few open problems are discussed in this survey.

Inferring network topology from complex dynamics

International Nuclear Information System (INIS)

Shandilya, Srinivas Gorur; Timme, Marc

2011-01-01

Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.

Complexity: Outline of the NWO strategic theme Dynamics of complex systems

NARCIS (Netherlands)

Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; van der Maas, H.; Mulder, B.; Stam, K.; van Steen, M.; Zandee, L.

2008-01-01

Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

Complexity : outline of the NWO strategic theme dynamics of complex systems

NARCIS (Netherlands)

Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; Maas, van der H.; Mulder, B.; Stam, K.; Steen, van M.; Zandee, L.

2008-01-01

Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

Dynamic complexities in a parasitoid-host-parasitoid ecological model

International Nuclear Information System (INIS)

Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

2009-01-01

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

Dynamic complexities in a parasitoid-host-parasitoid ecological model

Energy Technology Data Exchange (ETDEWEB)

Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

2009-01-15

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

Genetic and phenotypic characterization of complex hereditary spastic paraplegia

Science.gov (United States)

Kara, Eleanna; Tucci, Arianna; Manzoni, Claudia; Lynch, David S.; Elpidorou, Marilena; Bettencourt, Conceicao; Chelban, Viorica; Manole, Andreea; Hamed, Sherifa A.; Haridy, Nourelhoda A.; Federoff, Monica; Preza, Elisavet; Hughes, Deborah; Pittman, Alan; Jaunmuktane, Zane; Brandner, Sebastian; Xiromerisiou, Georgia; Wiethoff, Sarah; Schottlaender, Lucia; Proukakis, Christos; Morris, Huw; Warner, Tom; Bhatia, Kailash P.; Korlipara, L.V. Prasad; Singleton, Andrew B.; Hardy, John; Wood, Nicholas W.; Lewis, Patrick A.

2016-01-01

Abstract The hereditary spastic paraplegias are a heterogeneous group of degenerative disorders that are clinically classified as either pure with predominant lower limb spasticity, or complex where spastic paraplegia is complicated with additional neurological features, and are inherited in autosomal dominant, autosomal recessive or X-linked patterns. Genetic defects have been identified in over 40 different genes, with more than 70 loci in total. Complex recessive spastic paraplegias have in the past been frequently associated with mutations in SPG11 (spatacsin), ZFYVE26/SPG15 , SPG7 (paraplegin) and a handful of other rare genes, but many cases remain genetically undefined. The overlap with other neurodegenerative disorders has been implied in a small number of reports, but not in larger disease series. This deficiency has been largely due to the lack of suitable high throughput techniques to investigate the genetic basis of disease, but the recent availability of next generation sequencing can facilitate the identification of disease-causing mutations even in extremely heterogeneous disorders. We investigated a series of 97 index cases with complex spastic paraplegia referred to a tertiary referral neurology centre in London for diagnosis or management. The mean age of onset was 16 years (range 3 to 39). The SPG11 gene was first analysed, revealing homozygous or compound heterozygous mutations in 30/97 (30.9%) of probands, the largest SPG11 series reported to date, and by far the most common cause of complex spastic paraplegia in the UK, with severe and progressive clinical features and other neurological manifestations, linked with magnetic resonance imaging defects. Given the high frequency of SPG11 mutations, we studied the autophagic response to starvation in eight affected SPG11 cases and control fibroblast cell lines, but in our restricted study we did not observe correlations between disease status and autophagic or lysosomal markers. In the remaining

Dynamics in electron transfer protein complexes

OpenAIRE

Bashir, Qamar

2010-01-01

Recent studies have provided experimental evidence for the existence of an encounter complex, a transient intermediate in the formation of protein complexes. We have used paramagnetic relaxation enhancement NMR spectroscopy in combination with Monte Carlo simulations to characterize and visualize the ensemble of encounter orientations in the short-lived electron transfer complex of yeast Cc and CcP. The complete conformational space sampled by the protein molecules during the dynamic part of ...

Chaotic, fractional, and complex dynamics new insights and perspectives

CERN Document Server

Macau, Elbert; Sanjuan, Miguel

2018-01-01

The book presents nonlinear, chaotic and fractional dynamics, complex systems and networks, together with cutting-edge research on related topics. The fifteen chapters – written by leading scientists working in the areas of nonlinear, chaotic and fractional dynamics, as well as complex systems and networks – offer an extensive overview of cutting-edge research on a range of topics, including fundamental and applied research. These include but are not limited to aspects of synchronization in complex dynamical systems, universality features in systems with specific fractional dynamics, and chaotic scattering. As such, the book provides an excellent and timely snapshot of the current state of research, blending the insights and experiences of many prominent researchers.

Higher Complexity of Infection and Genetic Diversity of Plasmodium vivax Than Plasmodium falciparum across all Malaria Transmission Zones of Papua New Guinea

Science.gov (United States)

Fola, Abebe A.; Harrison, G. L. Abby; Hazairin, Mita Hapsari; Barnadas, Céline; Hetzel, Manuel W.; Iga, Jonah; Siba, Peter M.; Mueller, Ivo; Barry, Alyssa E.

2017-01-01

Plasmodium falciparum and Plasmodium vivax have varying transmission dynamics that are informed by molecular epidemiology. This study aimed to determine the complexity of infection and genetic diversity of P. vivax and P. falciparum throughout Papua New Guinea (PNG) to evaluate transmission dynamics across the country. In 2008–2009, a nationwide malaria indicator survey collected 8,936 samples from all 16 endemic provinces of PNG. Of these, 892 positive P. vivax samples were genotyped at PvMS16 and PvmspF3, and 758 positive P. falciparum samples were genotyped at Pfmsp2. The data were analyzed for multiplicity of infection (MOI) and genetic diversity. Overall, P. vivax had higher polyclonality (71%) and mean MOI (2.32) than P. falciparum (20%, 1.39). These measures were significantly associated with prevalence for P. falciparum but not for P. vivax. The genetic diversity of P. vivax (PvMS16: expected heterozygosity = 0.95, 0.85–0.98; PvMsp1F3: 0.78, 0.66–0.89) was higher and less variable than that of P. falciparum (Pfmsp2: 0.89, 0.65–0.97). Significant associations of MOI with allelic richness (rho = 0.69, P = 0.009) and expected heterozygosity (rho = 0.87, P < 0.001) were observed for P. falciparum. Conversely, genetic diversity was not correlated with polyclonality nor mean MOI for P. vivax. The results demonstrate higher complexity of infection and genetic diversity of P. vivax across the country. Although P. falciparum shows a strong association of these parameters with prevalence, a lack of association was observed for P. vivax and is consistent with higher potential for outcrossing of this species. PMID:28070005

Entropy for the Complexity of Physiological Signal Dynamics.

Science.gov (United States)

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Micro-Level Affect Dynamics in Psychopathology Viewed From Complex Dynamical System Theory

NARCIS (Netherlands)

Wichers, M.; Wigman, J. T. W.; Myin-Germeys, I.

2015-01-01

This article discusses the role of moment-to-moment affect dynamics in mental disorder and aims to integrate recent literature on this topic in the context of complex dynamical system theory. First, we will review the relevance of temporal and contextual aspects of affect dynamics in relation to

Advances in dynamics, patterns, cognition challenges in complexity

CERN Document Server

Pikovsky, Arkady; Rulkov, Nikolai; Tsimring, Lev

2017-01-01

This book focuses on recent progress in complexity research based on the fundamental nonlinear dynamical and statistical theory of oscillations, waves, chaos, and structures far from equilibrium. Celebrating seminal contributions to the field by Prof. M. I. Rabinovich of the University of California at San Diego, this volume brings together perspectives on both the fundamental aspects of complexity studies, as well as in applications in different fields ranging from granular patterns to understanding of the cognitive brain and mind dynamics. The slate of world-class authors review recent achievements that together present a broad and coherent coverage of modern research in complexity greater than the sum of its parts. Presents the most up-to-date developments in the studies of complexity Combines basic and applied aspects Links background nonlinear theory of oscillations and waves with modern approaches Allows readers to recognize general dynamical principles across the applications fields.

Amodified probabilistic genetic algorithm for the solution of complex constrained optimization problems

OpenAIRE

Vorozheikin, A.; Gonchar, T.; Panfilov, I.; Sopov, E.; Sopov, S.

2009-01-01

A new algorithm for the solution of complex constrained optimization problems based on the probabilistic genetic algorithm with optimal solution prediction is proposed. The efficiency investigation results in comparison with standard genetic algorithm are presented.

Genetic algorithms applied to nonlinear and complex domains; TOPICAL

International Nuclear Information System (INIS)

Barash, D; Woodin, A E

1999-01-01

The dissertation, titled ''Genetic Algorithms Applied to Nonlinear and Complex Domains'', describes and then applies a new class of powerful search algorithms (GAS) to certain domains. GAS are capable of solving complex and nonlinear problems where many parameters interact to produce a ''final'' result such as the optimization of the laser pulse in the interaction of an atom with an intense laser field. GAS can very efficiently locate the global maximum by searching parameter space in problems which are unsuitable for a search using traditional methods. In particular, the dissertation contains new scientific findings in two areas. First, the dissertation examines the interaction of an ultra-intense short laser pulse with atoms. GAS are used to find the optimal frequency for stabilizing atoms in the ionization process. This leads to a new theoretical formulation, to explain what is happening during the ionization process and how the electron is responding to finite (real-life) laser pulse shapes. It is shown that the dynamics of the process can be very sensitive to the ramp of the pulse at high frequencies. The new theory which is formulated, also uses a novel concept (known as the (t,t') method) to numerically solve the time-dependent Schrodinger equation Second, the dissertation also examines the use of GAS in modeling decision making problems. It compares GAS with traditional techniques to solve a class of problems known as Markov Decision Processes. The conclusion of the dissertation should give a clear idea of where GAS are applicable, especially in the physical sciences, in problems which are nonlinear and complex, i.e. difficult to analyze by other means

Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops.

Science.gov (United States)

Hammer, Graeme L; van Oosterom, Erik; McLean, Greg; Chapman, Scott C; Broad, Ian; Harland, Peter; Muchow, Russell C

2010-05-01

Progress in molecular plant breeding is limited by the ability to predict plant phenotype based on its genotype, especially for complex adaptive traits. Suitably constructed crop growth and development models have the potential to bridge this predictability gap. A generic cereal crop growth and development model is outlined here. It is designed to exhibit reliable predictive skill at the crop level while also introducing sufficient physiological rigour for complex phenotypic responses to become emergent properties of the model dynamics. The approach quantifies capture and use of radiation, water, and nitrogen within a framework that predicts the realized growth of major organs based on their potential and whether the supply of carbohydrate and nitrogen can satisfy that potential. The model builds on existing approaches within the APSIM software platform. Experiments on diverse genotypes of sorghum that underpin the development and testing of the adapted crop model are detailed. Genotypes differing in height were found to differ in biomass partitioning among organs and a tall hybrid had significantly increased radiation use efficiency: a novel finding in sorghum. Introducing these genetic effects associated with plant height into the model generated emergent simulated phenotypic differences in green leaf area retention during grain filling via effects associated with nitrogen dynamics. The relevance to plant breeding of this capability in complex trait dissection and simulation is discussed.

Design tools for complex dynamic security systems.

Energy Technology Data Exchange (ETDEWEB)

Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson; Laguna, Glenn A.; Robinett, Rush D. III (.; ); Groom, Kenneth Neal; Wilson, David Gerald; Bickerstaff, Robert J.; Harrington, John J.

2007-01-01

The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.

Genome complexity, robustness and genetic interactions in digital organisms

Science.gov (United States)

Lenski, Richard E.; Ofria, Charles; Collier, Travis C.; Adami, Christoph

1999-08-01

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined `metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.

Complex economic dynamics: Chaotic saddle, crisis and intermittency

International Nuclear Information System (INIS)

Chian, Abraham C.-L.; Rempel, Erico L.; Rogers, Colin

2006-01-01

Complex economic dynamics is studied by a forced oscillator model of business cycles. The technique of numerical modeling is applied to characterize the fundamental properties of complex economic systems which exhibit multiscale and multistability behaviors, as well as coexistence of order and chaos. In particular, we focus on the dynamics and structure of unstable periodic orbits and chaotic saddles within a periodic window of the bifurcation diagram, at the onset of a saddle-node bifurcation and of an attractor merging crisis, and in the chaotic regions associated with type-I intermittency and crisis-induced intermittency, in non-linear economic cycles. Inside a periodic window, chaotic saddles are responsible for the transient motion preceding convergence to a periodic or a chaotic attractor. The links between chaotic saddles, crisis and intermittency in complex economic dynamics are discussed. We show that a chaotic attractor is composed of chaotic saddles and unstable periodic orbits located in the gap regions of chaotic saddles. Non-linear modeling of economic chaotic saddle, crisis and intermittency can improve our understanding of the dynamics of financial intermittency observed in stock market and foreign exchange market. Characterization of the complex dynamics of economic systems is a powerful tool for pattern recognition and forecasting of business and financial cycles, as well as for optimization of management strategy and decision technology

Exponential rise of dynamical complexity in quantum computing through projections.

Science.gov (United States)

Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya

2014-10-10

The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.

Combinations of complex dynamical systems

CERN Document Server

Pilgrim, Kevin M

2003-01-01

This work is a research-level monograph whose goal is to develop a general combination, decomposition, and structure theory for branched coverings of the two-sphere to itself, regarded as the combinatorial and topological objects which arise in the classification of certain holomorphic dynamical systems on the Riemann sphere. It is intended for researchers interested in the classification of those complex one-dimensional dynamical systems which are in some loose sense tame. The program is motivated by the dictionary between the theories of iterated rational maps and Kleinian groups.

Genetic HLA Associations in Complex Regional Pain Syndrome With and Without Dystonia

NARCIS (Netherlands)

van Rooijen, D.E.; Roelen, D.L.; Verduijn, W.; Haasnoot, G.W.; Huygen, F.J.P.M.; Perez, R.S.G.M.; Claas, F.H.J.; Marinus, J.; van Hilten, J.J.; van den Maagdenberg, A.M.J.M.

2012-01-01

We previously showed evidence for a genetic association of the human leukocyte antigen (HLA) system and complex regional pain syndrome (CRPS) with dystonia. Involvement of the HLA system suggests that CRPS has a genetic component with perturbed regulation of inflammation and neuroplasticity as

Complex networks: Dynamics and security

Indian Academy of Sciences (India)

This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. ... Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona 85287, USA; Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil ...

Tetralogy of Fallot and Hypoplastic Left Heart Syndrome – Complex Clinical Phenotypes Meet Complex Genetic Networks

Science.gov (United States)

Lahm, Harald; Schön, Patric; Doppler, Stefanie; Dreßen, Martina; Cleuziou, Julie; Deutsch, Marcus-André; Ewert, Peter; Lange, Rüdiger; Krane, Markus

2015-01-01

In many cases congenital heart disease (CHD) is represented by a complex phenotype and an array of several functional and morphological cardiac disorders. These malformations will be briefly summarized in the first part focusing on two severe CHD phenotypes, hypoplastic left heart syndrome (HLHS) and tetralogy of Fallot (TOF). In most cases of CHD the genetic origin remains largely unknown, though the complexity of the clinical picture strongly argues against a dysregulation which can be attributed to a single candidate gene but rather suggests a multifaceted polygenetic origin with elaborate interactions. Consistent with this idea, genome-wide approaches using whole exome sequencing, comparative sequence analysis of multiplex families to identify de novo mutations and global technologies to identify single nucleotide polymorphisms, copy number variants, dysregulation of the transcriptome and epigenetic variations have been conducted to obtain information about genetic alterations and potential predispositions possibly linked to the occurrence of a CHD phenotype. In the second part of this review we will summarize and discuss the available literature on identified genetic alterations linked to TOF and HLHS. PMID:26069455

Genetic and epidemiological aspect of Complex Regional Pain Syndrome

NARCIS (Netherlands)

Rooij, Annetje Monique de

2010-01-01

Complex Regional Pain Syndrome (CRPS) is a painful disorder affecting one or more extremities. CRPS is characterized by various combinations of sensory, autonomic and motor disturbances. Genetic factors are suggested to play a role in CRPS, but this has not been extensively studied. Therefore the

Complex networks under dynamic repair model

Science.gov (United States)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Automated design of complex dynamic systems.

Directory of Open Access Journals (Sweden)

Michiel Hermans

Full Text Available Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems.

Dynamics of a complex quantum magnet

International Nuclear Information System (INIS)

Landry, James W.; Coppersmith, S. N.

2003-01-01

We have computed the low energy quantum states and low frequency dynamical susceptibility of complex quantum spin systems in the limit of strong interactions, obtaining exact results for system sizes enormously larger than accessible previously. The ground state is a complex superposition of a substantial fraction of all the classical ground states, and yet the dynamical susceptibility exhibits sharp resonances reminiscent of the behavior of single spins. These results show that strongly interacting quantum systems can organize to generate coherent excitations and shed light on recent experiments demonstrating that coherent excitations are present in a disordered spin liquid. The dependence of the energy spectra on system size differs qualitatively from that of the energy spectra of random undirected bipartite graphs with similar statistics, implying that strong interactions are giving rise to these unusual spectral properties

Integrating Nonadditive Genomic Relationship Matrices into the Study of Genetic Architecture of Complex Traits.

Science.gov (United States)

Nazarian, Alireza; Gezan, Salvador A

2016-03-01

The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Charge-Transfer Complexes Studied by Dynamic Force Spectroscopy

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Jurriaan Huskens

2013-03-01

Full Text Available In this paper, the strength and kinetics of two charge-transfer complexes, naphthol-methylviologen and pyrene-methylviologen, are studied using dynamic force spectroscopy. The dissociation rates indicate an enhanced stability of the pyrene-methylviologen complex, which agrees with its higher thermodynamic stability compared to naphthol-methylviologen complex.

Statistical power to detect genetic (covariance of complex traits using SNP data in unrelated samples.

Directory of Open Access Journals (Sweden)

Peter M Visscher

2014-04-01

Full Text Available We have recently developed analysis methods (GREML to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (covariation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases in particular when the traits (diseases are not measured on the same samples.

The Self as a Complex Dynamic System

Science.gov (United States)

Mercer, Sarah

2011-01-01

This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…

Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application

OpenAIRE

Li, Xiang

2005-01-01

In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...

Complex systems dynamics in aging: new evidence, continuing questions.

Science.gov (United States)

Cohen, Alan A

2016-02-01

There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.

Impact of the mitochondrial genetic background in complex III deficiency.

Directory of Open Access Journals (Sweden)

Mari Carmen Gil Borlado

Full Text Available BACKGROUND: In recent years clinical evidence has emphasized the importance of the mtDNA genetic background that hosts a primary pathogenic mutation in the clinical expression of mitochondrial disorders, but little experimental confirmation has been provided. We have analyzed the pathogenic role of a novel homoplasmic mutation (m.15533 A>G in the cytochrome b (MT-CYB gene in a patient presenting with lactic acidosis, seizures, mild mental delay, and behaviour abnormalities. METHODOLOGY: Spectrophotometric analyses of the respiratory chain enzyme activities were performed in different tissues, the whole muscle mitochondrial DNA of the patient was sequenced, and the novel mutation was confirmed by PCR-RFLP. Transmitochondrial cybrids were constructed to confirm the pathogenicity of the mutation, and assembly/stability studies were carried out in fibroblasts and cybrids by means of mitochondrial translation inhibition in combination with blue native gel electrophoresis. PRINCIPAL FINDINGS: Biochemical analyses revealed a decrease in respiratory chain complex III activity in patient's skeletal muscle, and a combined enzyme defect of complexes III and IV in fibroblasts. Mutant transmitochondrial cybrids restored normal enzyme activities and steady-state protein levels, the mutation was mildly conserved along evolution, and the proband's mother and maternal aunt, both clinically unaffected, also harboured the homoplasmic mutation. These data suggested a nuclear genetic origin of the disease. However, by forcing the de novo functioning of the OXPHOS system, a severe delay in the biogenesis of the respiratory chain complexes was observed in the mutants, which demonstrated a direct functional effect of the mitochondrial genetic background. CONCLUSIONS: Our results point to possible pitfalls in the detection of pathogenic mitochondrial mutations, and highlight the role of the genetic mtDNA background in the development of mitochondrial disorders.

Robustness of pinning a general complex dynamical network

International Nuclear Information System (INIS)

Wang Lei; Sun Youxian

2010-01-01

This Letter studies the robustness problem of pinning a general complex dynamical network toward an assigned synchronous evolution. Several synchronization criteria are presented to guarantee the convergence of the pinning process locally and globally by construction of Lyapunov functions. In particular, if a pinning strategy has been designed for synchronization of a given complex dynamical network, then no matter what uncertainties occur among the pinned nodes, synchronization can still be guaranteed through the pinning. The analytical results show that pinning control has a certain robustness against perturbations on network architecture: adding, deleting and changing the weights of edges. Numerical simulations illustrated by scale-free complex networks verify the theoretical results above-acquired.

Complex chloroplast RNA metabolism: just debugging the genetic programme?

Directory of Open Access Journals (Sweden)

Schmitz-Linneweber Christian

2008-08-01

Full Text Available Abstract Background The gene expression system of chloroplasts is far more complex than that of their cyanobacterial progenitor. This gain in complexity affects in particular RNA metabolism, specifically the transcription and maturation of RNA. Mature chloroplast RNA is generated by a plethora of nuclear-encoded proteins acquired or recruited during plant evolution, comprising additional RNA polymerases and sigma factors, and sequence-specific RNA maturation factors promoting RNA splicing, editing, end formation and translatability. Despite years of intensive research, we still lack a comprehensive explanation for this complexity. Results We inspected the available literature and genome databases for information on components of RNA metabolism in land plant chloroplasts. In particular, new inventions of chloroplast-specific mechanisms and the expansion of some gene/protein families detected in land plants lead us to suggest that the primary function of the additional nuclear-encoded components found in chloroplasts is the transgenomic suppression of point mutations, fixation of which occurred due to an enhanced genetic drift exhibited by chloroplast genomes. We further speculate that a fast evolution of transgenomic suppressors occurred after the water-to-land transition of plants. Conclusion Our inspections indicate that several chloroplast-specific mechanisms evolved in land plants to remedy point mutations that occurred after the water-to-land transition. Thus, the complexity of chloroplast gene expression evolved to guarantee the functionality of chloroplast genetic information and may not, with some exceptions, be involved in regulatory functions.

The SEA complex – the beginning

Directory of Open Access Journals (Sweden)

Dokudovskaya S. S.

2012-07-01

Full Text Available The presence of distinctive internal membrane compartments, dynamically connected via selective transport pathways, is a hallmark of eukaryotic cells. Many of the proteins required for formation and maintenance of these compartments share an evolutionary history. We have recently identified a new conserved protein complex – the SEA complex – that possesses proteins with structural characteristics similar to the membrane coating complexes such as the nuclear pore complex (NPC, the COPII vesicle coating complex and HOPS/CORVET tethering complexes. The SEA complex in yeast is dynamically associated to the vacuole. The data on the function of the SEA complex remain extremely limited. Here we will discuss a possible role of the SEA complex based on the data from genetic assays and a number of functional studies in both yeast and other eukaryotes.

Nonlinear Dynamics, Chaotic and Complex Systems

Science.gov (United States)

Infeld, E.; Zelazny, R.; Galkowski, A.

2011-04-01

Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet

Applications of Nonlinear Dynamics Model and Design of Complex Systems

CERN Document Server

In, Visarath; Palacios, Antonio

2009-01-01

This edited book is aimed at interdisciplinary, device-oriented, applications of nonlinear science theory and methods in complex systems. In particular, applications directed to nonlinear phenomena with space and time characteristics. Examples include: complex networks of magnetic sensor systems, coupled nano-mechanical oscillators, nano-detectors, microscale devices, stochastic resonance in multi-dimensional chaotic systems, biosensors, and stochastic signal quantization. "applications of nonlinear dynamics: model and design of complex systems" brings together the work of scientists and engineers that are applying ideas and methods from nonlinear dynamics to design and fabricate complex systems.

Polyacrylic acids–bovine serum albumin complexation: Structure and dynamics

International Nuclear Information System (INIS)

Othman, Mohamed; Aschi, Adel; Gharbi, Abdelhafidh

2016-01-01

The study of the mixture of BSA with polyacrylic acids at different masses versus pH allowed highlighting the existence of two regimes of weak and strong complexation. These complexes were studied in diluted regime concentration, by turbidimetry, dynamic light scattering (DLS), zeta-potential measurements and nuclear magnetic resonance (NMR). We have followed the pH effect on the structure and properties of the complex. This allowed refining the interpretation of the phase diagram and understanding the observed phenomena. The NMR measurements allowed probing the dynamics of the constituents versus the pH. The computational method was used to precisely determine the electrostatic potential of BSA and how the polyelectrolyte binds to it at different pH. - Highlights: • Influence of physico-chemical parameters on the electrostatic interactions in the complex system (polyelectrolyte/protein). • Stabilization and encapsulation of biological macromolecules solution by mean of polyelectrolyte. • Properties and structure of mixture obtained by screening the charges of globular protein and at different masses of polyacrylic acids. • Dynamic of the constituents formed by complexes particles. • Evaluation of the electrostatic properties of bovine serum albumin versus pH through solution of the Poisson-Boltzmann equation.

Complex and Adaptive Dynamical Systems A Primer

CERN Document Server

Gros, Claudius

2011-01-01

We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2007-01-01

We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

Analysis and design of a genetic circuit for dynamic metabolic engineering.

Science.gov (United States)

Anesiadis, Nikolaos; Kobayashi, Hideki; Cluett, William R; Mahadevan, Radhakrishnan

2013-08-16

Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

Complex-Dynamic Cosmology and Emergent World Structure

OpenAIRE

Kirilyuk, Andrei P.

2004-01-01

Universe structure emerges in the unreduced, complex-dynamic interaction process with the simplest initial configuration (two attracting homogeneous fields, quant-ph/9902015). The unreduced interaction analysis gives intrinsically creative cosmology, describing the real, explicitly emerging world structure with dynamic randomness on each scale. Without imposing any postulates or entities, we obtain physically real space, time, elementary particles with their detailed structure and intrinsic p...

Coupled disease-behavior dynamics on complex networks: A review

Science.gov (United States)

Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

Dynamics of Fos-Jun-NFAT1 complexes.

Science.gov (United States)

Ramirez-Carrozzi, V R; Kerppola, T K

2001-04-24

Transcription initiation in eukaryotes is controlled by nucleoprotein complexes formed through cooperative interactions among multiple transcription regulatory proteins. These complexes may be assembled via stochastic collisions or defined pathways. We investigated the dynamics of Fos-Jun-NFAT1 complexes by using a multicolor fluorescence resonance energy transfer assay. Fos-Jun heterodimers can bind to AP-1 sites in two opposite orientations, only one of which is populated in mature Fos-Jun-NFAT1 complexes. We studied the reversal of Fos-Jun binding orientation in response to NFAT1 by measuring the efficiencies of energy transfer from donor fluorophores linked to opposite ends of an oligonucleotide to an acceptor fluorophore linked to one subunit of the heterodimer. The reorientation of Fos-Jun by NFAT1 was not inhibited by competitor oligonucleotides or heterodimers. The rate of Fos-Jun reorientation was faster than the rate of heterodimer dissociation at some binding sites. The facilitated reorientation of Fos-Jun heterodimers therefore can enhance the efficiency of Fos-Jun-NFAT1 complex formation. We also examined the influence of the preferred orientation of Fos-Jun binding on the stability and transcriptional activity of Fos-Jun-NFAT1 complexes. Complexes formed at sites where Fos-Jun favored the same binding orientation in the presence and absence of NFAT1 exhibited an 8-fold slower dissociation rate than complexes formed at sites where Fos-Jun favored the opposite binding orientation. Fos-Jun-NFAT1 complexes also exhibited greater transcription activation at promoter elements that favored the same orientation of Fos-Jun binding in the presence and absence of NFAT1. Thus, the orientation of heterodimer binding can influence both the dynamics and promoter selectivity of multiprotein transcription regulatory complexes.

Investigating the structural impacts of I64T and P311S mutations in APE1-DNA complex: a molecular dynamics approach.

Directory of Open Access Journals (Sweden)

C George Priya Doss

Full Text Available Elucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA.In this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T and rs1803120 (P311S were taken further for structural analysis.Different parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis.

On the Organizational Dynamics of the Genetic Code

KAUST Repository

Zhang, Zhang

2011-06-07

The organization of the canonical genetic code needs to be thoroughly illuminated. Here we reorder the four nucleotides—adenine, thymine, guanine and cytosine—according to their emergence in evolution, and apply the organizational rules to devising an algebraic representation for the canonical genetic code. Under a framework of the devised code, we quantify codon and amino acid usages from a large collection of 917 prokaryotic genome sequences, and associate the usages with its intrinsic structure and classification schemes as well as amino acid physicochemical properties. Our results show that the algebraic representation of the code is structurally equivalent to a content-centric organization of the code and that codon and amino acid usages under different classification schemes were correlated closely with GC content, implying a set of rules governing composition dynamics across a wide variety of prokaryotic genome sequences. These results also indicate that codons and amino acids are not randomly allocated in the code, where the six-fold degenerate codons and their amino acids have important balancing roles for error minimization. Therefore, the content-centric code is of great usefulness in deciphering its hitherto unknown regularities as well as the dynamics of nucleotide, codon, and amino acid compositions.

On the Organizational Dynamics of the Genetic Code

KAUST Repository

Zhang, Zhang; Yu, Jun

2011-01-01

The organization of the canonical genetic code needs to be thoroughly illuminated. Here we reorder the four nucleotides—adenine, thymine, guanine and cytosine—according to their emergence in evolution, and apply the organizational rules to devising an algebraic representation for the canonical genetic code. Under a framework of the devised code, we quantify codon and amino acid usages from a large collection of 917 prokaryotic genome sequences, and associate the usages with its intrinsic structure and classification schemes as well as amino acid physicochemical properties. Our results show that the algebraic representation of the code is structurally equivalent to a content-centric organization of the code and that codon and amino acid usages under different classification schemes were correlated closely with GC content, implying a set of rules governing composition dynamics across a wide variety of prokaryotic genome sequences. These results also indicate that codons and amino acids are not randomly allocated in the code, where the six-fold degenerate codons and their amino acids have important balancing roles for error minimization. Therefore, the content-centric code is of great usefulness in deciphering its hitherto unknown regularities as well as the dynamics of nucleotide, codon, and amino acid compositions.

Genomic and Genetic Diversity within the Pseudomonas fluorescens Complex.

Directory of Open Access Journals (Sweden)

Daniel Garrido-Sanz

Full Text Available The Pseudomonas fluorescens complex includes Pseudomonas strains that have been taxonomically assigned to more than fifty different species, many of which have been described as plant growth-promoting rhizobacteria (PGPR with potential applications in biocontrol and biofertilization. So far the phylogeny of this complex has been analyzed according to phenotypic traits, 16S rDNA, MLSA and inferred by whole-genome analysis. However, since most of the type strains have not been fully sequenced and new species are frequently described, correlation between taxonomy and phylogenomic analysis is missing. In recent years, the genomes of a large number of strains have been sequenced, showing important genomic heterogeneity and providing information suitable for genomic studies that are important to understand the genomic and genetic diversity shown by strains of this complex. Based on MLSA and several whole-genome sequence-based analyses of 93 sequenced strains, we have divided the P. fluorescens complex into eight phylogenomic groups that agree with previous works based on type strains. Digital DDH (dDDH identified 69 species and 75 subspecies within the 93 genomes. The eight groups corresponded to clustering with a threshold of 31.8% dDDH, in full agreement with our MLSA. The Average Nucleotide Identity (ANI approach showed inconsistencies regarding the assignment to species and to the eight groups. The small core genome of 1,334 CDSs and the large pan-genome of 30,848 CDSs, show the large diversity and genetic heterogeneity of the P. fluorescens complex. However, a low number of strains were enough to explain most of the CDSs diversity at core and strain-specific genomic fractions. Finally, the identification and analysis of group-specific genome and the screening for distinctive characters revealed a phylogenomic distribution of traits among the groups that provided insights into biocontrol and bioremediation applications as well as their role as

Intertidal population genetic dynamics at a microgeographic seascape scale.

Science.gov (United States)

Hu, Zi-Min

2013-06-01

The intertidal community is among the most physically harsh niches on earth, with highly heterogeneous environmental and biological factors that impose strong habitat selection on population abundance, genetic connectivity and ecological adaptation of organisms in nature. However, most genetic studies to date have concentrated on the influence of basin-wide or regional marine environments (e.g. habitat discontinuities, oceanic currents and fronts, and geographic barriers) on spatiotemporal distribution and composition of intertidal invertebrates having planktonic stages or long-distance dispersal capability. Little is known about sessile marine organisms (e.g. seaweeds) in the context of topographic tidal gradients and reproductive traits at the microgeographic scale. In this issue of Molecular Ecology, Krueger-Hadfield et al. () implemented an elaborate sampling strategy with red seaweed (Chondrus crispus) from a 90-m transect stand near Roscoff and comprehensively detected genome-scale genetic differentiation and biases in ploidy level. This study not only revealed that tidal height resulted in genetic differentiation between high- and low-shore stands and restricted the genetic exchange within the high-shore habitat, but also demonstrated that intergametophytic nonrandom fertilization in C. crispus can cause significant deviation from Hardy-Weinberg equilibrium. Such new genetic insights highlight the importance of microgeographic genetic dynamics and life history characteristics for better understanding the evolutionary processes of speciation and diversification of intertidal marine organisms. © 2013 John Wiley & Sons Ltd.

The self as a complex dynamic system

Directory of Open Access Journals (Sweden)

Sarah Mercer

2011-04-01

Full Text Available This article explores the potential offered by complexity theories for understanding language learners’ sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual perspective that may inform future studies into the self and possibly other individual learner differences. The article concludes by critically considering the merits of a complexity perspective but also reflecting on the challenges it poses for research.

Complex Genetics of Behavior: BXDs in the Automated Home-Cage.

Science.gov (United States)

Loos, Maarten; Verhage, Matthijs; Spijker, Sabine; Smit, August B

2017-01-01

This chapter describes a use case for the genetic dissection and automated analysis of complex behavioral traits using the genetically diverse panel of BXD mouse recombinant inbred strains. Strains of the BXD resource differ widely in terms of gene and protein expression in the brain, as well as in their behavioral repertoire. A large mouse resource opens the possibility for gene finding studies underlying distinct behavioral phenotypes, however, such a resource poses a challenge in behavioral phenotyping. To address the specifics of large-scale screening we describe how to investigate: (1) how to assess mouse behavior systematically in addressing a large genetic cohort, (2) how to dissect automation-derived longitudinal mouse behavior into quantitative parameters, and (3) how to map these quantitative traits to the genome, deriving loci underlying aspects of behavior.

Advances in dynamic network modeling in complex transportation systems

CERN Document Server

Ukkusuri, Satish V

2013-01-01

This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

Genetic diversity and population genetic structure analysis of Echinococcus granulosus sensu stricto complex based on mitochondrial DNA signature.

Directory of Open Access Journals (Sweden)

Monika Sharma

Full Text Available The genetic diversity and population genetics of the Echinococcus granulosus sensu stricto complex were investigated based on sequencing of mitochondrial DNA (mtDNA. Total 81 isolates of hydatid cyst collected from ungulate animals from different geographical areas of North India were identified by sequencing of cytochrome c oxidase subunit1 (coxi gene. Three genotypes belonging to E. granulosus sensu stricto complex were identified (G1, G2 and G3 genotypes. Further the nucleotide sequences (retrieved from GenBank for the coxi gene from seven populations of E. granulosus sensu stricto complex covering 6 continents, were compared with sequences of isolates analysed in this study. Molecular diversity indices represent overall high mitochondrial DNA diversity for these populations, but low nucleotide diversity between haplotypes. The neutrality tests were used to analyze signatures of historical demographic events. The Tajima's D test and Fu's FS test showed negative value, indicating deviations from neutrality and both suggested recent population expansion for the populations. Pairwise fixation index was significant for pairwise comparison of different populations (except between South America and East Asia, Middle East and Europe, South America and Europe, Africa and Australia, indicating genetic differentiation among populations. Based on the findings of the present study and those from earlier studies, we hypothesize that demographic expansion occurred in E. granulosus after the introduction of founder haplotype particular by anthropogenic movements.

Topics in Complexity: Dynamical Patterns in the Cyberworld

Science.gov (United States)

Qi, Hong

Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

Effective control of complex turbulent dynamical systems through statistical functionals.

Science.gov (United States)

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

Searching for Appropriate Ways to Face the Challenges of Complexity and Dynamics

OpenAIRE

Sommerfeld, Peter; Hollenstein, Lea

2017-01-01

People, as bio-psychological systems, are just as dynamic and complex as the social systems that they create. Social work intervenes in the interplay of these two complex, dynamic systems. How can we capture these complexities and dynamics in social work research and practice? The paper introduces the theoretical grounds on which a mixed-methods design has been developed combining a longitudinal quantitative method called Real Time Monitoring that produces dense time series data with qualitat...

Complex spatial dynamics maintain northern leopard frog (Lithobates pipiens) genetic diversity in a temporally varying landscape

Science.gov (United States)

Mushet, David M.; Euliss, Ned H.; Chen, Yongjiu; Stockwell, Craig A.

2013-01-01

In contrast to most local amphibian populations, northeastern populations of the Northern Leopard Frog (Lithobates pipiens) have displayed uncharacteristically high levels of genetic diversity that have been attributed to large, stable populations. However, this widely distributed species also occurs in areas known for great climatic fluctuations that should be reflected in corresponding fluctuations in population sizes and reduced genetic diversity. To test our hypothesis that Northern Leopard Frog genetic diversity would be reduced in areas subjected to significant climate variability, we examined the genetic diversity of L. pipiens collected from 12 sites within the Prairie Pothole Region of North Dakota. Despite the region's fluctuating climate that includes periods of recurring drought and deluge, we found unexpectedly high levels of genetic diversity approaching that of northeastern populations. Further, genetic structure at a landscape scale was strikingly homogeneous; genetic differentiation estimates (Dest) averaged 0.10 (SD = 0.036) across the six microsatellite loci we studied, and two Bayesian assignment tests (STRUCTURE and BAPS) failed to reveal the development of significant population structure across the 68 km breadth of our study area. These results suggest that L. pipiens in the Prairie Pothole Region consists of a large, panmictic population capable of maintaining high genetic diversity in the face of marked climate variability.

Controlling complexity: the clinical relevance of mouse complex genetics

Czech Academy of Sciences Publication Activity Database

Forejt, Jiří

2013-01-01

Roč. 21, č. 11 (2013), s. 1191-1196 ISSN 1018-4813 Institutional support: RVO:68378050 Keywords : Mouse model * Forward genetics * Rewiev Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Genetics and heredity (medical genetics to be 3) Impact factor: 4.225, year: 2013

Genetic basis of haloperidol resistance in Saccharomyces cerevisiae is complex and dose dependent.

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Xin Wang

2014-12-01

Full Text Available The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain and RM11_1a (a vineyard strain, to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance.

Genetic Basis of Haloperidol Resistance in Saccharomyces cerevisiae Is Complex and Dose Dependent

Science.gov (United States)

Wang, Xin; Kruglyak, Leonid

2014-01-01

The genetic basis of most heritable traits is complex. Inhibitory compounds and their effects in model organisms have been used in many studies to gain insights into the genetic architecture underlying quantitative traits. However, the differential effect of compound concentration has not been studied in detail. In this study, we used a large segregant panel from a cross between two genetically divergent yeast strains, BY4724 (a laboratory strain) and RM11_1a (a vineyard strain), to study the genetic basis of variation in response to different doses of a drug. Linkage analysis revealed that the genetic architecture of resistance to the small-molecule therapeutic drug haloperidol is highly dose-dependent. Some of the loci identified had effects only at low doses of haloperidol, while other loci had effects primarily at higher concentrations of the drug. We show that a major QTL affecting resistance across all concentrations of haloperidol is caused by polymorphisms in SWH1, a homologue of human oxysterol binding protein. We identify a complex set of interactions among the alleles of the genes SWH1, MKT1, and IRA2 that are most pronounced at a haloperidol dose of 200 µM and are only observed when the remainder of the genome is of the RM background. Our results provide further insight into the genetic basis of drug resistance. PMID:25521586

Complexity theory and genetics: The computational power of crossing over

Czech Academy of Sciences Publication Activity Database

Pudlák, Pavel

2001-01-01

Roč. 171, č. 1 (2001), s. 201-223 ISSN 0890-5401 R&D Projects: GA AV ČR IAA1019901 Institutional research plan: CEZ:AV0Z1019905; CEZ:AV0Z1019905 Keywords : complexity * genetics * croning over Subject RIV: BA - General Mathematics Impact factor: 0.571, year: 2001

Note on transmitted complexity for quantum dynamical systems

Science.gov (United States)

Watanabe, Noboru; Muto, Masahiro

2017-10-01

Transmitted complexity (mutual entropy) is one of the important measures for quantum information theory developed recently in several ways. We will review the fundamental concepts of the Kossakowski, Ohya and Watanabe entropy and define a transmitted complexity for quantum dynamical systems. This article is part of the themed issue `Second quantum revolution: foundational questions'.

Research on application of complex-genetic algorithm in nuclear component optimal design

International Nuclear Information System (INIS)

He Shijing; Yan Changqi; Wang Jianjun; Wang Meng

2010-01-01

Complex algorithm is one of the most commonly used methods in the mechanical design optimization, such as the optimization of nuclear component. An improved method,complex-genetic algorithm(CGA), is developed based on traditional complex algorithm(TCA), in which the disadvantages of TCA have been overcome. An optimal calculation,which represents the pressurizer, is carried out in order to analyze the optimization capability of CGA. The results show that CGA has better optimizing performance than TCA. (authors)

Investigating dynamical complexity in the magnetosphere using various entropy measures

Science.gov (United States)

Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Kalimeri, Maria; Anastasiadis, Anastasios; Eftaxias, Konstantinos

2009-09-01

The complex system of the Earth's magnetosphere corresponds to an open spatially extended nonequilibrium (input-output) dynamical system. The nonextensive Tsallis entropy has been recently introduced as an appropriate information measure to investigate dynamical complexity in the magnetosphere. The method has been employed for analyzing Dst time series and gave promising results, detecting the complexity dissimilarity among different physiological and pathological magnetospheric states (i.e., prestorm activity and intense magnetic storms, respectively). This paper explores the applicability and effectiveness of a variety of computable entropy measures (e.g., block entropy, Kolmogorov entropy, T complexity, and approximate entropy) to the investigation of dynamical complexity in the magnetosphere. We show that as the magnetic storm approaches there is clear evidence of significant lower complexity in the magnetosphere. The observed higher degree of organization of the system agrees with that inferred previously, from an independent linear fractal spectral analysis based on wavelet transforms. This convergence between nonlinear and linear analyses provides a more reliable detection of the transition from the quiet time to the storm time magnetosphere, thus showing evidence that the occurrence of an intense magnetic storm is imminent. More precisely, we claim that our results suggest an important principle: significant complexity decrease and accession of persistency in Dst time series can be confirmed as the magnetic storm approaches, which can be used as diagnostic tools for the magnetospheric injury (global instability). Overall, approximate entropy and Tsallis entropy yield superior results for detecting dynamical complexity changes in the magnetosphere in comparison to the other entropy measures presented herein. Ultimately, the analysis tools developed in the course of this study for the treatment of Dst index can provide convenience for space weather

Using Genetic Algorithms for Navigation Planning in Dynamic Environments

Directory of Open Access Journals (Sweden)

Ferhat Uçan

2012-01-01

Full Text Available Navigation planning can be considered as a combination of searching and executing the most convenient flight path from an initial waypoint to a destination waypoint. Generally the aim is to follow the flight path, which provides minimum fuel consumption for the air vehicle. For dynamic environments, constraints change dynamically during flight. This is a special case of dynamic path planning. As the main concern of this paper is flight planning, the conditions and objectives that are most probable to be used in navigation problem are considered. In this paper, the genetic algorithm solution of the dynamic flight planning problem is explained. The evolutionary dynamic navigation planning algorithm is developed for compensating the existing deficiencies of the other approaches. The existing fully dynamic algorithms process unit changes to topology one modification at a time, but when there are several such operations occurring in the environment simultaneously, the algorithms are quite inefficient. The proposed algorithm may respond to the concurrent constraint updates in a shorter time for dynamic environment. The most secure navigation of the air vehicle is planned and executed so that the fuel consumption is minimum.

Lyapunov exponents a tool to explore complex dynamics

CERN Document Server

Pikovsky, Arkady

2016-01-01

Lyapunov exponents lie at the heart of chaos theory, and are widely used in studies of complex dynamics. Utilising a pragmatic, physical approach, this self-contained book provides a comprehensive description of the concept. Beginning with the basic properties and numerical methods, it then guides readers through to the most recent advances in applications to complex systems. Practical algorithms are thoroughly reviewed and their performance is discussed, while a broad set of examples illustrate the wide range of potential applications. The description of various numerical and analytical techniques for the computation of Lyapunov exponents offers an extensive array of tools for the characterization of phenomena such as synchronization, weak and global chaos in low and high-dimensional set-ups, and localization. This text equips readers with all the investigative expertise needed to fully explore the dynamical properties of complex systems, making it ideal for both graduate students and experienced researchers...

Understanding Learner Agency as a Complex Dynamic System

Science.gov (United States)

Mercer, Sarah

2011-01-01

This paper attempts to contribute to a fuller understanding of the nature of language learner agency by considering it as a complex dynamic system. The purpose of the study was to explore detailed situated data to examine to what extent it is feasible to view learner agency through the lens of complexity theory. Data were generated through a…

How spatio-temporal habitat connectivity affects amphibian genetic structure.

Science.gov (United States)

Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

How spatio-temporal habitat connectivity affects amphibian genetic structure

Science.gov (United States)

Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Random complex dynamics and devil's coliseums

Science.gov (United States)

Sumi, Hiroki

2015-04-01

We investigate the random dynamics of polynomial maps on the Riemann sphere \\hat{\\Bbb{C}} and the dynamics of semigroups of polynomial maps on \\hat{\\Bbb{C}} . In particular, the dynamics of a semigroup G of polynomials whose planar postcritical set is bounded and the associated random dynamics are studied. In general, the Julia set of such a G may be disconnected. We show that if G is such a semigroup, then regarding the associated random dynamics, the chaos of the averaged system disappears in the C0 sense, and the function T∞ of probability of tending to ∞ \\in \\hat{\\Bbb{C}} is Hölder continuous on \\hat{\\Bbb{C}} and varies only on the Julia set of G. Moreover, the function T∞ has a kind of monotonicity. It turns out that T∞ is a complex analogue of the devil's staircase, and we call T∞ a ‘devil’s coliseum'. We investigate the details of T∞ when G is generated by two polynomials. In this case, T∞ varies precisely on the Julia set of G, which is a thin fractal set. Moreover, under this condition, we investigate the pointwise Hölder exponents of T∞.

Modular interdependency in complex dynamical systems.

Science.gov (United States)

Watson, Richard A; Pollack, Jordan B

2005-01-01

Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability.

The Leadership Game : Experiencing Dynamic Complexity under Deep Uncertainty

NARCIS (Netherlands)

Pruyt, E.; Segers, J.; Oruc, S.

2011-01-01

In this ever more complex, interconnected, and uncertain world, leadership is needed more than ever. But the literature and most leaders largely ignore dynamic complexity and deep uncertainty: only futures characterized by ever faster change, ever more (required) flexibility, and ever more scarcity

Bistable responses in bacterial genetic networks: Designs and dynamical consequences

Science.gov (United States)

Tiwari, Abhinav; Ray, J. Christian J.; Narula, Jatin; Igoshin, Oleg A.

2011-01-01

A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles for networks with bistable responses. PMID:21385588

Encyclopedia of Complexity and Systems Science

CERN Document Server

Meyers, Robert A

2009-01-01

Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...

Conceptualizing Teacher Identity as a Complex Dynamic System: The Inner Dynamics of Transformations during a Practicum

Science.gov (United States)

Henry, Alastair

2016-01-01

Currently, the inner dynamics of teacher identity transformations remain a "black box." Conceptualizing preservice teacher identity as a complex dynamic system, and the notion of "being someone who teaches" in dialogical terms as involving shifts between different teacher voices, the study investigates the dynamical processes…

Global genetic response in a cancer cell: self-organized coherent expression dynamics.

Directory of Open Access Journals (Sweden)

Masa Tsuchiya

Full Text Available Understanding the basic mechanism of the spatio-temporal self-control of genome-wide gene expression engaged with the complex epigenetic molecular assembly is one of major challenges in current biological science. In this study, the genome-wide dynamical profile of gene expression was analyzed for MCF-7 breast cancer cells induced by two distinct ErbB receptor ligands: epidermal growth factor (EGF and heregulin (HRG, which drive cell proliferation and differentiation, respectively. We focused our attention to elucidate how global genetic responses emerge and to decipher what is an underlying principle for dynamic self-control of genome-wide gene expression. The whole mRNA expression was classified into about a hundred groups according to the root mean square fluctuation (rmsf. These expression groups showed characteristic time-dependent correlations, indicating the existence of collective behaviors on the ensemble of genes with respect to mRNA expression and also to temporal changes in expression. All-or-none responses were observed for HRG and EGF (biphasic statistics at around 10-20 min. The emergence of time-dependent collective behaviors of expression occurred through bifurcation of a coherent expression state (CES. In the ensemble of mRNA expression, the self-organized CESs reveals distinct characteristic expression domains for biphasic statistics, which exhibits notably the presence of criticality in the expression profile as a route for genomic transition. In time-dependent changes in the expression domains, the dynamics of CES reveals that the temporal development of the characteristic domains is characterized as autonomous bistable switch, which exhibits dynamic criticality (the temporal development of criticality in the genome-wide coherent expression dynamics. It is expected that elucidation of the biophysical origin for such critical behavior sheds light on the underlying mechanism of the control of whole genome.

Data based identification and prediction of nonlinear and complex dynamical systems

Science.gov (United States)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

Data based identification and prediction of nonlinear and complex dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

2016-07-12

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

Data based identification and prediction of nonlinear and complex dynamical systems

International Nuclear Information System (INIS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-01-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

Directory of Open Access Journals (Sweden)

Xianjun Shen

Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

Environmental coupling and population dynamics in the PE545 light-harvesting complex

Energy Technology Data Exchange (ETDEWEB)

Aghtar, Mortaza; Kleinekathöfer, Ulrich, E-mail: u.kleinekathoefer@jacobs-university.de

2016-01-15

Long-lived quantum coherences have been shown experimentally in the Fenna–Matthews–Olson (FMO) complex of green sulfur bacteria as well as in the phycoerythrin 545 (PE545) photosynthetic antenna system of marine algae. A combination of classical molecular dynamics simulations, quantum chemistry and quantum dynamical calculations is employed to determine the excitation transfer dynamics in PE545. One key property of the light-harvesting system concerning the excitation transfer and dephasing phenomena is the spectral density. This quantity is determined from time series of the vertical excitation energies of the aggregate. In the present study we focus on the quantum dynamical simulations using the earlier QM/MM calculations as input. Employing an ensemble-averaged classical path-based wave packet dynamics, the excitation transfer dynamics between the different bilins in the PE545 complex is determined and analyzed. Furthermore, the nature of the environmental fluctuations determining the transfer dynamics is discussed. - Highlights: • Modeling of excitation energy transfer in the light-harvesting system PE545. • Combination of molecular dynamics simulations, quantum chemistry and quantum dynamics. • Spectral densities for bilins in the PE545 complex.

Effects of complex life cycles on genetic diversity: cyclical parthenogenesis.

Science.gov (United States)

Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

2016-11-01

Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks).

Emergence of dynamical order synchronization phenomena in complex systems

CERN Document Server

Manrubia, Susanna C; Zanette, Damián H

2004-01-01

Synchronization processes bring about dynamical order and lead tospontaneous development of structural organization in complex systemsof various origins, from chemical oscillators and biological cells tohuman societies and the brain. This book provides a review and adetailed theoretical analysis of synchronization phenomena in complexsystems with different architectures, composed of elements withperiodic or chaotic individual dynamics. Special attention is paid tostatistical concepts, such as nonequilibrium phase transitions, orderparameters and dynamical glasses.

Bayesian state space models for dynamic genetic network construction across multiple tissues.

Science.gov (United States)

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Tracking excited-state charge and spin dynamics in iron coordination complexes

DEFF Research Database (Denmark)

Zhang, Wenkai; Alonso-Mori, Roberto; Bergmann, Uwe

2014-01-01

to spin state, can elucidate the spin crossover dynamics of [Fe(2,2'-bipyridine)(3)](2+) on photoinduced metal-to-ligand charge transfer excitation. We are able to track the charge and spin dynamics, and establish the critical role of intermediate spin states in the crossover mechanism. We anticipate......Crucial to many light-driven processes in transition metal complexes is the absorption and dissipation of energy by 3d electrons(1-4). But a detailed understanding of such non-equilibrium excited-state dynamics and their interplay with structural changes is challenging: a multitude of excited...... states and possible transitions result in phenomena too complex to unravel when faced with the indirect sensitivity of optical spectroscopy to spin dynamics(5) and the flux limitations of ultrafast X-ray sources(6,7). Such a situation exists for archetypal poly-pyridyl iron complexes, such as [Fe(2...

Drosophila growth cones: a genetically tractable platform for the analysis of axonal growth dynamics.

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Sánchez-Soriano, Natalia; Gonçalves-Pimentel, Catarina; Beaven, Robin; Haessler, Ulrike; Ofner-Ziegenfuss, Lisa; Ballestrem, Christoph; Prokop, Andreas

2010-01-01

The formation of neuronal networks, during development and regeneration, requires outgrowth of axons along reproducible paths toward their appropriate postsynaptic target cells. Axonal extension occurs at growth cones (GCs) at the tips of axons. GC advance and navigation requires the activity of their cytoskeletal networks, comprising filamentous actin (F-actin) in lamellipodia and filopodia as well as dynamic microtubules (MTs) emanating from bundles of the axonal core. The molecular mechanisms governing these two cytoskeletal networks, their cross-talk, and their response to extracellular signaling cues are only partially understood, hindering our conceptual understanding of how regulated changes in GC behavior are controlled. Here, we introduce Drosophila GCs as a suitable model to address these mechanisms. Morphological and cytoskeletal readouts of Drosophila GCs are similar to those of other models, including mammals, as demonstrated here for MT and F-actin dynamics, axonal growth rates, filopodial structure and motility, organizational principles of MT networks, and subcellular marker localization. Therefore, we expect fundamental insights gained in Drosophila to be translatable into vertebrate biology. The advantage of the Drosophila model over others is its enormous amenability to combinatorial genetics as a powerful strategy to address the complexity of regulatory networks governing axonal growth. Thus, using pharmacological and genetic manipulations, we demonstrate a role of the actin cytoskeleton in a specific form of MT organization (loop formation), known to regulate GC pausing behavior. We demonstrate these events to be mediated by the actin-MT linking factor Short stop, thus identifying an essential molecular player in this context.

Synchronization in Complex Networks of Nonlinear Dynamical Systems

CERN Document Server

Wu, Chai Wah

2007-01-01

This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ide

Transparency in complex dynamic food supply chains

NARCIS (Netherlands)

Trienekens, J.H.; Wognum, P.M.; Beulens, A.J.M.; Vorst, van der J.G.A.J.

2012-01-01

Food supply chains are increasingly complex and dynamic due to (i) increasing product proliferation to serve ever diversifying and globalising markets as a form of mass customisation with resulting global flows of raw materials, ingredients and products, and (ii) the need to satisfy changing and

Dynamic Load Balanced Clustering using Elitism based Random Immigrant Genetic Approach for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

K. Mohaideen Pitchai

2017-07-01

Full Text Available Wireless Sensor Network (WSN consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP. In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network.

Perceived price complexity of dynamic energy tariffs: An investigation of antecedents and consequences

International Nuclear Information System (INIS)

Layer, Patrick; Feurer, Sven; Jochem, Patrick

2017-01-01

Dynamic tariffs have the potential to contribute to a successful shift from conventional to renewable energies, but tapping this potential in Europe ultimately depends on residential consumers selecting them. This study proposes and finds that consumer reactions to dynamic tariffs depend on the level of perceived price complexity that represents the cognitive effort consumers must engage in to compute the overall bill amount. An online experiment conducted with a representative sample of 664 German residential energy consumers examines how salient characteristics of dynamic tariffs contribute to perceived price complexity. Subsequently, a structural equation model (SEM) reveals that the depth of information processing is central to understand how price complexity relates to consumers’ behavioral intentions. The results suggest that it will be challenging to convince European consumers to select complex dynamic tariffs under the current legal framework. Policymakers will need to find ways to make these tariffs more attractive. - Highlights: • Little is known about the processes by which consumers evaluate dynamic tariffs. • In this evaluation process perceived price complexity plays a central role. • Tariff type, price endings, and discount presentation format drive price complexity. • Perceived price complexity decreases the depth of information processing. • A decreased depth of information processing ultimately leads to lower behavioral intentions.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

Science.gov (United States)

Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

Monitoring Forest Dynamics in the Andean Amazon: The Applicability of Breakpoint Detection Methods Using Landsat Time-Series and Genetic Algorithms

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Fabián Santos

2017-01-01

Full Text Available The Andean Amazon is an endangered biodiversity hot spot but its forest dynamics are less studied than those of the Amazon lowland and forests from middle or high latitudes. This is because its landscape variability, complex topography and cloudy conditions constitute a challenging environment for any remote-sensing assessment. Breakpoint detection with Landsat time-series data is an established robust approach for monitoring forest dynamics around the globe but has not been properly evaluated for implementation in the Andean Amazon. We analyzed breakpoint detection-generated forest dynamics in order to determine its limitations when applied to three different study areas located along an altitude gradient in the Andean Amazon in Ecuador. Using all available Landsat imagery for the period 1997–2016, we evaluated different pre-processing approaches, noise reduction techniques, and breakpoint detection algorithms. These procedures were integrated into a complex function called the processing chain generator. Calibration was not straightforward since it required us to define values for 24 parameters. To solve this problem, we implemented a novel approach using genetic algorithms. We calibrated the processing chain generator by applying a stratified training sampling and a reference dataset based on high resolution imagery. After the best calibration solution was found and the processing chain generator executed, we assessed accuracy and found that data gaps, inaccurate co-registration, radiometric variability in sensor calibration, unmasked cloud, and shadows can drastically affect the results, compromising the application of breakpoint detection in mountainous areas of the Andean Amazon. Moreover, since breakpoint detection analysis of landscape variability in the Andean Amazon requires a unique calibration of algorithms, the time required to optimize analysis could complicate its proper implementation and undermine its application for large

Molecular dynamics study of thermodynamic stability and dynamics of [Li(glyme)]+ complex in lithium-glyme solvate ionic liquids

Science.gov (United States)

Shinoda, Wataru; Hatanaka, Yuta; Hirakawa, Masashi; Okazaki, Susumu; Tsuzuki, Seiji; Ueno, Kazuhide; Watanabe, Masayoshi

2018-05-01

Equimolar mixtures of glymes and organic lithium salts are known to produce solvate ionic liquids, in which the stability of the [Li(glyme)]+ complex plays an important role in determining the ionic dynamics. Since these mixtures have attractive physicochemical properties for application as electrolytes, it is important to understand the dependence of the stability of the [Li(glyme)]+ complex on the ion dynamics. A series of microsecond molecular dynamics simulations has been conducted to investigate the dynamic properties of these solvate ionic liquids. Successful solvate ionic liquids with high stability of the [Li(glyme)]+ complex have been shown to have enhanced ion dynamics. Li-glyme pair exchange rarely occurs: its characteristic time is longer than that of ion diffusion by one or two orders of magnitude. Li-glyme pair exchange most likely occurs through cluster formation involving multiple [Li(glyme)]+ pairs. In this process, multiple exchanges likely take place in a concerted manner without the production of energetically unfavorable free glyme or free Li+ ions.

Thinking in complexity the complex dynamics of matter, mind, and mankind

CERN Document Server

Mainzer, Klaus

1994-01-01

The theory of nonlinear complex systems has become a successful and widely used problem-solving approach in the natural sciences - from laser physics, quantum chaos and meteorology to molecular modeling in chemistry and computer simulations of cell growth in biology In recent times it has been recognized that many of the social, ecological and political problems of mankind are also of a global, complex and nonlinear nature And one of the most exciting topics of present scientific and public interest is the idea that even the human mind is governed largely by the nonlinear dynamics of complex systems In this wide-ranging but concise treatment Prof Mainzer discusses, in nontechnical language, the common framework behind these endeavours Special emphasis is given to the evolution of new structures in natural and cultural systems and it is seen clearly how the new integrative approach of complexity theory can give new insights that were not available using traditional reductionistic methods

Imaging dynamic redox processes with genetically encoded probes.

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Ezeriņa, Daria; Morgan, Bruce; Dick, Tobias P

2014-08-01

Redox signalling plays an important role in many aspects of physiology, including that of the cardiovascular system. Perturbed redox regulation has been associated with numerous pathological conditions; nevertheless, the causal relationships between redox changes and pathology often remain unclear. Redox signalling involves the production of specific redox species at specific times in specific locations. However, until recently, the study of these processes has been impeded by a lack of appropriate tools and methodologies that afford the necessary redox species specificity and spatiotemporal resolution. Recently developed genetically encoded fluorescent redox probes now allow dynamic real-time measurements, of defined redox species, with subcellular compartment resolution, in intact living cells. Here we discuss the available genetically encoded redox probes in terms of their sensitivity and specificity and highlight where uncertainties or controversies currently exist. Furthermore, we outline major goals for future probe development and describe how progress in imaging methodologies will improve our ability to employ genetically encoded redox probes in a wide range of situations. This article is part of a special issue entitled "Redox Signalling in the Cardiovascular System." Copyright © 2014 Elsevier Ltd. All rights reserved.

Spreading dynamics on complex networks: a general stochastic approach.

Science.gov (United States)

Noël, Pierre-André; Allard, Antoine; Hébert-Dufresne, Laurent; Marceau, Vincent; Dubé, Louis J

2014-12-01

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

NARCIS (Netherlands)

Heidema, A.G.; Boer, J.M.A.; Nagelkerke, N.; Mariman, E.C.M.; A, van der D.L.; Feskens, E.J.M.

2006-01-01

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods

Inferring genetic architecture of complex traits using Bayesian integrative analysis of genome and transcriptiome data

DEFF Research Database (Denmark)

Ehsani, Alireza; Sørensen, Peter; Pomp, Daniel

2012-01-01

Background To understand the genetic architecture of complex traits and bridge the genotype-phenotype gap, it is useful to study intermediate -omics data, e.g. the transcriptome. The present study introduces a method for simultaneous quantification of the contributions from single nucleotide......-modal distribution of genomic values collapses, when gene expressions are added to the model Conclusions With increased availability of various -omics data, integrative approaches are promising tools for understanding the genetic architecture of complex traits. Partitioning of explained variances at the chromosome...

Temporal dynamics of genetic variability in a mountain goat (Oreamnos americanus) population.

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Ortego, Joaquín; Yannic, Glenn; Shafer, Aaron B A; Mainguy, Julien; Festa-Bianchet, Marco; Coltman, David W; Côté, Steeve D

2011-04-01

The association between population dynamics and genetic variability is of fundamental importance for both evolutionary and conservation biology. We combined long-term population monitoring and molecular genetic data from 123 offspring and their parents at 28 microsatellite loci to investigate changes in genetic diversity over 14 cohorts in a small and relatively isolated population of mountain goats (Oreamnos americanus) during a period of demographic increase. Offspring heterozygosity decreased while parental genetic similarity and inbreeding coefficients (F(IS) ) increased over the study period (1995-2008). Immigrants introduced three novel alleles into the population and matings between residents and immigrants produced more heterozygous offspring than local crosses, suggesting that immigration can increase population genetic variability. The population experienced genetic drift over the study period, reflected by a reduced allelic richness over time and an 'isolation-by-time' pattern of genetic structure. The temporal decline of individual genetic diversity despite increasing population size probably resulted from a combination of genetic drift due to small effective population size, inbreeding and insufficient counterbalancing by immigration. This study highlights the importance of long-term genetic monitoring to understand how demographic processes influence temporal changes of genetic diversity in long-lived organisms. © 2011 Blackwell Publishing Ltd.

Dynamic properties of epidemic spreading on finite size complex networks

Science.gov (United States)

Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

2005-11-01

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Green turtle (Chelonia mydas genetic diversity at Paranaguá Estuarine Complex feeding grounds in Brazil

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Juliana Costa Jordão

2015-09-01

Full Text Available Sea turtles are marine reptiles that undertake long migrations through their life, with limited information regarding juvenile stages. Feeding grounds (FGs, where they spend most of their lives, are composed by individuals from different natal origins, known as mixed stock populations. The aim of this study was to assess genetic composition, natal origins and demographic history of juvenile green turtles (Chelonia mydas at the Paranaguá Estuarine Complex (PEC, Brazil, considered a Natural World Heritage site. Tissue samples of stranded animals were collected (n = 60, and 700 bp mitochondrial DNA sequences were generated and compared to shorter sequences from previously published studies. Global exact tests of differentiation revealed significant differences among PEC and the other FGs, except those at the South Atlantic Ocean. Green turtles at PEC present genetic signatures similar to those of nesting females from Ascension Island, Guinea Bissau and Aves Island/Surinam. Population expansion was evidenced to have occurred 20–25 kYA, reinforcing the hypothesis of recovery from Southern Atlantic refugia after the last Glacial Maximum. These results contribute to a better understanding of the dynamics of green turtle populations at a protected area by providing knowledge on the dispersion patterns and reinforcing the importance of the interconnectivity between nesting and foraging populations.

Dynamic coherence in excitonic molecular complexes under various excitation conditions

Energy Technology Data Exchange (ETDEWEB)

Chenu, Aurélia; Malý, Pavel; Mančal, Tomáš, E-mail: mancal@karlov.mff.cuni.cz

2014-08-17

Highlights: • Dynamic coherence does not improve energy transfer efficiency in natural conditions. • Photo-induced quantum jumps are discussed in classical context. • Natural time scale of a light excitation event is identified. • Coherence in FMO complex averages out under excitation by neighboring antenna. • This result is valid even in absence of dissipation. - Abstract: We investigate the relevance of dynamic quantum coherence in the energy transfer efficiency of molecular aggregates. We derive the time evolution of the density matrix for an open quantum system excited by light or by a neighboring antenna. Unlike in the classical case, the quantum description does not allow for a formal decomposition of the dynamics into sudden jumps in an observable quantity – an expectation value. Rather, there is a natural finite time-scale associated with the excitation process. We propose a simple experiment to test the influence of this time scale on the yield of photosynthesis. We demonstrate, using typical parameters of the Fenna–Matthews–Olson (FMO) complex and a typical energy transfer rate from the chlorosome baseplate, that dynamic coherences are averaged out in the complex even when the FMO model is completely free of all dissipation and dephasing.

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

Science.gov (United States)

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

How complex a dynamical network can be?

International Nuclear Information System (INIS)

Baptista, M.S.; Kakmeni, F. Moukam; Del Magno, Gianluigi; Hussein, M.S.

2011-01-01

Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen; (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes.

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

International Nuclear Information System (INIS)

Huang, Xiaobiao; Safranek, James

2014-01-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

Energy Technology Data Exchange (ETDEWEB)

Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

Complex Hamiltonian Dynamics

CERN Document Server

Bountis, Tassos

2012-01-01

This book introduces and explores modern developments in the well established field of Hamiltonian dynamical systems. It focuses on high degree-of-freedom systems and the transitional regimes between regular and chaotic motion. The role of nonlinear normal modes is highlighted and the importance of low-dimensional tori in the resolution of the famous FPU paradox is emphasized. Novel powerful numerical methods are used to study localization phenomena and distinguish order from strongly and weakly chaotic regimes. The emerging hierarchy of complex structures in such regimes gives rise to particularly long-lived patterns and phenomena called quasi-stationary states, which are explored in particular in the concrete setting of one-dimensional Hamiltonian lattices and physical applications in condensed matter systems.  The self-contained and pedagogical approach is blended with a unique balance between mathematical rigor, physics insights and concrete applications. End of chapter exercises and (more demanding) res...

A Comprehensive Genomic Analysis Reveals the Genetic Landscape of Mitochondrial Respiratory Chain Complex Deficiencies.

Directory of Open Access Journals (Sweden)

Masakazu Kohda

2016-01-01

Full Text Available Mitochondrial disorders have the highest incidence among congenital metabolic disorders characterized by biochemical respiratory chain complex deficiencies. It occurs at a rate of 1 in 5,000 births, and has phenotypic and genetic heterogeneity. Mutations in about 1,500 nuclear encoded mitochondrial proteins may cause mitochondrial dysfunction of energy production and mitochondrial disorders. More than 250 genes that cause mitochondrial disorders have been reported to date. However exact genetic diagnosis for patients still remained largely unknown. To reveal this heterogeneity, we performed comprehensive genomic analyses for 142 patients with childhood-onset mitochondrial respiratory chain complex deficiencies. The approach includes whole mtDNA and exome analyses using high-throughput sequencing, and chromosomal aberration analyses using high-density oligonucleotide arrays. We identified 37 novel mutations in known mitochondrial disease genes and 3 mitochondria-related genes (MRPS23, QRSL1, and PNPLA4 as novel causative genes. We also identified 2 genes known to cause monogenic diseases (MECP2 and TNNI3 and 3 chromosomal aberrations (6q24.3-q25.1, 17p12, and 22q11.21 as causes in this cohort. Our approaches enhance the ability to identify pathogenic gene mutations in patients with biochemically defined mitochondrial respiratory chain complex deficiencies in clinical settings. They also underscore clinical and genetic heterogeneity and will improve patient care of this complex disorder.

Metrical and dynamical aspects in complex analysis

CERN Document Server

2017-01-01

The central theme of this reference book is the metric geometry of complex analysis in several variables. Bridging a gap in the current literature, the text focuses on the fine behavior of the Kobayashi metric of complex manifolds and its relationships to dynamical systems, hyperbolicity in the sense of Gromov and operator theory, all very active areas of research. The modern points of view expressed in these notes, collected here for the first time, will be of interest to academics working in the fields of several complex variables and metric geometry. The different topics are treated coherently and include expository presentations of the relevant tools, techniques and objects, which will be particularly useful for graduate and PhD students specializing in the area.

Modeling and complexity of stochastic interacting Lévy type financial price dynamics

Science.gov (United States)

Wang, Yiduan; Zheng, Shenzhou; Zhang, Wei; Wang, Jun; Wang, Guochao

2018-06-01

In attempt to reproduce and investigate nonlinear dynamics of security markets, a novel nonlinear random interacting price dynamics, which is considered as a Lévy type process, is developed and investigated by the combination of lattice oriented percolation and Potts dynamics, which concerns with the instinctive random fluctuation and the fluctuation caused by the spread of the investors' trading attitudes, respectively. To better understand the fluctuation complexity properties of the proposed model, the complexity analyses of random logarithmic price return and corresponding volatility series are preformed, including power-law distribution, Lempel-Ziv complexity and fractional sample entropy. In order to verify the rationality of the proposed model, the corresponding studies of actual security market datasets are also implemented for comparison. The empirical results reveal that this financial price model can reproduce some important complexity features of actual security markets to some extent. The complexity of returns decreases with the increase of parameters γ1 and β respectively, furthermore, the volatility series exhibit lower complexity than the return series

The Influence of Information Acquisition on the Complex Dynamics of Market Competition

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Guo, Zhanbing; Ma, Junhai

In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

The Effects of Predator Evolution and Genetic Variation on Predator-Prey Population-Level Dynamics.

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Cortez, Michael H; Patel, Swati

2017-07-01

This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator-prey systems. We do this by analyzing a general eco-evolutionary predator-prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator-prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator-prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.

Genetic Complexity of Episodic Memory: A Twin Approach to Studies of Aging

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Kremen, William S.; Spoon, Kelly M.; Jacobson, Kristen C.; Vasilopoulos, Terrie; McCaffery, Jeanne M.; Panizzon, Matthew S.; Franz, Carol E.; Vuoksimaa, Eero; Xian, Hong; Rana, Brinda K.; Toomey, Rosemary; McKenzie, Ruth; Lyons, Michael J.

2016-01-01

Episodic memory change is a central issue in cognitive aging, and understanding that process will require elucidation of its genetic underpinnings. A key limiting factor in genetically informed research on memory has been lack of attention to genetic and phenotypic complexity, as if “memory is memory” and all well-validated assessments are essentially equivalent. Here we applied multivariate twin models to data from late-middle-aged participants in the Vietnam Era Twin Study of Aging to examine the genetic architecture of 6 measures from 3 standard neuropsychological tests: the California Verbal Learning Test-2, and Wechsler Memory Scale-III Logical Memory (LM) and Visual Reproductions (VR). An advantage of the twin method is that it can estimate the extent to which latent genetic influences are shared or independent across different measures before knowing which specific genes are involved. The best-fitting model was a higher order common pathways model with a heritable higher order general episodic memory factor and three test-specific subfactors. More importantly, substantial genetic variance was accounted for by genetic influences that were specific to the latent LM and VR subfactors (28% and 30%, respectively) and independent of the general factor. Such unique genetic influences could partially account for replication failures. Moreover, if different genes influence different memory phenotypes, they could well have different age-related trajectories. This approach represents an important step toward providing critical information for all types of genetically informative studies of aging and memory. PMID:24956007

Phylogenetic relationships and genetic diversity of the Polypedates leucomystax complex in Thailand

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Kittisak Buddhachat

2018-01-01

Full Text Available Taxonomic uncertainty of the Asian tree frog Polypedates leucomystax complex presents the challenging task of inferring its biogeographical history. Here, we describe its dispersion and the genetic relationships among different populations in Thailand, where we connect the population of the P. leucomystax complex of the Sunda Islands to the Indochina (mainland population based on analyses of 266 sequences of the mitochondrial cytochrome c oxidase subunit I (COI gene. Our maternal genealogy implies that there are four well-supported lineages in Thailand, consisting of Northern A (clade A: Polypedates sp., Nan (clade B: P. cf. impresus, Southern (clade C: P. cf. leucomystax and Northern D (clade D: P. cf. megacephalus, with Bayesian posterior probability >0.9. Phylogeny and haplotype networks indicate that clades A, B and D are sympatric. In contrast, clade C (P. cf. leucomystax and clade D (P. cf. megacephalus are genetically divergent due to the geographical barrier of the Isthmus of Kra, resulting in an allopatric distribution. Climatic conditions, in particular differences in rainfall on each side of the Isthmus of Kra, may play an important role in limiting the immigration of both clades. For the within-populations of either clades C or D, there was no significant correlation between geographic and genetic distance by the isolation-by-distance test, indicating intraspecific-dispersal of each clade. Population expansion occurred in clade C, whereas clade D showed a constant population. Taken together, the P. leucomystax complex in South East Asia may have diversified under climatic pressure, leading to allopatric and/or sympatric speciation.

Complex Human Dynamics From Mind to Societies

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Winkowska-Nowak, Katarzyna; Brée, David

2013-01-01

This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".

The landscape genetics of infectious disease emergence and spread.

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Biek, Roman; Real, Leslie A

2010-09-01

The spread of parasites is inherently a spatial process often embedded in physically complex landscapes. It is therefore not surprising that infectious disease researchers are increasingly taking a landscape genetics perspective to elucidate mechanisms underlying basic ecological processes driving infectious disease dynamics and to understand the linkage between spatially dependent population processes and the geographic distribution of genetic variation within both hosts and parasites. The increasing availability of genetic information on hosts and parasites when coupled to their ecological interactions can lead to insights for predicting patterns of disease emergence, spread and control. Here, we review research progress in this area based on four different motivations for the application of landscape genetics approaches: (i) assessing the spatial organization of genetic variation in parasites as a function of environmental variability, (ii) using host population genetic structure as a means to parameterize ecological dynamics that indirectly influence parasite populations, for example, gene flow and movement pathways across heterogeneous landscapes and the concurrent transport of infectious agents, (iii) elucidating the temporal and spatial scales of disease processes and (iv) reconstructing and understanding infectious disease invasion. Throughout this review, we emphasize that landscape genetic principles are relevant to infection dynamics across a range of scales from within host dynamics to global geographic patterns and that they can also be applied to unconventional 'landscapes' such as heterogeneous contact networks underlying the spread of human and livestock diseases. We conclude by discussing some general considerations and problems for inferring epidemiological processes from genetic data and try to identify possible future directions and applications for this rapidly expanding field.

YouGenMap: a web platform for dynamic multi-comparative mapping and visualization of genetic maps

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Keith Batesole; Kokulapalan Wimalanathan; Lin Liu; Fan Zhang; Craig S. Echt; Chun Liang

2014-01-01

Comparative genetic maps are used in examination of genome organization, detection of conserved gene order, and exploration of marker order variations. YouGenMap is an open-source web tool that offers dynamic comparative mapping capability of users' own genetic mapping between 2 or more map sets. Users' genetic map data and optional gene annotations are...

Evolving hard problems: Generating human genetics datasets with a complex etiology

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Himmelstein Daniel S

2011-07-01

Full Text Available Abstract Background A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models. Results Here we develop and evaluate a model free evolution strategy to generate datasets which display a complex relationship between individual genotype and disease susceptibility. We show that this model free approach is capable of generating a diverse array of datasets with distinct gene-disease relationships for an arbitrary interaction order and sample size. We specifically generate eight-hundred Pareto fronts; one for each independent run of our algorithm. In each run the predictiveness of single genetic variation and pairs of genetic variants have been minimized, while the predictiveness of third, fourth, or fifth-order combinations is maximized. Two hundred runs of the algorithm are further dedicated to creating datasets with predictive four or five order interactions and minimized lower-level effects. Conclusions This method and the resulting datasets will allow the capabilities of novel methods to be tested without pre-specified genetic models. This allows researchers to evaluate which methods will succeed on human genetics problems where the model is not known in advance. We further make freely available to the community the entire Pareto-optimal front of datasets from each run so that novel methods may be rigorously evaluated. These 76,600 datasets are available from http://discovery.dartmouth.edu/model_free_data/.

Genetic Divergence of the Rhesus Macaque Major Histocompatibility Complex

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Daza-Vamenta, Riza; Glusman, Gustavo; Rowen, Lee; Guthrie, Brandon; Geraghty, Daniel E.

2004-01-01

The major histocompatibility complex (MHC) is comprised of the class I, class II, and class III regions, including the MHC class I and class II genes that play a primary role in the immune response and serve as an important model in studies of primate evolution. Although nonhuman primates contribute significantly to comparative human studies, relatively little is known about the genetic diversity and genomics underlying nonhuman primate immunity. To address this issue, we sequenced a complete rhesus macaque MHC spanning over 5.3 Mb, and obtained an additional 2.3 Mb from a second haplotype, including class II and portions of class I and class III. A major expansion of from six class I genes in humans to as many as 22 active MHC class I genes in rhesus and levels of sequence divergence some 10-fold higher than a similar human comparison were found, averaging from 2% to 6% throughout extended portions of class I and class II. These data pose new interpretations of the evolutionary constraints operating between MHC diversity and T-cell selection by contrasting with models predicting an optimal number of antigen presenting genes. For the clinical model, these data and derivative genetic tools can be implemented in ongoing genetic and disease studies that involve the rhesus macaque. PMID:15289473

Markovian dynamics on complex reaction networks

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Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

2013-08-10

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

Markovian dynamics on complex reaction networks

International Nuclear Information System (INIS)

Goutsias, J.; Jenkinson, G.

2013-01-01

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples

Nonlinear stochastic interacting dynamics and complexity of financial gasket fractal-like lattice percolation

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Zhang, Wei; Wang, Jun

2018-05-01

A novel nonlinear stochastic interacting price dynamics is proposed and investigated by the bond percolation on Sierpinski gasket fractal-like lattice, aim to make a new approach to reproduce and study the complexity dynamics of real security markets. Fractal-like lattices correspond to finite graphs with vertices and edges, which are similar to fractals, and Sierpinski gasket is a well-known example of fractals. Fractional ordinal array entropy and fractional ordinal array complexity are introduced to analyze the complexity behaviors of financial signals. To deeper comprehend the fluctuation characteristics of the stochastic price evolution, the complexity analysis of random logarithmic returns and volatility are preformed, including power-law distribution, fractional sample entropy and fractional ordinal array complexity. For further verifying the rationality and validity of the developed stochastic price evolution, the actual security market dataset are also studied with the same statistical methods for comparison. The empirical results show that this stochastic price dynamics can reconstruct complexity behaviors of the actual security markets to some extent.

Complex, Dynamic Systems: A New Transdisciplinary Theme for Applied Linguistics?

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Larsen-Freeman, Diane

2012-01-01

In this plenary address, I suggest that Complexity Theory has the potential to contribute a transdisciplinary theme to applied linguistics. Transdisciplinary themes supersede disciplines and spur new kinds of creative activity (Halliday 2001 [1990]). Investigating complex systems requires researchers to pay attention to system dynamics. Since…

Dynamic organization of genetic recombination proteins and chromosomes

International Nuclear Information System (INIS)

Essers, J.; Van Cappellen, G.; Van Drunen, E.; Theil, A.; Jaspers, N.N.G.J.; Houtsmuller, A.B.; Vermeulen, W.; Kanaar, R.

2003-01-01

Homologous recombination requires the co-ordinated action of the RAD52 group proteins, including Rad51, Rad52 and Rad54. Upon treatment of mammalian cells with ionizing radiation, these proteins accumulate into foci at sites of DSB induction. We probed the nature of the DNA damage-induced foci in living cells with the use of photobleaching techniques. These foci are not static assemblies of DNA repair proteins. Instead, they are dynamic structures of which Rad51 is a stable core component, while Rad52 and Rad54 reversibly interact with the structure. Furthermore, even though the RAD52 group proteins colocalize in the DNA damage-induced foci, the majority of the proteins are not part of the same multi-protein complex in the absence of DNA damage. Executing DNA transactions through dynamic multi-protein complexes, rather than stable holo-complexes, allows greater flexibility during the transaction. In case of DNA repair, for example, it allows cross talk between different DNA repair pathways and coupling to other DNA transactions, such as replication. In addition to the behavior of proteins in living cells, we have tracked chromosomes during cell division. Our results suggest that the relative position of chromosomes in the mother cell is conserved in its daughter cells

Discrete Dynamics Lab

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Wuensche, Andrew

DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.

Dynamic airspace configuration by genetic algorithm

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Marina Sergeeva

2017-06-01

Full Text Available With the continuous air traffic growth and limits of resources, there is a need for reducing the congestion of the airspace systems. Nowadays, several projects are launched, aimed at modernizing the global air transportation system and air traffic management. In recent years, special interest has been paid to the solution of the dynamic airspace configuration problem. Airspace sector configurations need to be dynamically adjusted to provide maximum efficiency and flexibility in response to changing weather and traffic conditions. The main objective of this work is to automatically adapt the airspace configurations according to the evolution of traffic. In order to reach this objective, the airspace is considered to be divided into predefined 3D airspace blocks which have to be grouped or ungrouped depending on the traffic situation. The airspace structure is represented as a graph and each airspace configuration is created using a graph partitioning technique. We optimize airspace configurations using a genetic algorithm. The developed algorithm generates a sequence of sector configurations for one day of operation with the minimized controller workload. The overall methodology is implemented and successfully tested with air traffic data taken for one day and for several different airspace control areas of Europe.

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

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Jianhua Xu

2013-01-01

Full Text Available Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD, classical statistics, and geostatistics. The main conclusions are as follows (1 The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2 The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3 The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform.

Dynamics of genetic processes in chronically irradiated populations of small mammals

International Nuclear Information System (INIS)

Ryabokon', N.I.; Goncharova, R.I.; Smolich, I.I.; Kapitanova, N.P.; Nikitchenko, N.V.

2000-01-01

The distinctive features of dynamics of mutagenesis in mammalian populations under chronic low-intensive irradiation were first revealed. The main of them is gradual increase in mutability in somatic cells and embryonal lethality during series of irradiated generations of animals (bank vole - Clethrionomys glareolus). The data obtained strongly suggest that there are oppositely directed processes in natural populations after irradiation of more than 20 generations of animals: on the one hand, accumulation of mutations (genetic load of populations) and pre-mutation events which increase genome instability of germ and somatic cells in consecutive generations of animals, and on the other, formation of genetic radio adaptation through better functioning protection systems. In this period of micro evolution in chronically irradiated populations, the frequencies of genetic damages could be higher if the radiation adaptation doesn't form. (authors)

Analysis of Instantaneous Linear, Nonlinear and Complex Cardiovascular Dynamics from Videophotoplethysmography.

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Valenza, Gaetano; Iozzia, Luca; Cerina, Luca; Mainardi, Luca; Barbieri, Riccardo

2018-05-01

There is a fast growing interest in the use of non-contact devices for health and performance assessment in humans. In particular, the use of non-contact videophotoplethysmography (vPPG) has been recently demonstrated as a feasible way to extract cardiovascular information. Nevertheless, proper validation of vPPG-derived heartbeat dynamics is still missing. We aim to an in-depth validation of time-varying, linear and nonlinear/complex dynamics of the pulse rate variability extracted from vPPG. We apply inhomogeneous pointprocess nonlinear models to assess instantaneous measures defined in the time, frequency, and bispectral domains as estimated through vPPG and standard ECG. Instantaneous complexity measures, such as the instantaneous Lyapunov exponents and the recently defined inhomogeneous point-process approximate and sample entropy, were estimated as well. Video recordings were processed using our recently proposed method based on zerophase principal component analysis. Experimental data were gathered from 60 young healthy subjects (age: 24±3 years) undergoing postural changes (rest-to-stand maneuver). Group averaged results show that there is an overall agreement between linear and nonlinear/complexity indices computed from ECG and vPPG during resting state conditions. However, important differences are found, particularly in the bispectral and complexity domains, in recordings where the subjects has been instructed to stand up. Although significant differences exist between cardiovascular estimates from vPPG and ECG, it is very promising that instantaneous sympathovagal changes, as well as time-varying complex dynamics, were correctly identified, especially during resting state. In addition to a further improvement of the video signal quality, more research is advocated towards a more precise estimation of cardiovascular dynamics by a comprehensive nonlinear/complex paradigm specifically tailored to the non-contact quantification. Schattauer GmbH.

Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

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Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

2017-09-01

In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

Communication of genetic information to families with inherited rhythm disorders.

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Burns, Charlotte; James, Cynthia; Ingles, Jodie

2017-11-23

Given the dynamic nature of the electrical activity of the heart and ongoing challenges in the diagnostics of inherited heart rhythm disorders, genetic information can be a vital aspect of family management. Communication of genetic information is complex, and the responsibility to convey this information to the family lies with the proband. Current practice falls short, requiring additional support from the clinician and multidisciplinary team. Communication is a 2-part iterative process, reliant on both the understanding of the probands and their ability to effectively communicate with relatives. With the surge of high-throughput genetic testing, results generated are increasingly complex, making the task of communication more challenging. Here we discuss 3 key issues. First, the probabilistic nature of genetic test results means uncertainty is inherent to the practice. Second, secondary findings may arise. Third, personal preferences, values, and family dynamics also come into play and must be acknowledged when considering how best to support effective communication. Here we provide insight into the challenges and provide practical advice for clinicians to support effective family communication. These strategies include acknowledging and managing genetic uncertainty, genetic counseling and informed consent, and consideration of personal and familial barriers to effective communication. We will explore the potential for developing resources to assist clinicians in providing patients with sufficient knowledge and support to communicate complex information to their at-risk relatives. Specialized multidisciplinary clinics remain the best equipped to manage patients and families with inherited heart rhythm disorders given the need for a high level of information and support. Copyright © 2017 Heart Rhythm Society. All rights reserved.

Complexity, fractal dynamics and determinism in treadmill ambulation: Implications for clinical biomechanists.

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Hollman, John H; Watkins, Molly K; Imhoff, Angela C; Braun, Carly E; Akervik, Kristen A; Ness, Debra K

2016-08-01

Reduced inter-stride complexity during ambulation may represent a pathologic state. Evidence is emerging that treadmill training for rehabilitative purposes may constrain the locomotor system and alter gait dynamics in a way that mimics pathological states. The purpose of this study was to examine the dynamical system components of gait complexity, fractal dynamics and determinism during treadmill ambulation. Twenty healthy participants aged 23.8 (1.2) years walked at preferred walking speeds for 6min on a motorized treadmill and overground while wearing APDM 6 Opal inertial monitors. Stride times, stride lengths and peak sagittal plane trunk velocities were measured. Mean values and estimates of complexity, fractal dynamics and determinism were calculated for each parameter. Data were compared between overground and treadmill walking conditions. Mean values for each gait parameter were statistically equivalent between overground and treadmill ambulation (P>0.05). Through nonlinear analyses, however, we found that complexity in stride time signals (P<0.001), and long-range correlations in stride time and stride length signals (P=0.005 and P=0.024, respectively), were reduced on the treadmill. Treadmill ambulation induces more predictable inter-stride time dynamics and constrains fluctuations in stride times and stride lengths, which may alter feedback from destabilizing perturbations normally experienced by the locomotor control system during overground ambulation. Treadmill ambulation, therefore, may provide less opportunity for experiencing the adaptability necessary to successfully ambulate overground. Investigators and clinicians should be aware that treadmill ambulation will alter dynamic gait characteristics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Capturing complexity in work disability research: application of system dynamics modeling methodology.

Science.gov (United States)

Jetha, Arif; Pransky, Glenn; Hettinger, Lawrence J

2016-01-01

Work disability (WD) is characterized by variable and occasionally undesirable outcomes. The underlying determinants of WD outcomes include patterns of dynamic relationships among health, personal, organizational and regulatory factors that have been challenging to characterize, and inadequately represented by contemporary WD models. System dynamics modeling (SDM) methodology applies a sociotechnical systems thinking lens to view WD systems as comprising a range of influential factors linked by feedback relationships. SDM can potentially overcome limitations in contemporary WD models by uncovering causal feedback relationships, and conceptualizing dynamic system behaviors. It employs a collaborative and stakeholder-based model building methodology to create a visual depiction of the system as a whole. SDM can also enable researchers to run dynamic simulations to provide evidence of anticipated or unanticipated outcomes that could result from policy and programmatic intervention. SDM may advance rehabilitation research by providing greater insights into the structure and dynamics of WD systems while helping to understand inherent complexity. Challenges related to data availability, determining validity, and the extensive time and technical skill requirements for model building may limit SDM's use in the field and should be considered. Contemporary work disability (WD) models provide limited insight into complexity associated with WD processes. System dynamics modeling (SDM) has the potential to capture complexity through a stakeholder-based approach that generates a simulation model consisting of multiple feedback loops. SDM may enable WD researchers and practitioners to understand the structure and behavior of the WD system as a whole, and inform development of improved strategies to manage straightforward and complex WD cases.

Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming

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Habib Akbari Alashti

2014-11-01

Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.

Outlier-resilient complexity analysis of heartbeat dynamics

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Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

2015-03-01

Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.

Dynamic genetic linkage of intermediate blood pressure phenotypes during postural adaptations in a founder population

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Arenas, I. A.; Tremblay, J.; Deslauriers, B.; Sandoval, J.; Šeda, O.; Gaudet, D.; Merlo, E.; Kotchen, T.; Cowley, A. W.

2013-01-01

Blood pressure (BP) is a dynamic phenotype that varies rapidly to adjust to changing environmental conditions. Standing upright is a recent evolutionary trait, and genetic factors that influence postural adaptations may contribute to BP variability. We studied the effect of posture on the genetics of BP and intermediate BP phenotypes. We included 384 sib-pairs in 64 sib-ships from families ascertained by early-onset hypertension and dyslipidemia. Blood pressure, three hemodynamic and seven neuroendocrine intermediate BP phenotypes were measured with subjects lying supine and standing upright. The effect of posture on estimates of heritability and genetic covariance was investigated in full pedigrees. Linkage was conducted on 196 candidate genes by sib-pair analyses, and empirical estimates of significance were obtained. A permutation algorithm was implemented to study the postural effect on linkage. ADRA1A, APO, CAST, CORIN, CRHR1, EDNRB, FGF2, GC, GJA1, KCNB2, MMP3, NPY, NR3C2, PLN, TGFBR2, TNFRSF6, and TRHR showed evidence of linkage with any phenotype in the supine position and not upon standing, whereas AKR1B1, CD36, EDNRA, F5, MMP9, PKD2, PON1, PPARG, PPARGC1A, PRKCA, and RET were specifically linked to standing phenotypes. Genetic profiling was undertaken to show genetic interactions among intermediate BP phenotypes and genes specific to each posture. When investigators perform genetic studies exclusively on a single posture, important genetic components of BP are missed. Supine and standing BPs have distinct genetic signatures. Standardized maneuvers influence the results of genetic investigations into BP, thus reflecting its dynamic regulation. PMID:23269701

Contribution of Large Region Joint Associations to Complex Traits Genetics

Science.gov (United States)

Paré, Guillaume; Asma, Senay; Deng, Wei Q.

2015-01-01

A polygenic model of inheritance, whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability, has been proposed to underlie the genetic architecture of complex traits. However, relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability. We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance. Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones. To test this hypothesis, we first characterized the ability of commonly used genetic association models to identify large region joint associations. Through theoretical derivation and simulation, we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile. Based on these results, we tested for large region association with height in 3,740 European participants from the Health and Retirement Study (HRS) study. Adjusting for SNPs with known association with height, we demonstrated clustering of weak associations (p = 2x10-4) in regions extending up to 433.0 Kb from known height loci. The contribution of regional associations to phenotypic variance was estimated at 0.172 (95% CI 0.063-0.279; p < 0.001), which compared favorably to 0.129 explained by known height variants. Conversely, we showed that suggestively associated regions are enriched for known height loci. To extend our findings to other traits, we also tested BMI, HDLc and CRP for large region associations, with consistent results for CRP. Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs. PMID:25856144

Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

Science.gov (United States)

Gao, Zilin; Wang, Yinhe; Zhang, Lili

2018-02-01

In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

Patterns and processes in the genetic differentiation of the Brachionus calyciflorus complex, a passively dispersing freshwater zooplankton.

Science.gov (United States)

Xiang, Xian-ling; Xi, Yi-long; Wen, Xin-li; Zhang, Gen; Wang, Jin-xia; Hu, Ke

2011-05-01

Elucidating the evolutionary patterns and processes of extant species is an important objective of any research program that seeks to understand population divergence and, ultimately, speciation. The island-like nature and temporal fluctuation of limnetic habitats create opportunities for genetic differentiation in rotifers through space and time. To gain further understanding of spatio-temporal patterns of genetic differentiation in rotifers other than the well-studied Brachionus plicatilis complex in brackish water, a total of 318 nrDNA ITS sequences from the B. calyciflorus complex in freshwater were analysed using phylogenetic and phylogeographic methods. DNA taxonomy conducted by both the sequence divergence and the GMYC model suggested the occurrence of six potential cryptic species, supported also by reproductive isolation among the tested lineages. The significant genetic differentiation and non-significant correlation between geographic and genetic distances existed in the most abundant cryptic species, BcI-W and Bc-SW. The large proportion of genetic variability for cryptic species Bc-SW was due to differences between sampling localities within seasons, rather than between different seasons. Nested Clade Analysis suggested allopatric or past fragmentation, contiguous range expansion and long-distance colonization possibly coupled with subsequent fragmentation as the probable main forces shaping the present-day phylogeographic structure of the B. calyciflorus species complex. Copyright © 2011 Elsevier Inc. All rights reserved.

Complex genetics of familial exudative vitreoretinopathy and related pediatric retinal detachments

Science.gov (United States)

Kondo, Hiroyuki

2015-01-01

Familial exudative vitreoretinopathy (FEVR) is a hereditary vitreoretinal disorder that can cause various types of retinal detachments. The abnormalities in eyes with FEVR are caused by poor vascularization in the peripheral retina. The genetics of FEVR is highly heterogeneous, and mutations in the genes for Wnt signaling and a transcription factor have been reported to be responsible for FEVR. These factors have been shown to be the regulators of the pathophysiological pathways of retinal vascular development. Studies conducted to identify the causative genes of FEVR have uncovered a diverse and complex relationship between FEVR and other diseases; for example, Norrie disease, a Mendelian-inherited disease; retinopathy of prematurity, a multifactorial genetic disease; and Coats disease, a nongenetic disease, associated with pediatric retinal detachments. PMID:29018668

Autonomous Collision-Free Navigation of Microvehicles in Complex and Dynamically Changing Environments.

Science.gov (United States)

Li, Tianlong; Chang, Xiaocong; Wu, Zhiguang; Li, Jinxing; Shao, Guangbin; Deng, Xinghong; Qiu, Jianbin; Guo, Bin; Zhang, Guangyu; He, Qiang; Li, Longqiu; Wang, Joseph

2017-09-26

Self-propelled micro- and nanoscale robots represent a rapidly emerging and fascinating robotics research area. However, designing autonomous and adaptive control systems for operating micro/nanorobotics in complex and dynamically changing environments, which is a highly demanding feature, is still an unmet challenge. Here we describe a smart microvehicle for precise autonomous navigation in complicated environments and traffic scenarios. The fully autonomous navigation system of the smart microvehicle is composed of a microscope-coupled CCD camera, an artificial intelligence planner, and a magnetic field generator. The microscope-coupled CCD camera provides real-time localization of the chemically powered Janus microsphere vehicle and environmental detection for path planning to generate optimal collision-free routes, while the moving direction of the microrobot toward a reference position is determined by the external electromagnetic torque. Real-time object detection offers adaptive path planning in response to dynamically changing environments. We demonstrate that the autonomous navigation system can guide the vehicle movement in complex patterns, in the presence of dynamically changing obstacles, and in complex biological environments. Such a navigation system for micro/nanoscale vehicles, relying on vision-based close-loop control and path planning, is highly promising for their autonomous operation in complex dynamic settings and unpredictable scenarios expected in a variety of realistic nanoscale scenarios.

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2013-01-01

Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

Genetic addiction: selfish gene's strategy for symbiosis in the genome.

Science.gov (United States)

Mochizuki, Atsushi; Yahara, Koji; Kobayashi, Ichizo; Iwasa, Yoh

2006-02-01

The evolution and maintenance of the phenomenon of postsegregational host killing or genetic addiction are paradoxical. In this phenomenon, a gene complex, once established in a genome, programs death of a host cell that has eliminated it. The intact form of the gene complex would survive in other members of the host population. It is controversial as to why these genetic elements are maintained, due to the lethal effects of host killing, or perhaps some other properties are beneficial to the host. We analyzed their population dynamics by analytical methods and computer simulations. Genetic addiction turned out to be advantageous to the gene complex in the presence of a competitor genetic element. The advantage is, however, limited in a population without spatial structure, such as that in a well-mixed liquid culture. In contrast, in a structured habitat, such as the surface of a solid medium, the addiction gene complex can increase in frequency, irrespective of its initial density. Our demonstration that genomes can evolve through acquisition of addiction genes has implications for the general question of how a genome can evolve as a community of potentially selfish genes.

Modelling the dynamics of the health-production complex in livestock herds

DEFF Research Database (Denmark)

Sørensen, J.T.; Enevoldsen, Carsten

1992-01-01

This paper reviews how the dynamics of the health-production complex in livestock herds is mimicked by livestock herd simulation models. Twelve models simulating the dynamics of dairy, beef, sheep and sow herds were examined. All models basically included options to alter input and output...

Evolutionary dynamics of complex communications networks

CERN Document Server

Karyotis, Vasileios; Papavassiliou, Symeon

2013-01-01

Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks. Addressing the emerging aspects of modern network analysis and design, Evolutionary Dynamics of Complex Communications Networks introduces and develops a top-bottom approach where elements of the higher layer can be exploited in modifying the lowest physical topology-closing the network design loop in an evolutionary fashion similar to

A Single-Cell Biochemistry Approach Reveals PAR Complex Dynamics during Cell Polarization.

Science.gov (United States)

Dickinson, Daniel J; Schwager, Francoise; Pintard, Lionel; Gotta, Monica; Goldstein, Bob

2017-08-21

Regulated protein-protein interactions are critical for cell signaling, differentiation, and development. For the study of dynamic regulation of protein interactions in vivo, there is a need for techniques that can yield time-resolved information and probe multiple protein binding partners simultaneously, using small amounts of starting material. Here we describe a single-cell protein interaction assay. Single-cell lysates are generated at defined time points and analyzed using single-molecule pull-down, yielding information about dynamic protein complex regulation in vivo. We established the utility of this approach by studying PAR polarity proteins, which mediate polarization of many animal cell types. We uncovered striking regulation of PAR complex composition and stoichiometry during Caenorhabditis elegans zygote polarization, which takes place in less than 20 min. PAR complex dynamics are linked to the cell cycle by Polo-like kinase 1 and govern the movement of PAR proteins to establish polarity. Our results demonstrate an approach to study dynamic biochemical events in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

Implementation and Characterization of Dynamic Genetic Networks in Vitro

OpenAIRE

Niederholtmeyer, Henrike Marie

2015-01-01

Transcription and translation (TX-TL) can be performed in vitro, outside of cells, allowing the assembly and analysis of genetic networks. This approach to engineering biological networks in a less complex and more controllable environment could one day allow rapid prototyping of network designs before implementing them in living cells. Furthermore, the in vitro approach provides insight into how natural biological systems are built and is instructive to define the rules for engineering biolo...

Complex dynamics in the development of the first tarsal segment of Drosophila melanogaster

Directory of Open Access Journals (Sweden)

Juan Nicolas Malagon

2016-09-01

Full Text Available Gene, protein and cell interactions are vital for the development of a multicellular organism. As a result, complexity theory can be a fundamental tool to understand how diverse developmental and evolutionary processes occur. However, in most scientific programs these two fields are separated. In an effort to create a connection between the Evo-devo and complexity science, this article shows how the cell dynamics of epithelia can display behaviours with similar features to complex systems. Here, I propose that these cell dynamics, in addition to control cell density in epithelia, can provide high evolvability to this type of tissue. To achieve this goal, I used a as a systems the development of Drosophila melanogaster front legs. First, I provide an example in which order at the tissue level emerge from apparently random cell dynamics. Then, I show that small modifications in epithelial cellular components can produce highly organized or the opposite random cell dynamics. Therefore, this work shows that a developing epithelium displays signs of complex behaviours and I propose that the feedback between tension and cellular processes are key for understanding how multicellular organisms development and evolve. Such studies may reveal the mechanistic basis of complex processes that bridge several levels of organization.

Global Stability of Complex-Valued Genetic Regulatory Networks with Delays on Time Scales

Directory of Open Access Journals (Sweden)

Wang Yajing

2016-01-01

Full Text Available In this paper, the global exponential stability of complex-valued genetic regulatory networks with delays is investigated. Besides presenting conditions guaranteeing the existence of a unique equilibrium pattern, its global exponential stability is discussed. Some numerical examples for different time scales.

Complex postglacial recolonization inferred from population genetic structure of mottled sculpin Cottus bairdii in tributaries of eastern Lake Michigan, U.S.A.

Science.gov (United States)

Homola, J J; Ruetz, C R; Kohler, S L; Thum, R A

2016-11-01

This study used analyses of the genetic structure of a non-game fish species, the mottled sculpin Cottus bairdii to hypothesize probable recolonization routes used by cottids and possibly other Laurentian Great Lakes fishes following glacial recession. Based on samples from 16 small streams in five major Lake Michigan, U.S.A., tributary basins, significant interpopulation differentiation was documented (overall F ST = 0·235). Differentiation was complex, however, with unexpectedly high genetic similarity among basins as well as occasionally strong differentiation within basins, despite relatively close geographic proximity of populations. Genetic dissimilarities were identified between eastern and western populations within river basins, with similarities existing between eastern and western populations across basins. Given such patterns, recolonization is hypothesized to have occurred on three occasions from more than one glacial refugium, with a secondary vicariant event resulting from reduction in the water level of ancestral Lake Michigan. By studying the phylogeography of a small, non-game fish species, this study provides insight into recolonization dynamics of the region that could be difficult to infer from game species that are often broadly dispersed by humans. © 2016 The Fisheries Society of the British Isles.

Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation

Science.gov (United States)

Spaiser, Viktoria; Hedström, Peter; Ranganathan, Shyam; Jansson, Kim; Nordvik, Monica K.; Sumpter, David J. T.

2018-01-01

It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena…

Nonlinear dynamics, chaos and complex cardiac arrhythmias

Science.gov (United States)

Glass, L.; Courtemanche, M.; Shrier, A.; Goldberger, A. L.

1987-01-01

Periodic stimulation of a nonlinear cardiac oscillator in vitro gives rise to complex dynamics that is well described by one-dimensional finite difference equations. As stimulation parameters are varied, a large number of different phase-locked and chaotic rhythms is observed. Similar rhythms can be observed in the intact human heart when there is interaction between two pacemaker sites. Simplified models are analyzed, which show some correspondence to clinical observations.

Genetic complexity in a Drosophila model of diabetes-associated misfolded human proinsulin.

Science.gov (United States)

Park, Soo-Young; Ludwig, Michael Z; Tamarina, Natalia A; He, Bin Z; Carl, Sarah H; Dickerson, Desiree A; Barse, Levi; Arun, Bharath; Williams, Calvin L; Miles, Cecelia M; Philipson, Louis H; Steiner, Donald F; Bell, Graeme I; Kreitman, Martin

2014-02-01

Drosophila melanogaster has been widely used as a model of human Mendelian disease, but its value in modeling complex disease has received little attention. Fly models of complex disease would enable high-resolution mapping of disease-modifying loci and the identification of novel targets for therapeutic intervention. Here, we describe a fly model of permanent neonatal diabetes mellitus and explore the complexity of this model. The approach involves the transgenic expression of a misfolded mutant of human preproinsulin, hINS(C96Y), which is a cause of permanent neonatal diabetes. When expressed in fly imaginal discs, hINS(C96Y) causes a reduction of adult structures, including the eye, wing, and notum. Eye imaginal discs exhibit defects in both the structure and the arrangement of ommatidia. In the wing, expression of hINS(C96Y) leads to ectopic expression of veins and mechano-sensory organs, indicating disruption of wild-type signaling processes regulating cell fates. These readily measurable "disease" phenotypes are sensitive to temperature, gene dose, and sex. Mutant (but not wild-type) proinsulin expression in the eye imaginal disc induces IRE1-mediated XBP1 alternative splicing, a signal for endoplasmic reticulum stress response activation, and produces global change in gene expression. Mutant hINS transgene tester strains, when crossed to stocks from the Drosophila Genetic Reference Panel, produce F1 adults with a continuous range of disease phenotypes and large broad-sense heritability. Surprisingly, the severity of mutant hINS-induced disease in the eye is not correlated with that in the notum in these crosses, nor with eye reduction phenotypes caused by the expression of two dominant eye mutants acting in two different eye development pathways, Drop (Dr) or Lobe (L), when crossed into the same genetic backgrounds. The tissue specificity of genetic variability for mutant hINS-induced disease has, therefore, its own distinct signature. The genetic dominance

Dynamic and interacting complex networks

Science.gov (United States)

Dickison, Mark E.

This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth.

Science.gov (United States)

Ziv, Naomi; Shuster, Bentley M; Siegal, Mark L; Gresham, David

2017-07-01

In all organisms, the majority of traits vary continuously between individuals. Explaining the genetic basis of quantitative trait variation requires comprehensively accounting for genetic and nongenetic factors as well as their interactions. The growth of microbial cells can be characterized by a lag duration, an exponential growth phase, and a stationary phase. Parameters that characterize these growth phases can vary among genotypes (phenotypic variation), environmental conditions (phenotypic plasticity), and among isogenic cells in a given environment (phenotypic variability). We used a high-throughput microscopy assay to map genetic loci determining variation in lag duration and exponential growth rate in growth rate-limiting and nonlimiting glucose concentrations, using segregants from a cross of two natural isolates of the budding yeast, Saccharomyces cerevisiae We find that some quantitative trait loci (QTL) are common between traits and environments whereas some are unique, exhibiting gene-by-environment interactions. Furthermore, whereas variation in the central tendency of growth rate or lag duration is explained by many additive loci, differences in phenotypic variability are primarily the result of genetic interactions. We used bulk segregant mapping to increase QTL resolution by performing whole-genome sequencing of complex mixtures of an advanced intercross mapping population grown in selective conditions using glucose-limited chemostats. We find that sequence variation in the high-affinity glucose transporter HXT7 contributes to variation in growth rate and lag duration. Allele replacements of the entire locus, as well as of a single polymorphic amino acid, reveal that the effect of variation in HXT7 depends on genetic, and allelic, background. Amplifications of HXT7 are frequently selected in experimental evolution in glucose-limited environments, but we find that HXT7 amplifications result in antagonistic pleiotropy that is absent in naturally

Automated X-ray television complex for testing large dynamic objects

International Nuclear Information System (INIS)

Gusev, E.A.; Luk'yanenko, Eh.A.; Chelnokov, V.B.; Kuleshov, V.K.; Alkhimov, Yu.V.

1992-01-01

An automated X-ray television complex on the base of matrix gas-dischage large-area (2.1x1.0 m) converter for testing large cargoes and containers, as well as for inductrial article diagnostics is described. The complex pulsed operation with the 512 kbytes television digital memory unit provides for testing dynamic objects under minimal doses (20-100 μR)

Landscape genetics highlights the role of bank vole metapopulation dynamics in the epidemiology of Puumala hantavirus.

Science.gov (United States)

Guivier, E; Galan, M; Chaval, Y; Xuéreb, A; Ribas Salvador, A; Poulle, M-L; Voutilainen, L; Henttonen, H; Charbonnel, N; Cosson, J F

2011-09-01

Rodent host dynamics and dispersal are thought to be critical for hantavirus epidemiology as they determine pathogen persistence and transmission within and between host populations. We used landscape genetics to investigate how the population dynamics of the bank vole Myodes glareolus, the host of Puumala hantavirus (PUUV), vary with forest fragmentation and influence PUUV epidemiology. We sampled vole populations within the Ardennes, a French PUUV endemic area. We inferred demographic features such as population size, isolation and migration with regard to landscape configuration. We next analysed the influence of M. glareolus population dynamics on PUUV spatial distribution. Our results revealed that the global metapopulation dynamics of bank voles were strongly shaped by landscape features, including suitable patch size and connectivity. Large effective size in forest might therefore contribute to the higher observed levels of PUUV prevalence. By contrast, populations from hedge networks highly suffered from genetic drift and appeared strongly isolated from all other populations. This might result in high probabilities of local extinction for both M. glareolus and PUUV. Besides, we detected signatures of asymmetric bank vole migration from forests to hedges. These movements were likely to sustain PUUV in fragmented landscapes. In conclusion, our study provided arguments in favour of source-sink dynamics shaping PUUV persistence and spread in heterogeneous, Western European temperate landscapes. It illustrated the potential contribution of landscape genetics to the understanding of the epidemiological processes occurring at this local scale. © 2011 Blackwell Publishing Ltd.

Symposium on Short-Term Genetic Bioassays in the Evaluation of Complex Environmental Mixtures

CERN Document Server

Sandhu, Shahbeg; Lewtas, Joellen; Claxton, Larry; Strauss, Gary; Nesnow, Stephen

1985-01-01

With this proceedings of the fourth symposium on complex mixtures, we continue to revise and extend our knowledge of genetic methods for the evaluation of chemical mixtures in the environment. The early chapters of this volume are devoted to new bioassay techniques that are directly applicable to the monitoring of environments contaminated with genotoxic chemicals. Microbiological methods have been further refined to meet the special needs of atmospheric monitoring so that very small samples may now be efficiently tested. New in situ methods utilizing green plants actually avoid many of the usual difficulties of sample collection and preparation and offer special advantages in monitoring wastewater, sludges, and hazardous wastes. Insects also are being employed very effectively in the evaluation of gaseous air pollutants in controlled laboratory investigations. Increased emphasis has been placed on a comprehensive assessment of the potential of complex mixtures t9 cause various kinds of genetic damage. New as...

Software complex for developing dynamically packed program system for experiment automation

International Nuclear Information System (INIS)

Baluka, G.; Salamatin, I.M.

1985-01-01

Software complex for developing dynamically packed program system for experiment automation is considered. The complex includes general-purpose programming systems represented as the RT-11 standard operating system and specially developed problem-oriented moduli providing execution of certain jobs. The described complex is realized in the PASKAL' and MAKRO-2 languages and it is rather flexible to variations of the technique of the experiment

A New Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Complex Networks

Directory of Open Access Journals (Sweden)

Guoqiang Chen

2013-01-01

Full Text Available Community detection in dynamic networks is an important research topic and has received an enormous amount of attention in recent years. Modularity is selected as a measure to quantify the quality of the community partition in previous detection methods. But, the modularity has been exposed to resolution limits. In this paper, we propose a novel multiobjective evolutionary algorithm for dynamic networks community detection based on the framework of nondominated sorting genetic algorithm. Modularity density which can address the limitations of modularity function is adopted to measure the snapshot cost, and normalized mutual information is selected to measure temporal cost, respectively. The characteristics knowledge of the problem is used in designing the genetic operators. Furthermore, a local search operator was designed, which can improve the effectiveness and efficiency of community detection. Experimental studies based on synthetic datasets show that the proposed algorithm can obtain better performance than the compared algorithms.

Recent developments in computer modeling add ecological realism to landscape genetics

Science.gov (United States)

Background / Question / Methods A factor limiting the rate of progress in landscape genetics has been the shortage of spatial models capable of linking life history attributes such as dispersal behavior to complex dynamic landscape features. The recent development of new models...

Complexity, Chaos, and Nonlinear Dynamics: A New Perspective on Career Development Theory

Science.gov (United States)

Bloch, Deborah P.

2005-01-01

The author presents a theory of career development drawing on nonlinear dynamics and chaos and complexity theories. Career is presented as a complex adaptive entity, a fractal of the human entity. Characteristics of complex adaptive entities, including (a) autopiesis, or self-regeneration; (b) open exchange; (c) participation in networks; (d)…

Introduction to focus issue: quantitative approaches to genetic networks.

Science.gov (United States)

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

Controlling collective dynamics in complex minority-game resource-allocation systems

Science.gov (United States)

Zhang, Ji-Qiang; Huang, Zi-Gang; Dong, Jia-Qi; Huang, Liang; Lai, Ying-Cheng

2013-05-01

Resource allocation takes place in various kinds of real-world complex systems, such as traffic systems, social services institutions or organizations, or even ecosystems. The fundamental principle underlying complex resource-allocation dynamics is Boolean interactions associated with minority games, as resources are generally limited and agents tend to choose the least used resource based on available information. A common but harmful dynamical behavior in resource-allocation systems is herding, where there are time intervals during which a large majority of the agents compete for a few resources, leaving many other resources unused. Accompanying the herd behavior is thus strong fluctuations with time in the number of resources being used. In this paper, we articulate and establish that an intuitive control strategy, namely pinning control, is effective at harnessing the herding dynamics. In particular, by fixing the choices of resources for a few agents while leaving the majority of the agents free, herding can be eliminated completely. Our investigation is systematic in that we consider random and targeted pinning and a variety of network topologies, and we carry out a comprehensive analysis in the framework of mean-field theory to understand the working of control. The basic philosophy is then that, when a few agents waive their freedom to choose resources by receiving sufficient incentives, the majority of the agents benefit in that they will make fair, efficient, and effective use of the available resources. Our work represents a basic and general framework to address the fundamental issue of fluctuations in complex dynamical systems with significant applications to social, economical, and political systems.

A complex scenario of tuberculosis transmission is revealed through genetic and epidemiological surveys in Porto.

Science.gov (United States)

Rito, Teresa; Matos, Carlos; Carvalho, Carlos; Machado, Henrique; Rodrigues, Gabriela; Oliveira, Olena; Ferreira, Eduarda; Gonçalves, Jorge; Maio, Lurdes; Morais, Clara; Ramos, Helena; Guimarães, João Tiago; Santos, Catarina L; Duarte, Raquel; Correia-Neves, Margarida

2018-01-25

Tuberculosis (TB) incidence is decreasing worldwide and eradication is becoming plausible. In low-incidence countries, intervention on migrant populations is considered one of the most important strategies for elimination. However, such measures are inappropriate in European areas where TB is largely endemic, such as Porto in Portugal. We aim to understand transmission chains in Porto through a genetic characterization of Mycobacterium tuberculosis strains and through a detailed epidemiological evaluation of cases. We genotyped the M. tuberculosis strains using the MIRU-VNTR system. We performed an evolutionary reconstruction of the genotypes with median networks, used in this context for the first time. TB cases from a period of two years were evaluated combining genetic, epidemiological and georeferencing information. The data reveal a unique complex scenario in Porto where the autochthonous population acts as a genetic reservoir of M. tuberculosis diversity with discreet episodes of transmission, mostly undetected using classical epidemiology alone. Although control policies have been successful in decreasing incidence in Porto, the discerned complexity suggests that, for elimination to be a realistic goal, strategies need to be adjusted and coupled with a continuous genetic characterization of strains and detailed epidemiological evaluation, in order to successfully identify and interrupt transmission chains.

Practical synchronization on complex dynamical networks via optimal pinning control

Science.gov (United States)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Dynamic behavior and chaos control in a complex Riccati-type map ...

African Journals Online (AJOL)

This paper is devoted to analyze the dynamic behavior of a Riccati- type map with complex variables and complex parameters. Fixed points and their asymptotic stability are studied. Lyapunov exponent is computed to indicate chaos. Bifurcation and chaos are discussed. Chaotic behavior of the map has been controlled by ...

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

Science.gov (United States)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

Science.gov (United States)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Cilium transition zone proteome reveals compartmentalization and differential dynamics of ciliopathy complexes

Czech Academy of Sciences Publication Activity Database

Dean, S.; Moreira-Leite, F.; Varga, Vladimír; Gull, K.

2016-01-01

Roč. 113, č. 35 (2016), E5135-E5143 ISSN 0027-8424 Institutional support: RVO:68378050 Keywords : transition zone * cilium/flagellum * BBSome * MKS/B9 complex * trypanosome Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 9.661, year: 2016

Endocrine autoimmune disease: genetics become complex.

Science.gov (United States)

Wiebolt, Janneke; Koeleman, Bobby P C; van Haeften, Timon W

2010-12-01

The endocrine system is a frequent target in pathogenic autoimmune responses. Type 1 diabetes and autoimmune thyroid disease are the prevailing examples. When several diseases cluster together in one individual, the phenomenon is called autoimmune polyglandular syndrome. Progress has been made in understanding the genetic factors involved in endocrine autoimmune diseases. Studies on monogenic autoimmune diseases such as autoimmune polyglandular syndrome type 1, immunodysregulation, polyendocrinopathy, enteropathy, X-linked and primary immune deficiencies helped uncover the role of key regulators in the preservation of immune tolerance. Alleles of the major histocompatibility complex have been known to contribute to the susceptibility to most forms of autoimmunity for more than 3 decades. Furthermore, sequencing studies revealed three non-major histocompatibility complex loci and some disease specific loci, which control T lymphocyte activation or signalling. Recent genome-wide association studies (GWAS) have enabled acceleration in the identification of novel (non-HLA) loci and hence other relevant immune response pathways. Interestingly, several loci are shared between autoimmune diseases, and surprisingly some work in opposite direction. This means that the same allele which predisposes to a certain autoimmune disease can be protective in another. Well powered GWAS in type 1 diabetes has led to the uncovering of a significant number of risk variants with modest effect. These studies showed that the innate immune system may also play a role in addition to the adaptive immune system. It is anticipated that next generation sequencing techniques will uncover other (rare) variants. For other autoimmune disease (such as autoimmune thyroid disease) GWAS are clearly needed. © 2010 The Authors. European Journal of Clinical Investigation © 2010 Stichting European Society for Clinical Investigation Journal Foundation.

Synchronization criterion for Lur'e type complex dynamical networks with time-varying delay

International Nuclear Information System (INIS)

Ji, D.H.; Park, Ju H.; Yoo, W.J.; Won, S.C.; Lee, S.M.

2010-01-01

In this Letter, the synchronization problem for a class of complex dynamical networks in which every identical node is a Lur'e system with time-varying delay is considered. A delay-dependent synchronization criterion is derived for the synchronization of complex dynamical network that represented by Lur'e system with sector restricted nonlinearities. The derived criterion is a sufficient condition for absolute stability of error dynamics between the each nodes and the isolated node. Using a convex representation of the nonlinearity for error dynamics, the stability condition based on the discretized Lyapunov-Krasovskii functional is obtained via LMI formulation. The proposed delay-dependent synchronization criterion is less conservative than the existing ones. The effectiveness of our work is verified through numerical examples.

PREFACE: Complex dynamics of fluids in disordered and crowded environments Complex dynamics of fluids in disordered and crowded environments

Science.gov (United States)

Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

2011-06-01

Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized

Network dynamics and its relationships to topology and coupling structure in excitable complex networks

International Nuclear Information System (INIS)

Zhang Li-Sheng; Mi Yuan-Yuan; Gu Wei-Feng; Hu Gang

2014-01-01

All dynamic complex networks have two important aspects, pattern dynamics and network topology. Discovering different types of pattern dynamics and exploring how these dynamics depend on network topologies are tasks of both great theoretical importance and broad practical significance. In this paper we study the oscillatory behaviors of excitable complex networks (ECNs) and find some interesting dynamic behaviors of ECNs in oscillatory probability, the multiplicity of oscillatory attractors, period distribution, and different types of oscillatory patterns (e.g., periodic, quasiperiodic, and chaotic). In these aspects, we further explore strikingly sharp differences among network dynamics induced by different topologies (random or scale-free topologies) and different interaction structures (symmetric or asymmetric couplings). The mechanisms behind these differences are explained physically. (interdisciplinary physics and related areas of science and technology)

Dynamics of mathematical models in biology bringing mathematics to life

CERN Document Server

Zazzu, Valeria; Guarracino, Mario

2016-01-01

This volume focuses on contributions from both the mathematics and life science community surrounding the concepts of time and dynamicity of nature, two significant elements which are often overlooked in modeling process to avoid exponential computations. The book is divided into three distinct parts: dynamics of genomes and genetic variation, dynamics of motifs, and dynamics of biological networks. Chapters included in dynamics of genomes and genetic variation analyze the molecular mechanisms and evolutionary processes that shape the structure and function of genomes and those that govern genome dynamics. The dynamics of motifs portion of the volume provides an overview of current methods for motif searching in DNA, RNA and proteins, a key process to discover emergent properties of cells, tissues, and organisms. The part devoted to the dynamics of biological networks covers networks aptly discusses networks in complex biological functions and activities that interpret processes in cells. Moreover, chapters i...

Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling

International Nuclear Information System (INIS)

Wang Lifu; Kong Zhi; Jing Yuanwei

2010-01-01

This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)

Dynamics of complexation of a charged dendrimer by linear polyelectrolyte: Computer modelling

NARCIS (Netherlands)

Lyulin, S.V.; Darinskii, A.A.; Lyulin, A.V.

2007-01-01

Brownian-dynamics simulations have been performed for complexes formed by a charged dendrimer and a long oppositely charged linear polyelectrolyte when overcharging phenomenon is always observed. After a complex formation the orientational mobility of the individual dendrimer bonds, the fluctuations

Structure identification and adaptive synchronization of uncertain general complex dynamical networks

International Nuclear Information System (INIS)

Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian

2009-01-01

This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

Structure identification and adaptive synchronization of uncertain general complex dynamical networks

Energy Technology Data Exchange (ETDEWEB)

Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)

2009-12-28

This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

Science.gov (United States)

Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

Directory of Open Access Journals (Sweden)

Jose P. Perez

2014-01-01

Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.

No evidence for a genetic blueprint: The case of the "complex" mammalian photoreceptor

Directory of Open Access Journals (Sweden)

G Kumaramanickavel

2015-01-01

Full Text Available Despite the intensity of the search for genes causing inherited retinal degenerations over the past 3 decades, of the approximately 200 disease genes identified to date, all appear to be ordinary housekeeping genes specifying proteins playing basic structural and functional roles in the mature photoreceptor cells. No genes or genetic elements have been identified which can be construed as having a specific morphogenic role, directing the development of the cytoarchitecture of any particular retinal cell. The evidence suggests that the cytoarchitecture of the retinal photoreceptors, although enormously complex, arises from the self-organization of the cells constituents without any regulation or direction from an external genetic blueprint.

System crash as dynamics of complex networks.

Science.gov (United States)

Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

2016-10-18

Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

Portuguese crypto-Jews: the genetic heritage of a complex history

Science.gov (United States)

Nogueiro, Inês; Teixeira, João C.; Amorim, António; Gusmão, Leonor; Alvarez, Luis

2015-01-01

The first documents mentioning Jewish people in Iberia are from the Visigothic period. It was also in this period that the first documented anti-Judaic persecution took place. Other episodes of persecution would happen again and again during the long troubled history of the Jewish people in Iberia and culminated with the Decrees of Expulsion and the establishment of the Inquisition: some Jews converted to Catholicism while others resisted and were forcedly baptized, becoming the first Iberian Crypto-Jews. In the 18th century the official discrimination and persecution carried out by the Inquisition ended and several Jewish communities emerged in Portugal. From a populational genetics point of view, the worldwide Diaspora of contemporary Jewish communities has been intensely studied. Nevertheless, very little information is available concerning Sephardic and Iberian Crypto-Jewish descendants. Data from the Iberian Peninsula, the original geographic source of Sephardic Jews, is limited to two populations in Portugal, Belmonte, and Bragança district, and the Chueta community from Mallorca. Belmonte was the first Jewish community studied for uniparental markers. The construction of a reference model for the history of the Portuguese Jewish communities, in which the genetic and classical historical data interplay dynamically, is still ongoing. Recently an enlarged sample covering a wide region in the Northeast Portugal was undertaken, allowing the genetic profiling of male and female lineages. A Jewish specific shared female lineage (HV0b) was detected between the community of Belmonte and Bragança. In contrast to what was previously described as a hallmark of the Portuguese Jews, an unexpectedly high polymorphism of lineages was found in Bragança, showing a surprising resistance to the erosion of genetic diversity typical of small-sized isolate populations, as well as signs of admixture with the Portuguese host population. PMID:25699075

Portuguese crypto-Jews: the genetic heritage of a complex history.

Science.gov (United States)

Nogueiro, Inês; Teixeira, João C; Amorim, António; Gusmão, Leonor; Alvarez, Luis

2015-01-01

The first documents mentioning Jewish people in Iberia are from the Visigothic period. It was also in this period that the first documented anti-Judaic persecution took place. Other episodes of persecution would happen again and again during the long troubled history of the Jewish people in Iberia and culminated with the Decrees of Expulsion and the establishment of the Inquisition: some Jews converted to Catholicism while others resisted and were forcedly baptized, becoming the first Iberian Crypto-Jews. In the 18th century the official discrimination and persecution carried out by the Inquisition ended and several Jewish communities emerged in Portugal. From a populational genetics point of view, the worldwide Diaspora of contemporary Jewish communities has been intensely studied. Nevertheless, very little information is available concerning Sephardic and Iberian Crypto-Jewish descendants. Data from the Iberian Peninsula, the original geographic source of Sephardic Jews, is limited to two populations in Portugal, Belmonte, and Bragança district, and the Chueta community from Mallorca. Belmonte was the first Jewish community studied for uniparental markers. The construction of a reference model for the history of the Portuguese Jewish communities, in which the genetic and classical historical data interplay dynamically, is still ongoing. Recently an enlarged sample covering a wide region in the Northeast Portugal was undertaken, allowing the genetic profiling of male and female lineages. A Jewish specific shared female lineage (HV0b) was detected between the community of Belmonte and Bragança. In contrast to what was previously described as a hallmark of the Portuguese Jews, an unexpectedly high polymorphism of lineages was found in Bragança, showing a surprising resistance to the erosion of genetic diversity typical of small-sized isolate populations, as well as signs of admixture with the Portuguese host population.

PORTUGUESE CRYPTO-JEWS: THE GENETIC HERITAGE OF A COMPLEX HISTORY

Directory of Open Access Journals (Sweden)

Inês Pires Nogueiro

2015-02-01

Full Text Available The first documents mentioning Jewish people in Iberia are from the Visigothic period. It was also in this period that the first documented anti-Judaic persecution took place. Other episodes of persecution would happen again and again during the long troubled history of the Jewish people in Iberia and culminated with the Decrees of Expulsion and the establishment of the Inquisition: some Jews converted to Catholicism while others resisted and were forcedly baptized, becoming the first Iberian Crypto-Jews. In the 18th century the official discrimination and persecution carried out by the Inquisition ended and several Jewish communities emerged in Portugal. From a populational genetics point of view, the worldwide Diaspora of contemporary Jewish communities has been intensely studied. Nevertheless, very little information is available concerning Sephardic and Iberian Crypto-Jewish descendants. Data from the Iberian Peninsula, the original geographic source of Sephardic Jews, is limited to two populations in Portugal, Belmonte and Bragança district, and the Chueta community from Mallorca. Belmonte was the first Jewish community studied for uniparental markers. The construction of a reference model for the history of the Portuguese Jewish communities, in which the genetic and classical historical data interplay dynamically, is still ongoing. Recently an enlarged sample covering a wide region in the Northeast Portugal was undertaken, allowing the genetic profiling of male and female lineages. A Jewish specific shared female lineage (HV0b was detected between the community of Belmonte and Bragança. In contrast to what was previously described as a hallmark of the Portuguese Jews, an unexpectedly high polymorphism of lineages’ was found in Bragança, showing a surprising resistance to the erosion of genetic diversity typical of small-sized isolate populations, as well as signs of admixture with the Portuguese host population.

Topology Detection for Output-Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Directory of Open Access Journals (Sweden)

Xinwei Wang

2017-01-01

Full Text Available Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle’s invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.

Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli.

Directory of Open Access Journals (Sweden)

Mohan Babu

2014-02-01

Full Text Available Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI screens can provide insights into the biological role(s of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

Protein complexes and cholesterol in the control of late endosomal dynamicsCholesterol and multi-protein complexes in the control of late endosomal dynamics

NARCIS (Netherlands)

Kant, Rik Henricus Nicolaas van der

2013-01-01

Late endosomal transport is disrupted in several diseases such as Niemann-Pick type C, ARC syndrome and Alzheimer’s disease. This thesis describes the regulation of late endosomal dynamics by cholesterol and multi-protein complexes. We find that cholesterol acts as a cellular tomtom that steers the

Visualization of local Ca2+ dynamics with genetically encoded bioluminescent reporters.

Science.gov (United States)

Rogers, Kelly L; Stinnakre, Jacques; Agulhon, Cendra; Jublot, Delphine; Shorte, Spencer L; Kremer, Eric J; Brûlet, Philippe

2005-02-01

Measurements of local Ca2+ signalling at different developmental stages and/or in specific cell types is important for understanding aspects of brain functioning. The use of light excitation in fluorescence imaging can cause phototoxicity, photobleaching and auto-fluorescence. In contrast, bioluminescence does not require the input of radiative energy and can therefore be measured over long periods, with very high temporal resolution. Aequorin is a genetically encoded Ca(2+)-sensitive bioluminescent protein, however, its low quantum yield prevents dynamic measurements of Ca2+ responses in single cells. To overcome this limitation, we recently reported the bi-functional Ca2+ reporter gene, GFP-aequorin (GA), which was developed specifically to improve the light output and stability of aequorin chimeras [V. Baubet, et al., (2000) PNAS, 97, 7260-7265]. In the current study, we have genetically targeted GA to different microdomains important in synaptic transmission, including to the mitochondrial matrix, endoplasmic reticulum, synaptic vesicles and to the postsynaptic density. We demonstrate that these reporters enable 'real-time' measurements of subcellular Ca2+ changes in single mammalian neurons using bioluminescence. The high signal-to-noise ratio of these reporters is also important in that it affords the visualization of Ca2+ dynamics in cell-cell communication in neuronal cultures and tissue slices. Further, we demonstrate the utility of this approach in ex-vivo preparations of mammalian retina, a paradigm in which external light input should be controlled. This represents a novel molecular imaging approach for non-invasive monitoring of local Ca2+ dynamics and cellular communication in tissue or whole animal studies.

Spatial and temporal dynamics of the genetic organization of small mammal populations

International Nuclear Information System (INIS)

Smith, M.H.; Manlove, M.N.; Joule, J.

1978-01-01

A functional population is a group of organisms and their offspring that contributes to a common gene pool within a certain area and time period. It is also the unit of evolution and should be viewed both in quantitative and qualitative terms. Selection, drift, dispersal, and mutation can alter the composition of populations. Spatial heterogeneity in allele frequencies argues for a conceptual model that has a series of relatively small populations semi-isolated from one another. Because of the relatively high levels of genetic variability characteristic of most mammalian species, significant amounts of gene flow between these spatially subdivided populations must occur when longer time periods are considered. Fluctuations in the genetic structure of populations seem to be important in altering the fitness of the individuals within the populations. The interaction of populations through gene flow is important in changing the levels of intrapopulational genetic variability. Populations can be characterized as existing on a continuum from relatively stable to unstable numbers and by other associated changes in their characteristics. Temporal changes in allele frequency occur in a variety of mammals. Conceptually, a species can be viewed as a series of dynamic populations that vary in numbers and quality in both a spatial and temporal context even over short distances and time periods. Short term changes in the quality of individuals in a population can be important in altering the short term dynamics of a population

Antitumor Cell-Complex Vaccines Employing Genetically Modified Tumor Cells and Fibroblasts

Directory of Open Access Journals (Sweden)

Antonio Miguel

2014-02-01

Full Text Available The present study evaluates the immune response mediated by vaccination with cell complexes composed of irradiated B16 tumor cells and mouse fibroblasts genetically modified to produce GM-CSF. The animals were vaccinated with free B16 cells or cell complexes. We employed two gene plasmid constructions: one high producer (pMok and a low producer (p2F. Tumor transplant was performed by injection of B16 tumor cells. Plasma levels of total IgG and its subtypes were measured by ELISA. Tumor volumes were measured and survival curves were obtained. The study resulted in a cell complex vaccine able to stimulate the immune system to produce specific anti-tumor membrane proteins (TMP IgG. In the groups vaccinated with cells transfected with the low producer plasmid, IgG production was higher when we used free B16 cell rather than cell complexes. Nonspecific autoimmune response caused by cell complex was not greater than that induced by the tumor cells alone. Groups vaccinated with B16 transfected with low producer plasmid reached a tumor growth delay of 92% (p ≤ 0.01. When vaccinated with cell complex, the best group was that transfected with high producer plasmid, reaching a tumor growth inhibition of 56% (p ≤ 0.05. Significant survival (40% was only observed in the groups vaccinated with free transfected B16 cells.

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette's Syndrome and OCD

NARCIS (Netherlands)

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrio, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald W.; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Silgado, Julio C. Cardona; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniete; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L.; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Gruenblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M. J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Restrepo, Sandra C. Mesa; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlo N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosario, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Duarte, Ana V. Valencia; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G. M.; Shugart, Yin Yao; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Routeau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson B.; Stewart, Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

Objective: Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette's Syndrome and OCD

NARCIS (Netherlands)

Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Neale, Benjamin M; Davis, Lea K; Gamazon, Eric R; Derks, Eske M; Evans, Patrick; Edlund, Christopher K; Crane, Jacquelyn; Fagerness, Jesen A; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O Joseph; Black, Donald W; Bloch, Michael H; Brentani, Helena; Bruun, Ruth D; Budman, Cathy L; Camarena, Beatriz; Campbell, Desmond D; Cappi, Carolina; Silgado, Julio C Cardona; Cavallini, Maria C; Chavira, Denise A; Chouinard, Sylvain; Cook, Edwin H; Cookson, M R; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L; Girard, Simon L; Grabe, Hans J; Grados, Marco A; Greenberg, Benjamin D; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A; Hemmings, Sian M J; Herrera, Luis D; Hezel, Dianne M; Hoekstra, Pieter J; Jankovic, Joseph; Kennedy, James L; King, Robert A; Konkashbaev, Anuar I; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T; Mesa Restrepo, Sandra C; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L; Naarden, Allan L; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A; Pakstis, Andrew J; Pato, Michele T; Pato, Carlos N; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L; Renner, Tobias; Reus, Victor I; Richter, Margaret A; Riddle, Mark A; Robertson, Mary M; Romero, Roxana; Rosário, Maria C; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S; Samuels, Jack; Sandor, Paul; Service, Susan K; Sheppard, Brooke; Singer, Harvey S; Smit, Jan H|info:eu-repo/dai/nl/113700644; Stein, Dan J; Strengman, Eric; Tischfield, Jay A; Turiel, Maurizio; Valencia Duarte, Ana V; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R; Westenberg, Herman G M; Shugart, Yin Yao; Hounie, Ana G; Miguel, Euripedes C; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C|info:eu-repo/dai/nl/194111423; McMahon, William; Posthuma, Danielle; Oostra, Ben A; Nestadt, Gerald; Rouleau, Guy A; Purcell, Shaun; Jenike, Michael A; Heutink, Peter; Hanna, Gregory L; Conti, David V; Arnold, Paul D; Freimer, Nelson B; Stewart, S Evelyn; Knowles, James A; Cox, Nancy J; Pauls, David L

OBJECTIVE: Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD

NARCIS (Netherlands)

Yu, Dongmei; Cusi, Daniele; Delorme, Richard; Denys, D.; Dion, Yves; Eapen, Valsama; Heutink, Peter; Cox, Nancy J; Pauls, David L

OBJECTIVE: Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette's Syndrome and OCD

NARCIS (Netherlands)

Yu, D.M.; Mathews, C.A.; Scharf, J.M.; Neale, B.M.; Davis, L.K.; Gamazon, E.R.; Derks, E.M.; Evans, P.; Edlund, C.K.; Crane, J.; Osiecki, L.; Gallagher, P.; Gerber, G.; Haddad, S.; Illmann, C.; McGrath, L.M.; Mayerfeld, C.; Arepalli, S.; Barlassina, C.; Barr, C.L.; Bellodi, L.; Benarroch, F.; Berrio, G.B.; Bienvenu, O.J.; Black, D.W.; Bloch, M.H.; Brentani, H.; Bruun, R.D.; Budman, C.L.; Camarena, B.; Campbell, D.D.; Cappi, C.; Silgado, J.C.C.; Cavallini, M.C.; Chavira, D.A.; Chouinard, S.; Cook, E.H.; Cookson, M.R.; Coric, V.; Cullen, B.; Cusi, D.; Delorme, R.; Denys, D.; Dion, Y.; Eapen, V.; Egberts, K.; Falkai, P.; Fernandez, T.; Fournier, E.; Garrido, H.; Geller, D.; Gilbert, D.L.; Girard, S.L.; Grabe, H.J.; Grados, M.A.; Greenberg, B.D.; Gross-Tsur, V.; Grunblatt, E.; Hardy, J.; Heiman, G.A.; Hemmings, S.M.J.; Herrera, L.D.; Hezel, D.M.; Hoekstra, P.J.; Jankovic, J.; Kennedy, J.L.; King, R.A.; Konkashbaev, A.I.; Kremeyer, B.; Kurlan, R.; Lanzagorta, N.; Leboyer, M.; Leckman, J.F.; Lennertz, L.; Liu, C.Y.; Lochner, C.; Lowe, T.L.; Lupoli, S.; Macciardi, F.; Maier, W.; Manunta, P.; Marconi, M.; McCracken, J.T.; Restrepo, S.C.M.; Moessner, R.; Moorjani, P.; Morgan, J.; Muller, H.; Murphy, D.L.; Naarden, A.L.; Nurmi, E.; Ochoa, W.C.; Ophoff, R. A.; Pakstis, A.J.; Pato, M.T.; Pato, C.N.; Piacentini, J.; Pittenger, C.; Pollak, Y.; Smit, J.H.; Posthuma, D.; Cox, N.J.; Pauls, D.L.

2015-01-01

Objective: Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identi fication of definitive susceptibility genes for these etiologically complex disorders remains elusive. The

Game theory and extremal optimization for community detection in complex dynamic networks.

Science.gov (United States)

Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

2014-01-01

The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2015-01-01

This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

Transition Manifolds of Complex Metastable Systems: Theory and Data-Driven Computation of Effective Dynamics.

Science.gov (United States)

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-01-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Predictors for reproductive isolation in a ring species complex following genetic and ecological divergence.

Science.gov (United States)

Pereira, Ricardo J; Monahan, William B; Wake, David B

2011-07-06

Reproductive isolation (RI) is widely accepted as an important "check point" in the diversification process, since it defines irreversible evolutionary trajectories. Much less consensus exists about the processes that might drive RI. Here, we employ a formal quantitative analysis of genetic interactions at several stages of divergence within the ring species complex Ensatina eschscholtzii in order to assess the relative contribution of genetic and ecological divergence for the development of RI. By augmenting previous genetic datasets and adding new ecological data, we quantify levels of genetic and ecological divergence between populations and test how they correlate with a restriction of genetic admixture upon secondary contact. Our results indicate that the isolated effect of ecological divergence between parental populations does not result in reproductively isolated taxa, even when genetic transitions between parental taxa are narrow. Instead, processes associated with overall genetic divergence are the best predictors of reproductive isolation, and when parental taxa diverge in nuclear markers we observe a complete cessation of hybridization, even to sympatric occurrence of distinct evolutionary lineages. Although every parental population has diverged in mitochondrial DNA, its degree of divergence does not predict the extent of RI. These results show that in Ensatina, the evolutionary outcomes of ecological divergence differ from those of genetic divergence. While evident properties of taxa may emerge via ecological divergence, such as adaptation to local environment, RI is likely to be a byproduct of processes that contribute to overall genetic divergence, such as time in geographic isolation, rather than being a direct outcome of local adaptation.

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD

NARCIS (Netherlands)

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Fagerness, Jesen A.; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald W.; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Silgado, Julio C. Cardona; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L.; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M. J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Mesa Restrepo, Sandra C.; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlos N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosário, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Valencia Duarte, Ana V.; Vallada, Homero; Veenstra-Vanderweele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G. M.; Shugart, Yin Yao; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Rouleau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson B.; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2015-01-01

Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a

Chaperone-client complexes: A dynamic liaison

Science.gov (United States)

Hiller, Sebastian; Burmann, Björn M.

2018-04-01

Living cells contain molecular chaperones that are organized in intricate networks to surveil protein homeostasis by avoiding polypeptide misfolding, aggregation, and the generation of toxic species. In addition, cellular chaperones also fulfill a multitude of alternative functionalities: transport of clients towards a target location, help them fold, unfold misfolded species, resolve aggregates, or deliver clients towards proteolysis machineries. Until recently, the only available source of atomic resolution information for virtually all chaperones were crystal structures of their client-free, apo-forms. These structures were unable to explain details of the functional mechanisms underlying chaperone-client interactions. The difficulties to crystallize chaperones in complexes with clients arise from their highly dynamic nature, making solution NMR spectroscopy the method of choice for their study. With the advent of advanced solution NMR techniques, in the past few years a substantial number of structural and functional studies on chaperone-client complexes have been resolved, allowing unique insight into the chaperone-client interaction. This review summarizes the recent insights provided by advanced high-resolution NMR-spectroscopy to understand chaperone-client interaction mechanisms at the atomic scale.

Logic-based hierarchies for modeling behavior of complex dynamic systems with applications

International Nuclear Information System (INIS)

Hu, Y.S.; Modarres, M.

2000-01-01

Most complex systems are best represented in the form of a hierarchy. The Goal Tree Success Tree and Master Logic Diagram (GTST-MLD) are proven powerful hierarchic methods to represent complex snap-shot of plant knowledge. To represent dynamic behaviors of complex systems, fuzzy logic is applied to replace binary logic to extend the power of GTST-MLD. Such a fuzzy-logic-based hierarchy is called Dynamic Master Logic Diagram (DMLD). This chapter discusses comparison of the use of GTST-DMLD when applied as a modeling tool for systems whose relationships are modeled by either physical, binary logical or fuzzy logical relationships. This is shown by applying GTST-DMLD to the Direct Containment Heating (DCH) phenomenon at pressurized water reactors which is an important safety issue being addressed by the nuclear industry. (orig.)

Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

Directory of Open Access Journals (Sweden)

Joshua Rodewald

2016-10-01

Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

Clinical, immunological and genetic features in eleven Algerian patients with major histocompatibility complex class II expression deficiency

Directory of Open Access Journals (Sweden)

Djidjik Réda

2012-08-01

Full Text Available Abstract Presenting processed antigens to CD4+ lymphocytes during the immune response involves major histocompatibility complex class II molecules. MHC class II genes transcription is regulated by four transcription factors: CIITA, RFXANK, RFX5 and RFXAP. Defects in these factors result in major histocompatibility complex class II expression deficiency, a primary combined immunodeficiency frequent in North Africa. Autosomal recessive mutations in the RFXANK gene have been reported as being the principal defect found in North African patients with this disorder. In this paper, we describe clinical, immunological and genetic features of 11 unrelated Algerian patients whose monocytes display a total absence of MHC class II molecules. They shared mainly the same clinical picture which included protracted diarrhoea and respiratory tract recurrent infections. Genetic analysis revealed that 9 of the 11 patients had the same RFXANK founder mutation, a 26 bp deletion (named I5E6-25_I5E6+1, also known as 752delG26. Immunological and genetic findings in our series may facilitate genetic counselling implementation for Algerian consanguineous families. Further studies need to be conducted to determine 752delG26 heterozygous mutation frequency in Algerian population.

Genetic and chemical diversity of high mucilaginous plants of Sida complex by ISSR markers and chemical fingerprinting.

Science.gov (United States)

Thul, Sanjog T; Srivastava, Ankit K; Singh, Subhash C; Shanker, Karuna

2011-09-01

A method was developed based on multiple approaches wherein DNA and chemical analysis was carried out toward differentiation of important species of Sida complex that is being used for commercial preparation. Isolated DNA samples were successfully performed through PCR amplification using ISSR markers and degree of genetic diversity among the different species of Sida is compared with that of chemical diversity. For genetic fingerprint investigation, selected 10 ISSR primers generating reproducible banding patterns were used. Among the total of 63 amplicons, 62 were recorded as polymorphic, genetic similarity index deduced from ISSR profiles ranged from 12 to 51%. Based on similarity index, S. acuta and S. rhombifolia found to be most similar (51%). High number of species-specific bands played pivotal role to delineate species at genetic level. Investigation based on HPTLC fingerprints analysis revealed 23 bands representing to characteristic chemicals and similarity index ranged from 73 to 91%. Prominent distinguishable bands were observed only in S. acuta, while S. cordifolia and S. rhombifolia shared most bands making them difficult to identify on chemical fingerprint basis. This report summarizes the genotypic and chemotypic diversity and the use of profiles for authentication of species of Sida complex.

A Hypothesis for Using Pathway Genetic Load Analysis for Understanding Complex Outcomes in Bilirubin Encephalopathy

Science.gov (United States)

Riordan, Sean M.; Bittel, Douglas C.; Le Pichon, Jean-Baptiste; Gazzin, Silvia; Tiribelli, Claudio; Watchko, Jon F.; Wennberg, Richard P.; Shapiro, Steven M.

2016-01-01

Genetic-based susceptibility to bilirubin neurotoxicity and chronic bilirubin encephalopathy (kernicterus) is still poorly understood. Neonatal jaundice affects 60–80% of newborns, and considerable effort goes into preventing this relatively benign condition from escalating into the development of kernicterus making the incidence of this potentially devastating condition very rare in more developed countries. The current understanding of the genetic background of kernicterus is largely comprised of mutations related to alterations of bilirubin production, elimination, or both. Less is known about mutations that may predispose or protect against CNS bilirubin neurotoxicity. The lack of a monogenetic source for this risk of bilirubin neurotoxicity suggests that disease progression is dependent upon an overall decrease in the functionality of one or more essential genetically controlled metabolic pathways. In other words, a “load” is placed on key pathways in the form of multiple genetic variants that combine to create a vulnerable phenotype. The idea of epistatic interactions creating a pathway genetic load (PGL) that affects the response to a specific insult has been previously reported as a PGL score. We hypothesize that the PGL score can be used to investigate whether increased susceptibility to bilirubin-induced CNS damage in neonates is due to a mutational load being placed on key genetic pathways important to the central nervous system's response to bilirubin neurotoxicity. We propose a modification of the PGL score method that replaces the use of a canonical pathway with custom gene lists organized into three tiers with descending levels of evidence combined with the utilization of single nucleotide polymorphism (SNP) causality prediction methods. The PGL score has the potential to explain the genetic background of complex bilirubin induced neurological disorders (BIND) such as kernicterus and could be the key to understanding ranges of outcome severity

Complex dynamics analysis of impulsively coupled Duffing oscillators with ring structure

International Nuclear Information System (INIS)

Jiang Hai-Bo; Zhang Li-Ping; Yu Jian-Jiang

2015-01-01

Impulsively coupled systems are high-dimensional non-smooth systems that can exhibit rich and complex dynamics. This paper studies the complex dynamics of a non-smooth system which is unidirectionally impulsively coupled by three Duffing oscillators in a ring structure. By constructing a proper Poincaré map of the non-smooth system, an analytical expression of the Jacobian matrix of Poincaré map is given. Two-parameter Hopf bifurcation sets are obtained by combining the shooting method and the Runge–Kutta method. When the period is fixed and the coupling strength changes, the system undergoes stable, periodic, quasi-periodic, and hyper-chaotic solutions, etc. Floquet theory is used to study the stability of the periodic solutions of the system and their bifurcations. (paper)

Outer synchronization between two different fractional-order general complex dynamical networks

International Nuclear Information System (INIS)

Xiang-Jun, Wu; Hong-Tao, Lu

2010-01-01

Outer synchronization between two different fractional-order general complex dynamical networks is investigated in this paper. Based on the stability theory of the fractional-order system, the sufficient criteria for outer synchronization are derived analytically by applying the nonlinear control and the bidirectional coupling methods. The proposed synchronization method is applicable to almost all kinds of coupled fractional-order general complex dynamical networks. Neither a symmetric nor irreducible coupling configuration matrix is required. In addition, no constraint is imposed on the inner-coupling matrix. Numerical examples are also provided to demonstrate the validity of the presented synchronization scheme. Numeric evidence shows that both the feedback strength k and the fractional order α can be chosen appropriately to adjust the synchronization effect effectively. (general)

The heterogeneous dynamics of economic complexity.

Science.gov (United States)

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.

Adaptive synchronization of the complex dynamical network with non-derivative and derivative coupling

Energy Technology Data Exchange (ETDEWEB)

Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teachers' College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen [School of Mathematics and Information, Yangtze University, Hubei Jingzhou 434023 (China)

2010-04-05

This Letter investigates the synchronization of a general complex dynamical network with non-derivative and derivative coupling. Based on LaSalle's invariance principle, adaptive synchronization criteria are obtained. Analytical result shows that under the designed adaptive controllers, a general complex dynamical network with non-derivative and derivative coupling can asymptotically synchronize to a given trajectory, and several useful criteria for synchronization are given. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulations results show the method is effective.

Genetic variation in foundation species governs the dynamics of trophic interactions

Science.gov (United States)

Valencia-Cuevas, Leticia; Mussali-Galante, Patricia; Cano-Santana, Zenón; Pujade-Villar, Juli; Equihua-Martínez, Armando

2018-01-01

Abstract Various studies have demonstrated that the foundation species genetic diversity can have direct effects that extend beyond the individual or population level, affecting the dependent communities. Additionally, these effects may be indirectly extended to higher trophic levels throughout the entire community. Quercus castanea is an oak species with characteristics of foundation species beyond presenting a wide geographical distribution and being a dominant element of Mexican temperate forests. In this study, we analyzed the influence of population (He) and individual (HL) genetic diversity of Q. castanea on its canopy endophagous insect community and associated parasitoids. Specifically, we studied the composition, richness (S) and density of leaf-mining moths (Lepidoptera: Tischeridae, Citheraniidae), gall-forming wasps (Hymenoptera: Cynipidae), and canopy parasitoids of Q. castanea. We sampled 120 trees belonging to six populations (20/site) through the previously recognized gradient of genetic diversity. In total, 22 endophagous insect species belonging to three orders (Hymenoptera, Lepidoptera, and Diptera) and 20 parasitoid species belonging to 13 families were identified. In general, we observed that the individual genetic diversity of the host plant (HL) has a significant positive effect on the S and density of the canopy endophagous insect communities. In contrast, He has a significant negative effect on the S of endophagous insects. Additionally, indirect effects of HL were observed, affecting the S and density of parasitoid insects. Our results suggest that genetic variation in foundation species can be one of the most important factors governing the dynamics of tritrophic interactions that involve oaks, herbivores, and parasitoids. PMID:29492034

A UV-Induced Genetic Network Links the RSC Complex to Nucleotide Excision Repair and Shows Dose-Dependent Rewiring

Directory of Open Access Journals (Sweden)

Rohith Srivas

2013-12-01

Full Text Available Efficient repair of UV-induced DNA damage requires the precise coordination of nucleotide excision repair (NER with numerous other biological processes. To map this crosstalk, we generated a differential genetic interaction map centered on quantitative growth measurements of >45,000 double mutants before and after different doses of UV radiation. Integration of genetic data with physical interaction networks identified a global map of 89 UV-induced functional interactions among 62 protein complexes, including a number of links between the RSC complex and several NER factors. We show that RSC is recruited to both silenced and transcribed loci following UV damage where it facilitates efficient repair by promoting nucleosome remodeling. Finally, a comparison of the response to high versus low levels of UV shows that the degree of genetic rewiring correlates with dose of UV and reveals a network of dose-specific interactions. This study makes available a large resource of UV-induced interactions, and it illustrates a methodology for identifying dose-dependent interactions based on quantitative shifts in genetic networks.

Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks.

Science.gov (United States)

Kastrup, Christian J; Runyon, Matthew K; Lucchetta, Elena M; Price, Jessica M; Ismagilov, Rustem F

2008-04-01

Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to

Small System dynamics models for big issues : Triple jump towards real-world complexity

NARCIS (Netherlands)

Pruyt, E.

2013-01-01

System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and analysis facilitates the (re)design of systems and design of

The dynamic behavior of the exohedral transition metal complexes ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Chemical Sciences; Volume 129; Issue 7. The dynamic behavior of the exohedral transition metal complexes of B₄₀ : η⁶- and η⁷-B₄₀Cr(CO) ₃ and Cr(CO) ₃η⁷-B₄η₀-Cr(CO) ₃. NAIWRIT KARMODAK ELUVATHINGAL D JEMMIS. REGULAR ARTICLE Volume 129 Issue 7 July 2017 pp ...

Consent, ethics and genetic biobanks: the case of the Athlome project.

Science.gov (United States)

Thompson, Rachel; McNamee, Michael J

2017-11-14

This article provides a critical overview of the ethics and governance of genetic biobank research, using the Athlome Consortium as a large scale instance of collaborative sports genetic biobanking. We present a traditional model of written informed consent for the acquisition, storage, sharing and analysis of genetic data and articulate the challenges to it from new research practices such as genetic biobanking. We then articulate six possible alternative consent models: verbal consent, blanket consent, broad consent, meta consent, dynamic consent and waived consent. We argue that these models or conceptions of consent must be articulated in the context of the complexities of international legislation and non legislative national and international biobank governance frameworks and policies, those which govern research in the field of sports genetics. We discuss the tensions between individual rights and public benefits of genomic research as a critical ethical issue, particularly where benefits are less obvious, as in sports genomics. The inherent complexities of international regulation and biobanking governance are challenging in a relatively young field. We argue that there is much nuanced ethical work still to be done with regard to governance of sports genetic biobanking and the issues contained therein.

Homologous genetic recombination in the yellow head complex of nidoviruses infecting Penaeus monodon shrimp.

Science.gov (United States)

Wijegoonawardane, Priyanjalie K M; Sittidilokratna, Nusra; Petchampai, Natthida; Cowley, Jeff A; Gudkovs, Nicholas; Walker, Peter J

2009-07-20

Yellow head virus (YHV) is a highly virulent pathogen of Penaeus monodon shrimp. It is one of six known genotypes in the yellow head complex of nidoviruses which also includes mildly pathogenic gill-associated virus (GAV, genotype 2) and four other genotypes (genotypes 3-6) that have been detected only in healthy shrimp. In this study, comparative phylogenetic analyses conducted on replicase- (ORF1b) and glycoprotein- (ORF3) gene amplicons identified 10 putative natural recombinants amongst 28 viruses representing all six genotypes from across the Indo-Pacific region. The approximately 4.6 kb genomic region spanning the two amplicons was sequenced for three putative recombinant viruses from Vietnam (genotype 3/5), the Philippines (genotype 5/2) and Indonesia (genotype 3/2). SimPlot analysis using these and representative parental virus sequences confirmed that each was a recombinant genotype and identified a recombination hotspot in a region just upstream of the ORF1b C-terminus. Maximum-likelihood breakpoint analysis predicted identical crossover positions in the Vietnamese and Indonesian recombinants, and a crossover position 12 nt upstream in the Philippine recombinant. Homologous genetic recombination in the same genome region was also demonstrated in recombinants generated experimentally in shrimp co-infected with YHV and GAV. The high frequency with which natural recombinants were identified indicates that genetic exchange amongst genotypes is occurring commonly in Asia and playing a significant role in expanding the genetic diversity in the yellow head complex. This is the first evidence of genetic recombination in viruses infecting crustaceans and has significant implications for the pathogenesis of infection and diagnosis of these newly emerging invertebrate pathogens.

The dynamic complexity of a three species food chain model

International Nuclear Information System (INIS)

Lv Songjuan; Zhao Min

2008-01-01

In this paper, a three-species food chain model is analytically investigated on theories of ecology and using numerical simulation. Bifurcation diagrams are obtained for biologically feasible parameters. The results show that the system exhibits rich complexity features such as stable, periodic and chaotic dynamics

Multi-person tracking with overlapping cameras in complex, dynamic environments

NARCIS (Netherlands)

Liem, M.; Gavrila, D.M.

2009-01-01

This paper presents a multi-camera system to track multiple persons in complex, dynamic environments. Position measurements are obtained by carving out the space defined by foreground regions in the overlapping camera views and projecting these onto blobs on the ground plane. Person appearance is

Application of network methods for understanding evolutionary dynamics in discrete habitats.

Science.gov (United States)

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

The Effects of Different Types of Text and Individual Differences on View Complexity about Genetically Modified Organisms

Science.gov (United States)

Dinsmore, Daniel L.; Zoellner, Brian P.; Parkinson, Meghan M.; Rossi, Anthony M.; Monk, Mary J.; Vinnachi, Jenelle

2017-01-01

View change about socio-scientific issues has been well studied in the literature, but the change in the complexity of those views has not. In the current study, the change in the complexity of views about a specific scientific topic (i.e. genetically modified organisms; GMOs) and use of evidence in explaining those views was examined in relation…

Absorption dynamics and delay time in complex potentials

Science.gov (United States)

Villavicencio, Jorge; Romo, Roberto; Hernández-Maldonado, Alberto

2018-05-01

The dynamics of absorption is analyzed by using an exactly solvable model that deals with an analytical solution to Schrödinger’s equation for cutoff initial plane waves incident on a complex absorbing potential. A dynamical absorption coefficient which allows us to explore the dynamical loss of particles from the transient to the stationary regime is derived. We find that the absorption process is characterized by the emission of a series of damped periodic pulses in time domain, associated with damped Rabi-type oscillations with a characteristic frequency, ω = (E + ε)/ℏ, where E is the energy of the incident waves and ‑ε is energy of the quasidiscrete state of the system induced by the absorptive part of the Hamiltonian; the width γ of this resonance governs the amplitude of the pulses. The resemblance of the time-dependent absorption coefficient with a real decay process is discussed, in particular the transition from exponential to nonexponential regimes, a well-known feature of quantum decay. We have also analyzed the effect of the absorptive part of the potential on the dynamical delay time, which behaves differently from the one observed in attractive real delta potentials, exhibiting two regimes: time advance and time delay.

Genetic algorithm optimization for dynamic construction site layout planning

Directory of Open Access Journals (Sweden)

Farmakis Panagiotis M.

2018-02-01

Full Text Available The dynamic construction site layout planning (DCSLP problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indi­cate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process.

Dynamics on and of complex networks applications to biology, computer science, and the social sciences

CERN Document Server

Ganguly, Niloy; Mukherjee, Animesh

2009-01-01

This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. The theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline. The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Towards this goal, the work is thematically organized into three main sections: Part I studies th

Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example

Directory of Open Access Journals (Sweden)

Benjamin A Goldstein

2014-08-01

Full Text Available Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers. Materials & Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD in the Atherosclerosis Risk in Communities (ARIC cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.Results: The addition of a GRS to a clinical risk score (CRS improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor SNPs are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider. Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

Automated x-ray television complex for inspecting standard-size dynamic objects

International Nuclear Information System (INIS)

Gusev, E.A.; Luk'yanenko, E.A.; Chelnokov, V.B.; Kuleshov, V.K.; Alkhimov, Yu.V.

1993-01-01

An automated x-ray television complex based on a matrix gas-discharge converter having a large area (2.1 x 1.0 m) for inspecting standard-size freight and containers and for diagnosing industrial articles is presented. The pulsed operating mode of the complex with a 512K digital television storage makes it possible to inspect dynamic objects with a minimum dose load (20--100 μR). 6 refs., 5 figs

From Genetics to Genetic Algorithms

Indian Academy of Sciences (India)

artificial genetic system) string feature or ... called the genotype whereas it is called a structure in artificial genetic ... assigned a fitness value based on the cost function. Better ..... way it has produced complex, intelligent living organisms capable of ...

An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries

OpenAIRE

Vellev, Stoyan

2008-01-01

The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...

Experimental and theoretical evidence for the chaotic dynamics of complex structures

International Nuclear Information System (INIS)

Agop, M; Dimitriu, D G; Poll, E; Niculescu, O; Radu, V

2013-01-01

This paper presents the experimental results on the formation, dynamics and evolution towards chaos of complex space charge structures that emerge in front of a positively biased electrode immersed in a quiescent plasma. In certain experimental conditions, we managed to obtain the so-called multiple double layers (MDLs) with non-concentric configuration. Our experiments show that the interactions between each MDL's constituent entities are held responsible for the complex dynamics and eventually for its transition to chaos through cascades of spatio-temporal sub-harmonic bifurcations. Further, we build a theoretical model based on the fractal approximation (scale relativity theory) in order to reproduce the experimental results (plasma self-structuring and scenario of evolution to chaos). Comparing the experimental results with the theoretical ones, we observe a good correlation between them. (paper)

Transitions in genetic toggle switches driven by dynamic disorder in rate coefficients

International Nuclear Information System (INIS)

Chen, Hang; Thill, Peter; Cao, Jianshu

2016-01-01

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes with the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.

Transitions in genetic toggle switches driven by dynamic disorder in rate coefficients

Energy Technology Data Exchange (ETDEWEB)

Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu [Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

2016-05-07

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes with the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.

Framework based on communicability and flow to analyze complex network dynamics

Science.gov (United States)

Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.

2018-05-01

Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.

Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes

Science.gov (United States)

Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.

1996-01-01

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.

Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

Science.gov (United States)

Sastry, Kumara Narasimha

2007-03-01

Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

Exploring the dynamic and complex integration of sustainability performance measurement into product development

DEFF Research Database (Denmark)

Rodrigues, Vinicius Picanco; Morioka, S.; Pigosso, Daniela Cristina Antelmi

2016-01-01

In order to deal with the complex and dynamic nature of sustainability integration into the product development process, this research explore the use of a qualitative System Dynamics approach by using the causal loop diagram (CLD) tool. A literature analysis was followed by a case study, aiming ...

Structure and dynamics of weakly bound complexes

International Nuclear Information System (INIS)

Skouteris, D.

1998-01-01

The present thesis deals with the spectroscopic and theoretical investigation of weakly bound complexes involving a methane molecule. Studies of these Van der Waals complexes can give valuable information on the relevant intermolecular dynamics and promote the understanding of the interactions between molecules (which can ultimately lead to chemical reactions). Especially interesting are complexes involving molecules of high symmetry (e.g. tetrahedral, such as methane) because of the unusual effects arising from it (selection rules, nuclear Spin statistical weights etc.). The infrared spectrum of the Van der Waals complex between a CH 4 and a N 2 O molecule has been recorded and most of it has been assigned in the region of the N - O stretch (approximately 2225.0 cm -1 ). Despite the fact that this is really a weakly bound complex, it is nevertheless rigid enough so that the standard model for asymmetric top spectra can be applied to it with the usual quantum numbers. From the value of the inertial defect, it turns out that the methane unit is locked in a rigid configuration within the complex rather than freely rotating. The intermolecular distance as well as the tilting angle of the N 2 O linear unit are determined from the rotational constants. The complex itself turns out to have a T - shaped configuration. The infrared spectrum of the Ar - CH 4 complex at the ν 4 (bending) band of methane is also assigned. This is different from the previous one in that the methane unit rotates almost freely Within the complex. As a result, the quantum numbers used to classify rovibrational energy levels include these of the free unit. The concept of 'overall symmetry' is made use of to rationalise selection rules in various sub-bands of the spectrum. Moreover, new terms in the potential anisotropy Hamiltonian are calculated through the use of the overall symmetry concept. These are termed 'mixed anisotropy' terms since they involve both rotational and vibrational degrees of

On the Computational Complexity of the Languages of General Symbolic Dynamical Systems and Beta-Shifts

DEFF Research Database (Denmark)

Simonsen, Jakob Grue

2009-01-01

We consider the computational complexity of languages of symbolic dynamical systems. In particular, we study complexity hierarchies and membership of the non-uniform class P/poly. We prove: 1.For every time-constructible, non-decreasing function t(n)=@w(n), there is a symbolic dynamical system...... with language decidable in deterministic time O(n^2t(n)), but not in deterministic time o(t(n)). 2.For every space-constructible, non-decreasing function s(n)=@w(n), there is a symbolic dynamical system with language decidable in deterministic space O(s(n)), but not in deterministic space o(s(n)). 3.There...... are symbolic dynamical systems having hard and complete languages under @?"m^l^o^g^s- and @?"m^p-reduction for every complexity class above LOGSPACE in the backbone hierarchy (hence, P-complete, NP-complete, coNP-complete, PSPACE-complete, and EXPTIME-complete sets). 4.There are decidable languages of symbolic...

Epidemic dynamics and endemic states in complex networks

OpenAIRE

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-01-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below which the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are pron...

Dynamic complexities in a seasonal prevention epidemic model with birth pulses

International Nuclear Information System (INIS)

Gao Shujing; Chen Lansun; Sun Lihua

2005-01-01

In most of population dynamics, increases in population due to birth are assumed to be time-dependent, but many species reproduce only during a single period of the year. In this paper, we propose an epidemic model with density-dependent birth pulses and seasonal prevention. Using the discrete dynamical system determined by stroboscopic map, we obtain the local or global stability, numerical simulation shows there is a characteristic sequence of bifurcations, leading to chaotic dynamics, which implies that the dynamical behaviors of the epidemic model with birth pulses and seasonal prevention are very complex, including small amplitude oscillations, large-amplitude multi-annual cycles and chaos. This suggests that birth pulse, in effect, provides a natural period or cyclicity that may lead a period-doubling route to chaos

Complex Dynamic Development of Poliovirus Membranous Replication Complexes

Science.gov (United States)

Nair, Vinod; Hansen, Bryan T.; Hoyt, Forrest H.; Fischer, Elizabeth R.; Ehrenfeld, Ellie

2012-01-01

Replication of all positive-strand RNA viruses is intimately associated with membranes. Here we utilize electron tomography and other methods to investigate the remodeling of membranes in poliovirus-infected cells. We found that the viral replication structures previously described as “vesicles” are in fact convoluted, branching chambers with complex and dynamic morphology. They are likely to originate from cis-Golgi membranes and are represented during the early stages of infection by single-walled connecting and branching tubular compartments. These early viral organelles gradually transform into double-membrane structures by extension of membranous walls and/or collapsing of the luminal cavity of the single-membrane structures. As the double-membrane regions develop, they enclose cytoplasmic material. At this stage, a continuous membranous structure may have double- and single-walled membrane morphology at adjacent cross-sections. In the late stages of the replication cycle, the structures are represented mostly by double-membrane vesicles. Viral replication proteins, double-stranded RNA species, and actively replicating RNA are associated with both double- and single-membrane structures. However, the exponential phase of viral RNA synthesis occurs when single-membrane formations are predominant in the cell. It has been shown previously that replication complexes of some other positive-strand RNA viruses form on membrane invaginations, which result from negative membrane curvature. Our data show that the remodeling of cellular membranes in poliovirus-infected cells produces structures with positive curvature of membranes. Thus, it is likely that there is a fundamental divergence in the requirements for the supporting cellular membrane-shaping machinery among different groups of positive-strand RNA viruses. PMID:22072780

Complex Nonlinear Dynamic System of Oligopolies Price Game with Heterogeneous Players Under Noise

Science.gov (United States)

Liu, Feng; Li, Yaguang

A nonlinear four oligopolies price game with heterogeneous players, that are boundedly rational and adaptive, is built using two different special demand costs. Based on the theory of complex discrete dynamical system, the stability and the existing equilibrium point are investigated. The complex dynamic behavior is presented via bifurcation diagrams, the Lyapunov exponents to show equilibrium state, bifurcation and chaos with the variation in parameters. As disturbance is ubiquitous in economic systems, this paper focuses on the analysis of delay feedback control method under noise circumstances. Stable dynamics is confirmed to depend mainly on the low price adjustment speed, and if all four players have limited opportunities to stabilize the market, the new adaptive player facing profits of scale are found to be higher than the incumbents of bounded rational.

eQTL Networks Reveal Complex Genetic Architecture in the Immature Soybean Seed

Directory of Open Access Journals (Sweden)

Yung-Tsi Bolon

2014-03-01

Full Text Available The complex network of regulatory factors and interactions involved in transcriptional regulation within the seed is not well understood. To evaluate gene expression regulation in the immature seed, we utilized a genetical genomics approach on a soybean [ (L. Merr.] recombinant inbred line (RIL population and produced a genome-wide expression quantitative trait loci (eQTL dataset. The validity of the dataset was confirmed by mapping the eQTL hotspot for flavonoid biosynthesis-related genes to a region containing repeats of chalcone synthase (CHS genes known to correspond to the soybean inhibitor locus that regulates seed color. We then identified eQTL for genes with seed-specific expression and discovered striking eQTL hotspots at distinct genomic intervals on chromosomes (Chr 20, 7, and 13. The main eQTL hotspot for transcriptional regulation of fatty acid biosynthesis genes also coincided with regulation of oleosin genes. Transcriptional upregulation of genesets from eQTL with opposite allelic effects were also found. Gene–eQTL networks were constructed and candidate regulatory genes were identified from these three key loci specific to seed expression and enriched in genes involved in seed oil accumulation. Our data provides new insight into the complex nature of gene networks in the immature soybean seed and the genetic architecture that contributes to seed development.

Young Children's Knowledge About the Moon: A Complex Dynamic System

Science.gov (United States)

Venville, Grady J.; Louisell, Robert D.; Wilhelm, Jennifer A.

2012-08-01

The purpose of this research was to use a multidimensional theoretical framework to examine young children's knowledge about the Moon. The research was conducted in the interpretive paradigm and the design was a multiple case study of ten children between the ages of three and eight from the USA and Australia. A detailed, semi-structured interview was conducted with each child. In addition, each child's parents were interviewed to determine possible social and cultural influences on the child's knowledge. We sought evidence about how the social and cultural experiences of the children might have influenced the development of their ideas. From a cognitive perspective we were interested in whether the children's ideas were constructed in a theory like form or whether the knowledge was the result of gradual accumulation of fragments of isolated cultural information. Findings reflected the strong and complex relationship between individual children, their social and cultural milieu, and the way they construct ideas about the Moon and astronomy. Findings are presented around four themes including ontology, creatures and artefacts, animism, and permanence. The findings support a complex dynamic system view of students' knowledge that integrates the framework theory perspective and the knowledge in fragments perspective. An initial model of a complex dynamic system of young children's knowledge about the Moon is presented.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

Directory of Open Access Journals (Sweden)

Dowling Damian K

2011-07-01

Full Text Available Abstract Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass, and each trait harboured significant additive genetic variance in the standard temperature (27°C only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass. Of the female traits measured, only ovary mass for crickets

Unpacking complexities of managerial subjectivity: An analytic fixation on constitutive dynamics

DEFF Research Database (Denmark)

Plotnikof, Mie

2012-01-01

, and the analytic challenges of discourse/Discourse-distinctions and avoiding agency-structure-dualism. This paper proposes an integral conceptualization of subjectification that directs analytic attention to the complex constitutive dynamics of organizational discourses and agency normative to organizational...... is discussed with a case-study of public managers in collaborative governance processes in the Danish day-care sector. With complex-sensitive analytics the paper contributes to the ‘plurivocal’ debate on advancing organizational discourse approaches....

Protein dynamics during presynaptic complex assembly on individual ssDNA molecules

OpenAIRE

Gibb, Bryan; Ye, Ling F.; Kwon, YoungHo; Niu, Hengyao; Sung, Patrick; Greene, Eric C.

2014-01-01

Homologous recombination is a conserved pathway for repairing double?stranded breaks, which are processed to yield single?stranded DNA overhangs that serve as platforms for presynaptic complex assembly. Here we use single?molecule imaging to reveal the interplay between Saccharomyce cerevisiae RPA, Rad52, and Rad51 during presynaptic complex assembly. We show that Rad52 binds RPA?ssDNA and suppresses RPA turnover, highlighting an unanticipated regulatory influence on protein dynamics. Rad51 b...

A reconfigurable NAND/NOR genetic logic gate.

Science.gov (United States)

Goñi-Moreno, Angel; Amos, Martyn

2012-09-18

Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.

Impacts of large dams on the complexity of suspended sediment dynamics in the Yangtze River

Science.gov (United States)

Wang, Yuankun; Rhoads, Bruce L.; Wang, Dong; Wu, Jichun; Zhang, Xiao

2018-03-01

The Yangtze River is one of the largest and most important rivers in the world. Over the past several decades, the natural sediment regime of the Yangtze River has been altered by the construction of dams. This paper uses multi-scale entropy analysis to ascertain the impacts of large dams on the complexity of high-frequency suspended sediment dynamics in the Yangtze River system, especially after impoundment of the Three Gorges Dam (TGD). In this study, the complexity of sediment dynamics is quantified by framing it within the context of entropy analysis of time series. Data on daily sediment loads for four stations located in the mainstem are analyzed for the past 60 years. The results indicate that dam construction has reduced the complexity of short-term (1-30 days) variation in sediment dynamics near the structures, but that complexity has actually increased farther downstream. This spatial pattern seems to reflect a filtering effect of the dams on the on the temporal pattern of sediment loads as well as decreased longitudinal connectivity of sediment transfer through the river system, resulting in downstream enhancement of the influence of local sediment inputs by tributaries on sediment dynamics. The TGD has had a substantial impact on the complexity of sediment series in the mainstem of the Yangtze River, especially after it became fully operational. This enhanced impact is attributed to the high trapping efficiency of this dam and its associated large reservoir. The sediment dynamics "signal" becomes more spatially variable after dam construction. This study demonstrates the spatial influence of dams on the high-frequency temporal complexity of sediment regimes and provides valuable information that can be used to guide environmental conservation of the Yangtze River.

NATO Advanced Research Workshop on Dynamics of Polyatomic Van der Waals Complexes

CERN Document Server

Janda, Kenneth

1991-01-01

This publication is the Proceedings of the NATO Advanced Research Workshop (ARW) on the Dynamics of Polyatomic Van der Waals Molecules held at the Chateau de Bonas, Castera-Verduzan, France, from August 21 through August 26, 1989. Van der Waals complexes provide important model problems for understanding energy transfer and dissipation. These processes can be described in great detail for Van der Waals complexes, and the insight gained from such studies can be applied to more complicated chemical problems that are not amenable to detailed study. The workshop concentrated on the current questions and future prospects for extend­ ing our highly detailed knowledge of triatomic Van der Waals molecule dynamics to polyatomic molecules and clusters (one molecule surrounded by several, or up to sev­ eral tens of, atoms). Both experimental and theoretical studies were discussed, with particular emphasis on the dynamical behavior of dissociation as observed in the dis­ tributions of quantum states of the dissociatio...

Hash function construction using weighted complex dynamical networks

International Nuclear Information System (INIS)

Song Yu-Rong; Jiang Guo-Ping

2013-01-01

A novel scheme to construct a hash function based on a weighted complex dynamical network (WCDN) generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then, each block is divided into components, and the nodes and weighted edges are well defined from these components and their relations. Namely, the WCDN closely related to the original message is established. Furthermore, the node dynamics of the WCDN are chosen as a chaotic map. After chaotic iterations, quantization and exclusive-or operations, the fixed-length hash value is obtained. This scheme has the property that any tiny change in message can be diffused rapidly through the WCDN, leading to very different hash values. Analysis and simulation show that the scheme possesses good statistical properties, excellent confusion and diffusion, strong collision resistance and high efficiency. (general)

Exponentially asymptotical synchronization in uncertain complex dynamical networks with time delay

Energy Technology Data Exchange (ETDEWEB)

Luo Qun; Yang Han; Li Lixiang; Yang Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Han Jiangxue, E-mail: luoqun@bupt.edu.c [National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)

2010-12-10

Over the past decade, complex dynamical network synchronization has attracted more and more attention and important developments have been made. In this paper, we explore the scheme of globally exponentially asymptotical synchronization in complex dynamical networks with time delay. Based on Lyapunov stability theory and through defining the error function between adjacent nodes, four novel adaptive controllers are designed under four situations where the Lipschitz constants of the state function in nodes are known or unknown and the network structure is certain or uncertain, respectively. These controllers could not only globally asymptotically synchronize all nodes in networks, but also ensure that the error functions do not exceed the pre-scheduled exponential function. Finally, simulations of the synchronization among the chaotic system in the small-world and scale-free network structures are presented, which prove the effectiveness and feasibility of our controllers.

On the representation of contextual probabilistic dynamics in the complex Hilbert space: Linear and nonlinear evolutions, Schrodinger dynamics

International Nuclear Information System (INIS)

Khrennikov, A.

2005-01-01

We constructed the representation of contextual probabilistic dynamics in the complex Hilbert space. Thus dynamics of the wave function can be considered as Hilbert space projection of realistic dynamics in a pre space. The basic condition for representing the pre space-dynamics is the law of statistical conservation of energy-conservation of probabilities. The construction of the dynamical representation is an important step in the development of contextual statistical viewpoint of quantum processes. But the contextual statistical model is essentially more general than the quantum one. Therefore in general the Hilbert space projection of the pre space dynamics can be nonlinear and even irreversible (but it is always unitary). There were found conditions of linearity and reversibility of the Hilbert space dynamical projection. We also found conditions for the conventional Schrodinger dynamics (including time-dependent Hamiltonians). We remark that in general even the Schrodinger dynamics is based just on the statistical conservation of energy; for individual systems the law of conservation of energy can be violated (at least in our theoretical model)

Complex dynamics in Duffing system with two external forcings

International Nuclear Information System (INIS)

Jing Zhujun; Wang Ruiqi

2005-01-01

Duffing's equation with two external forcing terms have been discussed. The threshold values of chaotic motion under the periodic and quasi-periodic perturbations are obtained by using second-order averaging method and Melnikov's method. Numerical simulations not only show the consistence with the theoretical analysis but also exhibit the interesting bifurcation diagrams and the more new complex dynamical behaviors, including period-n (n=2,3,6,8) orbits, cascades of period-doubling and reverse period doubling bifurcations, quasi-periodic orbit, period windows, bubble from period-one to period-two, onset of chaos, hopping behavior of chaos, transient chaos, chaotic attractors and strange non-chaotic attractor, crisis which depends on the frequencies, amplitudes and damping. In particular, the second frequency plays a very important role for dynamics of the system, and the system can leave chaotic region to periodic motions by adjusting some parameter which can be considered as an control strategy of chaos. The computation of Lyapunov exponents confirm the dynamical behaviors

Identification of Complex Dynamical Systems with Neural Networks (2/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Identification of Complex Dynamical Systems with Neural Networks (1/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

Science.gov (United States)

Heidema, A Geert; Boer, Jolanda M A; Nagelkerke, Nico; Mariman, Edwin C M; van der A, Daphne L; Feskens, Edith J M

2006-04-21

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association

Preictal dynamics of EEG complexity in intracranially recorded epileptic seizure: a case report.

Science.gov (United States)

Bob, Petr; Roman, Robert; Svetlak, Miroslav; Kukleta, Miloslav; Chladek, Jan; Brazdil, Milan

2014-11-01

Recent findings suggest that neural complexity reflecting a number of independent processes in the brain may characterize typical changes during epileptic seizures and may enable to describe preictal dynamics. With respect to previously reported findings suggesting specific changes in neural complexity during preictal period, we have used measure of pointwise correlation dimension (PD2) as a sensitive indicator of nonstationary changes in complexity of the electroencephalogram (EEG) signal. Although this measure of complexity in epileptic patients was previously reported by Feucht et al (Applications of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures. Med Biol Comput. 1999;37:208-217), it was not used to study changes in preictal dynamics. With this aim to study preictal changes of EEG complexity, we have examined signals from 11 multicontact depth (intracerebral) EEG electrodes located in 108 cortical and subcortical brain sites, and from 3 scalp EEG electrodes in a patient with intractable epilepsy, who underwent preoperative evaluation before epilepsy surgery. From those 108 EEG contacts, records related to 44 electrode contacts implanted into lesional structures and white matter were not included into the experimental analysis.The results show that in comparison to interictal period (at about 8-6 minutes before seizure onset), there was a statistically significant decrease in PD2 complexity in the preictal period at about 2 minutes before seizure onset in all 64 intracranial channels localized in various brain sites that were included into the analysis and in 3 scalp EEG channels as well. Presented results suggest that using PD2 in EEG analysis may have significant implications for research of preictal dynamics and prediction of epileptic seizures.

Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

CERN Document Server

Knabe, Johannes F

2013-01-01

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

The Complexity of Dynamics in Small Neural Circuits.

Directory of Open Access Journals (Sweden)

Diego Fasoli

2016-08-01

Full Text Available Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing.

The effects of riverine physical complexity on anadromy and genetic diversity in steelhead or rainbow trout Oncorhynchus mykiss around the Pacific Rim.

Science.gov (United States)

McPhee, M V; Whited, D C; Kuzishchin, K V; Stanford, J A

2014-07-01

This study explored the relationship between riverine physical complexity, as determined from remotely sensed metrics, and anadromy and genetic diversity in steelhead or rainbow trout Oncorhynchus mykiss. The proportion of anadromy (estimated fraction of individuals within a drainage that are anadromous) was correlated with riverine complexity, but this correlation appeared to be driven largely by a confounding negative relationship between drainage area and the proportion of anadromy. Genetic diversity decreased with latitude, was lower in rivers with only non-anadromous individuals and also decreased with an increasing ratio of floodplain area to total drainage area. Anadromy may be less frequent in larger drainages due to the higher cost of migration associated with reaches farther from the ocean, and the negative relationship between genetic diversity and floodplain area may be due to lower effective population size resulting from greater population fluctuations associated with higher rates of habitat turnover. Ultimately, the relationships between riverine physical complexity and migratory life history or genetic diversity probably depend on the spatial scale of analysis. © 2014 The Fisheries Society of the British Isles.

Precise regulation of gene expression dynamics favors complex promoter architectures.

Directory of Open Access Journals (Sweden)

Dirk Müller

2009-01-01

Full Text Available Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure.

Return-to-Work Within a Complex and Dynamic Organizational Work Disability System

OpenAIRE

Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J.

2015-01-01

Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, an...

Quantum coherence spectroscopy reveals complex dynamics in bacterial light-harvesting complex 2 (LH2).

Science.gov (United States)

Harel, Elad; Engel, Gregory S

2012-01-17

Light-harvesting antenna complexes transfer energy from sunlight to photosynthetic reaction centers where charge separation drives cellular metabolism. The process through which pigments transfer excitation energy involves a complex choreography of coherent and incoherent processes mediated by the surrounding protein and solvent environment. The recent discovery of coherent dynamics in photosynthetic light-harvesting antennae has motivated many theoretical models exploring effects of interference in energy transfer phenomena. In this work, we provide experimental evidence of long-lived quantum coherence between the spectrally separated B800 and B850 rings of the light-harvesting complex 2 (LH2) of purple bacteria. Spectrally resolved maps of the detuning, dephasing, and the amplitude of electronic coupling between excitons reveal that different relaxation pathways act in concert for optimal transfer efficiency. Furthermore, maps of the phase of the signal suggest that quantum mechanical interference between different energy transfer pathways may be important even at ambient temperature. Such interference at a product state has already been shown to enhance the quantum efficiency of transfer in theoretical models of closed loop systems such as LH2.

Complex Dynamics in Nonequilibrium Economics and Chemistry

Science.gov (United States)

Wen, Kehong

Complex dynamics provides a new approach in dealing with economic complexity. We study interactively the empirical and theoretical aspects of business cycles. The way of exploring complexity is similar to that in the study of an oscillatory chemical system (BZ system)--a model for modeling complex behavior. We contribute in simulating qualitatively the complex periodic patterns observed from the controlled BZ experiments to narrow the gap between modeling and experiment. The gap between theory and reality is much wider in economics, which involves studies of human expectations and decisions, the essential difference from natural sciences. Our empirical and theoretical studies make substantial progress in closing this gap. With the help from the new development in nonequilibrium physics, i.e., the complex spectral theory, we advance our technique in detecting characteristic time scales from empirical economic data. We obtain correlation resonances, which give oscillating modes with decays for correlation decomposition, from different time series including S&P 500, M2, crude oil spot prices, and GNP. The time scales found are strikingly compatible with business experiences and other studies in business cycles. They reveal the non-Markovian nature of coherent markets. The resonances enhance the evidence of economic chaos obtained by using other tests. The evolving multi-humped distributions produced by the moving-time -window technique reveal the nonequilibrium nature of economic behavior. They reproduce the American economic history of booms and busts. The studies seem to provide a way out of the debate on chaos versus noise and unify the cyclical and stochastic approaches in explaining business fluctuations. Based on these findings and new expectation formulation, we construct a business cycle model which gives qualitatively compatible patterns to those found empirically. The soft-bouncing oscillator model provides a better alternative than the harmonic oscillator

A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation

Directory of Open Access Journals (Sweden)

Olympia Roeva

2004-10-01

Full Text Available This paper presents the use of genetic algorithms for identification of Escherichia coli fed-batch fermentation process. Genetic algorithms are a directed random search technique, based on the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search space. The dynamic behavior of considered process has known nonlinear structure, described with a system of deterministic nonlinear differential equations according to the mass balance. The parameters of the model are estimated using genetic algorithms. Simulation examples for demonstration of the effectiveness and robustness of the proposed identification scheme are included. As a result, the model accurately predicts the process of cultivation of E. coli.

Multiscale structure in eco-evolutionary dynamics

Science.gov (United States)

Stacey, Blake C.

In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

Science.gov (United States)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

Modularity and the spread of perturbations in complex dynamical systems.

Science.gov (United States)

Kolchinsky, Artemy; Gates, Alexander J; Rocha, Luis M

2015-12-01

We propose a method to decompose dynamical systems based on the idea that modules constrain the spread of perturbations. We find partitions of system variables that maximize "perturbation modularity," defined as the autocovariance of coarse-grained perturbed trajectories. The measure effectively separates the fast intramodular from the slow intermodular dynamics of perturbation spreading (in this respect, it is a generalization of the "Markov stability" method of network community detection). Our approach captures variation of modular organization across different system states, time scales, and in response to different kinds of perturbations: aspects of modularity which are all relevant to real-world dynamical systems. It offers a principled alternative to detecting communities in networks of statistical dependencies between system variables (e.g., "relevance networks" or "functional networks"). Using coupled logistic maps, we demonstrate that the method uncovers hierarchical modular organization planted in a system's coupling matrix. Additionally, in homogeneously coupled map lattices, it identifies the presence of self-organized modularity that depends on the initial state, dynamical parameters, and type of perturbations. Our approach offers a powerful tool for exploring the modular organization of complex dynamical systems.

Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

Science.gov (United States)

Gao, Zhongke; Jin, Ningde

2009-06-01

The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

Bifurcation and complex dynamics of a discrete-time predator-prey system

Directory of Open Access Journals (Sweden)

S. M. Sohel Rana

2015-06-01

Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system of Holling-I type in the closed first quadrant R+2. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. It has been found that the dynamical behavior of the model is very sensitive to the parameter values and the initial conditions. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamic behaviors, including phase portraits, period-9, 10, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. In particular, we observe that when the prey is in chaotic dynamic, the predator can tend to extinction or to a stable equilibrium. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors. The analysis and results in this paper are interesting in mathematics and biology.

Information transmission in genetic regulatory networks: a review

International Nuclear Information System (INIS)

Tkacik, Gasper; Walczak, Aleksandra M

2011-01-01

Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'. (topical review)

Complex scattering dynamics and the quantum Hall effects

International Nuclear Information System (INIS)

Trugman, S.A.

1994-01-01

We review both classical and quantum potential scattering in two dimensions in a magnetic field, with applications to the quantum Hall effect. Classical scattering is complex, due to the approach of scattering states to an infinite number of dynamically bound states. Quantum scattering follows the classical behavior rather closely, exhibiting sharp resonances in place of the classical bound states. Extended scatterers provide a quantitative explanation for the breakdown of the QHE at a comparatively small Hall voltage as seen by Kawaji et al., and possibly for noise effects

Dynamic torsional motion of a diruthenium complex with four homo-catecholates and first synthesis of a diruthenium complex with mixed-catecholates

Science.gov (United States)

Chang, Ho-Chol; Mochizuki, Katsunori; Kitagawa, Susumu

2008-11-01

Dynamic properties of a diruthenium complex with ligand-unsupported Ru-Ru triple bonds, Na 2[Ru 2(3,6-DTBCat) 4] ( 1), were studied using variable-temperature 1H NMR. Structural freedom derived from the ligand-unsupported structure leads to torsional motion about the Ru-Ru bonds in THF and in DMF. The observed solvent dependency corresponds to the electrostatic interactions between the diruthenium complex and Na + counter cations, which are sensitive to the polarity of solvents. In addition, a new diruthenium complex, [{Na(THF) 2(H 2O)}{Na(THF) 0.5(H 2O)}{Ru 2(3,6-DTBCat) 2(H 4Cat) 2}] ( 2·2.5THF·2H 2O), with a ligand-unsupported Ru-Ru bond surrounded by two different kinds of catecholate derivatives, has been synthesized and crystallographically characterized. The complex, which was characterized by single-crystal structural analysis, will provide an opportunity to investigate not only static molecular structures but also dynamic physicochemical properties in comparison with analogues containing four identical catecholate derivatives.

Presence of voltage-gated potassium channel complex antibody in a case of genetic prion disease.

Science.gov (United States)

Jammoul, Adham; Lederman, Richard J; Tavee, Jinny; Li, Yuebing

2014-06-05

Voltage-gated potassium channel (VGKC) complex antibody-mediated encephalitis is a recently recognised entity which has been reported to mimic the clinical presentation of Creutzfeldt-Jakob disease (CJD). Testing for the presence of this neuronal surface autoantibody in patients presenting with subacute encephalopathy is therefore crucial as it may both revoke the bleak diagnosis of prion disease and allow institution of potentially life-saving immunotherapy. Tempering this optimistic view is the rare instance when a positive VGKC complex antibody titre occurs in a definite case of prion disease. We present a pathologically and genetically confirmed case of CJD with elevated serum VGKC complex antibody titres. This case highlights the importance of interpreting the result of a positive VGKC complex antibody with caution and in the context of the overall clinical manifestation. 2014 BMJ Publishing Group Ltd.

Genetic population structure of sympatric and allopatric populations of Baltic ciscoes (Coregonus albula complex, Teleostei, Coregonidae).

Science.gov (United States)

Mehner, Thomas; Pohlmann, Kirsten; Elkin, Che; Monaghan, Michael T; Nitz, Barbara; Freyhof, Jörg

2010-03-29

Teleost fishes of the Coregonidae are good model systems for studying postglacial evolution, adaptive radiation and ecological speciation. Of particular interest is whether the repeated occurrence of sympatric species pairs results from in-situ divergence from a single lineage or from multiple invasions of one or more different lineages. Here, we analysed the genetic structure of Baltic ciscoes (Coregonus albula complex), examining 271 individuals from 8 lakes in northern Germany using 1244 polymorphic AFLP loci. Six lakes had only one population of C. albula while the remaining two lakes had C. albula as well as a sympatric species (C. lucinensis or C. fontanae). AFLP demonstrated a significant population structure (Bayesian thetaB = 0.22). Lower differentiation between allopatric (thetaB = 0.028) than sympatric (0.063-0.083) populations contradicts the hypothesis of a sympatric origin of taxa, and there was little evidence for stocking or ongoing hybridization. Genome scans found only three loci that appeared to be under selection in both sympatric population pairs, suggesting a low probability of similar mechanisms of ecological segregation. However, removal of all non-neutral loci decreased the genetic distance between sympatric pairs, suggesting recent adaptive divergence at a few loci. Sympatric pairs in the two lakes were genetically distinct from the six other C. albula populations, suggesting introgression from another lineage may have influenced these two lakes. This was supported by an analysis of isolation-by-distance, where the drift-gene flow equilibrium observed among allopatric populations was disrupted when the sympatric pairs were included. While the population genetic data alone can not unambiguously uncover the mode of speciation, our data indicate that multiple lineages may be responsible for the complex patterns typically observed in Coregonus. Relative differences within and among lakes raises the possibility that multiple lineages may be

Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes.

Science.gov (United States)

Nielsen, H Bjørn; Almeida, Mathieu; Juncker, Agnieszka Sierakowska; Rasmussen, Simon; Li, Junhua; Sunagawa, Shinichi; Plichta, Damian R; Gautier, Laurent; Pedersen, Anders G; Le Chatelier, Emmanuelle; Pelletier, Eric; Bonde, Ida; Nielsen, Trine; Manichanh, Chaysavanh; Arumugam, Manimozhiyan; Batto, Jean-Michel; Quintanilha Dos Santos, Marcelo B; Blom, Nikolaj; Borruel, Natalia; Burgdorf, Kristoffer S; Boumezbeur, Fouad; Casellas, Francesc; Doré, Joël; Dworzynski, Piotr; Guarner, Francisco; Hansen, Torben; Hildebrand, Falk; Kaas, Rolf S; Kennedy, Sean; Kristiansen, Karsten; Kultima, Jens Roat; Léonard, Pierre; Levenez, Florence; Lund, Ole; Moumen, Bouziane; Le Paslier, Denis; Pons, Nicolas; Pedersen, Oluf; Prifti, Edi; Qin, Junjie; Raes, Jeroen; Sørensen, Søren; Tap, Julien; Tims, Sebastian; Ussery, David W; Yamada, Takuji; Renault, Pierre; Sicheritz-Ponten, Thomas; Bork, Peer; Wang, Jun; Brunak, Søren; Ehrlich, S Dusko

2014-08-01

Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.

Complex dynamics of the generic and brand advertising strategies in duopoly

International Nuclear Information System (INIS)

Qi Jie; Ding Yongsheng; Chen Liang

2008-01-01

By using the optimal profit adjusting strategies, a dynamic advertising competition model in duopoly is extended from Krishnamurthy's static model. Both generic and brand effects for advertising are considered. This model can create complex bifurcating and chaotic behavior for the generic advertising efforts, which lead to chaotic dynamics for the brand advertising and even for the whole system. The asymptotic properties of the symmetric system and the asymmetric system are also investigated, which reflect interactions between the two firms' advertising strategies and relationships between the brand and the generic advertising expenditures

Complex dynamics of the generic and brand advertising strategies in duopoly

Energy Technology Data Exchange (ETDEWEB)

Qi Jie [College of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)], E-mail: jieqi@dhu.edu.cn; Ding Yongsheng [College of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)], E-mail: ysding@dhu.edu.cn; Chen Liang [College of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)

2008-04-15

By using the optimal profit adjusting strategies, a dynamic advertising competition model in duopoly is extended from Krishnamurthy's static model. Both generic and brand effects for advertising are considered. This model can create complex bifurcating and chaotic behavior for the generic advertising efforts, which lead to chaotic dynamics for the brand advertising and even for the whole system. The asymptotic properties of the symmetric system and the asymmetric system are also investigated, which reflect interactions between the two firms' advertising strategies and relationships between the brand and the generic advertising expenditures.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

Directory of Open Access Journals (Sweden)

Eric A Yen

2014-05-01

Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

The dynamical complexity of optically injected semiconductor lasers

International Nuclear Information System (INIS)

Wieczorek, S.; Krauskopf, B.; Simpson, T.B.; Lenstra, D.

2005-01-01

This report presents a modern approach to the theoretical and experimental study of complex nonlinear behavior of a semiconductor laser with optical injection-an example of a widely applied and technologically relevant forced nonlinear oscillator. We show that the careful bifurcation analysis of a rate equation model yields (i) a deeper understanding of already studied physical phenomena, and (ii) the discovery of new dynamical effects, such as multipulse excitability. Different instabilities, cascades of bifurcations, multistability, and sudden chaotic transitions, which are often viewed as independent, are in fact logically connected into a consistent web of bifurcations via special points called organizing centers. This theoretical bifurcation analysis has predictive power, which manifests itself in good agreement with experimental measurements over a wide range of parameters and diversity of dynamics. While it is dealing with the specific system of an optically injected laser, our work constitutes the state-of-the-art in the understanding and modeling of a nonlinear physical system in general

Dynamics of anion exchange of lanthanides in aqueous-organic complexing media

International Nuclear Information System (INIS)

Sheveleva, I.V.; Bogatyrev, I.O.

1987-01-01

Effect of organic solvents (ethanol, acetone, acetonitrile) on change in kinetic parameters of the anion exchange process (anion-exchange column chromatography) of r.e.e. (europium and gadolinium) in complexing nitric acid media has been studied. It is established that complex LnA 4 anion is the only sorbing form of europium and gadolinium on anionite. When the organic component content of the solution being the same, the dynamic parameters of lanthanide exchange have higher values in aqueous-acetonitrile and aqueous-acetone media in comparison with aqueous-enthanol solutions of nitric acid. Lesser mobility of complex lanthanide anions in aqueous-alcoholic solutions can be explained by stronger solvation in the presence of solvents with higher acceptor properties

EPR & Klein Paradoxes in Complex Hamiltonian Dynamics and Krein Space Quantization

Science.gov (United States)

Payandeh, Farrin

2015-07-01

Negative energy states are applied in Krein space quantization approach to achieve a naturally renormalized theory. For example, this theory by taking the full set of Dirac solutions, could be able to remove the propagator Green function's divergences and automatically without any normal ordering, to vanish the expected value for vacuum state energy. However, since it is a purely mathematical theory, the results are under debate and some efforts are devoted to include more physics in the concept. Whereas Krein quantization is a pure mathematical approach, complex quantum Hamiltonian dynamics is based on strong foundations of Hamilton-Jacobi (H-J) equations and therefore on classical dynamics. Based on complex quantum Hamilton-Jacobi theory, complex spacetime is a natural consequence of including quantum effects in the relativistic mechanics, and is a bridge connecting the causality in special relativity and the non-locality in quantum mechanics, i.e. extending special relativity to the complex domain leads to relativistic quantum mechanics. So that, considering both relativistic and quantum effects, the Klein-Gordon equation could be derived as a special form of the Hamilton-Jacobi equation. Characterizing the complex time involved in an entangled energy state and writing the general form of energy considering quantum potential, two sets of positive and negative energies will be realized. The new states enable us to study the spacetime in a relativistic entangled “space-time” state leading to 12 extra wave functions than the four solutions of Dirac equation for a free particle. Arguing the entanglement of particle and antiparticle leads to a contradiction with experiments. So, in order to correct the results, along with a previous investigation [1], we realize particles and antiparticles as physical entities with positive energy instead of considering antiparticles with negative energy. As an application of modified descriptions for entangled (space

Lack of genetic association of neutral endopeptidase (NEP) with complex regional pain syndrome (CRPS).

Science.gov (United States)

Huehne, Kathrin; Schaal, Ute; Leis, Stefan; Uebe, Steffen; Gosso, M Florencia; van den Maagdenberg, Arn M J M; Maihöfner, Christian; Birklein, Frank; Rautenstrauss, Bernd; Winterpacht, Andreas

2010-03-12

Complex regional pain syndrome (CRPS) is a condition that is characterized by severe pain and exaggerated neurogenic inflammation, which may develop after injury or surgery. Neurogenic inflammation is mediated by neuropeptides, such as calcitonin gene-related peptide (CGRP) and substance P (SP) that are released from nociceptors. Genetic factors may play a role in CRPS as was suggested by the occurrence of familial cases and several genetic association studies investigating mainly the human leukocyte antigen (HLA) system. Here we investigated the role of neutral endopeptidase (NEP), a key enzyme in neuropeptide catabolism. NEP dysfunction resulting in reduced inactivation of neuropeptides may be a possible pathomechanism in CRPS. To this end, we tested a GT-repeat polymorphism in the NEP promoter region as well as 18 tag-SNPs in six linkage disequilibrium (LD) blocks in the NEP gene region in 320 CRPS patients and 376 controls. No significant genetic association was observed. Thus, we conclude that the NEP gene does not seem to be a major risk factor for CRPS. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Application of PCR – RFLP markers for identification of genetically delimited groups of the Calypogeia fissa complex (Jungermanniopsida, Calypogeiaceae

Directory of Open Access Journals (Sweden)

Buczkowska Katarzyna

2015-06-01

Full Text Available Currently, two subspecies are formally recognized within Calypogeia fissa: C. fissa subsp. fissa occurring in Europe and C. fissa subsp. neogea known from North America. Genetic studies have revealed a complex structure of this species. Within the European part of distribution, three genetically distinct groups PS, PB and G are distinguished. The combination of the SCAR marker Cal04 and PCR-RFLP markers with three restriction enzymes (SmaI, TaqI and TspGWI allowed the recognition of all groups within the C. fissa complex. The TaqI enzyme recognizing the restriction sites in the PCR product of SCAR marker Ca104 turned out to be the best marker

Extracting quantum dynamics from genetic learning algorithms through principal control analysis

International Nuclear Information System (INIS)

White, J L; Pearson, B J; Bucksbaum, P H

2004-01-01

Genetic learning algorithms are widely used to control ultrafast optical pulse shapes for photo-induced quantum control of atoms and molecules. An unresolved issue is how to use the solutions found by these algorithms to learn about the system's quantum dynamics. We propose a simple method based on covariance analysis of the control space, which can reveal the degrees of freedom in the effective control Hamiltonian. We have applied this technique to stimulated Raman scattering in liquid methanol. A simple model of two-mode stimulated Raman scattering is consistent with the results. (letter to the editor)

Conservation and Divergence in the Candida Species Biofilm Matrix Mannan-Glucan Complex Structure, Function, and Genetic Control.

Science.gov (United States)

Dominguez, Eddie; Zarnowski, Robert; Sanchez, Hiram; Covelli, Antonio S; Westler, William M; Azadi, Parastoo; Nett, Jeniel; Mitchell, Aaron P; Andes, David R

2018-04-03

Candida biofilms resist the effects of available antifungal therapies. Prior studies with Candida albicans biofilms show that an extracellular matrix mannan-glucan complex (MGCx) contributes to antifungal sequestration, leading to drug resistance. Here we implement biochemical, pharmacological, and genetic approaches to explore a similar mechanism of resistance for the three most common clinically encountered non- albicans Candida species (NAC). Our findings reveal that each Candida species biofilm synthesizes a mannan-glucan complex and that the antifungal-protective function of this complex is conserved. Structural similarities extended primarily to the polysaccharide backbone (α-1,6-mannan and β-1,6-glucan). Surprisingly, biochemical analysis uncovered stark differences in the branching side chains of the MGCx among the species. Consistent with the structural analysis, similarities in the genetic control of MGCx production for each Candida species also appeared limited to the synthesis of the polysaccharide backbone. Each species appears to employ a unique subset of modification enzymes for MGCx synthesis, likely accounting for the observed side chain diversity. Our results argue for the conservation of matrix function among Candida spp. While biogenesis is preserved at the level of the mannan-glucan complex backbone, divergence emerges for construction of branching side chains. Thus, the MGCx backbone represents an ideal drug target for effective pan- Candida species biofilm therapy. IMPORTANCE Candida species, the most common fungal pathogens, frequently grow as a biofilm. These adherent communities tolerate extremely high concentrations of antifungal agents, due in large part, to a protective extracellular matrix. The present studies define the structural, functional, and genetic similarities and differences in the biofilm matrix from the four most common Candida species. Each species synthesizes an extracellular mannan-glucan complex (MGCx) which

Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments

Science.gov (United States)

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research…

Analysis of Dynamic Complexity of the Cyber Security Ecosystem of Colombia

Directory of Open Access Journals (Sweden)

Angélica Flórez

2016-07-01

Full Text Available This paper presents two proposals for the analysis of the complexity of the Cyber security Ecosystem of Colombia (CEC. This analysis shows the available knowledge about entities engaged in cyber security in Colombia and the relationships between them, which allow an understanding of the synergy between the different existing components. The complexity of the CEC is detailed from the view of the Influence Diagram of System Dynamics and the Domain Diagram of Software Engineering. The resulting model makes cyber security evident as a strategic component of national security.

Structural elucidation of dendritic host-guest complexes by X-ray crystallography and molecular dynamics simulations

NARCIS (Netherlands)

Chang, T.; Pieterse, K.; Broeren, M.A.C.; Kooijman, H.; Spek, A.L.; Hilbers, P.A.J.; Meijer, E.W.

2007-01-01

The multiple monovalent binding of adamantyl-urea poly(propyleneimine) dendrimers with carboxylic acid-urea guests was investigated using molecular dynamics simulations and X-ray crystallography to better understand the structure and behavior of the dynamic multivalent complex in solution. The

[Current options of preimplantion genetic screening and preimplantation genetic diagnostics].

Science.gov (United States)

Šimečková, V

The aim of this work is to summarize the current knowledge about preimplantation genetic screening and diagnostics. A review article. Department of Gynecology and Obstetrics, District Hospital Šternberk, IVF Clinic, Olomouc. Preimplantation genetic testing is a complex of genetic and molecular cytogenetic examinations, which can help to detect abnormalities in embryos before transfer into the uterus of the mother. These specialized examinations are based on the latest findings in genetics and assisted reproduction. The preimplantation genetic testing is necessarily associated with a method of in vitro fertilization. It is performed on isolated blastomeres on the third day of embryo cultivation. Nowadays, it is preferred trophectoderm examination of cells from the five-day blastocysts. Generally speaking, after preimplantation genetic testing, we can select only embryos without genetic load to transfer into uterus. Preimplantation genetic testing is an important part of treatment of infertility. Complex diagnostics and treatment of infertile couples are increasingly influenced by the development and use of advanced genomic technologies. Further development and application of these modern methods require close cooperation between the field of assisted reproduction and clinical genetics.

Recovery time after localized perturbations in complex dynamical networks

International Nuclear Information System (INIS)

Mitra, Chiranjit; Kittel, Tim; Kurths, Jürgen; Donner, Reik V; Choudhary, Anshul

2017-01-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed

Recovery time after localized perturbations in complex dynamical networks

Science.gov (United States)

Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed

EXAFS study on dynamic structural property of porous morph-genetic SiC

International Nuclear Information System (INIS)

Ding, J.; Sun, B.H.; Fan, T.X.; Zhang, D.; Kamada, M.; Ogawa, H.; Guo, Q.X.

2005-01-01

Novel porous morph-genetic silicon carbide has been fabricated through sintering treatment, after infiltrating the methyl organic silicone resin to the bio-template. Its dynamic transition of structure during sintering process is investigated by extended X-ray absorption fine structure (EXAFS) for the first time. By analyzing Si K-edge EXAFS, it is found that the coordination number of the nearest C shell remains almost unchanged while that of the nearest Si shell dramatically changes when the structure is transformed from amorphous into crystalline state

Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective

International Nuclear Information System (INIS)

Peng, Weiwen; Li, Yan-Feng; Mi, Jinhua; Yu, Le; Huang, Hong-Zhong

2016-01-01

Degradation analysis is critical to reliability assessment and operational management of complex systems. Two types of assumptions are often adopted for degradation analysis: (1) single degradation indicator and (2) constant external factors. However, modern complex systems are generally characterized as multiple functional and suffered from multiple failure modes due to dynamic operating conditions. In this paper, Bayesian degradation analysis of complex systems with multiple degradation indicators under dynamic conditions is investigated. Three practical engineering-driven issues are addressed: (1) to model various combinations of degradation indicators, a generalized multivariate hybrid degradation process model is proposed, which subsumes both monotonic and non-monotonic degradation processes models as special cases, (2) to study effects of external factors, two types of dynamic covariates are incorporated jointly, which include both environmental conditions and operating profiles, and (3) to facilitate degradation based reliability analysis, a serial of Bayesian strategy is constructed, which covers parameter estimation, factor-related degradation prediction, and unit-specific remaining useful life assessment. Finally, degradation analysis of a type of heavy machine tools is presented to demonstrate the application and performance of the proposed method. A comparison of the proposed model with a traditional model is studied as well in the example. - Highlights: • A generalized multivariate hybrid degradation process model is introduced. • Various types of dependent degradation processes can be modeled coherently. • The effects of environmental conditions and operating profiles are investigated. • Unit-specific RUL assessment is implemented through a two-step Bayesian method.

Universal dynamics of complex adaptive systems: Gauge theory of things alive

International Nuclear Information System (INIS)

Mack, G.

1994-04-01

A universal dynamics of objects and their relations - a kind of ''universal chemistry'' - is discussed which satisfies general principles of locality and relativity. Einsteins theory of gravitation and the gauge theory of elementary particles are prototypes, but complex adaptive systems - anything that is alive in the widest sense - fall under the same paradigma. Frustration and gauge symmetry arise naturally in this context. Besides a nondissipative deterministic dynamics, which is thought to operate at a fundamental levle, a Thermo-Dynamics in sense of Prigogine is introduced by adding a diffusion process. It introduces irreversibility and entropy production. It equilibrates the chaotic local model of the time development (only) and is designed to be undetectable under continued observation with given finite measuring accuracy. Compositeness and the development of structure can be described in this framework. The existence of a critical equilibrium state may be postulated which is invariant under the dynamics. But it is usually not reached in a finite time from a given starting configuration, because local dynamics suffers from critical slowing down, especially in the presence of frustration. (orig.)

Stochastic dynamics of complex systems: from glasses to evolution (series on complexity science)

CERN Document Server

Sibani, Paolo

2013-01-01

Dynamical evolution over long time scales is a prominent feature of all the systems we intuitively think of as complex - for example, ecosystems, the brain or the economy. In physics, the term ageing is used for this type of slow change, occurring over time scales much longer than the patience, or indeed the lifetime, of the observer. The main focus of this book is on the stochastic processes which cause ageing, and the surprising fact that the ageing dynamics of systems which are very different at the microscopic level can be treated in similar ways. The first part of this book provides the necessary mathematical and computational tools and the second part describes the intuition needed to deal with these systems. Some of the first few chapters have been covered in several other books, but the emphasis and selection of the topics reflect both the authors' interests and the overall theme of the book. The second part contains an introduction to the scientific literature and deals in some detail with the desc...

Complexity, Sustainability, Justice, and Meaning: Chronological Versus Dynamical Time

Directory of Open Access Journals (Sweden)

Horacio Velasco

2009-11-01

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When nonlinear dynamics came to be complemented with semiotic modulation through the implement of symbol-mediated language (a complementation subsequently termed semantic closure as first instantiated through the communicating (as opposed  to merely dynamically interacting molecular complexes of the cell, what can be termed semiotic hysteresis was born. The paper attempts to show that indefinitely evolving complexity, sustainability, justice, and meaning are indissolubly bound with chronological time in the sense of semiotic hysteresis (as afforded initially by non-cognitive semantic closure and subsequently, at least one hopes, by cognitive semantic closure: This semiotic hysteresis yields the indefinite evolutionary time of the living condition—including culture.

Genetic ablation of root cap cells in Arabidopsis

OpenAIRE

Tsugeki, Ryuji; Fedoroff, Nina V.

1999-01-01

The root cap is increasingly appreciated as a complex and dynamic plant organ. Root caps sense and transmit environmental signals, synthesize and secrete small molecules and macromolecules, and in some species shed metabolically active cells. However, it is not known whether root caps are essential for normal shoot and root development. We report the identification of a root cap-specific promoter and describe its use to genetically ablate root caps by directing root cap-specific expression of...

Without bounds a scientific canvas of nonlinearity and complex dynamics

CERN Document Server

Ryazantsev, Yuri; Starov, Victor; Huang, Guo-Xiang; Chetverikov, Alexander; Arena, Paolo; Nepomnyashchy, Alex; Ferrus, Alberto; Morozov, Eugene

2013-01-01

Bringing together over fifty contributions on all aspects of nonlinear and complex dynamics, this impressive topical collection is both a scientific and personal tribute, on the occasion of his 70th birthday, by many outstanding colleagues in the broad fields of research pursued by Prof. Manuel G Velarde. The topics selected reflect the research areas covered by the famous Instituto Pluridisciplinar at the Universidad Complutense of Madrid, which he co-founded over two decades ago, and include: fluid physics and related nonlinear phenomena at interfaces and in other geometries, wetting and spreading dynamics, geophysical and astrophysical flows, and novel aspects of electronic transport in anharmonic lattices, as well as topics in neurodynamics and robotics.

Dynamic polarizability of a complex atom in strong laser fields

International Nuclear Information System (INIS)

Rapoport, L.P.; Klinskikh, A.F.; Mordvinov, V.V.

1997-01-01

An asymptotic expansion of the dynamic polarizability of a complex atom in a strong circularly polarized light field is found for the case of high frequencies. The self-consistent approximation of the Hartree-Fock type for the ''atom+field'' system is developed, within the framework of which a numerical calculation of the dynamic polarizability of Ne, Kr, and Ar atoms in a strong radiation field is performed. The strong field effect is shown to manifest itself not only in a change of the energy spectrum and the character of behavior of the wave functions of atomic electrons, but also in a modification of the one-electron self-consistent potential for the atom in the field

Probing the dynamics of complexed local anesthetics via neutron scattering spectroscopy and DFT calculations

DEFF Research Database (Denmark)

Longo Martins, Murillo; Eckert, Juergen; Jacobsen, Henrik

2017-01-01

Since potential changes in the dynamics and mobility of drugs upon complexation for delivery may affect their ultimate efficacy, we have investigated the dynamics of two local anesthetic molecules, bupivacaine (BVC, C18H28N2O) and ropivacaine (RVC, C17H26N2O), in both their crystalline forms...

Empirical complexities in the genetic foundations of lethal mutagenesis.

Science.gov (United States)

Bull, James J; Joyce, Paul; Gladstone, Eric; Molineux, Ian J

2013-10-01

From population genetics theory, elevating the mutation rate of a large population should progressively reduce average fitness. If the fitness decline is large enough, the population will go extinct in a process known as lethal mutagenesis. Lethal mutagenesis has been endorsed in the virology literature as a promising approach to viral treatment, and several in vitro studies have forced viral extinction with high doses of mutagenic drugs. Yet only one empirical study has tested the genetic models underlying lethal mutagenesis, and the theory failed on even a qualitative level. Here we provide a new level of analysis of lethal mutagenesis by developing and evaluating models specifically tailored to empirical systems that may be used to test the theory. We first quantify a bias in the estimation of a critical parameter and consider whether that bias underlies the previously observed lack of concordance between theory and experiment. We then consider a seemingly ideal protocol that avoids this bias-mutagenesis of virions-but find that it is hampered by other problems. Finally, results that reveal difficulties in the mere interpretation of mutations assayed from double-strand genomes are derived. Our analyses expose unanticipated complexities in testing the theory. Nevertheless, the previous failure of the theory to predict experimental outcomes appears to reside in evolutionary mechanisms neglected by the theory (e.g., beneficial mutations) rather than from a mismatch between the empirical setup and model assumptions. This interpretation raises the specter that naive attempts at lethal mutagenesis may augment adaptation rather than retard it.

Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach

Directory of Open Access Journals (Sweden)

Hongyong Wang

2018-01-01

Full Text Available In order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity research, no simple means is available to integrate airspace and traffic flow characteristics. In this paper, we propose a new approach for the measurement of air traffic situation complexity. This approach considers the effects of both airspace and traffic flow and objectively quantifies air traffic situation complexity. Considering the aircraft, waypoints, and airways as nodes, and the complexity relationships among these nodes as edges, a dynamic weighted network is constructed. Air traffic situation complexity is defined as the sum of the weights of all edges in the network, and the relationships of complexity with some commonly used indices are statistically analyzed. The results indicate that the new complexity index is more accurate than traffic count and reflects the number of trajectory changes as well as the high-risk situations. Additionally, analysis of potential applications reveals that this new index contributes to achieving complexity-based management, which represents an efficient method for increasing airspace system capacity.

Short-Term Memories in "Drosophila" Are Governed by General and Specific Genetic Systems

Science.gov (United States)

Zars, Troy

2010-01-01

In a dynamic environment, there is an adaptive value in the ability of animals to acquire and express memories. That both simple and complex animals can learn is therefore not surprising. How animals have solved this problem genetically and anatomically probably lies somewhere in a range between a single molecular/anatomical mechanism that applies…

Heterobimetallic porphyrin complexes displaying triple dynamics: coupled metal motions controlled by constitutional evolution.

Science.gov (United States)

Le Gac, Stéphane; Fusaro, Luca; Roisnel, Thierry; Boitrel, Bernard

2014-05-07

A bis-strap porphyrin ligand (1), with an overhanging carboxylic acid group on each side of the macrocycle, has been investigated toward the formation of dynamic libraries of bimetallic complexes with Hg(II), Cd(II), and Pb(II). Highly heteroselective metalation processes occurred in the presence of Pb(II), with Hg(II) or Cd(II) bound out-of-plane to the N-core and "PbOAc" bound to a carboxylate group of a strap on the opposite side. The resulting complexes, 1(Hg)·PbOAc and 1(Cd)·PbOAc, display three levels of dynamics. The first is strap-level (interactional dynamics), where the PbOAc moiety swings between the left and right side of the strap owing to a second sphere of coordination with lateral amide functions. The second is ligand-level (motional dynamics), where 1(Hg)·PbOAc and 1(Cd)·PbOAc exist as two degenerate states in equilibrium controlled by a chemical effector (AcO(-)). The process corresponds to a double translocation of the metal ions according to an intramolecular migration of Hg(II) or Cd(II) through the N-core, oscillating between the two equivalent overhanging carbonyl groups, coupled to an intermolecular pathway for PbOAc exchanging between the two equivalent overhanging carboxylate groups (N-core(up) ⇆ N-core(down) coupled to strap(down) ⇆ strap(up), i.e., coupled motion #1 in the abstract graphic). The third is library-level (constitutional dynamics), where a dynamic constitutional evolution of the system was achieved by the successive addition of two chemical effectors (DMAP and then AcO(-)). It allowed shifting equilibrium forward and backward between 1(Hg)·PbOAc and the corresponding homobimetallic complexes 1(Hg2)·DMAP and 1(Pb)·PbOAc. The latter displays a different ligand-level dynamics, in the form of an intraligand coupled migration of the Pb(II) ions (N-core(up) ⇆ strap(up) coupled to strap(down) ⇆ N-core(down), i.e., coupled motion #2 in the abstract graphic). In addition, the neutral "bridged" complexes 1HgPb and 1Cd

Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems

Directory of Open Access Journals (Sweden)

DimitrisG. Stavrakoudis

2012-04-01

Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

Science.gov (United States)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories

KAUST Repository

Abdel-Azeim, Safwat

2014-05-06

Background: Molecular Dynamics ( MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. Results: On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. Conclusions: MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes.

Complexity and network dynamics in physiological adaptation: An integrated view

OpenAIRE

Baffy, Gyorgy; Loscalzo, Joseph

2014-01-01

Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of t...

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

Energy Technology Data Exchange (ETDEWEB)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc [Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003 (United States)

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

The dynamic complexity of a three-species Beddington-type food chain with impulsive control strategy

International Nuclear Information System (INIS)

Wang Weiming; Wang Hailing; Li Zhenqing

2007-01-01

In this paper, by using theories and methods of ecology and ordinary differential equation, the dynamics complexity of a prey-predator system with Beddington-type functional response and impulsive control strategy is established. Conditions for the system to be extinct are given by using the Floquet theory of impulsive equation and small amplitude perturbation skills. Furthermore, by using the method of numerical simulation with the international software Maple, the influence of the impulsive perturbations on the inherent oscillation is investigated, which shows rich dynamics, such as quasi-periodic oscillation, narrow periodic window, wide periodic window, chaotic bands, period doubling bifurcation, symmetry-breaking pitchfork bifurcation, period-halving bifurcation and crises, etc. The numerical results indicate that computer simulation is a useful method for studying the complex dynamic systems

The genetic architecture of a complex ecological trait: host plant use in the specialist moth, HELIOTHIS SUBFLEXA

Science.gov (United States)

The study of the genetic basis of ecological adaptation remains in its infancy, and most studies have focused on phenotypically simple traits. Host plant use by herbivorous insects is phenotypically complex. While research has illuminated the evolutionary determinants of host use, knowledge of its...

COMBINED DELAY AND GRAPH EMBEDDING OF EPILEPTIC DISCHARGES IN EEG REVEALS COMPLEX AND RECURRENT NONLINEAR DYNAMICS.

Science.gov (United States)

Erem, B; Hyde, D E; Peters, J M; Duffy, F H; Brooks, D H; Warfield, S K

2015-04-01

The dynamical structure of the brain's electrical signals contains valuable information about its physiology. Here we combine techniques for nonlinear dynamical analysis and manifold identification to reveal complex and recurrent dynamics in interictal epileptiform discharges (IEDs). Our results suggest that recurrent IEDs exhibit some consistent dynamics, which may only last briefly, and so individual IED dynamics may need to be considered in order to understand their genesis. This could potentially serve to constrain the dynamics of the inverse source localization problem.

Diversification in the South American Pampas: the genetic and morphological variation of the widespread Petunia axillaris complex (Solanaceae).

Science.gov (United States)

Turchetto, Caroline; Fagundes, Nelson J R; Segatto, Ana L A; Kuhlemeier, Cris; Solís Neffa, Viviana G; Speranza, Pablo R; Bonatto, Sandro L; Freitas, Loreta B

2014-02-01

Understanding the spatiotemporal distribution of genetic variation and the ways in which this distribution is connected to the ecological context of natural populations is fundamental for understanding the nature and mode of intraspecific and, ultimately, interspecific differentiation. The Petunia axillaris complex is endemic to the grasslands of southern South America and includes three subspecies: P. a. axillaris, P. a. parodii and P. a. subandina. These subspecies are traditionally delimited based on both geography and floral morphology, although the latter is highly variable. Here, we determined the patterns of genetic (nuclear and cpDNA), morphological and ecological (bioclimatic) variation of a large number of P. axillaris populations and found that they are mostly coincident with subspecies delimitation. The nuclear data suggest that the subspecies are likely independent evolutionary units, and their morphological differences may be associated with local adaptations to diverse climatic and/or edaphic conditions and population isolation. The demographic dynamics over time estimated by skyline plot analyses showed different patterns for each subspecies in the last 100 000 years, which is compatible with a divergence time between 35 000 and 107 000 years ago between P. a. axillaris and P. a. parodii, as estimated with the IMa program. Coalescent simulation tests using Approximate Bayesian Computation do not support previous suggestions of extensive gene flow between P. a. axillaris and P. a. parodii in their contact zone. © 2013 John Wiley & Sons Ltd.

Control of complex dynamics and chaos in distributed parameter systems

Energy Technology Data Exchange (ETDEWEB)

Chakravarti, S.; Marek, M.; Ray, W.H. [Univ. of Wisconsin, Madison, WI (United States)

1995-12-31

This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in the complex quasi-periodic or chaotic spatiotemporal patterns.

Genetic interactions underlying hybrid male sterility in the Drosophila bipectinata species complex.

Science.gov (United States)

Mishra, Paras Kumar; Singh, Bashisth Narayan

2006-06-01

Understanding genetic mechanisms underlying hybrid male sterility is one of the most challenging problems in evolutionary biology especially speciation. By using the interspecific hybridization method roles of Y chromosome, Major Hybrid Sterility (MHS) genes and cytoplasm in sterility of hybrid males have been investigated in a promising group, the Drosophila bipectinata species complex that consists of four closely related species: D. pseudoananassae, D. bipectinata, D. parabipectinata and D. malerkotliana. The interspecific introgression analyses show that neither cytoplasm nor MHS genes are involved but X-Y interactions may be playing major role in hybrid male sterility between D. pseudoananassae and the other three species. The results of interspecific introgression analyses also show considerable decrease in the number of males in the backcross offspring and all males have atrophied testes. There is a significant positive correlation between sex - ratio distortion and severity of sterility in backcross males. These findings provide evidence that D. pseudoananassae is remotely related with other three species of the D. bipectinata species complex.

Genetics, mental illness, and complex disease: development and distribution of an interactive CD-ROM for genetic counselors. Final report for period 15 August 2000 - 31 December 2002

Energy Technology Data Exchange (ETDEWEB)

McInerney, Joseph D.

2003-03-31

"Genetics and Major Psychiatric Disorders: A Program for Genetic Counselors" provides an introduction to psychiatric genetics, with a focus on the genetics of common complex disease, for genetics professionals. The program is available as a CD-ROM and an online educational resource. The on-line version requires a direct internet connection. Each educational module begins with an interactive case study that raises significant issues addressed in each module. In addition, case studies provided throughout the educational materials support teaching of major concepts. Incorporated throughout the content are expert video clips, video clips from individuals affected by psychiatric illness, and optional "learn more" materials that offer greater depth about a particular topic. The structure of the CD-ROM permits self-navigation, but we have suggested a sequence that allows materials to build upon each other. At any point in the materials, users may pause and look up terms in the glossary or review the DSM-IV criteria for selected psychiatric disorders. A detailed site map is available for those who choose to self navigate through the content.

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

Science.gov (United States)

Riccioni, Giulia; Stagioni, Marco; Landi, Monica; Ferrara, Giorgia; Barbujani, Guido; Tinti, Fausto

2013-01-01

Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation. PMID:24260341

A complex, nonlinear dynamic systems perspective on Ayurveda and Ayurvedic research.

Science.gov (United States)

Rioux, Jennifer

2012-07-01

The fields of complexity theory and nonlinear dynamic systems (NDS) are relevant for analyzing the theory and practice of Ayurvedic medicine from a Western scientific perspective. Ayurvedic definitions of health map clearly onto the tenets of both systems and complexity theory and focus primarily on the preservation of organismic equanimity. Health care research informed by NDS and complexity theory would prioritize (1) ascertaining patterns reflected in whole systems as opposed to isolating components; (2) relationships and dynamic interaction rather than static end-points; (3) transitions, change and cumulative effects, consistent with delivery of therapeutic packages in the reality of the clinical setting; and (4) simultaneously exploring both local and global levels of healing phenomena. NDS and complexity theory are useful in examining nonlinear transitions between states of health and illness; the qualitative nature of shifts in health status; and looking at emergent properties and behaviors stemming from interactions between organismic and environmental systems. Complexity and NDS theory also demonstrate promise for enhancing the suitability of research strategies applied to Ayurvedic medicine through utilizing core concepts such as initial conditions, emergent properties, fractal patterns, and critical fluctuations. In the Ayurvedic paradigm, multiple scales and their interactions are addressed simultaneously, necessitating data collection on change patterns that occur on continuums of both time and space, and are viewed as complementary rather than isolated and discrete. Serious consideration of Ayurvedic clinical understandings will necessitate new measurement options that can account for the relevance of both context and environmental factors, in terms of local biology and the processual features of the clinical encounter. Relevant research design issues will need to address clinical tailoring strategies and provide mechanisms for mapping patterns of

Complex genetic architecture of cardiac disease in a wild type inbred strain of Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Zhi Zhang

Full Text Available Natural populations of the fruit fly, Drosophila melanogaster, segregate genetic variation that leads to cardiac disease phenotypes. One nearly isogenic line from a North Carolina peach orchard, WE70, is shown to harbor two genetically distinct heart phenotypes: elevated incidence of arrhythmias, and a dramatically constricted heart diameter in both diastole and systole, with resemblance to restrictive cardiomyopathy in humans. Assuming the source to be rare variants of large effect, we performed Bulked Segregant Analysis using genomic DNA hybridization to Affymetrix chips to detect single feature polymorphisms, but found that the mutant phenotypes are more likely to have a polygenic basis. Further mapping efforts revealed a complex architecture wherein the constricted cardiomyopathy phenotype was observed in individual whole chromosome substitution lines, implying that variants on both major autosomes are sufficient to produce the phenotype. A panel of 170 Recombinant Inbred Lines (RIL was generated, and a small subset of mutant lines selected, but these each complemented both whole chromosome substitutions, implying a non-additive (epistatic contribution to the "disease" phenotype. Low coverage whole genome sequencing was also used to attempt to map chromosomal regions contributing to both the cardiomyopathy and arrhythmia, but a polygenic architecture had to be again inferred to be most likely. These results show that an apparently simple rare phenotype can have a complex genetic basis that would be refractory to mapping by deep sequencing in pedigrees. We present this as a cautionary tale regarding assumptions related to attempts to map new disease mutations on the assumption that probands carry a single causal mutation.

Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

CERN Document Server

Baianu, I C

2004-01-01

A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

Science.gov (United States)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Synchronization of complex delayed dynamical networks with nonlinearly coupled nodes

International Nuclear Information System (INIS)

Liu Tao; Zhao Jun; Hill, David J.

2009-01-01

In this paper, we study the global synchronization of nonlinearly coupled complex delayed dynamical networks with both directed and undirected graphs. Via Lyapunov-Krasovskii stability theory and the network topology, we investigate the global synchronization of such networks. Under the assumption that coupling coefficients are known, a family of delay-independent decentralized nonlinear feedback controllers are designed to globally synchronize the networks. When coupling coefficients are unavailable, an adaptive mechanism is introduced to synthesize a family of delay-independent decentralized adaptive controllers which guarantee the global synchronization of the uncertain networks. Two numerical examples of directed and undirected delayed dynamical network are given, respectively, using the Lorenz system as the nodes of the networks, which demonstrate the effectiveness of proposed results.

The Living, Dynamic and Complex Environment Care in Intensive Care Unit.

Science.gov (United States)

Backes, Marli Terezinha Stein; Erdmann, Alacoque Lorenzini; Büscher, Andreas

2015-01-01

to understand the meaning of the Adult Intensive Care Unit environment of care, experienced by professionals working in this unit, managers, patients, families and professional support services, as well as build a theoretical model about the Adult Intensive Care Unit environment of care. Grounded Theory, both for the collection and for data analysis. Based on theoretical sampling, we carried out 39 in-depth interviews semi-structured from three different Adult Intensive Care Units. built up the so-called substantive theory "Sustaining life in the complex environment of care in the Intensive Care Unit". It was bounded by eight categories: "caring and continuously monitoring the patient" and "using appropriate and differentiated technology" (causal conditions); "Providing a suitable environment" and "having relatives with concern" (context); "Mediating facilities and difficulties" (intervenienting conditions); "Organizing the environment and managing the dynamics of the unit" (strategy) and "finding it difficult to accept and deal with death" (consequences). confirmed the thesis that "the care environment in the Intensive Care Unit is a living environment, dynamic and complex that sustains the life of her hospitalized patients".

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Canetta, Raffaele

2004-01-01

In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

Energy Technology Data Exchange (ETDEWEB)

Marseguerra, Marzio E-mail: marzio.marseguerra@polimi.it; Zio, Enrico E-mail: enrico.zio@polimi.it; Canetta, Raffaele

2004-07-01

In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved.

Cryptic Genetic Variation in Evolutionary Developmental Genetics

Directory of Open Access Journals (Sweden)

Annalise B. Paaby

2016-06-01

Full Text Available Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes—processes that cannot be fully observed in continuously varying visible traits.

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade.

Science.gov (United States)

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-28

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade

Science.gov (United States)

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-01

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Complex spatial dynamics of oncolytic viruses in vitro: mathematical and experimental approaches.

Directory of Open Access Journals (Sweden)

Dominik Wodarz

Full Text Available Oncolytic viruses replicate selectively in tumor cells and can serve as targeted treatment agents. While promising results have been observed in clinical trials, consistent success of therapy remains elusive. The dynamics of virus spread through tumor cell populations has been studied both experimentally and computationally. However, a basic understanding of the principles underlying virus spread in spatially structured target cell populations has yet to be obtained. This paper studies such dynamics, using a newly constructed recombinant adenovirus type-5 (Ad5 that expresses enhanced jellyfish green fluorescent protein (EGFP, AdEGFPuci, and grows on human 293 embryonic kidney epithelial cells, allowing us to track cell numbers and spatial patterns over time. The cells are arranged in a two-dimensional setting and allow virus spread to occur only to target cells within the local neighborhood. Despite the simplicity of the setup, complex dynamics are observed. Experiments gave rise to three spatial patterns that we call "hollow ring structure", "filled ring structure", and "disperse pattern". An agent-based, stochastic computational model is used to simulate and interpret the experiments. The model can reproduce the experimentally observed patterns, and identifies key parameters that determine which pattern of virus growth arises. The model is further used to study the long-term outcome of the dynamics for the different growth patterns, and to investigate conditions under which the virus population eliminates the target cells. We find that both the filled ring structure and disperse pattern of initial expansion are indicative of treatment failure, where target cells persist in the long run. The hollow ring structure is associated with either target cell extinction or low-level persistence, both of which can be viewed as treatment success. Interestingly, it is found that equilibrium properties of ordinary differential equations describing the

Landscape genetics of high mountain frog metapopulations

Science.gov (United States)

Murphy, M.A.; Dezzani, R.; Pilliod, D.S.; Storfer, A.

2010-01-01

Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between-site (landscape resistance) landscape characteristics and at-site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between-site and at-site landscape processes in metapopulations of Columbia spotted frogs (Rana luteiventris) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at-site landscape process) and resistance (e.g. between-site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at-site) and topographic complexity (between-site). Conversely, site productivity (as measured by heat load index, at-site) and growing season (as measured by frost-free period between-sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source-sink dynamics. In conclusion, gravity models provide a

Ultrafast Dynamics of Dansylated POPAM Dendrimers and Energy Transfer in their Dye Complexes

Science.gov (United States)

Aumanen, J.; Kesti, T.; Sundström, V.; Vögtle, F.; Korppi-Tommola, J.

We have studied internal dynamics of dansylated poly(propyleneamine) dendrimers of different generations in solution and excitation energy transfer from dansyl chromophores to xanthene dyes that form van der Waals complexes with the dendrimers

From complex spatial dynamics to simple Markov chain models: do predators and prey leave footprints?

DEFF Research Database (Denmark)

Nachman, Gøsta Støger; Borregaard, Michael Krabbe

2010-01-01

to another, are then depicted in a state transition diagram, constituting the "footprints" of the underlying population dynamics. We investigate to what extent changes in the population processes modeled in the complex simulation (i.e. the predator's functional response and the dispersal rates of both......In this paper we present a concept for using presence-absence data to recover information on the population dynamics of predator-prey systems. We use a highly complex and spatially explicit simulation model of a predator-prey mite system to generate simple presence-absence data: the number...... of transition probabilities on state variables, and combine this information in a Markov chain transition matrix model. Finally, we use this extended model to predict the long-term dynamics of the system and to reveal its asymptotic steady state properties....

Quantum Genetics in terms of Quantum Reversible Automata and Quantum Computation of Genetic Codes and Reverse Transcription

CERN Document Server

Baianu,I C

2004-01-01

The concepts of quantum automata and quantum computation are studied in the context of quantum genetics and genetic networks with nonlinear dynamics. In previous publications (Baianu,1971a, b) the formal concept of quantum automaton and quantum computation, respectively, were introduced and their possible implications for genetic processes and metabolic activities in living cells and organisms were considered. This was followed by a report on quantum and abstract, symbolic computation based on the theory of categories, functors and natural transformations (Baianu,1971b; 1977; 1987; 2004; Baianu et al, 2004). The notions of topological semigroup, quantum automaton, or quantum computer, were then suggested with a view to their potential applications to the analogous simulation of biological systems, and especially genetic activities and nonlinear dynamics in genetic networks. Further, detailed studies of nonlinear dynamics in genetic networks were carried out in categories of n-valued, Lukasiewicz Logic Algebra...

Complex Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

CERN Document Server

Baianu, I C

2004-01-01

Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

An introduction to complex systems society, ecology, and nonlinear dynamics

CERN Document Server

Fieguth, Paul

2017-01-01

This undergraduate text explores a variety of large-scale phenomena - global warming, ice ages, water, poverty - and uses these case studies as a motivation to explore nonlinear dynamics, power-law statistics, and complex systems. Although the detailed mathematical descriptions of these topics can be challenging, the consequences of a system being nonlinear, power-law, or complex are in fact quite accessible. This book blends a tutorial approach to the mathematical aspects of complex systems together with a complementary narrative on the global/ecological/societal implications of such systems. Nearly all engineering undergraduate courses focus on mathematics and systems which are small scale, linear, and Gaussian. Unfortunately there is not a single large-scale ecological or social phenomenon that is scalar, linear, and Gaussian. This book offers students insights to better understand the large-scale problems facing the world and to realize that these cannot be solved by a single, narrow academic field or per...

Dynamics of electronic dephasing in the Fenna-Matthews-Olson complex

International Nuclear Information System (INIS)

Hayes, Dugan; Panitchayangkoon, Gitt; Fransted, Kelly A; Caram, Justin R; Freed, Karl F; Engel, Gregory S; Wen Jianzhong

2010-01-01

Electronic coherence has been shown to persist in the Fenna-Matthews-Olson (FMO) antenna complex from green sulfur bacteria at 77 K for at least 660 fs, several times longer than the typical lifetime of a coherence in a dynamic environment at this temperature. Such long-lived coherence was proposed to improve energy transfer efficiency in photosynthetic systems by allowing an excitation to follow a quantum random walk as it approaches the reaction centre. Here we present a model for bath-induced electronic transitions, demonstrating that the protein matrix protects coherences by globally correlating fluctuations in transition energies. We also quantify the dephasing rates for two particular electronic coherences in the FMO complex at 77 K using two-dimensional Fourier transform electronic spectroscopy and find that the lifetimes of individual coherences are distinct. Within the framework of noise-assisted transport, this result suggests that the FMO complex has been locally tuned by natural selection to optimize transfer efficiency by exploiting quantum coherence.

Complexity and network dynamics in physiological adaptation: an integrated view.

Science.gov (United States)

Baffy, György; Loscalzo, Joseph

2014-05-28

Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. Published by Elsevier Inc.

Purification of Arp2/3 complex from Saccharomyces cerevisiae

Science.gov (United States)

Doolittle, Lynda K.; Rosen, Michael K.; Padrick, Shae B.

2014-01-01

Summary Much of cellular control over actin dynamics comes through regulation of actin filament initiation. At the molecular level, this is accomplished through a collection of cellular protein machines, called actin nucleation factors, which position actin monomers to initiate a new actin filament. The Arp2/3 complex is a principal actin nucleation factor used throughout the eukaryotic family tree. The budding yeast Saccharomyces cerevisiae has proven to be not only an excellent genetic platform for the study of the Arp2/3 complex, but also an excellent source for the purification of endogenous Arp2/3 complex. Here we describe a protocol for the preparation of endogenous Arp2/3 complex from wild type Saccharomyces cerevisiae. This protocol produces material suitable for biochemical study, and yields milligram quantities of purified Arp2/3 complex. PMID:23868593

Protein dynamics during presynaptic complex assembly on individual ssDNA molecules

Science.gov (United States)

Gibb, Bryan; Ye, Ling F.; Kwon, YoungHo; Niu, Hengyao; Sung, Patrick; Greene, Eric C.

2014-01-01

Homologous recombination is a conserved pathway for repairing double–stranded breaks, which are processed to yield single–stranded DNA overhangs that serve as platforms for presynaptic complex assembly. Here we use single–molecule imaging to reveal the interplay between Saccharomyce cerevisiae RPA, Rad52, and Rad51 during presynaptic complex assembly. We show that Rad52 binds RPA–ssDNA and suppresses RPA turnover, highlighting an unanticipated regulatory influence on protein dynamics. Rad51 binding extends the ssDNA, and Rad52–RPA clusters remain interspersed along the presynaptic complex. These clusters promote additional binding of RPA and Rad52. Together, our work illustrates the spatial and temporal progression of RPA and Rad52 association with the presynaptic complex, and reveals a novel RPA–Rad52–Rad51–ssDNA intermediate, which has implications for understanding how the activities of Rad52 and RPA are coordinated with Rad51 during the later stages recombination. PMID:25195049

Epidemic dynamics and endemic states in complex networks

Science.gov (United States)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-06-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Epidemic dynamics and endemic states in complex networks

International Nuclear Information System (INIS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-01-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks

Complex Dynamics of an Adnascent-Type Game Model

Directory of Open Access Journals (Sweden)

Baogui Xin

2008-01-01

Full Text Available The paper presents a nonlinear discrete game model for two oligopolistic firms whose products are adnascent. (In biology, the term adnascent has only one sense, “growing to or on something else,” e.g., “moss is an adnascent plant.” See Webster's Revised Unabridged Dictionary published in 1913 by C. & G. Merriam Co., edited by Noah Porter. The bifurcation of its Nash equilibrium is analyzed with Schwarzian derivative and normal form theory. Its complex dynamics is demonstrated by means of the largest Lyapunov exponents, fractal dimensions, bifurcation diagrams, and phase portraits. At last, bifurcation and chaos anticontrol of this system are studied.

Genetic variation in social influence on mate preferences

Science.gov (United States)

Rebar, Darren; Rodríguez, Rafael L.

2013-01-01

Patterns of phenotypic variation arise in part from plasticity owing to social interactions, and these patterns contribute, in turn, to the form of selection that shapes the variation we observe in natural populations. This proximate–ultimate dynamic brings genetic variation in social environments to the forefront of evolutionary theory. However, the extent of this variation remains largely unknown. Here, we use a member of the Enchenopa binotata species complex of treehoppers (Hemiptera: Membracidae) to assess how mate preferences are influenced by genetic variation in the social environment. We used full-sibling split-families as ‘treatment’ social environments, and reared focal females alongside each treatment family, describing the mate preferences of the focal females. With this method, we detected substantial genetic variation in social influence on mate preferences. The mate preferences of focal females varied according to the treatment families along with which they grew up. We discuss the evolutionary implications of the presence of such genetic variation in social influence on mate preferences, including potential contributions to the maintenance of genetic variation, the promotion of divergence, and the adaptive evolution of social effects on fitness-related traits. PMID:23698010

Phase dynamics of complex-valued neural networks and its application to traffic signal control.

Science.gov (United States)

Nishikawa, Ikuko; Iritani, Takeshi; Sakakibara, Kazutoshi; Kuroe, Yasuaki

2005-01-01

Complex-valued Hopfield networks which possess the energy function are analyzed. The dynamics of the network with certain forms of an activation function is de-composable into the dynamics of the amplitude and phase of each neuron. Then the phase dynamics is described as a coupled system of phase oscillators with a pair-wise sinusoidal interaction. Therefore its phase synchronization mechanism is useful for the area-wide offset control of the traffic signals. The computer simulations show the effectiveness under the various traffic conditions.

Structural dynamics of a noncovalent charge transfer complex from femtosecond stimulated Raman spectroscopy.

Science.gov (United States)

Fujisawa, Tomotsumi; Creelman, Mark; Mathies, Richard A

2012-09-06

Femtosecond stimulated Raman spectroscopy is used to examine the structural dynamics of photoinduced charge transfer within a noncovalent electron acceptor/donor complex of pyromellitic dianhydride (PMDA, electron acceptor) and hexamethylbenzene (HMB, electron donor) in ethylacetate and acetonitrile. The evolution of the vibrational spectrum reveals the ultrafast structural changes that occur during the charge separation (Franck-Condon excited state complex → contact ion pair) and the subsequent charge recombination (contact ion pair → ground state complex). The Franck-Condon excited state is shown to have significant charge-separated character because its vibrational spectrum is similar to that of the ion pair. The charge separation rate (2.5 ps in ethylacetate and ∼0.5 ps in acetonitrile) is comparable to solvation dynamics and is unaffected by the perdeuteration of HMB, supporting the dominant role of solvent rearrangement in charge separation. On the other hand, the charge recombination slows by a factor of ∼1.4 when using perdeuterated HMB, indicating that methyl hydrogen motions of HMB mediate the charge recombination process. Resonance Raman enhancement of the HMB vibrations in the complex reveals that the ring stretches of HMB, and especially the C-CH(3) deformations are the primary acceptor modes promoting charge recombination.

Complexity and multifractality of neuronal noise in mouse and human hippocampal epileptiform dynamics

Science.gov (United States)

Serletis, Demitre; Bardakjian, Berj L.; Valiante, Taufik A.; Carlen, Peter L.

2012-10-01

Fractal methods offer an invaluable means of investigating turbulent nonlinearity in non-stationary biomedical recordings from the brain. Here, we investigate properties of complexity (i.e. the correlation dimension, maximum Lyapunov exponent, 1/fγ noise and approximate entropy) and multifractality in background neuronal noise-like activity underlying epileptiform transitions recorded at the intracellular and local network scales from two in vitro models: the whole-intact mouse hippocampus and lesional human hippocampal slices. Our results show evidence for reduced dynamical complexity and multifractal signal features following transition to the ictal epileptiform state. These findings suggest that pathological breakdown in multifractal complexity coincides with loss of signal variability or heterogeneity, consistent with an unhealthy ictal state that is far from the equilibrium of turbulent yet healthy fractal dynamics in the brain. Thus, it appears that background noise-like activity successfully captures complex and multifractal signal features that may, at least in part, be used to classify and identify brain state transitions in the healthy and epileptic brain, offering potential promise for therapeutic neuromodulatory strategies for afflicted patients suffering from epilepsy and other related neurological disorders. This paper is based on chapter 5 of Serletis (2010 PhD Dissertation Department of Physiology, Institute of Biomaterials and Biomedical Engineering, University of Toronto).

A dissipative particle dynamics method for arbitrarily complex geometries

Science.gov (United States)

Li, Zhen; Bian, Xin; Tang, Yu-Hang; Karniadakis, George Em

2018-02-01

Dissipative particle dynamics (DPD) is an effective Lagrangian method for modeling complex fluids in the mesoscale regime but so far it has been limited to relatively simple geometries. Here, we formulate a local detection method for DPD involving arbitrarily shaped geometric three-dimensional domains. By introducing an indicator variable of boundary volume fraction (BVF) for each fluid particle, the boundary of arbitrary-shape objects is detected on-the-fly for the moving fluid particles using only the local particle configuration. Therefore, this approach eliminates the need of an analytical description of the boundary and geometry of objects in DPD simulations and makes it possible to load the geometry of a system directly from experimental images or computer-aided designs/drawings. More specifically, the BVF of a fluid particle is defined by the weighted summation over its neighboring particles within a cutoff distance. Wall penetration is inferred from the value of the BVF and prevented by a predictor-corrector algorithm. The no-slip boundary condition is achieved by employing effective dissipative coefficients for liquid-solid interactions. Quantitative evaluations of the new method are performed for the plane Poiseuille flow, the plane Couette flow and the Wannier flow in a cylindrical domain and compared with their corresponding analytical solutions and (high-order) spectral element solution of the Navier-Stokes equations. We verify that the proposed method yields correct no-slip boundary conditions for velocity and generates negligible fluctuations of density and temperature in the vicinity of the wall surface. Moreover, we construct a very complex 3D geometry - the "Brown Pacman" microfluidic device - to explicitly demonstrate how to construct a DPD system with complex geometry directly from loading a graphical image. Subsequently, we simulate the flow of a surfactant solution through this complex microfluidic device using the new method. Its

Better decision making in complex, dynamic tasks training with human-facilitated interactive learning environments

CERN Document Server

Qudrat-Ullah, Hassan

2015-01-01

This book describes interactive learning environments (ILEs) and their underlying concepts. It explains how ILEs can be used to improve the decision-making process and how these improvements can be empirically verified. The objective of this book is to enhance our understanding of and to gain insights into the process by which human facilitated ILEs are effectively designed and used in improving users’ decision making in complex, dynamic tasks. This book is divided into four major parts. Part I serves as an introduction to the importance and complexity of decision making in dynamic tasks. Part II provides background material, drawing upon relevant literature, for the development of an integrated process model on the effectiveness of human facilitated ILEs in improving decision making in dynamic tasks. Part III focuses on the design, development, and application of FishBankILE in laboratory experiments to gather empirical evidence for the validity of the process model. Finally, part IV presents a comprehensi...

Transferability of MCR-1/2 Polymyxin Resistance: Complex Dissemination and Genetic Mechanism.

Science.gov (United States)

Feng, Youjun

2018-03-09

Polymyxins, a group of cationic antimicrobial polypeptides, act as a last-resort defense against lethal infections by carbapenem-resistant Gram-negative pathogens. Recent emergence and fast spread of mobilized colistin resistance determinant mcr-1 argue the renewed interest of colistin in clinical therapies, threatening global public health and agriculture production. This mini-review aims to present an updated overview of mcr-1, covering its global dissemination, the diversity of its hosts/plasmid reservoirs, the complexity in the genetic environment adjacent to mcr-1, the appearance of new mcr-like genes, and the molecular mechanisms for mobilized colistin resistance determinant 1/2 (MCR-1/2).

EPR and Klein Paradoxes in Complex Hamiltonian Dynamics and Krein Space Quantization