Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces
Partha, Raghavendran; Raman, Karthik
2014-01-01
Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to normal populations evolving on neutral networks. PMID:25390641
Morphological change in machines accelerates the evolution of robust behavior
Bongard, Josh
2011-01-01
Most animals exhibit significant neurological and morphological change throughout their lifetime. No robots to date, however, grow new morphological structure while behaving. This is due to technological limitations but also because it is unclear that morphological change provides a benefit to the acquisition of robust behavior in machines. Here I show that in evolving populations of simulated robots, if robots grow from anguilliform into legged robots during their lifetime in the early stages of evolution, and the anguilliform body plan is gradually lost during later stages of evolution, gaits are evolved for the final, legged form of the robot more rapidly—and the evolved gaits are more robust—compared to evolving populations of legged robots that do not transition through the anguilliform body plan. This suggests that morphological change, as well as the evolution of development, are two important processes that improve the automatic generation of robust behaviors for machines. It also provides an experimental platform for investigating the relationship between the evolution of development and robust behavior in biological organisms. PMID:21220304
Functional modules of sigma factor regulons guarantee adaptability and evolvability
Binder, Sebastian C.; Eckweiler, Denitsa; Schulz, Sebastian; Bielecka, Agata; Nicolai, Tanja; Franke, Raimo; Häussler, Susanne; Meyer-Hermann, Michael
2016-01-01
The focus of modern molecular biology turns from assigning functions to individual genes towards understanding the expression and regulation of complex sets of molecules. Here, we provide evidence that alternative sigma factor regulons in the pathogen Pseudomonas aeruginosa largely represent insulated functional modules which provide a critical level of biological organization involved in general adaptation and survival processes. Analysis of the operational state of the sigma factor network revealed that transcription factors functionally couple the sigma factor regulons and significantly modulate the transcription levels in the face of challenging environments. The threshold quality of newly evolved transcription factors was reached faster and more robustly in in silico testing when the structural organization of sigma factor networks was taken into account. These results indicate that the modular structures of alternative sigma factor regulons provide P. aeruginosa with a robust framework to function adequately in its environment and at the same time facilitate evolutionary change. Our data support the view that widespread modularity guarantees robustness of biological networks and is a key driver of evolvability. PMID:26915971
A VHDL Core for Intrinsic Evolution of Discrete Time Filters with Signal Feedback
NASA Technical Reports Server (NTRS)
Gwaltney, David A.; Dutton, Kenneth
2005-01-01
The design of an Evolvable Machine VHDL Core is presented, representing a discrete-time processing structure capable of supporting control system applications. This VHDL Core is implemented in an FPGA and is interfaced with an evolutionary algorithm implemented in firmware on a Digital Signal Processor (DSP) to create an evolvable system platform. The salient features of this architecture are presented. The capability to implement IIR filter structures is presented along with the results of the intrinsic evolution of a filter. The robustness of the evolved filter design is tested and its unique characteristics are described.
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S
2016-01-01
Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.
Evolution of robustness to damage in artificial 3-dimensional development.
Joachimczak, Michał; Wróbel, Borys
2012-09-01
GReaNs is an Artificial Life platform we have built to investigate the general principles that guide evolution of multicellular development and evolution of artificial gene regulatory networks. The embryos develop in GReaNs in a continuous 3-dimensional (3D) space with simple physics. The developmental trajectories are indirectly encoded in linear genomes. The genomes are not limited in size and determine the topology of gene regulatory networks that are not limited in the number of nodes. The expression of the genes is continuous and can be modified by adding environmental noise. In this paper we evolved development of structures with a specific shape (an ellipsoid) and asymmetrical pattering (a 3D pattern inspired by the French flag problem), and investigated emergence of the robustness to damage in development and the emergence of the robustness to noise. Our results indicate that both types of robustness are related, and that including noise during evolution promotes higher robustness to damage. Interestingly, we have observed that some evolved gene regulatory networks rely on noise for proper behaviour. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Chen, Bor-Sen; Lin, Ying-Po
2011-01-01
In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563
Steiner, Christopher F.
2012-01-01
The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934
Evolving polycentric governance of the Great Barrier Reef
Morrison, Tiffany H.
2017-01-01
A growing field of sustainability science examines how environments are transformed through polycentric governance. However, many studies are only snapshot analyses of the initial design or the emergent structure of polycentric regimes. There is less systematic analysis of the longitudinal robustness of polycentric regimes. The problem of robustness is approached by focusing not only on the structure of a regime but also on its context and effectiveness. These dimensions are examined through a longitudinal analysis of the Great Barrier Reef (GBR) governance regime, drawing on in-depth interviews and demographic, economic, and employment data, as well as organizational records and participant observation. Between 1975 and 2011, the GBR regime evolved into a robust polycentric structure as evident in an established set of multiactor, multilevel arrangements addressing marine, terrestrial, and global threats. However, from 2005 onward, multiscale drivers precipitated at least 10 types of regime change, ranging from contextual change that encouraged regime drift to deliberate changes that threatened regime conversion. More recently, regime realignment also has occurred in response to steering by international organizations and shocks such as the 2016 mass coral-bleaching event. The results show that structural density and stability in a governance regime can coexist with major changes in that regime’s context and effectiveness. Clear analysis of the vulnerability of polycentric governance to both diminishing effectiveness and the masking effects of increasing complexity provides sustainability science and governance actors with a stronger basis to understand and respond to regime change. PMID:28348238
Evolving polycentric governance of the Great Barrier Reef.
Morrison, Tiffany H
2017-04-11
A growing field of sustainability science examines how environments are transformed through polycentric governance. However, many studies are only snapshot analyses of the initial design or the emergent structure of polycentric regimes. There is less systematic analysis of the longitudinal robustness of polycentric regimes. The problem of robustness is approached by focusing not only on the structure of a regime but also on its context and effectiveness. These dimensions are examined through a longitudinal analysis of the Great Barrier Reef (GBR) governance regime, drawing on in-depth interviews and demographic, economic, and employment data, as well as organizational records and participant observation. Between 1975 and 2011, the GBR regime evolved into a robust polycentric structure as evident in an established set of multiactor, multilevel arrangements addressing marine, terrestrial, and global threats. However, from 2005 onward, multiscale drivers precipitated at least 10 types of regime change, ranging from contextual change that encouraged regime drift to deliberate changes that threatened regime conversion. More recently, regime realignment also has occurred in response to steering by international organizations and shocks such as the 2016 mass coral-bleaching event. The results show that structural density and stability in a governance regime can coexist with major changes in that regime's context and effectiveness. Clear analysis of the vulnerability of polycentric governance to both diminishing effectiveness and the masking effects of increasing complexity provides sustainability science and governance actors with a stronger basis to understand and respond to regime change.
Flexibility of centromere and kinetochore structures
Burrack, Laura S.; Berman, Judith
2012-01-01
Centromeres, and the kinetochores that assemble on them, are essential for accurate chromosome segregation. Diverse centromere organization patterns and kinetochore structures have evolved in eukaryotes ranging from yeast to humans. In addition, centromere DNA and kinetochore position can vary even within individual cells. This flexibility manifests in several ways: centromere DNA sequences evolve rapidly, kinetochore positions shift in response to altered chromosome structure, and kinetochore complex numbers change in response to fluctuations in kinetochore protein levels. Despite their differences, all of these diverse structures promote efficient chromosome segregation. This robustness is inherent to chromosome segregation mechanisms and balances genome stability with adaptability. In this review, we explore the mechanisms and consequences of centromere and kinetochore flexibility as well as the benefits and limitations of different experimental model systems for studying them. PMID:22445183
Growth Control and Disease Mechanisms in Computational Embryogeny
NASA Technical Reports Server (NTRS)
Shapiro, Andrew A.; Yogev, Or; Antonsson, Erik K.
2008-01-01
This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.
The evolvability of programmable hardware.
Raman, Karthik; Wagner, Andreas
2011-02-06
In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected 'neutral networks' in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 10(45) logic circuits ('genotypes') and 10(19) logic functions ('phenotypes'). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry.
The evolvability of programmable hardware
Raman, Karthik; Wagner, Andreas
2011-01-01
In biological systems, individual phenotypes are typically adopted by multiple genotypes. Examples include protein structure phenotypes, where each structure can be adopted by a myriad individual amino acid sequence genotypes. These genotypes form vast connected ‘neutral networks’ in genotype space. The size of such neutral networks endows biological systems not only with robustness to genetic change, but also with the ability to evolve a vast number of novel phenotypes that occur near any one neutral network. Whether technological systems can be designed to have similar properties is poorly understood. Here we ask this question for a class of programmable electronic circuits that compute digital logic functions. The functional flexibility of such circuits is important in many applications, including applications of evolutionary principles to circuit design. The functions they compute are at the heart of all digital computation. We explore a vast space of 1045 logic circuits (‘genotypes’) and 1019 logic functions (‘phenotypes’). We demonstrate that circuits that compute the same logic function are connected in large neutral networks that span circuit space. Their robustness or fault-tolerance varies very widely. The vicinity of each neutral network contains circuits with a broad range of novel functions. Two circuits computing different functions can usually be converted into one another via few changes in their architecture. These observations show that properties important for the evolvability of biological systems exist in a commercially important class of electronic circuitry. They also point to generic ways to generate fault-tolerant, adaptable and evolvable electronic circuitry. PMID:20534598
The structure and resilience of financial market networks
NASA Astrophysics Data System (ADS)
Kauê Dal'Maso Peron, Thomas; da Fontoura Costa, Luciano; Rodrigues, Francisco A.
2012-03-01
Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.
Ogushi, Fumiko; Kertész, János; Kaski, Kimmo; Shimada, Takashi
2017-08-01
Living organisms, ecosystems, and social systems are examples of complex systems in which robustness against inclusion of new elements is an essential feature. A recently proposed simple model has revealed a general mechanism by which such systems can become robust against inclusion of elements with totally random interactions when the elements have a moderate number of links. The interaction is, however, in many systems often intrinsically bidirectional like for mutual symbiosis and competition in ecology. This study reports the strong reinforcement effect of the bidirectionality of the interactions on the robustness of evolving systems. We show that the system with purely bidirectional interactions can grow with twofold average degree, in comparison with the purely unidirectional system. This drastic shift of the transition point comes from the reinforcement of each node, not from a change in structure of the emergent system. For systems with partially bidirectional interactions we find that the regime of the growing phase gets expanded. In the dense interaction regime, there exists an optimum proportion of bidirectional interactions for the growth rate at around 1/3. In the sparsely connected systems, small but finite fraction of bidirectional links can change the system's behaviour from non-growing to growing.
Recent Developments in Hydrogen Evolving Molecular Cobalt(II)-Polypyridyl Catalysts
Queyriaux, N.; Jane, R. T.; Massin, J.; Artero, V.; Chavarot-Kerlidou, M.
2015-01-01
The search for efficient noble metal-free hydrogen-evolving catalysts is the subject of intense research activity. A new family of molecular cobalt(II)-polypyridyl catalysts has recently emerged. These catalysts prove more robust under reductive conditions than other cobalt-based systems and display high activities under fully aqueous conditions. This review discusses the design, characterization, and evaluation of these catalysts for electrocatalytic and light-driven hydrogen production. Mechanistic considerations are addressed and structure-catalytic activity relationships identified in order to guide the future design of more efficient catalytic systems. PMID:26688590
Kitano, Hiroaki
2004-11-01
Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems. Robustness facilitates evolvability and robust traits are often selected by evolution. Such a mutually beneficial process is made possible by specific architectural features observed in robust systems. But there are trade-offs between robustness, fragility, performance and resource demands, which explain system behaviour, including the patterns of failure. Insights into inherent properties of robust systems will provide us with a better understanding of complex diseases and a guiding principle for therapy design.
Link Prediction in Evolving Networks Based on Popularity of Nodes.
Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian
2017-08-02
Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.
Free selection: a silvicultural option
Russell T. Graham; Theresa B. Jain; Jonathan Sandquist
2007-01-01
Forest management objectives continue to evolve as the desires and needs of society change. The practice of silviculture has risen to the challenge by supplying silvicultural methods and systems to produce desired stand and forest structures and compositions to meet these changing objectives. For the most part, the practice of silviculture offers a robust set of...
Application of free selection in mixed forests of the inland northwestern United States
Russell T. Graham; Theresa B. Jain
2005-01-01
Forest management objectives continue to evolve as the desires and needs of society change. The practice of silviculture has risen to the challenge by supplying silvicultural methods and systems to produce desired stand and forest structures and compositions to meet these changing objectives. For the most part, the practice of silviculture offers a robust set of...
Environmental change makes robust ecological networks fragile
Strona, Giovanni; Lafferty, Kevin D.
2016-01-01
Complex ecological networks appear robust to primary extinctions, possibly due to consumers’ tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems.
Fernandez-Leon, Jose A; Acosta, Gerardo G; Rozenfeld, Alejandro
2014-10-01
Researchers in diverse fields, such as in neuroscience, systems biology and autonomous robotics, have been intrigued by the origin and mechanisms for biological robustness. Darwinian evolution, in general, has suggested that adaptive mechanisms as a way of reaching robustness, could evolve by natural selection acting successively on numerous heritable variations. However, is this understanding enough for realizing how biological systems remain robust during their interactions with the surroundings? Here, we describe selected studies of bio-inspired systems that show behavioral robustness. From neurorobotics, cognitive, self-organizing and artificial immune system perspectives, our discussions focus mainly on how robust behaviors evolve or emerge in these systems, having the capacity of interacting with their surroundings. These descriptions are twofold. Initially, we introduce examples from autonomous robotics to illustrate how the process of designing robust control can be idealized in complex environments for autonomous navigation in terrain and underwater vehicles. We also include descriptions of bio-inspired self-organizing systems. Then, we introduce other studies that contextualize experimental evolution with simulated organisms and physical robots to exemplify how the process of natural selection can lead to the evolution of robustness by means of adaptive behaviors. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Environmental change makes robust ecological networks fragile
Strona, Giovanni; Lafferty, Kevin D.
2016-01-01
Complex ecological networks appear robust to primary extinctions, possibly due to consumers' tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems. PMID:27511722
Robustness to Faults Promotes Evolvability: Insights from Evolving Digital Circuits
Nolfi, Stefano
2016-01-01
We demonstrate how the need to cope with operational faults enables evolving circuits to find more fit solutions. The analysis of the results obtained in different experimental conditions indicates that, in absence of faults, evolution tends to select circuits that are small and have low phenotypic variability and evolvability. The need to face operation faults, instead, drives evolution toward the selection of larger circuits that are truly robust with respect to genetic variations and that have a greater level of phenotypic variability and evolvability. Overall our results indicate that the need to cope with operation faults leads to the selection of circuits that have a greater probability to generate better circuits as a result of genetic variation with respect to a control condition in which circuits are not subjected to faults. PMID:27409589
Female mating preferences determine system-level evolution in a gene network model.
Fierst, Janna L
2013-06-01
Environmental patterns of directional, stabilizing and fluctuating selection can influence the evolution of system-level properties like evolvability and mutational robustness. Intersexual selection produces strong phenotypic selection and these dynamics may also affect the response to mutation and the potential for future adaptation. In order to to assess the influence of mating preferences on these evolutionary properties, I modeled a male trait and female preference determined by separate gene regulatory networks. I studied three sexual selection scenarios: sexual conflict, a Gaussian model of the Fisher process described in Lande (in Proc Natl Acad Sci 78(6):3721-3725, 1981) and a good genes model in which the male trait signalled his mutational condition. I measured the effects these mating preferences had on the potential for traits and preferences to evolve towards new states, and mutational robustness of both the phenotype and the individual's overall viability. All types of sexual selection increased male phenotypic robustness relative to a randomly mating population. The Fisher model also reduced male evolvability and mutational robustness for viability. Under good genes sexual selection, males evolved an increased mutational robustness for viability. Females choosing their mates is a scenario that is sufficient to create selective forces that impact genetic evolution and shape the evolutionary response to mutation and environmental selection. These dynamics will inevitably develop in any population where sexual selection is operating, and affect the potential for future adaptation.
Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity.
Wagner, Andreas
2014-02-18
Novel phenotypes can originate either through mutations in existing genotypes or through phenotypic plasticity, the ability of one genotype to form multiple phenotypes. From molecules to organisms, plasticity is a ubiquitous feature of life, and a potential source of exaptations, adaptive traits that originated for nonadaptive reasons. Another ubiquitous feature is robustness to mutations, although it is unknown whether such robustness helps or hinders the origin of new phenotypes through plasticity. RNA is ideal to address this question, because it shows extensive plasticity in its secondary structure phenotypes, a consequence of their continual folding and unfolding, and these phenotypes have important biological functions. Moreover, RNA is to some extent robust to mutations. This robustness structures RNA genotype space into myriad connected networks of genotypes with the same phenotype, and it influences the dynamics of evolving populations on a genotype network. In this study I show that both effects help accelerate the exploration of novel phenotypes through plasticity. My observations are based on many RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules. They are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolution of biological RNA. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.
A slowly evolving host moves first in symbiotic interactions
NASA Astrophysics Data System (ADS)
Damore, James; Gore, Jeff
2011-03-01
Symbiotic relationships, both parasitic and mutualistic, are ubiquitous in nature. Understanding how these symbioses evolve, from bacteria and their phages to humans and our gut microflora, is crucial in understanding how life operates. Often, symbioses consist of a slowly evolving host species with each host only interacting with its own sub-population of symbionts. The Red Queen hypothesis describes coevolutionary relationships as constant arms races with each species rushing to evolve an advantage over the other, suggesting that faster evolution is favored. Here, we use a simple game theoretic model of host- symbiont coevolution that includes population structure to show that if the symbionts evolve much faster than the host, the equilibrium distribution is the same as it would be if it were a sequential game where the host moves first against its symbionts. For the slowly evolving host, this will prove to be advantageous in mutualisms and a handicap in antagonisms. The model allows for symbiont adaptation to its host, a result that is robust to changes in the parameters and generalizes to continuous and multiplayer games. Our findings provide insight into a wide range of symbiotic phenomena and help to unify the field of coevolutionary theory.
A Complex Network Analysis of Granular Fabric Evolution in Three-Dimensions
2011-01-01
organized pattern formation (e.g., strain localization), and co-evolution of emergent in- ternal structures (e.g., force cycles and force chains) [15...these networks, particularly recurring patterns or motifs, and understanding how these co-evolve are crucial to the robust characterization and...the lead up to and during failure. Since failure patterns and boundaries of flow in three-dimensional specimens can be quite complicated and difficult
Pagan, Rafael F; Massey, Steven E
2014-02-01
Proteins are regarded as being robust to the deleterious effects of mutations. Here, the neutral emergence of mutational robustness in a population of single domain proteins is explored using computer simulations. A pairwise contact model was used to calculate the ΔG of folding (ΔG folding) using the three dimensional protein structure of leech eglin C. A random amino acid sequence with low mutational robustness, defined as the average ΔΔG resulting from a point mutation (ΔΔG average), was threaded onto the structure. A population of 1,000 threaded sequences was evolved under selection for stability, using an upper and lower energy threshold. Under these conditions, mutational robustness increased over time in the most common sequence in the population. In contrast, when the wild type sequence was used it did not show an increase in robustness. This implies that the emergence of mutational robustness is sequence specific and that wild type sequences may be close to maximal robustness. In addition, an inverse relationship between ∆∆G average and protein stability is shown, resulting partly from a larger average effect of point mutations in more stable proteins. The emergence of mutational robustness was also observed in the Escherichia coli colE1 Rop and human CD59 proteins, implying that the property may be common in single domain proteins under certain simulation conditions. The results indicate that at least a portion of mutational robustness in small globular proteins might have arisen by a process of neutral emergence, and could be an example of a beneficial trait that has not been directly selected for, termed a "pseudaptation."
Neutral evolution of mutational robustness
van Nimwegen, Erik; Crutchfield, James P.; Huynen, Martijn
1999-01-01
We introduce and analyze a general model of a population evolving over a network of selectively neutral genotypes. We show that the population’s limit distribution on the neutral network is solely determined by the network topology and given by the principal eigenvector of the network’s adjacency matrix. Moreover, the average number of neutral mutant neighbors per individual is given by the matrix spectral radius. These results quantify the extent to which populations evolve mutational robustness—the insensitivity of the phenotype to mutations—and thus reduce genetic load. Because the average neutrality is independent of evolutionary parameters—such as mutation rate, population size, and selective advantage—one can infer global statistics of neutral network topology by using simple population data available from in vitro or in vivo evolution. Populations evolving on neutral networks of RNA secondary structures show excellent agreement with our theoretical predictions. PMID:10449760
Greenbury, Sam F.; Schaper, Steffen; Ahnert, Sebastian E.; Louis, Ard A.
2016-01-01
Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps—a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure—to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so increase evolvability. PMID:26937652
NASA Astrophysics Data System (ADS)
Najafi, Ali; Acar, Erdem; Rais-Rohani, Masoud
2014-02-01
The stochastic uncertainties associated with the material, process and product are represented and propagated to process and performance responses. A finite element-based sequential coupled process-performance framework is used to simulate the forming and energy absorption responses of a thin-walled tube in a manner that both material properties and component geometry can evolve from one stage to the next for better prediction of the structural performance measures. Metamodelling techniques are used to develop surrogate models for manufacturing and performance responses. One set of metamodels relates the responses to the random variables whereas the other relates the mean and standard deviation of the responses to the selected design variables. A multi-objective robust design optimization problem is formulated and solved to illustrate the methodology and the influence of uncertainties on manufacturability and energy absorption of a metallic double-hat tube. The results are compared with those of deterministic and augmented robust optimization problems.
Genome-scale rates of evolutionary change in bacteria
Duchêne, Sebastian; Holt, Kathryn E.; Weill, François-Xavier; Le Hello, Simon; Hawkey, Jane; Edwards, David J.; Fourment, Mathieu
2016-01-01
Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host–pathogen associations and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with ‘ancient DNA’ data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10−5 to 10−8 nucleotide substitutions per site year−1. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria. PMID:28348834
Lachowiec, Jennifer; Queitsch, Christine; Kliebenstein, Daniel J.
2016-01-01
Background Robustness to genetic and environmental perturbation is a salient feature of multicellular organisms. Loss of developmental robustness can lead to severe phenotypic defects and fitness loss. However, perfect robustness, i.e. no variation at all, is evolutionarily unfit as organisms must be able to change phenotype to properly respond to changing environments and biotic challenges. Plasticity is the ability to adjust phenotypes predictably in response to specific environmental stimuli, which can be considered a transient shift allowing an organism to move from one robust phenotypic state to another. Plants, as sessile organisms that undergo continuous development, are particularly dependent on an exquisite fine-tuning of the processes that balance robustness and plasticity to maximize fitness. Scope and Conclusions This paper reviews recently identified mechanisms, both systems-level and molecular, that modulate robustness, and discusses their implications for the optimization of plant fitness. Robustness in living systems arises from the structure of genetic networks, the specific molecular functions of the underlying genes, and their interactions. This very same network responsible for the robustness of specific developmental states also has to be built such that it enables plastic yet robust shifts in response to environmental changes. In plants, the interactions and functions of signal transduction pathways activated by phytohormones and the tendency for plants to tolerate whole-genome duplications, tandem gene duplication and hybridization are emerging as major regulators of robustness in development. Despite their obvious implications for plant evolution and plant breeding, the mechanistic underpinnings by which plants modulate precise levels of robustness, plasticity and evolvability in networks controlling different phenotypes are under-studied. PMID:26473020
The genotype-phenotype map of an evolving digital organism.
Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas
2017-02-01
To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.
The genotype-phenotype map of an evolving digital organism
Zaman, Luis; Wagner, Andreas
2017-01-01
To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039
Holonic Rationale and Bio-inspiration on Design of Complex Emergent and Evolvable Systems
NASA Astrophysics Data System (ADS)
Leitao, Paulo
Traditional centralized and rigid control structures are becoming inflexible to face the requirements of reconfigurability, responsiveness and robustness, imposed by customer demands in the current global economy. The Holonic Manufacturing Systems (HMS) paradigm, which was pointed out as a suitable solution to face these requirements, translates the concepts inherited from social organizations and biology to the manufacturing world. It offers an alternative way of designing adaptive systems where the traditional centralized control is replaced by decentralization over distributed and autonomous entities organized in hierarchical structures formed by intermediate stable forms. In spite of its enormous potential, methods regarding the self-adaptation and self-organization of complex systems are still missing. This paper discusses how the insights from biology in connection with new fields of computer science can be useful to enhance the holonic design aiming to achieve more self-adaptive and evolvable systems. Special attention is devoted to the discussion of emergent behavior and self-organization concepts, and the way they can be combined with the holonic rationale.
Ni, Xiao Yu; Drengstig, Tormod; Ruoff, Peter
2009-09-02
Organisms have the property to adapt to a changing environment and keep certain components within a cell regulated at the same level (homeostasis). "Perfect adaptation" describes an organism's response to an external stepwise perturbation by regulating some of its variables/components precisely to their original preperturbation values. Numerous examples of perfect adaptation/homeostasis have been found, as for example, in bacterial chemotaxis, photoreceptor responses, MAP kinase activities, or in metal-ion homeostasis. Two concepts have evolved to explain how perfect adaptation may be understood: In one approach (robust perfect adaptation), the adaptation is a network property, which is mostly, but not entirely, independent of rate constant values; in the other approach (nonrobust perfect adaptation), a fine-tuning of rate constant values is needed. Here we identify two classes of robust molecular homeostatic mechanisms, which compensate for environmental variations in a controlled variable's inflow or outflow fluxes, and allow for the presence of robust temperature compensation. These two classes of homeostatic mechanisms arise due to the fact that concentrations must have positive values. We show that the concept of integral control (or integral feedback), which leads to robust homeostasis, is associated with a control species that has to work under zero-order flux conditions and does not necessarily require the presence of a physico-chemical feedback structure. There are interesting links between the two identified classes of homeostatic mechanisms and molecular mechanisms found in mammalian iron and calcium homeostasis, indicating that homeostatic mechanisms may underlie similar molecular control structures.
Garland, Ellen C; Rendell, Luke; Lilley, Matthew S; Poole, M Michael; Allen, Jenny; Noad, Michael J
2017-07-01
Identifying and quantifying variation in vocalizations is fundamental to advancing our understanding of processes such as speciation, sexual selection, and cultural evolution. The song of the humpback whale (Megaptera novaeangliae) presents an extreme example of complexity and cultural evolution. It is a long, hierarchically structured vocal display that undergoes constant evolutionary change. Obtaining robust metrics to quantify song variation at multiple scales (from a sound through to population variation across the seascape) is a substantial challenge. Here, the authors present a method to quantify song similarity at multiple levels within the hierarchy. To incorporate the complexity of these multiple levels, the calculation of similarity is weighted by measurements of sound units (lower levels within the display) to bridge the gap in information between upper and lower levels. Results demonstrate that the inclusion of weighting provides a more realistic and robust representation of song similarity at multiple levels within the display. This method permits robust quantification of cultural patterns and processes that will also contribute to the conservation management of endangered humpback whale populations, and is applicable to any hierarchically structured signal sequence.
Evolution and inheritance of early embryonic patterning in D. simulans and D. sechellia
Lott, Susan E.; Ludwig, Michael Z.; Kreitman, Martin
2010-01-01
Pattern formation in Drosophila is a widely studied example of a robust developmental system. Such robust systems pose a challenge to adaptive evolution, as they mask variation which selection may otherwise act upon. Yet we find variation in the localization of expression domains (henceforth ‘stripe allometry’) in the pattern formation pathway. Specifically, we characterize differences in the gap genes giant and Kruppel, and the pair-rule gene even-skipped, which differ between the sibling species D. simulans and D. sechellia. In a double-backcross experiment, stripe allometry is consistent with maternal inheritance of stripe positioning and multiple genetic factors, with a distinct genetic basis from embryo length. Embryos produced by F1 and F2 backcross mothers exhibit novel spatial patterns of gene expression relative to the parental species, with no measurable increase in positional variance among individuals. Buffering of novel spatial patterns in the backcross genotypes suggests that robustness need not be disrupted in order for the trait to evolve, and perhaps the system is incapable of evolving to prevent the expression of all genetic variation. This limitation, and the ability of natural selection to act on minute genetic differences that are within the “margin of error” for the buffering mechanism, indicates that developmentally buffered traits can evolve without disruption of robustness PMID:21121913
Neilson, Matthew P; Mackenzie, John A; Webb, Steven D; Insall, Robert H
2010-11-01
In this paper we present a computational tool that enables the simulation of mathematical models of cell migration and chemotaxis on an evolving cell membrane. Recent models require the numerical solution of systems of reaction-diffusion equations on the evolving cell membrane and then the solution state is used to drive the evolution of the cell edge. Previous work involved moving the cell edge using a level set method (LSM). However, the LSM is computationally very expensive, which severely limits the practical usefulness of the algorithm. To address this issue, we have employed the parameterised finite element method (PFEM) as an alternative method for evolving a cell boundary. We show that the PFEM is far more efficient and robust than the LSM. We therefore suggest that the PFEM potentially has an essential role to play in computational modelling efforts towards the understanding of many of the complex issues related to chemotaxis.
Tse, Longping Victor; Klinc, Kelli A; Madigan, Victoria J; Castellanos Rivera, Ruth M; Wells, Lindsey F; Havlik, L Patrick; Smith, J Kennon; Agbandje-McKenna, Mavis; Asokan, Aravind
2017-06-13
Preexisting neutralizing antibodies (NAbs) against adeno-associated viruses (AAVs) pose a major, unresolved challenge that restricts patient enrollment in gene therapy clinical trials using recombinant AAV vectors. Structural studies suggest that despite a high degree of sequence variability, antibody recognition sites or antigenic hotspots on AAVs and other related parvoviruses might be evolutionarily conserved. To test this hypothesis, we developed a structure-guided evolution approach that does not require selective pressure exerted by NAbs. This strategy yielded highly divergent antigenic footprints that do not exist in natural AAV isolates. Specifically, synthetic variants obtained by evolving murine antigenic epitopes on an AAV serotype 1 capsid template can evade NAbs without compromising titer, transduction efficiency, or tissue tropism. One lead AAV variant generated by combining multiple evolved antigenic sites effectively evades polyclonal anti-AAV1 neutralizing sera from immunized mice and rhesus macaques. Furthermore, this variant displays robust immune evasion in nonhuman primate and human serum samples at dilution factors as high as 1:5, currently mandated by several clinical trials. Our results provide evidence that antibody recognition of AAV capsids is conserved across species. This approach can be applied to any AAV strain to evade NAbs in prospective patients for human gene therapy.
Robustness, evolvability, and the logic of genetic regulation.
Payne, Joshua L; Moore, Jason H; Wagner, Andreas
2014-01-01
In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene's cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: For the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield identical gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, so that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype.
Robustness, Evolvability, and the Logic of Genetic Regulation
Moore, Jason H.; Wagner, Andreas
2014-01-01
In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene’s cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: for the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield idential gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, such that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype. PMID:23373974
Mello, Marco Aurelio Ribeiro; Marquitti, Flávia Maria Darcie; Guimarães, Paulo R; Kalko, Elisabeth Klara Viktoria; Jordano, Pedro; de Aguiar, Marcus Aloizio Martinez
2011-09-01
In networks of plant-animal mutualisms, different animal groups interact preferentially with different plants, thus forming distinct modules responsible for different parts of the service. However, what we currently know about seed dispersal networks is based only on birds. Therefore, we wished to fill this gap by studying bat-fruit networks and testing how they differ from bird-fruit networks. As dietary overlap of Neotropical bats and birds is low, they should form distinct mutualistic modules within local networks. Furthermore, since frugivory evolved only once among Neotropical bats, but several times independently among Neotropical birds, greater dietary overlap is expected among bats, and thus connectance and nestedness should be higher in bat-fruit networks. If bat-fruit networks have higher nestedness and connectance, they should be more robust to extinctions. We analyzed 1 mixed network of both bats and birds and 20 networks that consisted exclusively of either bats (11) or birds (9). As expected, the structure of the mixed network was both modular (M = 0.45) and nested (NODF = 0.31); one module contained only birds and two only bats. In 20 datasets with only one disperser group, bat-fruit networks (NODF = 0.53 ± 0.09, C = 0.30 ± 0.11) were more nested and had a higher connectance than bird-fruit networks (NODF = 0.42 ± 0.07, C = 0.22 ± 0.09). Unexpectedly, robustness to extinction of animal species was higher in bird-fruit networks (R = 0.60 ± 0.13) than in bat-fruit networks (R = 0.54 ± 0.09), and differences were explained mainly by species richness. These findings suggest that a modular structure also occurs in seed dispersal networks, similar to pollination networks. The higher nestedness and connectance observed in bat-fruit networks compared with bird-fruit networks may be explained by the monophyletic evolution of frugivory in Neotropical bats, among which the diets of specialists seem to have evolved from the pool of fruits consumed by generalists.
Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.
Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne
2016-01-01
Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.
Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots
Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne
2016-01-01
Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers. PMID:26999614
Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies
Edwards, Hannah; Abeln, Sanne; Deane, Charlotte M.
2013-01-01
The evolution of proteins is one of the fundamental processes that has delivered the diversity and complexity of life we see around ourselves today. While we tend to define protein evolution in terms of sequence level mutations, insertions and deletions, it is hard to translate these processes to a more complete picture incorporating a polypeptide's structure and function. By considering how protein structures change over time we can gain an entirely new appreciation of their long-term evolutionary dynamics. In this work we seek to identify how populations of proteins at different stages of evolution explore their possible structure space. We use an annotation of superfamily age to this space and explore the relationship between these ages and a diverse set of properties pertaining to a superfamily's sequence, structure and function. We note several marked differences between the populations of newly evolved and ancient structures, such as in their length distributions, secondary structure content and tertiary packing arrangements. In particular, many of these differences suggest a less elaborate structure for newly evolved superfamilies when compared with their ancient counterparts. We show that the structural preferences we report are not a residual effect of a more fundamental relationship with function. Furthermore, we demonstrate the robustness of our results, using significant variation in the algorithm used to estimate the ages. We present these age estimates as a useful tool to analyse protein populations. In particularly, we apply this in a comparison of domains containing greek key or jelly roll motifs. PMID:24244135
Maury, Carl Peter J
2015-10-07
The question of the origin of life on Earth can largely be reduced to the question of what was the first molecular replicator system that was able to replicate and evolve under the presumably very harsh conditions on the early Earth. It is unlikely that a functional RNA could have existed under such conditions and it is generally assumed that some other kind of information system preceded the RNA world. Here, I present an informational molecular system that is stable, self-replicative, environmentally responsive, and evolvable under conditions characterized by high temperatures, ultraviolet and cosmic radiation. This postulated pregenetic system is based on the amyloid fold, a functionally unique polypeptide fold characterized by a cross beta-sheet structure in which the beta strands are arranged perpendicular to the fiber axis. Beside an extraordinary structural robustness, the amyloid fold possesses a unique ability to transmit information by a three-dimensional templating mechanism. In amyloidogenesis short peptide monomers are added one by one to the growing end of the fiber. From the same monomeric subunits several structural variants of amyloid may be formed. Then, in a self-replicative mode, a specific amyloid conformer can act as a template and confer its spatially encoded information to daughter molecular entities in a repetitive way. In this process, the specific conformational information, the spatially changed organization, is transmitted; the coding element is the steric zipper structure, and recognition occurs by amino acid side chain complementarity. The amyloid information system fulfills several basic requirements of a primordial evolvable replicator system: (i) it is stable under the presumed primitive Earth conditions, (ii) the monomeric building blocks of the informational polymer can be formed from available prebiotic compounds, (iii) the system is self-assembling and self-replicative and (iv) it is adaptive to changes in the environment and evolvable. Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.
Evolution and inheritance of early embryonic patterning in Drosophila simulans and D. sechellia.
Lott, Susan E; Ludwig, Michael Z; Kreitman, Martin
2011-05-01
Pattern formation in Drosophila is a widely studied example of a robust developmental system. Such robust systems pose a challenge to adaptive evolution, as they mask variation that selection may otherwise act upon. Yet we find variation in the localization of expression domains (henceforth "stripe allometry") in the pattern formation pathway. Specifically, we characterize differences in the gap genes giant and Kruppel, and the pair-rule gene even-skipped, which differ between the sibling species Drosophila simulans and D. sechellia. In a double-backcross experiment, stripe allometry is consistent with maternal inheritance of stripe positioning and multiple genetic factors, with a distinct genetic basis from embryo length. Embryos produced by F1 and F2 backcross mothers exhibit novel spatial patterns of gene expression relative to the parental species, with no measurable increase in positional variance among individuals. Buffering of novel spatial patterns in the backcross genotypes suggests that robustness need not be disrupted in order for the trait to evolve, and perhaps the system is incapable of evolving to prevent the expression of all genetic variation. This limitation, and the ability of natural selection to act on minute genetic differences that are within the "margin of error" for the buffering mechanism, indicates that developmentally buffered traits can evolve without disruption of robustness. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.
Nanomechanical strength mechanisms of hierarchical biological materials and tissues.
Buehler, Markus J; Ackbarow, Theodor
2008-12-01
Biological protein materials (BPMs), intriguing hierarchical structures formed by assembly of chemical building blocks, are crucial for critical functions of life. The structural details of BPMs are fascinating: They represent a combination of universally found motifs such as alpha-helices or beta-sheets with highly adapted protein structures such as cytoskeletal networks or spider silk nanocomposites. BPMs combine properties like strength and robustness, self-healing ability, adaptability, changeability, evolvability and others into multi-functional materials at a level unmatched in synthetic materials. The ability to achieve these properties depends critically on the particular traits of these materials, first and foremost their hierarchical architecture and seamless integration of material and structure, from nano to macro. Here, we provide a brief review of this field and outline new research directions, along with a review of recent research results in the development of structure-property relationships of biological protein materials exemplified in a study of vimentin intermediate filaments.
Damage-mitigating control of aerospace systems for high performance and extended life
NASA Technical Reports Server (NTRS)
Ray, Asok; Wu, Min-Kuang; Carpino, Marc; Lorenzo, Carl F.; Merrill, Walter C.
1992-01-01
The concept of damage-mitigating control is to minimize fatigue (as well as creep and corrosion) damage of critical components of mechanical structures while simultaneously maximizing the system dynamic performance. Given a dynamic model of the plant and the specifications for performance and stability robustness, the task is to synthesize a control law that would meet the system requirements and, at the same time, satisfy the constraints that are imposed by the material and structural properties of the critical components. The authors present the concept of damage-mitigating control systems design with the following objectives: (1) to achieve high performance with a prolonged life span; and (2) to systematically update the controller as the new technology of advanced materials evolves. The major challenge is to extract the information from the material properties and then utilize this information in a mathematical form so that it can be directly applied to robust control synthesis for mechanical systems. The basic concept of damage-mitigating control is illustrated using a relatively simplified model of a space shuttle main engine.
In silico ribozyme evolution in a metabolically coupled RNA population.
Könnyű, Balázs; Szilágyi, András; Czárán, Tamás
2015-05-27
The RNA World hypothesis offers a plausible bridge from no-life to life on prebiotic Earth, by assuming that RNA, the only known molecule type capable of playing genetic and catalytic roles at the same time, could have been the first evolvable entity on the evolutionary path to the first living cell. We have developed the Metabolically Coupled Replicator System (MCRS), a spatially explicit simulation modelling approach to prebiotic RNA-World evolution on mineral surfaces, in which we incorporate the most important experimental facts and theoretical considerations to comply with recent knowledge on RNA and prebiotic evolution. In this paper the MCRS model framework has been extended in order to investigate the dynamical and evolutionary consequences of adding an important physico-chemical detail, namely explicit replicator structure - nucleotide sequence and 2D folding calculated from thermodynamical criteria - and their possible mutational changes, to the assumptions of a previously less detailed toy model. For each mutable nucleotide sequence the corresponding 2D folded structure with minimum free energy is calculated, which in turn is used to determine the fitness components (degradation rate, replicability and metabolic enzyme activity) of the replicator. We show that the community of such replicators providing the monomer supply for their own replication by evolving metabolic enzyme activities features an improved propensity for stable coexistence and structural adaptation. These evolutionary advantages are due to the emergent uniformity of metabolic replicator fitnesses imposed on the community by local group selection and attained through replicator trait convergence, i.e., the tendency of replicator lengths, ribozyme activities and population sizes to become similar between the coevolving replicator species that are otherwise both structurally and functionally different. In the most general terms it is the surprisingly high extra viability of the metabolic replicator system that the present model adds to the MCRS concept of the origin of life. Surface-bound, metabolically coupled RNA replicators tend to evolve different, enzymatically active sites within thermodynamically stable secondary structures, and the system as a whole evolves towards the robust coexistence of a complete set of such ribozymes driving the metabolism producing monomers for their own replication.
NASA Astrophysics Data System (ADS)
Trindade, B. C.; Reed, P. M.; Zeff, H. B.; Characklis, G. W.
2016-12-01
Water scarcity in historically water-rich regions such as the southeastern United States is becoming a more prevalent concern. It has been shown that cooperative short-term planning that relies on conservation and transfers of existing supplies amongst communities can be used by water utilities to mitigate the effects of water scarcity in the near future. However, in the longer term, infrastructure expansion is likely to be necessary to address imbalances between growing water demands and the available supply capacity. This study seeks to better diagnose and avoid candidate modes for system failure. Although it is becoming more common for water utilities to evaluate the robustness of their water supply, defined as the insensitivity of their systems to errors in deeply uncertain projections or assumptions, defining robustness is particularly challenging in multi-stakeholder regional contexts for decisions that encompass short management actions and long-term infrastructure planning. Planning and management decisions are highly interdependent and strongly shape how a region's infrastructure itself evolves. This research advances the concept of system robustness by making it evolve over time rather than static, so that it is applicable to an adaptive system and therefore more suited for use for combined short and long-term planning efforts. The test case for this research is the Research Triangle area of North Carolina, where the cities of Raleigh, Durham, Cary and Chapel Hill are experiencing rapid population growth and increasing concerns over drought. This study is facilitating their engagement in cooperative and robust regional water portfolio planning. The insights from this work have general merit for regions where adjacent municipalities can benefit from improving cooperative infrastructure investments and more efficient resource management strategies.
Evolution of robustness in the signaling network of Pristionchus vulva development
Zauner, Hans; Sommer, Ralf J.
2007-01-01
Robustness to environmental or genetic perturbation, like any other trait, is affected by evolutionary change. However, direct studies on the interplay of robustness and evolvability are limited and require experimental microevolutionary studies of developmental processes. One system in which such microevolutionary studies can be performed is vulva development in the nematode Pristionchus pacificus. Three vulval precursor cells respond to redundant cell–cell interactions, including signals from the gonad and the epidermal cell P8.p. Interestingly, P. pacificus P8.p is involved in cell fate specification of the future vulva cells by lateral inhibition but is incompetent to respond to the inductive signal from the gonad itself. These functional properties of P8.p are unknown from other nematodes, such as Caenorhabditis elegans. We began an experimental and genetic analysis of the microevolution of P8.p function. We show that vulva misspecification events differ between Pristionchus strains and species. Similarly, lateral inhibition and developmental competence of P8.p evolved within the genus Pristionchus and between natural isolates of P. pacificus. Surprisingly, in some recombinant inbred lines of two distinct P. pacificus isolates, P8.p gained competence to form vulva tissue, a trait that was never observed in P. pacificus isolates. Our results suggest differences in developmental stability between natural isolates, and we hypothesize that the remarkable evolvability of redundant cell–cell interactions allows for adaptive evolution of robustness to developmental noise. PMID:17551021
Robustness and Vulnerability of Networks with Dynamical Dependency Groups.
Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi
2016-11-28
The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.
Evolutionary transitions in controls reconcile adaptation with continuity of evolution.
Badyaev, Alexander V
2018-05-19
Evolution proceeds by accumulating functional solutions, necessarily forming an uninterrupted lineage from past solutions of ancestors to the current design of extant forms. At the population level, this process requires an organismal architecture in which the maintenance of local adaptation does not preclude the ability to innovate in the same traits and their continuous evolution. Representing complex traits as networks enables us to visualize a fundamental principle that resolves tension between adaptation and continuous evolution: phenotypic states encompassing adaptations traverse the continuous multi-layered landscape of past physical, developmental and functional associations among traits. The key concept that captures such traversing is network controllability - the ability to move a network from one state into another while maintaining its functionality (reflecting evolvability) and to efficiently propagate information or products through the network within a phenotypic state (maintaining its robustness). Here I suggest that transitions in network controllability - specifically in the topology of controls - help to explain how robustness and evolvability are balanced during evolution. I will focus on evolutionary transitions in degeneracy of metabolic networks - a ubiquitous property of phenotypic robustness where distinct pathways achieve the same end product - to suggest that associated changes in network controls is a common rule underlying phenomena as distinct as phenotypic plasticity, organismal accommodation of novelties, genetic assimilation, and macroevolutionary diversification. Capitalizing on well understood principles by which network structure translates into function of control nodes, I show that accumulating redundancy in one type of network controls inevitably leads to the emergence of another type of controls, forming evolutionary cycles of network controllability that, ultimately, reconcile local adaptation with continuity of evolution. Copyright © 2018 Elsevier Ltd. All rights reserved.
A Genomic View of the Peopling and Population Structure of India
Majumder, Partha P.; Basu, Analabha
2015-01-01
Recent advances in molecular and statistical genetics have enabled the reconstruction of human history by studying living humans. The ability to sequence and study DNA by calibrating the rate of accumulation of changes with evolutionary time has enabled robust inferences about how humans have evolved. These data indicate that modern humans evolved in Africa about 150,000 years ago and, consistent with paleontological evidence, migrated out of Africa. And through a series of settlements, demographic expansions, and further migrations, they populated the entire world. One of the first waves of migration from Africa was into India. Subsequent, more recent, waves of migration from other parts of the world have resulted in India being a genetic melting pot. Contemporary India has a rich tapestry of cultures and ecologies. There are about 400 tribal groups and more than 4000 groups of castes and subcastes, speaking dialects of 22 recognized languages belonging to four major language families. The contemporary social structure of Indian populations is characterized by endogamy with different degrees of porosity. The social structure, possibly coupled with large ecological heterogeneity, has resulted in considerable genetic diversity and local genetic differences within India. In this essay, we provide genetic evidence of how India may have been peopled, the nature and extent of its genetic diversity, and genetic structure among the extant populations of India. PMID:25147176
Alcalde Cuesta, Fernando; González Sequeiros, Pablo; Lozano Rojo, Álvaro
2016-02-10
For a network, the accomplishment of its functions despite perturbations is called robustness. Although this property has been extensively studied, in most cases, the network is modified by removing nodes. In our approach, it is no longer perturbed by site percolation, but evolves after site invasion. The process transforming resident/healthy nodes into invader/mutant/diseased nodes is described by the Moran model. We explore the sources of robustness (or its counterpart, the propensity to spread favourable innovations) of the US high-voltage power grid network, the Internet2 academic network, and the C. elegans connectome. We compare them to three modular and non-modular benchmark networks, and samples of one thousand random networks with the same degree distribution. It is found that, contrary to what happens with networks of small order, fixation probability and robustness are poorly correlated with most of standard statistics, but they depend strongly on the degree distribution. While community detection techniques are able to detect the existence of a central core in Internet2, they are not effective in detecting hierarchical structures whose topological complexity arises from the repetition of a few rules. Box counting dimension and Rent's rule are applied to show a subtle trade-off between topological and wiring complexity.
Alcalde Cuesta, Fernando; González Sequeiros, Pablo; Lozano Rojo, Álvaro
2016-01-01
For a network, the accomplishment of its functions despite perturbations is called robustness. Although this property has been extensively studied, in most cases, the network is modified by removing nodes. In our approach, it is no longer perturbed by site percolation, but evolves after site invasion. The process transforming resident/healthy nodes into invader/mutant/diseased nodes is described by the Moran model. We explore the sources of robustness (or its counterpart, the propensity to spread favourable innovations) of the US high-voltage power grid network, the Internet2 academic network, and the C. elegans connectome. We compare them to three modular and non-modular benchmark networks, and samples of one thousand random networks with the same degree distribution. It is found that, contrary to what happens with networks of small order, fixation probability and robustness are poorly correlated with most of standard statistics, but they depend strongly on the degree distribution. While community detection techniques are able to detect the existence of a central core in Internet2, they are not effective in detecting hierarchical structures whose topological complexity arises from the repetition of a few rules. Box counting dimension and Rent’s rule are applied to show a subtle trade-off between topological and wiring complexity. PMID:26861189
McCowan, Brenda; Beisner, Brianne A.; Capitanio, John P.; Jackson, Megan E.; Cameron, Ashley N.; Seil, Shannon; Atwill, Edward R.; Fushing, Hsieh
2011-01-01
Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups. PMID:21857922
McCowan, Brenda; Beisner, Brianne A; Capitanio, John P; Jackson, Megan E; Cameron, Ashley N; Seil, Shannon; Atwill, Edward R; Fushing, Hsieh
2011-01-01
Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups.
On the Evolution of Behaviors through Embodied Imitation.
Erbas, Mehmet D; Bull, Larry; Winfield, Alan F T
2015-01-01
This article describes research in which embodied imitation and behavioral adaptation are investigated in collective robotics. We model social learning in artificial agents with real robots. The robots are able to observe and learn each others' movement patterns using their on-board sensors only, so that imitation is embodied. We show that the variations that arise from embodiment allow certain behaviors that are better adapted to the process of imitation to emerge and evolve during multiple cycles of imitation. As these behaviors are more robust to uncertainties in the real robots' sensors and actuators, they can be learned by other members of the collective with higher fidelity. Three different types of learned-behavior memory have been experimentally tested to investigate the effect of memory capacity on the evolution of movement patterns, and results show that as the movement patterns evolve through multiple cycles of imitation, selection, and variation, the robots are able to, in a sense, agree on the structure of the behaviors that are imitated.
Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks
Albergante, Luca; Blow, J Julian; Newman, Timothy J
2014-01-01
The gene regulatory network (GRN) is the central decision‐making module of the cell. We have developed a theory called Buffered Qualitative Stability (BQS) based on the hypothesis that GRNs are organised so that they remain robust in the face of unpredictable environmental and evolutionary changes. BQS makes strong and diverse predictions about the network features that allow stable responses under arbitrary perturbations, including the random addition of new connections. We show that the GRNs of E. coli, M. tuberculosis, P. aeruginosa, yeast, mouse, and human all verify the predictions of BQS. BQS explains many of the small- and large‐scale properties of GRNs, provides conditions for evolvable robustness, and highlights general features of transcriptional response. BQS is severely compromised in a human cancer cell line, suggesting that loss of BQS might underlie the phenotypic plasticity of cancer cells, and highlighting a possible sequence of GRN alterations concomitant with cancer initiation. DOI: http://dx.doi.org/10.7554/eLife.02863.001 PMID:25182846
Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks.
Albergante, Luca; Blow, J Julian; Newman, Timothy J
2014-09-02
The gene regulatory network (GRN) is the central decision-making module of the cell. We have developed a theory called Buffered Qualitative Stability (BQS) based on the hypothesis that GRNs are organised so that they remain robust in the face of unpredictable environmental and evolutionary changes. BQS makes strong and diverse predictions about the network features that allow stable responses under arbitrary perturbations, including the random addition of new connections. We show that the GRNs of E. coli, M. tuberculosis, P. aeruginosa, yeast, mouse, and human all verify the predictions of BQS. BQS explains many of the small- and large-scale properties of GRNs, provides conditions for evolvable robustness, and highlights general features of transcriptional response. BQS is severely compromised in a human cancer cell line, suggesting that loss of BQS might underlie the phenotypic plasticity of cancer cells, and highlighting a possible sequence of GRN alterations concomitant with cancer initiation. Copyright © 2014, Albergante et al.
Developmental mechanisms underlying variable, invariant and plastic phenotypes
Abley, Katie; Locke, James C. W.; Leyser, H. M. Ottoline
2016-01-01
Background Discussions of phenotypic robustness often consider scenarios where invariant phenotypes are optimal and assume that developmental mechanisms have evolved to buffer the phenotypes of specific traits against stochastic and environmental perturbations. However, plastic plant phenotypes that vary between environments or variable phenotypes that vary stochastically within an environment may also be advantageous in some scenarios. Scope Here the conditions under which invariant, plastic and variable phenotypes of specific traits may confer a selective advantage in plants are examined. Drawing on work from microbes and multicellular organisms, the mechanisms that may give rise to each type of phenotype are discussed. Conclusion In contrast to the view of robustness as being the ability of a genotype to produce a single, invariant phenotype, changes in a phenotype in response to the environment, or phenotypic variability within an environment, may also be delivered consistently (i.e. robustly). Thus, for some plant traits, mechanisms have probably evolved to produce plasticity or variability in a reliable manner. PMID:27072645
Scale dependence of deuteron electrodisintegration
NASA Astrophysics Data System (ADS)
More, S. N.; Bogner, S. K.; Furnstahl, R. J.
2017-11-01
Background: Isolating nuclear structure properties from knock-out reactions in a process-independent manner requires a controlled factorization, which is always to some degree scale and scheme dependent. Understanding this dependence is important for robust extractions from experiment, to correctly use the structure information in other processes, and to understand the impact of approximations for both. Purpose: We seek insight into scale dependence by exploring a model calculation of deuteron electrodisintegration, which provides a simple and clean theoretical laboratory. Methods: By considering various kinematic regions of the longitudinal structure function, we can examine how the components—the initial deuteron wave function, the current operator, and the final-state interactions (FSIs)—combine at different scales. We use the similarity renormalization group to evolve each component. Results: When evolved to different resolutions, the ingredients are all modified, but how they combine depends strongly on the kinematic region. In some regions, for example, the FSIs are largely unaffected by evolution, while elsewhere FSIs are greatly reduced. For certain kinematics, the impulse approximation at a high renormalization group resolution gives an intuitive picture in terms of a one-body current breaking up a short-range correlated neutron-proton pair, although FSIs distort this simple picture. With evolution to low resolution, however, the cross section is unchanged but a very different and arguably simpler intuitive picture emerges, with the evolved current efficiently represented at low momentum through derivative expansions or low-rank singular value decompositions. Conclusions: The underlying physics of deuteron electrodisintegration is scale dependent and not just kinematics dependent. As a result, intuition about physics such as the role of short-range correlations or D -state mixing in particular kinematic regimes can be strongly scale dependent. Understanding this dependence is crucial in making use of extracted properties.
A model to assess the Mars Telecommunications Network relay robustness
NASA Technical Reports Server (NTRS)
Girerd, Andre R.; Meshkat, Leila; Edwards, Charles D., Jr.; Lee, Charles H.
2005-01-01
The relatively long mission durations and compatible radio protocols of current and projected Mars orbiters have enabled the gradual development of a heterogeneous constellation providing proximity communication services for surface assets. The current and forecasted capability of this evolving network has reached the point that designers of future surface missions consider complete dependence on it. Such designers, along with those architecting network requirements, have a need to understand the robustness of projected communication service. A model has been created to identify the robustness of the Mars Network as a function of surface location and time. Due to the decade-plus time horizon considered, the network will evolve, with emerging productive nodes and nodes that cease or fail to contribute. The model is a flexible framework to holistically process node information into measures of capability robustness that can be visualized for maximum understanding. Outputs from JPL's Telecom Orbit Analysis Simulation Tool (TOAST) provide global telecom performance parameters for current and projected orbiters. Probabilistic estimates of orbiter fuel life are derived from orbit keeping burn rates, forecasted maneuver tasking, and anomaly resolution budgets. Orbiter reliability is estimated probabilistically. A flexible scheduling framework accommodates the projected mission queue as well as potential alterations.
Encouraging Reactivity to Create Robust Machines
2013-07-01
Performance Evaluation and Benchmarking of Intelligent Systems, 113 137. Baldwin, J. (1896). A new factor in evolution. The American Naturalist, 30(355...Once more unto the breach: Co evolving a robot and its simulator. In Proceed ings of the international conference on artifical life (alife9) (pp.57...Pfeifer, R. (2003). Evolving complete agents using artificial ontogeny. In (pp. 237 258). Springer Verlag. Brooks, R. (1994). Artifical life and
Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso; Elena, Santiago F
2009-01-01
Background Understanding the molecular mechanisms plants have evolved to adapt their biological activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a network analysis of genome-wide expression data combined with reverse-engineering network modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory network is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes. Results We show that the A. thaliana regulatory network has the characteristic properties of hierarchical networks. We successfully applied our quantitative network model to predict the full transcriptome of the plant for a set of microarray experiments not included in the training dataset. We also used our model to analyze the robustness in expression levels conferred by network motifs such as the coherent feed-forward loop. In addition, the meta-analysis presented here has allowed us to identify regulatory and robust genetic structures. Conclusions These data suggest that A. thaliana has evolved high connectivity in terms of transcriptional regulation among cellular functions involved in response and adaptation to changing environments, while gene networks constitutively expressed or less related to stress response are characterized by a lower connectivity. Taken together, these findings suggest conserved regulatory strategies that have been selected during the evolutionary history of this eukaryote. PMID:19754933
Transhydrogenase Promotes the Robustness and Evolvability of E. coli Deficient in NADPH Production
Chou, Hsin-Hung; Marx, Christopher J.; Sauer, Uwe
2015-01-01
Metabolic networks revolve around few metabolites recognized by diverse enzymes and involved in myriad reactions. Though hub metabolites are considered as stepping stones to facilitate the evolutionary expansion of biochemical pathways, changes in their production or consumption often impair cellular physiology through their system-wide connections. How does metabolism endure perturbations brought immediately by pathway modification and restore hub homeostasis in the long run? To address this question we studied laboratory evolution of pathway-engineered Escherichia coli that underproduces the redox cofactor NADPH on glucose. Literature suggests multiple possibilities to restore NADPH homeostasis. Surprisingly, genetic dissection of isolates from our twelve evolved populations revealed merely two solutions: (1) modulating the expression of membrane-bound transhydrogenase (mTH) in every population; (2) simultaneously consuming glucose with acetate, an unfavored byproduct normally excreted during glucose catabolism, in two subpopulations. Notably, mTH displays broad phylogenetic distribution and has also played a predominant role in laboratory evolution of Methylobacterium extorquens deficient in NADPH production. Convergent evolution of two phylogenetically and metabolically distinct species suggests mTH as a conserved buffering mechanism that promotes the robustness and evolvability of metabolism. Moreover, adaptive diversification via evolving dual substrate consumption highlights the flexibility of physiological systems to exploit ecological opportunities. PMID:25715029
Krupnik, Tomasz; Kotabová, Eva; van Bezouwen, Laura S.; Mazur, Radosław; Garstka, Maciej; Nixon, Peter J.; Barber, James; Kaňa, Radek; Boekema, Egbert J.; Kargul, Joanna
2013-01-01
Members of the rhodophytan order Cyanidiales are unique among phototrophs in their ability to live in extremely low pH levels and moderately high temperatures. The photosynthetic apparatus of the red alga Cyanidioschyzon merolae represents an intermediate type between cyanobacteria and higher plants, suggesting that this alga may provide the evolutionary link between prokaryotic and eukaryotic phototrophs. Although we now have a detailed structural model of photosystem II (PSII) from cyanobacteria at an atomic resolution, no corresponding structure of the eukaryotic PSII complex has been published to date. Here we report the isolation and characterization of a highly active and robust dimeric PSII complex from C. merolae. We show that this complex is highly stable across a range of extreme light, temperature, and pH conditions. By measuring fluorescence quenching properties of the isolated C. merolae PSII complex, we provide the first direct evidence of pH-dependent non-photochemical quenching in the red algal PSII reaction center. This type of quenching, together with high zeaxanthin content, appears to underlie photoprotection mechanisms that are efficiently employed by this robust natural water-splitting complex under excess irradiance. In order to provide structural details of this eukaryotic form of PSII, we have employed electron microscopy and single particle analyses to obtain a 17 Å map of the C. merolae PSII dimer in which we locate the position of the protein mass corresponding to the additional extrinsic protein stabilizing the oxygen-evolving complex, PsbQ′. We conclude that this lumenal subunit is present in the vicinity of the CP43 protein, close to the membrane plane. PMID:23775073
Epigenomics and the concept of degeneracy in biological systems
Mason, Paul H.; Barron, Andrew B.
2014-01-01
Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy—referring to the multiple pathways that a system recruits to achieve functional plasticity—is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability. PMID:24335757
Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking
Xue, Ming; Yang, Hua; Zheng, Shibao; Zhou, Yi; Yu, Zhenghua
2014-01-01
To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks. PMID:24549252
Criticality Is an Emergent Property of Genetic Networks that Exhibit Evolvability
Torres-Sosa, Christian; Huang, Sui; Aldana, Maximino
2012-01-01
Accumulating experimental evidence suggests that the gene regulatory networks of living organisms operate in the critical phase, namely, at the transition between ordered and chaotic dynamics. Such critical dynamics of the network permits the coexistence of robustness and flexibility which are necessary to ensure homeostatic stability (of a given phenotype) while allowing for switching between multiple phenotypes (network states) as occurs in development and in response to environmental change. However, the mechanisms through which genetic networks evolve such critical behavior have remained elusive. Here we present an evolutionary model in which criticality naturally emerges from the need to balance between the two essential components of evolvability: phenotype conservation and phenotype innovation under mutations. We simulated the Darwinian evolution of random Boolean networks that mutate gene regulatory interactions and grow by gene duplication. The mutating networks were subjected to selection for networks that both (i) preserve all the already acquired phenotypes (dynamical attractor states) and (ii) generate new ones. Our results show that this interplay between extending the phenotypic landscape (innovation) while conserving the existing phenotypes (conservation) suffices to cause the evolution of all the networks in a population towards criticality. Furthermore, the networks produced by this evolutionary process exhibit structures with hubs (global regulators) similar to the observed topology of real gene regulatory networks. Thus, dynamical criticality and certain elementary topological properties of gene regulatory networks can emerge as a byproduct of the evolvability of the phenotypic landscape. PMID:22969419
Vertical Transmission of Social Roles Drives Resilience to Poaching in Elephant Networks.
Goldenberg, Shifra Z; Douglas-Hamilton, Iain; Wittemyer, George
2016-01-11
Network resilience to perturbation is fundamental to functionality in systems ranging from synthetic communication networks to evolved social organization [1]. While theoretical work offers insight into causes of network robustness, examination of natural networks can identify evolved mechanisms of resilience and how they are related to the selective pressures driving structure. Female African elephants (Loxodonta africana) exhibit complex social networks with node heterogeneity in which older individuals serve as connectivity hubs [2, 3]. Recent ivory poaching targeting older elephants in a well-studied population has mirrored the targeted removal of highly connected nodes in the theoretical literature that leads to structural collapse [4, 5]. Here we tested the response of this natural network to selective knockouts. We find that the hierarchical network topology characteristic of elephant societies was highly conserved across the 16-year study despite ∼70% turnover in individual composition of the population. At a population level, the oldest available individuals persisted to fill socially central positions in the network. For analyses using known mother-daughter pairs, social positions of daughters during the disrupted period were predicted by those of their mothers in years prior, were unrelated to individual histories of family mortality, and were actively built. As such, daughters replicated the social network roles of their mothers, driving the observed network resilience. Our study provides a rare bridge between network theory and an evolved system, demonstrating social redundancy to be the mechanism by which resilience to perturbation occurred in this socially advanced species. Copyright © 2016 Elsevier Ltd. All rights reserved.
Characterizing the evolution of climate networks
NASA Astrophysics Data System (ADS)
Tupikina, L.; Rehfeld, K.; Molkenthin, N.; Stolbova, V.; Marwan, N.; Kurths, J.
2014-06-01
Complex network theory has been successfully applied to understand the structural and functional topology of many dynamical systems from nature, society and technology. Many properties of these systems change over time, and, consequently, networks reconstructed from them will, too. However, although static and temporally changing networks have been studied extensively, methods to quantify their robustness as they evolve in time are lacking. In this paper we develop a theory to investigate how networks are changing within time based on the quantitative analysis of dissimilarities in the network structure. Our main result is the common component evolution function (CCEF) which characterizes network development over time. To test our approach we apply it to several model systems, Erdős-Rényi networks, analytically derived flow-based networks, and transient simulations from the START model for which we control the change of single parameters over time. Then we construct annual climate networks from NCEP/NCAR reanalysis data for the Asian monsoon domain for the time period of 1970-2011 CE and use the CCEF to characterize the temporal evolution in this region. While this real-world CCEF displays a high degree of network persistence over large time lags, there are distinct time periods when common links break down. This phasing of these events coincides with years of strong El Niño/Southern Oscillation phenomena, confirming previous studies. The proposed method can be applied for any type of evolving network where the link but not the node set is changing, and may be particularly useful to characterize nonstationary evolving systems using complex networks.
Cross Cutting Structural Design for Exploration Systems
NASA Technical Reports Server (NTRS)
Semmes, Edmund B.
2007-01-01
The challenge of our new National Space Policy and NASA's Vision for Space Exploration (VSE) is keyed to the development of more effective space access and transportation systems. Optimizing in-space systems through innovative cross cutting structural designs that reduce mass, combine functional requirements and improve performance can significantly advance spacecraft designs to meet the ever growing demands of our new National Space Policy. Dependence on limited structural designs is no longer an option. We must create robust materials, forms, function and evolvable systems. We must advance national policy objectives in the design, development, test and operation of multi-billion dollar new generation crew capsules by enabling them to evolve in meeting the requirements of long duration missions to the moon and mars. This paper discusses several current issues and major design drivers for consideration in structural design of advanced spacecraft systems. Approaches to addressing these multifunctional requirements is presented as well as a discussion on utilizing Functional Analysis System Technique (FAST) in developing cross cutting structural designs for future spacecraft. It will be shown how easy it is to deploy such techniques in any conceptual architecture definition or ongoing preliminary design. As experts in merging mission, safety and life support requirements of the frail human existence into robust vehicle and habitat design, we will conquer the final frontier, harness new resources and develop life giving technologies for mankind through more innovative designs. The rocket equation tells us that a reduction in mass optimizes our propulsive results. Primary and secondary structural elements provide for the containment of gases, fluids and solids; translate and sustain loads/impacts; conduct/radiate thermal energy; shield from the harmful effects of radiation; provide for grounding/bonding of electrical power systems; compartmentalize operational functions; and provide physical interface with multiple systems. How can we redefine, combine, substitute, rearrange and otherwise modify our structural systems to reduce mass? New technologies will be needed to fill knowledge gaps and propagate new design methods. Such an integrated process is paramount in maintaining U.S. leadership and in executing our national policy goals. The cross cutting process can take many forms, but all forms will have a positive affect on the demanding design environment through initial radical thinking. The author will illustrate such cross cutting results achievable through a formal process called FAST. The FAST example will be used to show how a multifunctional structural system concept for long duration spacecraft might be generated.
RNA structure in splicing: An evolutionary perspective.
Lin, Chien-Ling; Taggart, Allison J; Fairbrother, William G
2016-09-01
Pre-mRNA splicing is a key post-transcriptional regulation process in which introns are excised and exons are ligated together. A novel class of structured intron was recently discovered in fish. Simple expansions of complementary AC and GT dimers at opposite boundaries of an intron were found to form a bridging structure, thereby enforcing correct splice site pairing across the intron. In some fish introns, the RNA structures are strong enough to bypass the need of regulatory protein factors for splicing. Here, we discuss the prevalence and potential functions of highly structured introns. In humans, structured introns usually arise through the co-occurrence of C and G-rich repeats at intron boundaries. We explore the potentially instructive example of the HLA receptor genes. In HLA pre-mRNA, structured introns flank the exons that encode the highly polymorphic β sheet cleft, making the processing of the transcript robust to variants that disrupt splicing factor binding. While selective forces that have shaped HLA receptor are fairly atypical, numerous other highly polymorphic genes that encode receptors contain structured introns. Finally, we discuss how the elevated mutation rate associated with the simple repeats that often compose structured intron can make structured introns themselves rapidly evolving elements.
Huang, He; Sarai, Akinori
2012-12-01
The evolvability of proteins is not only restricted by functional and structural importance, but also by other factors such as gene duplication, protein stability, and an organism's robustness. Recently, intrinsically disordered proteins (IDPs)/regions (IDRs) have been suggested to play a role in facilitating protein evolution. However, the mechanisms by which this occurs remain largely unknown. To address this, we have systematically analyzed the relationship between the evolvability, stability, and function of IDPs/IDRs. Evolutionary analysis shows that more recently emerged IDRs have higher evolutionary rates with more functional constraints relaxed (or experiencing more positive selection), and that this may have caused accelerated evolution in the flanking regions and in the whole protein. A systematic analysis of observed stability changes due to single amino acid mutations in IDRs and ordered regions shows that while most mutations induce a destabilizing effect in proteins, mutations in IDRs cause smaller stability changes than in ordered regions. The weaker impact of mutations in IDRs on protein stability may have advantages for protein evolvability in the gain of new functions. Interestingly, however, an analysis of functional motifs in the PROSITE and ELM databases showed that motifs in IDRs are more conserved, characterized by smaller entropy and lower evolutionary rate, than in ordered regions. This apparently opposing evolutionary effect may be partly due to the flexible nature of motifs in IDRs, which require some key amino acid residues to engage in tighter interactions with other molecules. Our study suggests that the unique conformational and thermodynamic characteristics of IDPs/IDRs play an important role in the evolvability of proteins to gain new functions. Copyright © 2012 Elsevier Ltd. All rights reserved.
2013-01-01
Background Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured. Methods We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima. Results and conclusions Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions. PMID:24565020
Functional amyloids in bacteria.
Romero, Diego; Kolter, Roberto
2014-06-01
The term amyloidosis is used to refer to a family of pathologies altering the homeostasis of human organs. Despite having a name that alludes to starch content, the amyloid accumulations are made up of proteins that polymerize as long and rigid fibers. Amyloid proteins vary widely with respect to their amino acid sequences but they share similarities in their quaternary structure; the amyloid fibers are enriched in β-sheets arranged perpendicular to the axis of the fiber. This structural feature provides great robustness, remarkable stability, and insolubility. In addition, amyloid proteins specifically stain with certain dyes such as Congo red and thioflavin-T. The aggregation into amyloid fibers, however, it is not restricted to pathogenic processes, rather it seems to be widely distributed among proteins and polypeptides. Amyloid fibers are present in insects, fungi and bacteria, and they are important in maintaining the homeostasis of the organism. Such findings have motivated the use of the term "functional amyloid" to differentiate these amyloid proteins from their toxic siblings. This review focuses on systems that have evolved in bacteria that control the expression and assembly of amyloid proteins on cell surfaces, such that the robustness of amyloid proteins are used towards a beneficial end. Copyright© by the Spanish Society for Microbiology and Institute for Catalan Studies.
Perturbation propagation in random and evolved Boolean networks
NASA Astrophysics Data System (ADS)
Fretter, Christoph; Szejka, Agnes; Drossel, Barbara
2009-03-01
In this paper, we investigate the propagation of perturbations in Boolean networks by evaluating the Derrida plot and its modifications. We show that even small random Boolean networks agree well with the predictions of the annealed approximation, but nonrandom networks show a very different behaviour. We focus on networks that were evolved for high dynamical robustness. The most important conclusion is that the simple distinction between frozen, critical and chaotic networks is no longer useful, since such evolved networks can display the properties of all three types of networks. Furthermore, we evaluate a simplified empirical network and show how its specific state space properties are reflected in the modified Derrida plots.
Richards, Christopher; Albin, John S; Demir, Özlem; Shaban, Nadine M; Luengas, Elizabeth M; Land, Allison M; Anderson, Brett D; Holten, John R; Anderson, John S; Harki, Daniel A; Amaro, Rommie E; Harris, Reuben S
2015-12-01
APOBEC3 family DNA cytosine deaminases provide overlapping defenses against pathogen infections. However, most viruses have elaborate evasion mechanisms such as the HIV-1 Vif protein, which subverts cellular CBF-β and a polyubiquitin ligase complex to neutralize these enzymes. Despite advances in APOBEC3 and Vif biology, a full understanding of this direct host-pathogen conflict has been elusive. We combine virus adaptation and computational studies to interrogate the APOBEC3F-Vif interface and build a robust structural model. A recurring compensatory amino acid substitution from adaptation experiments provided an initial docking constraint, and microsecond molecular dynamic simulations optimized interface contacts. Virus infectivity experiments validated a long-lasting electrostatic interaction between APOBEC3F E289 and HIV-1 Vif R15. Taken together with mutagenesis results, we propose a wobble model to explain how HIV-1 Vif has evolved to bind different APOBEC3 enzymes and, more generally, how pathogens may evolve to escape innate host defenses. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Motor cortex embeds muscle-like commands in an untangled population response
Russo, Abigail A.; Bittner, Sean R.; Perkins, Sean M.; Seely, Jeffrey S.; London, Brian M.; Lara, Antonio H.; Miri, Andrew; Marshall, Najja J.; Kohn, Adam; Jessell, Thomas M.; Abbott, Laurence F.; Cunningham, John P.; Churchland, Mark M.
2018-01-01
Summary Primate motor cortex projects to spinal interneurons and motor neurons, suggesting that motor cortex activity may be dominated by muscle-like commands. Extensive observations during reaching lend support to this view, but evidence remains ambiguous and much-debated. To provide a different perspective, we employed a novel behavioral paradigm that affords extensive comparison between time-evolving neural and muscle activity. We found that single motor cortex neurons displayed many muscle-like properties, but the structure of population activity was not muscle-like. Unlike muscle activity, neural activity was structured to avoid ‘tangling’: moments where similar activity patterns led to dissimilar future patterns. Avoidance of tangling was present across tasks and species. Network models revealed a potential reason for this consistent feature: low tangling confers noise robustness. Finally, we were able to predict motor cortex activity from muscle activity alone, by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low tangling. PMID:29398358
Sarkar, Kanchan; Sharma, Rahul; Bhattacharyya, S P
2010-03-09
A density matrix based soft-computing solution to the quantum mechanical problem of computing the molecular electronic structure of fairly long polythiophene (PT) chains is proposed. The soft-computing solution is based on a "random mutation hill climbing" scheme which is modified by blending it with a deterministic method based on a trial single-particle density matrix [P((0))(R)] for the guessed structural parameters (R), which is allowed to evolve under a unitary transformation generated by the Hamiltonian H(R). The Hamiltonian itself changes as the geometrical parameters (R) defining the polythiophene chain undergo mutation. The scale (λ) of the transformation is optimized by making the energy [E(λ)] stationary with respect to λ. The robustness and the performance levels of variants of the algorithm are analyzed and compared with those of other derivative free methods. The method is further tested successfully with optimization of the geometry of bipolaron-doped long PT chains.
Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity
Effenberger, Felix; Jost, Jürgen; Levina, Anna
2015-01-01
Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network. PMID:26335425
In silico modeling of the yeast protein and protein family interaction network
NASA Astrophysics Data System (ADS)
Goh, K.-I.; Kahng, B.; Kim, D.
2004-03-01
Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.
NASA Astrophysics Data System (ADS)
Esposito, C.; Bianchi-Fasani, G.; Martino, S.; Scarascia-Mugnozza, G.
2013-10-01
This paper focuses on a study aimed at defining the role of geological-structural setting and Quaternary morpho-structural evolution on the onset and development of a deep-seated gravitational slope deformation which affects the western slope of Mt. Genzana ridge (Central Apennines, Italy). This case history is particularly significant as it comprises several aspects of such gravitational processes both in general terms and with particular reference to the Apennines. In fact: i) the morpho-structural setting is representative of widespread conditions in Central Apennines; ii) the deforming slope partially evolved in a large rockslide-avalanche; iii) the deformational process provides evidence of an ongoing state of activity; iv) the rockslide-avalanche debris formed a stable natural dam, thus implying significant variations in the morphologic, hydraulic and hydrogeological setting; v) the gravitational deformation as well as the rockslide-avalanche reveal a strong structural control. The main study activities were addressed to define a detailed geological model of the gravity-driven process, by means of geological, structural, geomorphological and geomechanical surveys. As a result, a robust hypothesis about the kinematics of the process was possible, with particular reference to the identification of geological-structural constraints. The process, in fact, involves a specific section of the slope exactly where a dextral transtensional structure is present, thus implying local structural conditions that favor sliding processes: the rock mass is intensively jointed by high angle discontinuity sets and the bedding attitude is quite parallel to the slope angle. Within this frame the gravitational process can be classified as a structurally constrained translational slide, locally evolved into a rockslide-avalanche. The activation of such a deformation can be in its turn related to the Quaternary morphological evolution of the area, which was affected by a significant topographic stress increase, testified by stratigraphic and morphologic evidence.
Ultra-robust high-field magnetization plateau and supersolidity in bond-frustrated MnCr2S4
Tsurkan, Vladimir; Zherlitsyn, Sergei; Prodan, Lilian; Felea, Viorel; Cong, Pham Thanh; Skourski, Yurii; Wang, Zhe; Deisenhofer, Joachim; von Nidda, Hans-Albrecht Krug; Wosnitza, Joahim; Loidl, Alois
2017-01-01
Frustrated magnets provide a promising avenue for realizing exotic quantum states of matter, such as spin liquids and spin ice or complex spin molecules. Under an external magnetic field, frustrated magnets can exhibit fractional magnetization plateaus related to definite spin patterns stabilized by field-induced lattice distortions. Magnetization and ultrasound experiments in MnCr2S4 up to 60 T reveal two fascinating features: (i) an extremely robust magnetization plateau with an unusual spin structure and (ii) two intermediate phases, indicating possible realizations of supersolid phases. The magnetization plateau characterizes fully polarized chromium moments, without any contributions from manganese spins. At 40 T, the middle of the plateau, a regime evolves, where sound waves propagate almost without dissipation. The external magnetic field exactly compensates the Cr–Mn exchange field and decouples Mn and Cr sublattices. In analogy to predictions of quantum lattice-gas models, the changes of the spin order of the manganese ions at the phase boundaries of the magnetization plateau are interpreted as transitions to supersolid phases. PMID:28345038
Madaoui, Hocine; Guerois, Raphaël
2008-01-01
Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of protein–protein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein–protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact. PMID:18511568
NASA Technical Reports Server (NTRS)
Fuerst, Steven V.; Mizuno, Yosuke; Nishikawa, Ken-Ichi; Wu, Kinwah
2007-01-01
We have calculated the emission from relativistic flows in black hole systems using a fully general relativistic radiative transfer, with flow structures obtained by general relativistic magnetohydrodynamic simulations. We consider thermal free-free emission and thermal synchrotron emission. Bright filament-like features are found protruding (visually) from the accretion disk surface, which are enhancements of synchrotron emission when the magnetic field is roughly aligned with the line-of-sight in the co-moving frame. The features move back and forth as the accretion flow evolves, but their visibility and morphology are robust. We propose that variations and location drifts of the features are responsible for certain X-ray quasi-periodic oscillations (QPOs) observed in black-hole X-ray binaries.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fuerst, Steven V.; /KIPAC, Menlo Park; Mizuno, Yosuke
2007-01-05
We calculate the emission from relativistic flows in black hole systems using a fully general relativistic radiative transfer formulation, with flow structures obtained by general relativistic magneto-hydrodynamic simulations. We consider thermal free-free emission and thermal synchrotron emission. Bright filament-like features protrude (visually) from the accretion disk surface, which are enhancements of synchrotron emission where the magnetic field roughly aligns with the line-of-sight in the co-moving frame. The features move back and forth as the accretion flow evolves, but their visibility and morphology are robust. We propose that variations and drifts of the features produce certain X-ray quasi-periodic oscillations (QPOs) observedmore » in black-hole X-ray binaries.« less
Adaptive estimation of the log fluctuating conductivity from tracer data at the Cape Cod Site
Deng, F.W.; Cushman, J.H.; Delleur, J.W.
1993-01-01
An adaptive estimation scheme is used to obtain the integral scale and variance of the log-fluctuating conductivity at the Cape Cod site based on the fast Fourier transform/stochastic model of Deng et al. (1993) and a Kalmanlike filter. The filter incorporates prior estimates of the unknown parameters with tracer moment data to adaptively obtain improved estimates as the tracer evolves. The results show that significant improvement in the prior estimates of the conductivity can lead to substantial improvement in the ability to predict plume movement. The structure of the covariance function of the log-fluctuating conductivity can be identified from the robustness of the estimation. Both the longitudinal and transverse spatial moment data are important to the estimation.
The Baculum was Gained and Lost Multiple Times during Mammalian Evolution.
Schultz, Nicholas G; Lough-Stevens, Michael; Abreu, Eric; Orr, Teri; Dean, Matthew D
2016-10-01
The rapid evolution of male genitalia is a nearly ubiquitous pattern across sexually reproducing organisms, likely driven by the evolutionary pressures of male-male competition, male-female interactions, and perhaps pleiotropic effects of selection. The penis of many mammalian species contains a baculum, a bone that displays astonishing morphological diversity. The evolution of baculum size and shape does not consistently correlate with any aspects of mating system, hindering our understanding of the evolutionary processes affecting it. One potential explanation for the lack of consistent comparative results is that the baculum is not actually a homologous structure. If the baculum of different groups evolved independently, then the assumption of homology inherent in comparative studies is violated. Here, we specifically test this hypothesis by modeling the presence/absence of bacula of 954 mammalian species across a well-established phylogeny and show that the baculum evolved a minimum of nine times, and was lost a minimum of ten times. Three different forms of bootstrapping show our results are robust to species sampling. Furthermore, groups with a baculum show evidence of higher rates of diversification. Our study offers an explanation for the inconsistent results in the literature, and provides insight into the evolution of this remarkable structure. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.
NASA Technical Reports Server (NTRS)
Koopmann, Gary H.; Lesieutre, George A.; Yoshikawa, Shoko; Chen, Weicheng; Fahnline, John B.; Pai, Suresh; Dershem, Brian
1996-01-01
In this presentation, the authors describe the design and fabrication processes for a PZT strain actuator that evolved during the initial stages of a research effort to synthesize and process intelligent, cost effective structures (SPICES). The actuator performance requirements were similar to those of conventional actuators, e.g., it had to be robust, highly efficient with adequate force and stroke, as lightweight as possible, and most importantly, affordable. Further, since the actuator was to be integrated within a composite structure, it had to be compatible with the host material and easily embeddable during the fabrication process. In control applications employing strain devices as actuators, a good bond between this actuator and host material is critical to their successful operation. This criterion is often difficult to achieve when attempting to join ceramics with metals or polymers with dissimilar properties such as Young's moduli, thermal expansion coefficients, etc. One unique feature of the actuator design that evolved in this project is that the need for direct bonding between the PZT ceramic and polymers was circumvented, i.e. the strain transfer to the host material was achieved via a frame surrounding the ceramic. Consequently, the frame material could be selected (or coated) for compatibility with the host material. A second feature is that the frame enclosed a co-fired, multilayered, PZT stack that was used to minimize the voltage requirements while maximizing the output strain.
The topological requirements for robust perfect adaptation in networks of any size.
Araujo, Robyn P; Liotta, Lance A
2018-05-01
Robustness, and the ability to function and thrive amid changing and unfavorable environments, is a fundamental requirement for living systems. Until now it has been an open question how large and complex biological networks can exhibit robust behaviors, such as perfect adaptation to a variable stimulus, since complexity is generally associated with fragility. Here we report that all networks that exhibit robust perfect adaptation (RPA) to a persistent change in stimulus are decomposable into well-defined modules, of which there exist two distinct classes. These two modular classes represent a topological basis for all RPA-capable networks, and generate the full set of topological realizations of the internal model principle for RPA in complex, self-organizing, evolvable bionetworks. This unexpected result supports the notion that evolutionary processes are empowered by simple and scalable modular design principles that promote robust performance no matter how large or complex the underlying networks become.
Are genetically robust regulatory networks dynamically different from random ones?
NASA Astrophysics Data System (ADS)
Sevim, Volkan; Rikvold, Per Arne
We study a genetic regulatory network model developed to demonstrate that genetic robustness can evolve through stabilizing selection for optimal phenotypes. We report preliminary results on whether such selection could result in a reorganization of the state space of the system. For the chosen parameters, the evolution moves the system slightly toward the more ordered part of the phase diagram. We also find that strong memory effects cause the Derrida annealed approximation to give erroneous predictions about the model's phase diagram.
Genetic architecture and the evolution of sex.
Lohaus, Rolf; Burch, Christina L; Azevedo, Ricardo B R
2010-01-01
Theoretical investigations of the advantages of sex have tended to treat the genetic architecture of organisms as static and have not considered that genetic architecture might coevolve with reproductive mode. As a result, some potential advantages of sex may have been missed. Using a gene network model, we recently showed that recombination imposes selection for robustness to mutation and that negative epistasis can evolve as a by-product of this selection. These results motivated a detailed exploration of the mutational deterministic hypothesis, a hypothesis in which the advantage of sex depends critically on epistasis. We found that sexual populations do evolve higher mean fitness and lower genetic load than asexual populations at equilibrium, and, under moderate stabilizing selection and large population size, these equilibrium sexual populations resist invasion by asexuals. However, we found no evidence that these long- and short-term advantages to sex were explained by the negative epistasis that evolved in our experiments. The long-term advantage of sex was that sexual populations evolved a lower deleterious mutation rate, but this property was not sufficient to account for the ability of sexual populations to resist invasion by asexuals. The ability to resist asexual invasion was acquired simultaneously with an increase in recombinational robustness that minimized the cost of sex. These observations provide the first direct evidence that sexual reproduction does indeed select for conditions that favor its own maintenance. Furthermore, our results highlight the importance of considering a dynamic view of the genetic architecture to understand the evolution of sex and recombination.
Aziz, Ramy K; Monk, Jonathan M; Andrews, Kathleen A; Nhan, Jenny; Khaw, Valerie L; Wong, Hesper; Palsson, Bernhard O; Charusanti, Pep
2017-01-01
Most Escherichia coli strains are naturally unable to grow on 1,2-propanediol (PDO) as a sole carbon source. Recently, however, a K-12 descendent E. coli strain was evolved to grow on 1,2-PDO, and it was hypothesized that this evolved ability was dependent on the aldehyde dehydrogenase, AldA, which is highly conserved among members of the family Enterobacteriacea. To test this hypothesis, we first performed computational model simulation, which confirmed the essentiality of the aldA gene for 1,2-PDO utilization by the evolved PDO-degrading E. coli. Next, we deleted the aldA gene from the evolved strain, and this deletion was sufficient to abolish the evolved phenotype. On re-introducing the gene on a plasmid, the evolved phenotype was restored. These findings provide experimental evidence for the computationally predicted role of AldA in 1,2-PDO utilization, and represent a good example of E. coli robustness, demonstrated by the bacterial deployment of a generalist enzyme (here AldA) in multiple pathways to survive carbon starvation and to grow on a non-native substrate when no native carbon source is available. Copyright © 2016 Elsevier GmbH. All rights reserved.
Design principles for robust vesiculation in clathrin-mediated endocytosis
Hassinger, Julian E.; Oster, George; Drubin, David G.; Rangamani, Padmini
2017-01-01
A critical step in cellular-trafficking pathways is the budding of membranes by protein coats, which recent experiments have demonstrated can be inhibited by elevated membrane tension. The robustness of processes like clathrin-mediated endocytosis (CME) across a diverse range of organisms and mechanical environments suggests that the protein machinery in this process has evolved to take advantage of some set of physical design principles to ensure robust vesiculation against opposing forces like membrane tension. Using a theoretical model for membrane mechanics and membrane protein interaction, we have systematically investigated the influence of membrane rigidity, curvature induced by the protein coat, area covered by the protein coat, membrane tension, and force from actin polymerization on bud formation. Under low tension, the membrane smoothly evolves from a flat to budded morphology as the coat area or spontaneous curvature increases, whereas the membrane remains essentially flat at high tensions. At intermediate, physiologically relevant, tensions, the membrane undergoes a “snap-through instability” in which small changes in the coat area, spontaneous curvature or membrane tension cause the membrane to “snap” from an open, U-shape to a closed bud. This instability can be smoothed out by increasing the bending rigidity of the coat, allowing for successful budding at higher membrane tensions. Additionally, applied force from actin polymerization can bypass the instability by inducing a smooth transition from an open to a closed bud. Finally, a combination of increased coat rigidity and force from actin polymerization enables robust vesiculation even at high membrane tensions. PMID:28126722
Biomimetics on seed dispersal: survey and insights for space exploration.
Pandolfi, Camilla; Izzo, Dario
2013-06-01
Seeds provide the vital genetic link and dispersal agent between successive generations of plants. Without seed dispersal as a means of reproduction, many plants would quickly die out. Because plants lack any sort of mobility and remain in the same spot for their entire lives, they rely on seed dispersal to transport their offspring throughout the environment. This can be accomplished either collectively or individually; in any case as seeds ultimately abdicate their movement, they are at the mercy of environmental factors. Thus, seed dispersal strategies are characterized by robustness, adaptability, intelligence (both behavioral and morphological), and mass and energy efficiency (including the ability to utilize environmental sources of energy available): all qualities that advanced engineering systems aim at in general, and in particular those that need to enable complex endeavors such as space exploration. Plants evolved and adapted their strategy according to their environment, and taken together, they enclose many desirable characteristics that a space mission needs to have. Understanding in detail how plants control the development of seeds, fabricate structural components for their dispersal, build molecular machineries to keep seeds dormant up to the right moment and monitor the environment to release them at the right time could provide several solutions impacting current space mission design practices. It can lead to miniaturization, higher integration and packing efficiency, energy efficiency and higher autonomy and robustness. Consequently, there would appear to be good reasons for considering biomimetic solutions from plant kingdom when designing space missions, especially to other celestial bodies, where solid and liquid surfaces, atmosphere, etc constitute and are obviously parallel with the terrestrial environment where plants evolved. In this paper, we review the current state of biomimetics on seed dispersal to improve space mission design.
Advanced Space Flight and Environmental Concerns
NASA Technical Reports Server (NTRS)
Whitaker, A.
2001-01-01
The aerospace industry has conquered numerous environmental challenges during the last decade. The aerospace industry of today has evolved due in part to the environmental challenges, becoming stronger, more robust, learning to push the limits of technology, materials and manufacturing, and performing cutting edge engineering.
Motivation and Prospects for Spatio-spectral Interferometry in the Far-infrared
NASA Technical Reports Server (NTRS)
Leisawitz, David
2013-01-01
Consensus developed through a series of workshops, starting in 1998. Compelling science case for high angular resolution imaging and spectroscopy, and mission concepts. A robust plan - it has evolved over the years, but has consistently called for high resolution.
Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design
NASA Astrophysics Data System (ADS)
Schaffer, J. David
2015-06-01
Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.
HOT Faults", Fault Organization, and the Occurrence of the Largest Earthquakes
NASA Astrophysics Data System (ADS)
Carlson, J. M.; Hillers, G.; Archuleta, R. J.
2006-12-01
We apply the concept of "Highly Optimized Tolerance" (HOT) for the investigation of spatio-temporal seismicity evolution, in particular mechanisms associated with largest earthquakes. HOT provides a framework for investigating both qualitative and quantitative features of complex feedback systems that are far from equilibrium and punctuated by rare, catastrophic events. In HOT, robustness trade-offs lead to complexity and power laws in systems that are coupled to evolving environments. HOT was originally inspired by biology and engineering, where systems are internally very highly structured, through biological evolution or deliberate design, and perform in an optimum manner despite fluctuations in their surroundings. Though faults and fault systems are not designed in ways comparable to biological and engineered structures, feedback processes are responsible in a conceptually comparable way for the development, evolution and maintenance of younger fault structures and primary slip surfaces of mature faults, respectively. Hence, in geophysical applications the "optimization" approach is perhaps more aptly replaced by "organization", reflecting the distinction between HOT and random, disorganized configurations, and highlighting the importance of structured interdependencies that evolve via feedback among and between different spatial and temporal scales. Expressed in the terminology of the HOT concept, mature faults represent a configuration optimally organized for the release of strain energy; whereas immature, more heterogeneous fault networks represent intermittent, suboptimal systems that are regularized towards structural simplicity and the ability to generate large earthquakes more easily. We discuss fault structure and associated seismic response pattern within the HOT concept, and outline fundamental differences between this novel interpretation to more orthodox viewpoints like the criticality concept. The discussion is flanked by numerical simulations of a 2D fault model, where we investigate different feedback mechanisms and their effect on seismicity evolution. We introduce an approach to estimate the state of a fault and thus its capability of generating a large (system-wide) event assuming likely heterogeneous distributions of hypocenters and stresses, respectively.
Robustness analysis of elastoplastic structure subjected to double impulse
NASA Astrophysics Data System (ADS)
Kanno, Yoshihiro; Takewaki, Izuru
2016-11-01
The double impulse has extensively been used to evaluate the critical response of an elastoplastic structure against a pulse-type input, including near-fault earthquake ground motions. In this paper, we propose a robustness assessment method for elastoplastic single-degree-of-freedom structures subjected to the double impulse input. Uncertainties in the initial velocity of the input, as well as the natural frequency and the strength of the structure, are considered. As fundamental properties of the structural robustness, we show monotonicity of the robustness measure with respect to the natural frequency. In contrast, we show that robustness is not necessarily improved even if the structural strength is increased. Moreover, the robustness preference between two structures with different values of structural strength can possibly reverse when the performance requirement is changed.
NASA Astrophysics Data System (ADS)
Noirel, Josselin; Simonson, Thomas
2008-11-01
Following Kimura's neutral theory of molecular evolution [M. Kimura, The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983) (reprinted in 1986)], it has become common to assume that the vast majority of viable mutations of a gene confer little or no functional advantage. Yet, in silico models of protein evolution have shown that mutational robustness of sequences could be selected for, even in the context of neutral evolution. The evolution of a biological population can be seen as a diffusion on the network of viable sequences. This network is called a "neutral network." Depending on the mutation rate μ and the population size N, the biological population can evolve purely randomly (μN ≪1) or it can evolve in such a way as to select for sequences of higher mutational robustness (μN ≫1). The stringency of the selection depends not only on the product μN but also on the exact topology of the neutral network, the special arrangement of which was named "superfunnel." Even though the relation between mutation rate, population size, and selection was thoroughly investigated, a study of the salient topological features of the superfunnel that could affect the strength of the selection was wanting. This question is addressed in this study. We use two different models of proteins: on lattice and off lattice. We compare neutral networks computed using these models to random networks. From this, we identify two important factors of the topology that determine the stringency of the selection for mutationally robust sequences. First, the presence of highly connected nodes ("hubs") in the network increases the selection for mutationally robust sequences. Second, the stringency of the selection increases when the correlation between a sequence's mutational robustness and its neighbors' increases. The latter finding relates a global characteristic of the neutral network to a local one, which is attainable through experiments or molecular modeling.
Noirel, Josselin; Simonson, Thomas
2008-11-14
Following Kimura's neutral theory of molecular evolution [M. Kimura, The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983) (reprinted in 1986)], it has become common to assume that the vast majority of viable mutations of a gene confer little or no functional advantage. Yet, in silico models of protein evolution have shown that mutational robustness of sequences could be selected for, even in the context of neutral evolution. The evolution of a biological population can be seen as a diffusion on the network of viable sequences. This network is called a "neutral network." Depending on the mutation rate mu and the population size N, the biological population can evolve purely randomly (muN<1) or it can evolve in such a way as to select for sequences of higher mutational robustness (muN>1). The stringency of the selection depends not only on the product muN but also on the exact topology of the neutral network, the special arrangement of which was named "superfunnel." Even though the relation between mutation rate, population size, and selection was thoroughly investigated, a study of the salient topological features of the superfunnel that could affect the strength of the selection was wanting. This question is addressed in this study. We use two different models of proteins: on lattice and off lattice. We compare neutral networks computed using these models to random networks. From this, we identify two important factors of the topology that determine the stringency of the selection for mutationally robust sequences. First, the presence of highly connected nodes ("hubs") in the network increases the selection for mutationally robust sequences. Second, the stringency of the selection increases when the correlation between a sequence's mutational robustness and its neighbors' increases. The latter finding relates a global characteristic of the neutral network to a local one, which is attainable through experiments or molecular modeling.
Dormal, Giulia; Lepore, Franco; Harissi-Dagher, Mona; Albouy, Geneviève; Bertone, Armando; Rossion, Bruno
2014-01-01
Visual deprivation leads to massive reorganization in both the structure and function of the occipital cortex, raising crucial challenges for sight restoration. We tracked the behavioral, structural, and neurofunctional changes occurring in an early and severely visually impaired patient before and 1.5 and 7 mo after sight restoration with magnetic resonance imaging. Robust presurgical auditory responses were found in occipital cortex despite residual preoperative vision. In primary visual cortex, crossmodal auditory responses overlapped with visual responses and remained elevated even 7 mo after surgery. However, these crossmodal responses decreased in extrastriate occipital regions after surgery, together with improved behavioral vision and with increases in both gray matter density and neural activation in low-level visual regions. Selective responses in high-level visual regions involved in motion and face processing were observable even before surgery and did not evolve after surgery. Taken together, these findings demonstrate that structural and functional reorganization of occipital regions are present in an individual with a long-standing history of severe visual impairment and that such reorganizations can be partially reversed by visual restoration in adulthood. PMID:25520432
Toward link predictability of complex networks
Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene
2015-01-01
The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742
Coexistence and chaos in complex ecologies [rapid communication
NASA Astrophysics Data System (ADS)
Sprott, J. C.; Vano, J. A.; Wildenberg, J. C.; Anderson, M. B.; Noel, J. K.
2005-02-01
Many complex dynamical systems in ecology, economics, neurology, and elsewhere, in which agents compete for limited resources, exhibit apparently chaotic fluctuations. This Letter proposes a purely deterministic mechanism for evolving robustly but weakly chaotic systems that exhibit adaptation, self-organization, sporadic volatility, and punctuated equilibria.
Somatic evolution of head and neck cancer - biological robustness and latent vulnerability.
Masuda, Muneyuki; Toh, Satoshi; Wakasaki, Takahiro; Suzui, Masumi; Joe, Andrew K
2013-02-01
Despite recent advancements in multidisciplinary treatments, the overall survival and quality of life of patients with advanced head and neck squamous cell carcinoma (HNSCC) have not improved significantly over the past decade. Molecular targeted therapies, which have been addressed and advanced by the concept of "oncogene addiction", have demonstrated only limited successes so far. To explore a novel clue for clinically effective targeted therapies, we analyzed the molecular circuitry of HNSCC through the lens that HNSCC is an evolving system. In the trajectory of this somatic evolution, HNSCC acquires biological robustness under a variety of selective pressures including genetic, epigenetic, micro-environmental and metabolic stressors, which well explains the major mechanism of "escaping from oncogene addiction". On the other hand, this systemic view appears to instruct us approaches to target latent vulnerability of HNSCC that is masked behind the plasticity and evolvability of this complex adaptive system. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Evolution of plant–pollinator mutualisms in response to climate change
Gilman, R Tucker; Fabina, Nicholas S; Abbott, Karen C; Rafferty, Nicole E
2012-01-01
Climate change has the potential to desynchronize the phenologies of interdependent species, with potentially catastrophic effects on mutualist populations. Phenologies can evolve, but the role of evolution in the response of mutualisms to climate change is poorly understood. We developed a model that explicitly considers both the evolution and the population dynamics of a plant–pollinator mutualism under climate change. How the populations evolve, and thus whether the populations and the mutualism persist, depends not only on the rate of climate change but also on the densities and phenologies of other species in the community. Abundant alternative mutualist partners with broad temporal distributions can make a mutualism more robust to climate change, while abundant alternative partners with narrow temporal distributions can make a mutualism less robust. How community composition and the rate of climate change affect the persistence of mutualisms is mediated by two-species Allee thresholds. Understanding these thresholds will help researchers to identify those mutualisms at highest risk owing to climate change. PMID:25568025
Neutrality and evolvability of designed protein sequences
NASA Astrophysics Data System (ADS)
Bhattacherjee, Arnab; Biswas, Parbati
2010-07-01
The effect of foldability on protein’s evolvability is analyzed by a two-prong approach consisting of a self-consistent mean-field theory and Monte Carlo simulations. Theory and simulation models representing protein sequences with binary patterning of amino acid residues compatible with a particular foldability criteria are used. This generalized foldability criterion is derived using the high temperature cumulant expansion approximating the free energy of folding. The effect of cumulative point mutations on these designed proteins is studied under neutral condition. The robustness, protein’s ability to tolerate random point mutations is determined with a selective pressure of stability (ΔΔG) for the theory designed sequences, which are found to be more robust than that of Monte Carlo and mean-field-biased Monte Carlo generated sequences. The results show that this foldability criterion selects viable protein sequences more effectively compared to the Monte Carlo method, which has a marked effect on how the selective pressure shapes the evolutionary sequence space. These observations may impact de novo sequence design and its applications in protein engineering.
Loop, Carole
2013-01-01
Carrying out critical business functions without interruption requires a resilient and robust business continuity framework. By embedding an industry-standard incident management system within its business continuity structure, the Bank of Canada strengthened its response plan by enabling timely response to incidents while maintaining a strong focus on business continuity. A total programme approach, integrating the two disciplines, provided for enhanced recovery capabilities. While the value of an effective and efficient response organisation is clear, as demonstrated by emergency events around the world, incident response structures based on normal operating hierarchy can experience unique challenges. The internationally-recognised Incident Command System (ICS) model addresses these issues and reflects the five primary incident management functions, each contributing to the overall strength and effectiveness of the response organisation. The paper focuses on the Bank of Canada's successful implementation of the ICS model as its incident management and continuity of operations programmes evolved to reflect current best practices.
Emerging diagnostic and therapeutic molecular imaging applications in vascular disease
Eraso, Luis H; Reilly, Muredach P; Sehgal, Chandra; Mohler, Emile R
2013-01-01
Assessment of vascular disease has evolved from mere indirect and direct measurements of luminal stenosis to sophisticated imaging methods to depict millimeter structural changes of the vasculature. In the near future, the emergence of multimodal molecular imaging strategies may enable robust therapeutic and diagnostic (‘theragnostic’) approaches to vascular diseases that comprehensively consider structural, functional, biological and genomic characteristics of the disease in individualized risk assessment, early diagnosis and delivery of targeted interventions. This review presents a summary of recent preclinical and clinical developments in molecular imaging and theragnostic applications covering diverse atherosclerosis events such as endothelial activation, macrophage infammatory activity, plaque neovascularization and arterial thrombosis. The main focus is on molecular targets designed for imaging platforms commonly used in clinical medicine including magnetic resonance, computed tomography and positron emission tomography. A special emphasis is given to vascular ultrasound applications, considering the important role this imaging platform plays in the clinical and research practice of the vascular medicine specialty. PMID:21310769
The Feeding Biomechanics and Dietary Ecology of Paranthropus boisei
Smith, Amanda L.; Benazzi, Stefano; Ledogar, Justin A.; Tamvada, Kelli; Pryor Smith, Leslie C.; Weber, Gerhard W.; Spencer, Mark A.; Lucas, Peter W.; Michael, Shaji; Shekeban, Ali; Al-Fadhalah, Khaled; Almusallam, Abdulwahab S.; Dechow, Paul C.; Grosse, Ian R.; Ross, Callum F.; Madden, Richard H.; Richmond, Brian G.; Wright, Barth W.; Wang, Qian; Byron, Craig; Slice, Dennis E.; Wood, Sarah; Dzialo, Christine; Berthaume, Michael A.; Casteren, Adam Van; Strait, David S.
2015-01-01
The African Plio-Pleistocene hominins known as australopiths evolved derived craniodental features frequently interpreted as adaptations for feeding on either hard, or compliant/tough foods. Among australopiths, Paranthropus boisei is the most robust form, exhibiting traits traditionally hypothesized to produce high bite forces efficiently and strengthen the face against feeding stresses. However, recent mechanical analyses imply that P. boisei may not have been an efficient producer of bite force and that robust morphology in primates is not necessarily strong. Here we use an engineering method, finite element analysis, to show that the facial skeleton of P. boisei is structurally strong, exhibits a strain pattern different from that in chimpanzees (Pan troglodytes) and Australopithecus africanus, and efficiently produces high bite force. It has been suggested that P. boisei consumed a diet of compliant/tough foods like grass blades and sedge pith. However, the blunt occlusal topography of this and other species suggests that australopiths are adapted to consume hard foods, perhaps including grass and sedge seeds. A consideration of evolutionary trends in morphology relating to feeding mechanics suggests that food processing behaviors in gracile australopiths evidently were disrupted by environmental change, perhaps contributing to the eventual evolution of Homo and Paranthropus. PMID:25529240
Neigel, J E; Avise, J C
1993-12-01
In rapidly evolving molecules, such as animal mitochondrial DNA, mutations that delineate specific lineages may not be dispersed at sufficient rates to attain an equilibrium between genetic drift and gene flow. Here we predict conditions that lead to nonequilibrium geographic distributions of mtDNA lineages, test the robustness of these predictions and examine mtDNA data sets for consistency with our model. Under a simple isolation by distance model, the variance of an mtDNA lineage's geographic distribution is expected be proportional to its age. Simulation results indicated that this relationship is fairly robust. Analysis of mtDNA data from natural populations revealed three qualitative distributional patterns: (1) significant departure of lineage structure from equilibrium geographic distributions, a pattern exhibited in three rodent species with limited dispersal; (2) nonsignificant departure from equilibrium expectations, exhibited by two avian and two marine fish species with potentials for relatively long-distance dispersal; and (3) a progression from nonequilibrium distributions for younger lineages to equilibrium distributions for older lineages, a condition displayed by one surveyed avian species. These results demonstrate the advantages of considering mutation and genealogy in the interpretation of mtDNA geographic variation.
Understanding Multicultural Education: Equity for All Students
ERIC Educational Resources Information Center
Rios, Francisco; Stanton, Christine Rogers
2011-01-01
Multicultural education has evolved over the last 25 years to become a promising, productive, and positive approach to education within an increasingly diverse schooling context. The academic discipline has developed models, robust definitions and goals, and specific pedagogical principles related to an education that is multicultural. Almost all…
ERIC Educational Resources Information Center
Finlay, Barbara L.
2007-01-01
The marriage of evolution and development to produce the new discipline "evo-devo" in biology is situated in the general history of evolutionary biology, and its significance for developmental cognitive science is discussed. The discovery and description of the highly conserved, robust and "evolvable" mechanisms that organize the vertebrate body…
Understanding multi-scale structural evolution in granular systems through gMEMS
NASA Astrophysics Data System (ADS)
Walker, David M.; Tordesillas, Antoinette
2013-06-01
We show how the rheological response of a material to applied loads can be systematically coded, analyzed and succinctly summarized, according to an individual grain's property (e.g. kinematics). Individual grains are considered as their own smart sensor akin to microelectromechanical systems (e.g. gyroscopes, accelerometers), each capable of recognizing their evolving role within self-organizing building block structures (e.g. contact cycles and force chains). A symbolic time series is used to represent their participation in such self-assembled building blocks and a complex network summarizing their interrelationship with other grains is constructed. In particular, relationships between grain time series are determined according to the information theory Hamming distance or the metric Euclidean distance. We then use topological distance to find network communities enabling groups of grains at remote physical metric distances in the material to share a classification. In essence grains with similar structural and functional roles at different scales are identified together. This taxonomy distills the dissipative structural rearrangements of grains down to its essential features and thus provides pointers for objective physics-based internal variable formalisms used in the construction of robust predictive continuum models.
Spoken language achieves robustness and evolvability by exploiting degeneracy and neutrality.
Winter, Bodo
2014-10-01
As with biological systems, spoken languages are strikingly robust against perturbations. This paper shows that languages achieve robustness in a way that is highly similar to many biological systems. For example, speech sounds are encoded via multiple acoustically diverse, temporally distributed and functionally redundant cues, characteristics that bear similarities to what biologists call "degeneracy". Speech is furthermore adequately characterized by neutrality, with many different tongue configurations leading to similar acoustic outputs, and different acoustic variants understood as the same by recipients. This highlights the presence of a large neutral network of acoustic neighbors for every speech sound. Such neutrality ensures that a steady backdrop of variation can be maintained without impeding communication, assuring that there is "fodder" for subsequent evolution. Thus, studying linguistic robustness is not only important for understanding how linguistic systems maintain their functioning upon the background of noise, but also for understanding the preconditions for language evolution. © 2014 WILEY Periodicals, Inc.
RSRE: RNA structural robustness evaluator
Shu, Wenjie; Zheng, Zhiqiang; Wang, Shengqi
2007-01-01
Biological robustness, defined as the ability to maintain stable functioning in the face of various perturbations, is an important and fundamental topic in current biology, and has become a focus of numerous studies in recent years. Although structural robustness has been explored in several types of RNA molecules, the origins of robustness are still controversial. Computational analysis results are needed to make up for the lack of evidence of robustness in natural biological systems. The RNA structural robustness evaluator (RSRE) web server presented here provides a freely available online tool to quantitatively evaluate the structural robustness of RNA based on the widely accepted definition of neutrality. Several classical structure comparison methods are employed; five randomization methods are implemented to generate control sequences; sub-optimal predicted structures can be optionally utilized to mitigate the uncertainty of secondary structure prediction. With a user-friendly interface, the web application is easy to use. Intuitive illustrations are provided along with the original computational results to facilitate analysis. The RSRE will be helpful in the wide exploration of RNA structural robustness and will catalyze our understanding of RNA evolution. The RSRE web server is freely available at http://biosrv1.bmi.ac.cn/RSRE/ or http://biotech.bmi.ac.cn/RSRE/. PMID:17567615
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-24
..., Vehicle-to-Infrastructure, and Testing programs; along with a special session discussing lessons learned... evolving in terms of a robust Vehicle-to- Infrastructure environment, and identify what we have learned... wireless communication between vehicles, infrastructure, and personal communications devices to [[Page...
Evidence for the implication of the histone code in building the genome structure.
Prakash, Kirti; Fournier, David
2018-02-01
Histones are punctuated with small chemical modifications that alter their interaction with DNA. One attractive hypothesis stipulates that certain combinations of these histone modifications may function, alone or together, as a part of a predictive histone code to provide ground rules for chromatin folding. We consider four features that relate histone modifications to chromatin folding: charge neutralisation, molecular specificity, robustness and evolvability. Next, we present evidence for the association among different histone modifications at various levels of chromatin organisation and show how these relationships relate to function such as transcription, replication and cell division. Finally, we propose a model where the histone code can set critical checkpoints for chromatin to fold reversibly between different orders of the organisation in response to a biological stimulus. Copyright © 2017 Elsevier B.V. All rights reserved.
Shindey, Radhika; Varma, Vishwanath; Nikhil, K L; Sharma, Vijay Kumar
2017-01-01
Organisms are believed to have evolved circadian clocks as adaptations to deal with cyclic environmental changes, and therefore it has been hypothesized that evolution in constant environments would lead to regression of such clocks. However, previous studies have yielded mixed results, and evolution of circadian clocks under constant conditions has remained an unsettled topic of debate in circadian biology. In continuation of our previous studies, which reported persistence of circadian rhythms in Drosophila melanogaster populations evolving under constant light, here we intended to examine whether circadian clocks and the associated properties evolve differently under constant light and constant darkness. In this regard, we assayed activity-rest, adult emergence and oviposition rhythms of D. melanogaster populations which have been maintained for over 19 years (~330 generations) under three different light regimes - constant light (LL), light-dark cycles of 12:12 h (LD) and constant darkness (DD). We observed that while circadian rhythms in all the three behaviors persist in both LL and DD stocks with no differences in circadian period, they differed in certain aspects of the entrained rhythms when compared to controls reared in rhythmic environment (LD). Interestingly, we also observed that DD stocks have evolved significantly higher robustness or power of free-running activity-rest and adult emergence rhythms compared to LL stocks. Thus, our study, in addition to corroborating previous results of circadian clock evolution in constant light, also highlights that, contrary to the expected regression of circadian clocks, rearing in constant darkness leads to the evolution of more robust circadian clocks which may be attributed to an intrinsic adaptive advantage of circadian clocks and/or pleiotropic functions of clock genes in other traits.
Assuring SS7 dependability: A robustness characterization of signaling network elements
NASA Astrophysics Data System (ADS)
Karmarkar, Vikram V.
1994-04-01
Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.
Least dissipation cost as a design principle for robustness and function of cellular networks
NASA Astrophysics Data System (ADS)
Han, Bo; Wang, Jin
2008-03-01
From a study of the budding yeast cell cycle, we found that the cellular network evolves to have the least cost for realizing its biological function. We quantify the cost in terms of the dissipation or heat loss characterized through the steady-state properties: the underlying landscape and the associated flux. We found that the dissipation cost is intimately related to the stability and robustness of the network. With the least dissipation cost, the network becomes most stable and robust under mutations and perturbations on the sharpness of the response from input to output as well as self-degradations. The least dissipation cost may provide a general design principle for the cellular network to survive from the evolution and realize the biological function.
Academic Library Web Sites: Current Practice and Future Directions
ERIC Educational Resources Information Center
Detlor, Brian; Lewis, Vivian
2006-01-01
To address competitive threats, academic libraries are encouraged to build robust Web sites personalized to learning and research tasks. Through an evaluation of Association of Research Libraries (ARL)-member Web sites, we suggest how library Web sites should evolve and reflect upon the impacts such recommendations may have on academic libraries…
Sexual and Emotional Infidelity: Evolved Gender Differences in Jealousy Prove Robust and Replicable.
Buss, David M
2018-03-01
Infidelity poses threats to high-investment mating relationships. Because of gender differences in some aspects of reproductive biology, such as internal female fertilization, the nature of these threats differs for men and women. Men, but not women, for example, have recurrently faced the problem of uncertainty in their genetic parenthood. Jealousy is an emotion hypothesized to have evolved to combat these threats. The 1992 article Sex Differences in Jealousy: Evolution, Physiology, and Psychology reported three empirical studies using two different methods, forced-choice and physiological experiments. Results supported the evolution-based hypotheses. The article became highly cited for several reasons. It elevated the status of jealousy as an important emotion to be explained by any comprehensive theory of human emotions. Subsequent meta-analyses robustly supported the evolutionary hypotheses. Moreover, the work supported the evolutionary meta-theory of gender differences, which posits differences only in domains in which the sexes have recurrently faced distinct adaptive problems. It also heralded the newly emerging field of evolutionary psychology as a useful perspective that possesses the scientific virtues of testability, falsifiability, and heuristic value in discovering previously unknown psychological phenomena.
Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments
NASA Astrophysics Data System (ADS)
Lane, Peter C. R.; Gobet, Fernand
2013-03-01
Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.
Sumpter, David
2017-01-01
Community ecosystems at very different levels of biological organization often have similar properties. Coexistence of multiple species, cross-feeding, biodiversity and fluctuating population dynamics are just a few of the properties that arise in a range of ecological settings. Here we develop a bottom-up model of consumer–resource interactions, in the form of an artificial ecosystem ‘number soup’, which reflects basic properties of many bacterial and other community ecologies. We demonstrate four key properties of the number soup model: (i) communities self-organize so that all available resources are fully consumed; (ii) reciprocal cross-feeding is a common evolutionary outcome, which evolves in a number of stages, and many transitional species are involved; (iii) the evolved ecosystems are often ‘robust yet fragile’, with keystone species required to prevent the whole system from collapsing; (iv) non-equilibrium dynamics and chaotic patterns are general properties, readily generating rich biodiversity. These properties have been observed in empirical ecosystems, ranging from bacteria to rainforests. Establishing similar properties in an evolutionary model as simple as the number soup suggests that these four properties are ubiquitous features of all community ecosystems, and raises questions about how we interpret ecosystem structure in the context of natural selection. PMID:28100827
Biomimetics of fetal alveolar flow phenomena using microfluidics.
Tenenbaum-Katan, Janna; Fishler, Rami; Rothen-Rutishauser, Barbara; Sznitman, Josué
2015-01-01
At the onset of life in utero, the respiratory system begins as a liquid-filled tubular organ and undergoes significant morphological changes during fetal development towards establishing a respiratory organ optimized for gas exchange. As airspace morphology evolves, respiratory alveolar flows have been hypothesized to exhibit evolving flow patterns. In the present study, we have investigated flow topologies during increasing phases of embryonic life within an anatomically inspired microfluidic device, reproducing real-scale features of fetal airways representative of three distinct phases of in utero gestation. Micro-particle image velocimetry measurements, supported by computational fluid dynamics simulations, reveal distinct respiratory alveolar flow patterns throughout different stages of fetal life. While attached, streamlined flows characterize the shallow structures of premature alveoli indicative of the onset of saccular stage, separated recirculating vortex flows become the signature of developed and extruded alveoli characteristic of the advanced stages of fetal development. To further mimic physiological aspects of the cellular environment of developing airways, our biomimetic devices integrate an alveolar epithelium using the A549 cell line, recreating a confluent monolayer that produces pulmonary surfactant. Overall, our in vitro biomimetic fetal airways model delivers a robust and reliable platform combining key features of alveolar morphology, flow patterns, and physiological aspects of fetal lungs developing in utero.
Attigala, Lakshmi; Wysocki, William P; Duvall, Melvin R; Clark, Lynn G
2016-08-01
We explored phylogenetic relationships among the twelve lineages of the temperate woody bamboo clade (tribe Arundinarieae) based on plastid genome (plastome) sequence data. A representative sample of 28 taxa was used and maximum parsimony, maximum likelihood and Bayesian inference analyses were conducted to estimate the Arundinarieae phylogeny. All the previously recognized clades of Arundinarieae were supported, with Ampelocalamus calcareus (Clade XI) as sister to the rest of the temperate woody bamboos. Well supported sister relationships between Bergbambos tessellata (Clade I) and Thamnocalamus spathiflorus (Clade VII) and between Kuruna (Clade XII) and Chimonocalmus (Clade III) were revealed by the current study. The plastome topology was tested by taxon removal experiments and alternative hypothesis testing and the results supported the current plastome phylogeny as robust. Neighbor-net analyses showed few phylogenetic signal conflicts, but suggested some potentially complex relationships among these taxa. Analyses of morphological character evolution of rhizomes and reproductive structures revealed that pachymorph rhizomes were most likely the ancestral state in Arundinarieae. In contrast leptomorph rhizomes either evolved once with reversions to the pachymorph condition or multiple times in Arundinarieae. Further, pseudospikelets evolved independently at least twice in the Arundinarieae, but the ancestral state is ambiguous. Copyright © 2016 Elsevier Inc. All rights reserved.
Superlinearly scalable noise robustness of redundant coupled dynamical systems.
Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L
2016-03-01
We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.
Thermotaxis is a Robust Mechanism for Thermoregulation in C. elegans Nematodes
Ramot, Daniel; MacInnis, Bronwyn L.; Lee, Hau-Chen; Goodman, Miriam B.
2013-01-01
Many biochemical networks are robust to variations in network or stimulus parameters. Although robustness is considered an important design principle of such networks, it is not known whether this principle also applies to higher-level biological processes such as animal behavior. In thermal gradients, C. elegans uses thermotaxis to bias its movement along the direction of the gradient. Here we develop a detailed, quantitative map of C. elegans thermotaxis and use these data to derive a computational model of thermotaxis in the soil, a natural environment of C. elegans. This computational analysis indicates that thermotaxis enables animals to avoid temperatures at which they cannot reproduce, to limit excursions from their adapted temperature, and to remain relatively close to the surface of the soil, where oxygen is abundant. Furthermore, our analysis reveals that this mechanism is robust to large variations in the parameters governing both worm locomotion and temperature fluctuations in the soil. We suggest that, similar to biochemical networks, animals evolve behavioral strategies that are robust, rather than strategies that rely on fine-tuning of specific behavioral parameters. PMID:19020047
Period doubling in period-one steady states
NASA Astrophysics Data System (ADS)
Wang, Reuben R. W.; Xing, Bo; Carlo, Gabriel G.; Poletti, Dario
2018-02-01
Nonlinear classical dissipative systems present a rich phenomenology in their "route to chaos," including period doubling, i.e., the system evolves with a period which is twice that of the driving. However, typically the attractor of a periodically driven quantum open system evolves with a period which exactly matches that of the driving. Here, we analyze a periodically driven many-body open quantum system whose classical correspondent presents period doubling. We show that by studying the dynamical correlations, it is possible to show the occurrence of period doubling in the quantum (period-one) steady state. We also discuss that such systems are natural candidates for clean and intrinsically robust Floquet time crystals.
The evolution of intelligence in mammalian carnivores.
Holekamp, Kay E; Benson-Amram, Sarah
2017-06-06
Although intelligence should theoretically evolve to help animals solve specific types of problems posed by the environment, it is unclear which environmental challenges favour enhanced cognition, or how general intelligence evolves along with domain-specific cognitive abilities. The social intelligence hypothesis posits that big brains and great intelligence have evolved to cope with the labile behaviour of group mates. We have exploited the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas to test predictions of the social intelligence hypothesis in regard to both cognition and brain size. Behavioural data indicate that there has been considerable convergence between primates and hyaenas with respect to their social cognitive abilities. Moreover, compared with other hyaena species, spotted hyaenas have larger brains and expanded frontal cortex, as predicted by the social intelligence hypothesis. However, broader comparative study suggests that domain-general intelligence in carnivores probably did not evolve in response to selection pressures imposed specifically in the social domain. The cognitive buffer hypothesis, which suggests that general intelligence evolves to help animals cope with novel or changing environments, appears to offer a more robust explanation for general intelligence in carnivores than any hypothesis invoking selection pressures imposed strictly by sociality or foraging demands.
The evolution of intelligence in mammalian carnivores
Benson-Amram, Sarah
2017-01-01
Although intelligence should theoretically evolve to help animals solve specific types of problems posed by the environment, it is unclear which environmental challenges favour enhanced cognition, or how general intelligence evolves along with domain-specific cognitive abilities. The social intelligence hypothesis posits that big brains and great intelligence have evolved to cope with the labile behaviour of group mates. We have exploited the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas to test predictions of the social intelligence hypothesis in regard to both cognition and brain size. Behavioural data indicate that there has been considerable convergence between primates and hyaenas with respect to their social cognitive abilities. Moreover, compared with other hyaena species, spotted hyaenas have larger brains and expanded frontal cortex, as predicted by the social intelligence hypothesis. However, broader comparative study suggests that domain-general intelligence in carnivores probably did not evolve in response to selection pressures imposed specifically in the social domain. The cognitive buffer hypothesis, which suggests that general intelligence evolves to help animals cope with novel or changing environments, appears to offer a more robust explanation for general intelligence in carnivores than any hypothesis invoking selection pressures imposed strictly by sociality or foraging demands. PMID:28479979
NASA Astrophysics Data System (ADS)
Reed, Patrick; Zeff, Harrison; Characklis, Gregory
2017-04-01
Water supply adaptation frameworks that seek robustness must adaptively trigger actions that are contextually appropriate to emerging system observations and avoid long term high regret lock-ins. As an example, emerging water scarcity concerns in southeastern United States are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that regional water utilities identify regionally coordinated, scarcity-mitigating infrastructure development pathways that trigger time appropriate actions. Mistakes can lead to water shortages, overbuilt stranded assets and possibly financial failures. This presentation uses the Research Triangle area of North Carolina to illustrate the key concerns and challenges that emerged when helping Raleigh, Durham, Cary and Chapel Hill develop their long term water supply infrastructure pathways through 2060. This example shows how the region's water utilities' long term infrastructure pathways are strongly shaped by their short term conservation policies (i.e., reacting to evolving demands) and their ability to consider regional water transfers (i.e., reacting to supply imbalances). Cooperatively developed, shared investments across the four municipalities expand their capacity to use short term transfers to better manage severe droughts with fewer investments in irreversible infrastructure options. Cooperative pathways are also important for avoiding regional robustness conflicts, where one party benefits strongly at the expense of one or more the others. A significant innovation of this work is the exploitation of weekly and annual dynamic risk-of-failure action triggers that exploit evolving feedbacks between co-evolving human demands and regional supplies. These dynamic action triggers provide high levels of adaptivity, tailor actions to their specific context, and motivate the value of joint human—natural system observation systems. The insights from this work have general merit globally for urban regions where adjacent municipalities can benefit from cooperative planning.
Cosmology with cosmic shear observations: a review.
Kilbinger, Martin
2015-07-01
Cosmic shear is the distortion of images of distant galaxies due to weak gravitational lensing by the large-scale structure in the Universe. Such images are coherently deformed by the tidal field of matter inhomogeneities along the line of sight. By measuring galaxy shape correlations, we can study the properties and evolution of structure on large scales as well as the geometry of the Universe. Thus, cosmic shear has become a powerful probe into the nature of dark matter and the origin of the current accelerated expansion of the Universe. Over the last years, cosmic shear has evolved into a reliable and robust cosmological probe, providing measurements of the expansion history of the Universe and the growth of its structure. We review here the principles of weak gravitational lensing and show how cosmic shear is interpreted in a cosmological context. Then we give an overview of weak-lensing measurements, and present the main observational cosmic-shear results since it was discovered 15 years ago, as well as the implications for cosmology. We then conclude with an outlook on the various future surveys and missions, for which cosmic shear is one of the main science drivers, and discuss promising new weak cosmological lensing techniques for future observations.
Reducing Undue Conservatism in "Higher Frequency" Structural Design Loads in Aerospace Components
NASA Technical Reports Server (NTRS)
Knight, J. Brent
2012-01-01
This study is intended to investigate the frequency dependency of significant strain due to vibratory loads in aerospace vehicle components. The notion that "higher frequency" dynamic loads applied as static loads is inherently conservative is perceived as widely accepted. This effort is focused on demonstrating that principle and attempting to evolve methods to capitalize on it to mitigate undue conservatism. It has been suggested that observations of higher frequency modes that resulted in very low corresponding strain did so due to those modes not being significant. Two avionics boxes, one with its first significant mode at 341 Hz and the other at 857 Hz, were attached to a flat panel installed on a curved orthogrid panel which was driven acoustically in tests performed at NASA/MSFC. Strain and acceleration were measured at select locations on each of the boxes. When possible, strain gage rosettes and accelerometers were installed on either side of a given structural member so that measured strain and acceleration data would directly correspond to one another. Ultimately, a frequency above which vibratory loads can be disregarded for purposes of static structural analyses and sizing of typical robust aerospace components is sought.
Effect of surface texturing on superoleophobicity, contact angle hysteresis, and "robustness".
Zhao, Hong; Park, Kyoo-Chul; Law, Kock-Yee
2012-10-23
Previously, we reported the creation of a fluorosilane (FOTS) modified pillar array silicon surface comprising ~3-μm-diameter pillars (6 μm pitch with ~7 μm height) that is both superhydrophobic and superoleophobic, with water and hexadecane contact angles exceeding 150° and sliding angles at ~10° owing to the surface fluorination and the re-entrant structure in the side wall of the pillar. In this work, the effects of surface texturing (pillar size, spacing, and height) on wettability, contact angle hysteresis, and "robustness" are investigated. We study the static, advancing, and receding contact angles, as well as the sliding angles as a function of the solid area fraction. The results reveal that pillar size and pillar spacing have very little effect on the static and advancing contact angles, as they are found to be insensitive to the solid area fraction from 0.04 to ~0.4 as the pillar diameter varies from 1 to 5 μm and the center-to-center spacing varies from 4.5 to 12 μm. On the other hand, sliding angle, receding contact angle, and contact angle hysteresis are found to be dependent on the solid area fraction. Specifically, receding contact angle decreases and sliding angle and hysteresis increase as the solid area fraction increases. This effect can be attributable to the increase in pinning as the solid area fraction increases. Surface Evolver modeling shows that water wets and pins the pillar surface whereas hexadecane wets the pillar surface and then penetrates into the side wall of the pillar with the contact line pinning underneath the re-entrant structure. Due to the penetration of the hexadecane drop into the pillar structure, the effect on the receding contact angle and hysteresis is larger relative to that of water. This interpretation is supported by studying a series of FOTS pillar array surfaces with varying overhang thickness. With the water drop, the contact line is pinned on the pillar surface and very little overhang thickness effect was observed. On the other hand, the hexadecane drop is shown to wet the pillar surface and the side wall of the overhang. It then pins at the lower edge of the overhang structure. A plot of the thickness of the overhang as a function of the static, advancing, and receding contact angles and sliding angle of hexadecane reveals that static, advancing, and receding contact angles decrease and sliding angle increases as the thickness of the overhang increases. A larger overhang effect is observed with octane due to its lower surface tension. The robustness of the pillar array surface against external pressure induced wetting and abrasion was modeled. Surface Evolver simulation (with the hexadecane drop) indicates that wetting breakthrough pressure as high as ~70 kPa is achievable with 0.5-μm-diameter pillar array FOTS surfaces. Mechanical modeling shows that bending of the pillars is the key failure by abrasion, which can be avoided with a short pillar structure. The path to fabricate a superoleophobic surface that can withstand the external force equivalent of a gentle cleaning blade (up to ~30 kPa) without wetting and abrasion failure is discussed.
NASA Technical Reports Server (NTRS)
Uchida, Hiroyuki; Tsunemi, Hiroshi; Katsuda, Satoru; Mori, Koji; Petre, Robert; Yamaguchi, Hiroya
2012-01-01
We report an X-ray study of the evolved Galactic supernova remnant (SNR) G1S6.2+S.7 based on six pointing observations with Suzaku. The remnant's large extent (100' in diameter) allows us to investigate its radial structure in the northwestern and eastern directions from the apparent center. The X-ray spectra. were well fit with a two-component non-equilibrium ionization model representing the swept-up interstellar medium (ISM) and the metal-rich ejecta. We found prominent central concentrations of Si, S and Fe from the ejecta component; the lighter elements of O, Ne and Mg were distributed more uniformly. The temperature of the ISM component suggests a slow shock (610-960 km/s), hence the remnant's age is estimated to be 7,000-15,000 yr, assuming its distance to be approx. 1.1 kpc. G1S6.2+5.7 has also been thought to emit hard, non-thermal X-rays, despite being considerably older than any other such remnant. In response to a recent discovery of a background cluster of galaxies (2XMM J045637.2+522411), we carefully excluded its contribution, and reexamined the origin of the hard X-ray emission. We found that the residual hard X-ray emission is consistent with the expected level of the cosmic X-ray background. Thus, no robust evidence for the non-thermal emission was obtained from G156.2+5.7. These results are consistent with the picture of an evolved SNR.
Knotty structures of the evolving heliospheric magnetic fields.
NASA Astrophysics Data System (ADS)
Roth, Ilan
2013-04-01
The analogy between MHD and knot theory is utilized in an analysis of structure, stability and evolution of complex magnetic heliospheric flux tubes. Planar projection of a three-dimensional magnetic configuration depicts the structure as a two-dimensional diagram with crossings, to which one may assign mathematical operations leading to robust topological invariants. These invariants enrich the topological information of magnetic configurations beyond helicity. It is conjectured that the field which emerges from the solar photosphere is structured as one of simplest knot invariants - unknot or prime knot, and these flux ropes are then stretched while carried by the solar wind into the interplanetary medium. Preservation of invariants for small diffusivity and large cross section of the emerging magnetic flux makes them impervious to large scale reconnection, allowing us to predict the observed structures at 1AU as elongated prime knots. Similar structures may be observed in magnetic clouds which got disconnected from their foot-points and in ion drop-out configurations from a compact flare source in solar impulsive solar events. Observation of small scale magnetic features consistent with prime knot may indicate spatial intermittency and non-Gaussian statistics in the turbulent cascade process. For flux tubes with higher resistivity, magnetic energy decay rate should decrease with increased knot complexity as the invariants are then harder to be violated. Future measurements are suggested for distinctly oriented magnetic fields with directionally varying suprathermal particle fluxes.
Characterizing metabolic pathway diversification in the context of perturbation size.
Yang, Laurence; Srinivasan, Shyamsundhar; Mahadevan, Radhakrishnan; Cluett, William R
2015-03-01
Cell metabolism is an important platform for sustainable biofuel, chemical and pharmaceutical production but its complexity presents a major challenge for scientists and engineers. Although in silico strains have been designed in the past with predicted performances near the theoretical maximum, real-world performance is often sub-optimal. Here, we simulate how strain performance is impacted when subjected to many randomly varying perturbations, including discrepancies between gene expression and in vivo flux, osmotic stress, and substrate uptake perturbations due to concentration gradients in bioreactors. This computational study asks whether robust performance can be achieved by adopting robustness-enhancing mechanisms from naturally evolved organisms-in particular, redundancy. Our study shows that redundancy, typically perceived as a ubiquitous robustness-enhancing strategy in nature, can either improve or undermine robustness depending on the magnitude of the perturbations. We also show that the optimal number of redundant pathways used can be predicted for a given perturbation size. Copyright © 2015. Published by Elsevier Inc.
How Physician Perspectives on E-Prescribing Evolve over Time
Patel, Vaishali; Pfoh, Elizabeth R.; Kaushal, Rainu
2016-01-01
Summary Background Physicians are expending tremendous resources transitioning to new electronic health records (EHRs), with electronic prescribing as a key functionality of most systems. Physician dissatisfaction post-transition can be quite marked, especially initially. However, little is known about how physicians’ experiences using new EHRs for e-prescribing evolve over time. We previously published a qualitative case study about the early physician experience transitioning from an older to a newer, more robust EHR, in the outpatient setting, focusing on their perceptions of the electronic prescribing functionality. Objective Our current objective was to examine how perceptions about using the new HER evolved over time, again with a focus on electronic prescribing. Methods We interviewed thirteen internists at an academic medical center-affiliated ambulatory care clinic who transitioned to the new EHR two years prior. We used a grounded theory approach to analyze semi-structured interviews and generate key themes. Results We identified five themes: efficiency and usability, effects on safety, ongoing training requirements, customization, and competing priorities for the EHR. We found that for even experienced e-prescribers, achieving prior levels of perceived prescribing efficiency took nearly two years. Despite the fact that speed in performing prescribing-related tasks was highly important, most were still not utilizing system short cuts or customization features designed to maximize efficiency. Alert fatigue remained common. However, direct transmission of prescriptions to pharmacies was highly valued and its benefits generally outweighed the other features considered poorly designed for physician workflow. Conclusions Ensuring that physicians are able to do key prescribing tasks efficiently is critical to the perceived value of e-prescribing applications. However, successful transitions may take longer than expected and e-prescribing system features that do not support workflow or require constant upgrades may further prolong the process. Additionally, as system features continually evolve, physicians may need ongoing training and support to maintain efficiency. PMID:27786335
Emergent gamma synchrony in all-to-all interneuronal networks.
Ratnadurai-Giridharan, Shivakeshavan; Khargonekar, Pramod P; Talathi, Sachin S
2015-01-01
We investigate the emergence of in-phase synchronization in a heterogeneous network of coupled inhibitory interneurons in the presence of spike timing dependent plasticity (STDP). Using a simple network of two mutually coupled interneurons (2-MCI), we first study the effects of STDP on in-phase synchronization. We demonstrate that, with STDP, the 2-MCI network can evolve to either a state of stable 1:1 in-phase synchronization or exhibit multiple regimes of higher order synchronization states. We show that the emergence of synchronization induces a structural asymmetry in the 2-MCI network such that the synapses onto the high frequency firing neurons are potentiated, while those onto the low frequency firing neurons are de-potentiated, resulting in the directed flow of information from low frequency firing neurons to high frequency firing neurons. Finally, we demonstrate that the principal findings from our analysis of the 2-MCI network contribute to the emergence of robust synchronization in the Wang-Buzsaki network (Wang and Buzsáki, 1996) of all-to-all coupled inhibitory interneurons (100-MCI) for a significantly larger range of heterogeneity in the intrinsic firing rate of the neurons in the network. We conclude that STDP of inhibitory synapses provide a viable mechanism for robust neural synchronization.
Emergent gamma synchrony in all-to-all interneuronal networks
Ratnadurai-Giridharan, Shivakeshavan; Khargonekar, Pramod P.; Talathi, Sachin S.
2015-01-01
We investigate the emergence of in-phase synchronization in a heterogeneous network of coupled inhibitory interneurons in the presence of spike timing dependent plasticity (STDP). Using a simple network of two mutually coupled interneurons (2-MCI), we first study the effects of STDP on in-phase synchronization. We demonstrate that, with STDP, the 2-MCI network can evolve to either a state of stable 1:1 in-phase synchronization or exhibit multiple regimes of higher order synchronization states. We show that the emergence of synchronization induces a structural asymmetry in the 2-MCI network such that the synapses onto the high frequency firing neurons are potentiated, while those onto the low frequency firing neurons are de-potentiated, resulting in the directed flow of information from low frequency firing neurons to high frequency firing neurons. Finally, we demonstrate that the principal findings from our analysis of the 2-MCI network contribute to the emergence of robust synchronization in the Wang-Buzsaki network (Wang and Buzsáki, 1996) of all-to-all coupled inhibitory interneurons (100-MCI) for a significantly larger range of heterogeneity in the intrinsic firing rate of the neurons in the network. We conclude that STDP of inhibitory synapses provide a viable mechanism for robust neural synchronization. PMID:26528174
Robust nanopatterning by laser-induced dewetting of metal nanofilms.
Favazza, Christopher; Kalyanaraman, Ramki; Sureshkumar, Radhakrishna
2006-08-28
We have observed nanopattern formation with robust and controllable spatial ordering by laser-induced dewetting in nanoscopic metal films. Pattern evolution in Co film of thickness 1≤h≤8 nm on SiO(2) was achieved under multiple pulse irradiation using a 9 ns pulse laser. Dewetting leads to the formation of cellular patterns which evolve into polygons that eventually break up into nanoparticles with unimodal size distribution and short range ordering in nearest neighbour spacing R. Spatial ordering was attributed to a hydrodynamic thin film instability and resulted in a predictable variation of R and particle diameter D with h. The length scales R and D were found to be independent of the laser energy. These results suggest that spatially ordered metal nanoparticles can be robustly assembled by laser-induced dewetting.
NASA Technical Reports Server (NTRS)
1998-01-01
As summarized in this pamphlet, some of the far-reaching underlying issues to be addressed include: What is the origin of the universe and its destiny; Why is the universe lumpy; How did the known structures of the universe evolve; How do galaxies evolve; How do massive black holes grow; How did the elemental composition of the universe evolve; What is the structure and behavior of matter in the extreme; and Is Einstein's general relativity theory right.
Robust Mean and Covariance Structure Analysis through Iteratively Reweighted Least Squares.
ERIC Educational Resources Information Center
Yuan, Ke-Hai; Bentler, Peter M.
2000-01-01
Adapts robust schemes to mean and covariance structures, providing an iteratively reweighted least squares approach to robust structural equation modeling. Each case is weighted according to its distance, based on first and second order moments. Test statistics and standard error estimators are given. (SLD)
Scaling a Model of Teacher Professional Learning--To MOOC or Not to MOOC?
ERIC Educational Resources Information Center
Butler, Deirdre; Leahy, Margaret; Hallissy, Michael; Brown, Mark
2016-01-01
This paper describes an innovative model of teacher professional learning that has evolved over a decade. Working in a range of different school contexts, in conjunction with an ongoing engagement with the research literature, has enabled the development over three phases of a robust, yet, flexible framework that meets teachers' expressed needs.…
ERIC Educational Resources Information Center
Shah, Rebecca
2011-01-01
As a result of state, national and federal leadership and political will, states have dramatically increased their capacity to collect robust longitudinal education data. However, without an equally ambitious effort to ensure access and build stakeholders' capacity to use data to increase student achievement, these infrastructure investments…
ERIC Educational Resources Information Center
Data Quality Campaign, 2011
2011-01-01
As a result of state, national and federal leadership and political will, states have dramatically increased their capacity to collect robust longitudinal education data. However, without an equally ambitious effort to ensure access and build stakeholders' capacity to use data to increase student achievement, these infrastructure investments…
Historical evolution of medical quality assurance in the Department of Defense.
Granger, Elder; Boyer, John; Weiss, Richard; Linton, Andrea; Williams, Thomas V
2010-08-01
The Department of Defense (DoD) Military Health System (MHS) embodies decades of health care practice that has evolved in scope and complexity to meet the demands for quality care to which its beneficiaries are entitled. War, Base Realignment and Closure (BRAC), and other dynamic forces require the ongoing review and revision of health care policy and practice in military hospitals as well as the expanded network of civilian providers who care for our nation's soldiers, sailors, airmen, and marines and their families. The result has been an incrementally constructed quality assurance (QA) program with emphasis on organizational structures, programs, and systems, and the use of robust data sources and standard measures to analyze and improve processes, manage disease, assess patient perceptions of care, and ensure that a uniform health care benefit and high quality health care is accessible to all MHS beneficiaries.
Evolution of regulatory networks towards adaptability and stability in a changing environment
NASA Astrophysics Data System (ADS)
Lee, Deok-Sun
2014-11-01
Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.
Benefits of tolerance in public goods games.
Szolnoki, Attila; Chen, Xiaojie
2015-10-01
Leaving the joint enterprise when defection is unveiled is always a viable option to avoid being exploited. Although loner strategy helps the population not to be trapped into the tragedy of the commons state, it could offer only a modest income for nonparticipants. In this paper we demonstrate that showing some tolerance toward defectors could not only save cooperation in harsh environments but in fact results in a surprisingly high average payoff for group members in public goods games. Phase diagrams and the underlying spatial patterns reveal the high complexity of evolving states where cyclic dominant strategies or two-strategy alliances can characterize the final state of evolution. We identify microscopic mechanisms which are responsible for the superiority of global solutions containing tolerant players. This phenomenon is robust and can be observed both in well-mixed and in structured populations highlighting the importance of tolerance in our everyday life.
Translation Control: A Multifaceted Regulator of Inflammatory Response
Mazumder, Barsanjit; Li, Xiaoxia; Barik, Sailen
2010-01-01
A robust innate immune response is essential to the protection of all vertebrates from infection, but it often comes with the price tag of acute inflammation. If unchecked, a runaway inflammatory response can cause significant tissue damage, resulting in myriad disorders, such as dermatitis, toxicshock, cardiovascular disease, acute pelvic and arthritic inflammatory diseases, and various infections. To prevent such pathologies, cells have evolved mechanisms to rapidly and specifically shut off these beneficial inflammatory activities before they become detrimental. Our review of recent literature, including our own work, reveals that the most dominant and common mechanism is translational silencing, in which specific regulatory proteins or complexes are recruited to cis-acting RNA structures in the untranslated regions of single or multiple mRNAs that code for the inflammatory protein(s). Enhancement of the silencing function may constitute a novel pharmacological approach to prevent immunity-related inflammation. PMID:20304832
Translation control: a multifaceted regulator of inflammatory response.
Mazumder, Barsanjit; Li, Xiaoxia; Barik, Sailen
2010-04-01
A robust innate immune response is essential to the protection of all vertebrates from infection, but it often comes with the price tag of acute inflammation. If unchecked, a runaway inflammatory response can cause significant tissue damage, resulting in myriad disorders, such as dermatitis, toxic shock, cardiovascular disease, acute pelvic and arthritic inflammatory diseases, and various infections. To prevent such pathologies, cells have evolved mechanisms to rapidly and specifically shut off these beneficial inflammatory activities before they become detrimental. Our review of recent literature, including our own work, reveals that the most dominant and common mechanism is translational silencing, in which specific regulatory proteins or complexes are recruited to cis-acting RNA structures in the untranslated regions of single or multiple mRNAs that code for the inflammatory protein(s). Enhancement of the silencing function may constitute a novel pharmacological approach to prevent immunity-related inflammation.
Enabling Technology to Advance Health-Protecting Individual Rights-Are We Walking the Talk?
NASA Astrophysics Data System (ADS)
Sharp, Crystal; Gwadry-Sridhar, Femida
The evolving structure and business of health care services and delivery need the functionality and capability offered by electronic health record (EHR) systems. By electronically diffusing the traditional patient record, however, this new model blurs the long-established medical data home, raising concerns about data ownership, confidentiality, access and individual rights. In 2008 the Lawson Health Research Institute began the process of instituting a robust health informatics and collaborative research infrastructure, now known as I-THINK Research. As data are migrated to the platform and policies are developed, we are forced to confront the complexity of issues around protection of individual rights. The paper presents, in a broader context, the main issues surrounding the privacy debate and the need for education, accountability and new legislation to help define and protect individual rights as new e-health business models emerge.
Model-free learning on robot kinematic chains using a nested multi-agent topology
NASA Astrophysics Data System (ADS)
Karigiannis, John N.; Tzafestas, Costas S.
2016-11-01
This paper proposes a model-free learning scheme for the developmental acquisition of robot kinematic control and dexterous manipulation skills. The approach is based on a nested-hierarchical multi-agent architecture that intuitively encapsulates the topology of robot kinematic chains, where the activity of each independent degree-of-freedom (DOF) is finally mapped onto a distinct agent. Each one of those agents progressively evolves a local kinematic control strategy in a game-theoretic sense, that is, based on a partial (local) view of the whole system topology, which is incrementally updated through a recursive communication process according to the nested-hierarchical topology. Learning is thus approached not through demonstration and training but through an autonomous self-exploration process. A fuzzy reinforcement learning scheme is employed within each agent to enable efficient exploration in a continuous state-action domain. This paper constitutes in fact a proof of concept, demonstrating that global dexterous manipulation skills can indeed evolve through such a distributed iterative learning of local agent sensorimotor mappings. The main motivation behind the development of such an incremental multi-agent topology is to enhance system modularity, to facilitate extensibility to more complex problem domains and to improve robustness with respect to structural variations including unpredictable internal failures. These attributes of the proposed system are assessed in this paper through numerical experiments in different robot manipulation task scenarios, involving both single and multi-robot kinematic chains. The generalisation capacity of the learning scheme is experimentally assessed and robustness properties of the multi-agent system are also evaluated with respect to unpredictable variations in the kinematic topology. Furthermore, these numerical experiments demonstrate the scalability properties of the proposed nested-hierarchical architecture, where new agents can be recursively added in the hierarchy to encapsulate individual active DOFs. The results presented in this paper demonstrate the feasibility of such a distributed multi-agent control framework, showing that the solutions which emerge are plausible and near-optimal. Numerical efficiency and computational cost issues are also discussed.
Effects of topology on network evolution
NASA Astrophysics Data System (ADS)
Oikonomou, Panos; Cluzel, Philippe
2006-08-01
The ubiquity of scale-free topology in nature raises the question of whether this particular network design confers an evolutionary advantage. A series of studies has identified key principles controlling the growth and the dynamics of scale-free networks. Here, we use neuron-based networks of boolean components as a framework for modelling a large class of dynamical behaviours in both natural and artificial systems. Applying a training algorithm, we characterize how networks with distinct topologies evolve towards a pre-established target function through a process of random mutations and selection. We find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. Whereas homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously. Remarkably, this latter property is robust to variations of the degree exponent. In contrast, homogeneous random networks require a specific tuning of their connectivity to optimize their ability to evolve. These results highlight an organizing principle that governs the evolution of complex networks and that can improve the design of engineered systems.
Robust control for uncertain structures
NASA Technical Reports Server (NTRS)
Douglas, Joel; Athans, Michael
1991-01-01
Viewgraphs on robust control for uncertain structures are presented. Topics covered include: robust linear quadratic regulator (RLQR) formulas; mismatched LQR design; RLQR design; interpretations of RLQR design; disturbance rejection; and performance comparisons: RLQR vs. mismatched LQR.
Evolving Organizational Structures in Special Education.
ERIC Educational Resources Information Center
McCarthy, Eileen F., Ed.; Sage, Daniel D., Ed.
The monograph addresses evolving organizational structures in special education from the perspectives of theory and practice. The initial paper, "Issues in Organizational Structure" (D. Sage), focuses on how the multiple units and operations of the special education system should be related and how the management authority and responsibility for…
Modern CACSD using the Robust-Control Toolbox
NASA Technical Reports Server (NTRS)
Chiang, Richard Y.; Safonov, Michael G.
1989-01-01
The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.
Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity
NASA Technical Reports Server (NTRS)
Frost, S. A.; Balas, M. J.
2010-01-01
We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.
Parente, Daniel J; Ray, J Christian J; Swint-Kruse, Liskin
2015-12-01
As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions. © 2015 Wiley Periodicals, Inc.
Catching Galactic open clusters in advanced stages of dynamical evolution
NASA Astrophysics Data System (ADS)
Angelo, M. S.; Piatti, A. E.; Dias, W. S.; Maia, F. F. S.
2018-04-01
During their dynamical evolution, Galactic open clusters (OCs) gradually lose their stellar content mainly because of internal relaxation and tidal forces. In this context, the study of dynamically evolved OCs is necessary to properly understand such processes. We present a comprehensive Washington CT1 photometric analysis of six sparse OCs, namely: ESO 518-3, Ruprecht 121, ESO 134-12, NGC 6573, ESO 260-7 and ESO 065-7. We employed Markov chain Monte-Carlo simulations to robustly determine the central coordinates and the structural parameters and T1 × (C - T1) colour-magnitude diagrams (CMDs) cleaned from field contamination were used to derive the fundamental parameters. ESO 518-03, Ruprecht 121, ESO 134-12 and NGC 6573 resulted to be of nearly the same young age (8.2 ≤log(t yr-1) ≤ 8.3); ESO 260-7 and ESO065-7 are of intermediate age (9.2 ≤log(t yr-1) ≤ 9.4). All studied OCs are located at similar Galactocentric distances (RG ˜ 6 - 6.9 kpc), considering uncertainties, except for ESO 260-7 (RG = 8.9 kpc). These OCs are in a tidally filled regime and are dynamically evolved, since they are much older than their half-mass relaxation times (t/trh ≳ 30) and present signals of low-mass star depletion. We distinguished two groups: those dynamically evolving towards final disruptions and those in an advanced dynamical evolutionary stage. Although we do not rule out that the Milky Way potential could have made differentially faster their dynamical evolutions, we speculate here with the possibility that they have been mainly driven by initial formation conditions.
Catching Galactic open clusters in advanced stages of dynamical evolution
NASA Astrophysics Data System (ADS)
Angelo, M. S.; Piatti, A. E.; Dias, W. S.; Maia, F. F. S.
2018-07-01
During their dynamical evolution, Galactic open clusters (OCs) gradually lose their stellar content mainly because of internal relaxation and tidal forces. In this context, the study of dynamically evolved OCs is necessary to properly understand such processes. We present a comprehensive Washington CT1 photometric analysis of six sparse OCs, namely ESO 518-3, Ruprecht 121, ESO 134-12, NGC 6573, ESO 260-7, and ESO 065-7. We employed Markov chain Monte Carlo simulations to robustly determine the central coordinates and the structural parameters and T1 × (C - T1) colour-magnitude diagrams cleaned from field contamination were used to derive the fundamental parameters. ESO 518-03, Ruprecht 121, ESO 134-12, and NGC 6573 resulted to be of nearly the same young age [8.2 ≤log(t yr-1) ≤ 8.3]; ESO 260-7 and ESO065-7 are of intermediate age [9.2 ≤log(t yr-1) ≤ 9.4]. All studied OCs are located at similar Galactocentric distances (RG ˜6-6.9 kpc), considering uncertainties, except for ESO 260-7 (RG = 8.9 kpc). These OCs are in a tidally filled regime and are dynamically evolved, since they are much older than their half-mass relaxation times (t/trh ≳ 30) and present signals of low-mass star depletion. We distinguished two groups: those dynamically evolving towards final disruptions and those in an advanced dynamical evolutionary stage. Although we do not rule out that the Milky Way potential could have made differentially faster their dynamical evolutions, we speculate here with the possibility that they have been mainly driven by initial formation conditions.
Mutation Bias Favors Protein Folding Stability in the Evolution of Small Populations
Porto, Markus; Bastolla, Ugo
2010-01-01
Mutation bias in prokaryotes varies from extreme adenine and thymine (AT) in obligatory endosymbiotic or parasitic bacteria to extreme guanine and cytosine (GC), for instance in actinobacteria. GC mutation bias deeply influences the folding stability of proteins, making proteins on the average less hydrophobic and therefore less stable with respect to unfolding but also less susceptible to misfolding and aggregation. We study a model where proteins evolve subject to selection for folding stability under given mutation bias, population size, and neutrality. We find a non-neutral regime where, for any given population size, there is an optimal mutation bias that maximizes fitness. Interestingly, this optimal GC usage is small for small populations, large for intermediate populations and around 50% for large populations. This result is robust with respect to the definition of the fitness function and to the protein structures studied. Our model suggests that small populations evolving with small GC usage eventually accumulate a significant selective advantage over populations evolving without this bias. This provides a possible explanation to the observation that most species adopting obligatory intracellular lifestyles with a consequent reduction of effective population size shifted their mutation spectrum towards AT. The model also predicts that large GC usage is optimal for intermediate population size. To test these predictions we estimated the effective population sizes of bacterial species using the optimal codon usage coefficients computed by dos Reis et al. and the synonymous to non-synonymous substitution ratio computed by Daubin and Moran. We found that the population sizes estimated in these ways are significantly smaller for species with small and large GC usage compared to species with no bias, which supports our prediction. PMID:20463869
Najafpour, Mohammad Mahdi
2011-01-01
The oxygen evolving complex in photosystem II which induces the oxidation of water to dioxygen in plants, algae and certain bacteria contains a cluster of one calcium and four manganese ions. It serves as a model to split water by sunlight. Reports on the mechanism and structure of photosystem II provide a more detailed architecture of the oxygen evolving complex and the surrounding amino acids. One challenge in this field is the development of artificial model compounds to study oxygen evolution reaction outside the complicated environment of the enzyme. Calcium-manganese oxides as structural and functional models for the active site of photosystem II are explained and reviewed in this paper. Because of related structures of these calcium-manganese oxides and the catalytic centers of active site of the oxygen evolving complex of photosystem II, the study may help to understand more about mechanism of oxygen evolution by the oxygen evolving complex of photosystem II. Copyright © 2010 Elsevier B.V. All rights reserved.
Visualization of evolving laser-generated structures by frequency domain tomography
NASA Astrophysics Data System (ADS)
Chang, Yenyu; Li, Zhengyan; Wang, Xiaoming; Zgadzaj, Rafal; Downer, Michael
2011-10-01
We introduce frequency domain tomography (FDT) for single-shot visualization of time-evolving refractive index structures (e.g. laser wakefields, nonlinear index structures) moving at light-speed. Previous researchers demonstrated single-shot frequency domain holography (FDH), in which a probe-reference pulse pair co- propagates with the laser-generated structure, to obtain snapshot-like images. However, in FDH, information about the structure's evolution is averaged. To visualize an evolving structure, we use several frequency domain streak cameras (FDSCs), in each of which a probe-reference pulse pair propagates at an angle to the propagation direction of the laser-generated structure. The combination of several FDSCs constitutes the FDT system. We will present experimental results for a 4-probe FDT system that has imaged the whole-beam self-focusing of a pump pulse propagating through glass in a single laser shot. Combining temporal and angle multiplexing methods, we successfully processed data from four probe pulses in one spectrometer in a single-shot. The output of data processing is a multi-frame movie of the self- focusing pulse. Our results promise the possibility of visualizing evolving laser wakefield structures that underlie laser-plasma accelerators used for multi-GeV electron acceleration.
ERIC Educational Resources Information Center
Darwin, Stephen
2011-01-01
Cultural-historical activity theory (CHAT), founded on the seminal work of Vygotsky and evolving in the subsequent work of Leont'ev and Engestrom, continues to emerge as a robust and increasingly widely used conceptual framework for the research and analysis of the complex social mediation of human learning and development. Yet there remains…
Selfish cellular networks and the evolution of complex organisms.
Kourilsky, Philippe
2012-03-01
Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment. Copyright © 2012 Académie des sciences. Published by Elsevier SAS. All rights reserved.
Genonets server-a web server for the construction, analysis and visualization of genotype networks.
Khalid, Fahad; Aguilar-Rodríguez, José; Wagner, Andreas; Payne, Joshua L
2016-07-08
A genotype network is a graph in which vertices represent genotypes that have the same phenotype. Edges connect vertices if their corresponding genotypes differ in a single small mutation. Genotype networks are used to study the organization of genotype spaces. They have shed light on the relationship between robustness and evolvability in biological systems as different as RNA macromolecules and transcriptional regulatory circuits. Despite the importance of genotype networks, no tool exists for their automatic construction, analysis and visualization. Here we fill this gap by presenting the Genonets Server, a tool that provides the following features: (i) the construction of genotype networks for categorical and univariate phenotypes from DNA, RNA, amino acid or binary sequences; (ii) analyses of genotype network topology and how it relates to robustness and evolvability, as well as analyses of genotype network topography and how it relates to the navigability of a genotype network via mutation and natural selection; (iii) multiple interactive visualizations that facilitate exploratory research and education. The Genonets Server is freely available at http://ieu-genonets.uzh.ch. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.
Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke
2016-01-01
Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.
Evolution of canalizing Boolean networks
NASA Astrophysics Data System (ADS)
Szejka, A.; Drossel, B.
2007-04-01
Boolean networks with canalizing functions are used to model gene regulatory networks. In order to learn how such networks may behave under evolutionary forces, we simulate the evolution of a single Boolean network by means of an adaptive walk, which allows us to explore the fitness landscape. Mutations change the connections and the functions of the nodes. Our fitness criterion is the robustness of the dynamical attractors against small perturbations. We find that with this fitness criterion the global maximum is always reached and that there is a huge neutral space of 100% fitness. Furthermore, in spite of having such a high degree of robustness, the evolved networks still share many features with “chaotic” networks.
Robustness trade-offs and host–microbial symbiosis in the immune system
Kitano, Hiroaki; Oda, Kanae
2006-01-01
The immune system provides organisms with robustness against pathogen threats, yet it also often adversely affects the organism as in autoimmune diseases. Recently, the molecular interactions involved in the immune system have been uncovered. At the same time, the role of the bacterial flora and its interactions with the host immune system have been identified. In this article, we try to reconcile these findings to draw a consistent picture of the host defense system. Specifically, we first argue that the network of molecular interactions involved in immune functions has a bow-tie architecture that entails inherent trade-offs among robustness, fragility, resource limitation, and performance. Second, we discuss the possibility that commensal bacteria and the host immune system constitute an integrated defense system. This symbiotic association has evolved to optimize its robustness against pathogen attacks and nutrient perturbations by harboring a broad range of microorganisms. Owing to the inherent propensity of a host immune system toward hyperactivity, maintenance of bacterial flora homeostasis might be particularly important in the development of preventive strategies against immune disorders such as autoimmune diseases. PMID:16738567
Betz, J.W.; Cahn, C.R.; Dafesh, P.A.; Hegarty, C.J.; Hudnut, K.W.; Jones, A.J.; Keegan, R.; Kovach, K.; Lenahan, L.S.; Ma, H.H.; Rushanan, J.J.; Stansell, T.A.; Wang, C.C.; Yi, S.K.
2006-01-01
Design activities for a new civil signal centered at 1575.42 MHz, called L1C, began in 2003, and the Phase 1 effort was completed in 2004. The L1C signal design has evolved and matured during a Phase 2 design activity that began in 2005. Phase 2 has built on the initial design activity, guided by responses to international user surveys conducted during Phase 1. A common core of signal characteristics has been developed to provide advances in robustness and performance. The Phase 2 activity produced five design options, all drawing upon the core signal characteristics, while representing different blends of characteristics and capabilities. A second round of international user surveys was completed to solicit advice concerning these design options. This paper provides an update of the L1C design process, and describes the current L1C design options. Initial performance estimates are presented for each design option, displaying trades between signal tracking robustness, the speed and robustness of clock and ephemeris data, and the rate and robustness of other data message contents. Planned remaining activities are summarized, leading to optimization of the L1C design.
Whitacre, James M; Rohlfshagen, Philipp; Bender, Axel; Yao, Xin
2012-09-01
Engineered systems are designed to deftly operate under predetermined conditions yet are notoriously fragile when unexpected perturbations arise. In contrast, biological systems operate in a highly flexible manner; learn quickly adequate responses to novel conditions, and evolve new routines and traits to remain competitive under persistent environmental change. A recent theory on the origins of biological flexibility has proposed that degeneracy-the existence of multi-functional components with partially overlapping functions-is a primary determinant of the robustness and adaptability found in evolved systems. While degeneracy's contribution to biological flexibility is well documented, there has been little investigation of degeneracy design principles for achieving flexibility in systems engineering. Actually, the conditions that can lead to degeneracy are routinely eliminated in engineering design. With the planning of transportation vehicle fleets taken as a case study, this article reports evidence that degeneracy improves the robustness and adaptability of a simulated fleet towards unpredicted changes in task requirements without incurring costs to fleet efficiency. We find that degeneracy supports faster rates of design adaptation and ultimately leads to better fleet designs. In investigating the limitations of degeneracy as a design principle, we consider decision-making difficulties that arise from degeneracy's influence on fleet complexity. While global decision-making becomes more challenging, we also find degeneracy accommodates rapid distributed decision-making leading to (near-optimal) robust system performance. Given the range of conditions where favorable short-term and long-term performance outcomes are observed, we propose that degeneracy may fundamentally alter the propensity for adaptation and is useful within different engineering and planning contexts.
Wang, Yueliang; Fang, Lingling; Chen, Gaoli; Song, Lei; Deng, Zhaoxiang
2018-02-01
Despite the versatile forms of colloidal aggregates, these spontaneously formed structures are often hard to find a suitable application in nanotechnology and materials science. A determinate reason is the lack of a suitable method to capture the transiently formed and quickly evolving colloidal structures in solution. To address this challenge, a simple but highly efficient strategy is herein reported to capture the dynamic and metastable colloidal assemblies formed in an aqueous or nonaqueous solution. This process takes advantage of a recently developed Ag ion soldering reaction to realize a rapid fixation of as-formed metastable assemblies. This method works efficiently for both solid (3D) nanoparticle aggregates and weakly bonded fractal nanoparticle chains (1D). In both cases, very high capturing speed and close to 100% efficiency are achieved to fully retain a quickly growing structure. The soldered nanochains further enable a fabrication of discrete, uniform, and functionalizable nanoparticle clusters with enriched linear conformation by mechanical shearing, which would otherwise be difficult to make. The captured products are water dispersible and mechanically robust, favoring an exploration of their properties toward possible applications. The work paves a way to previously untouched aspects of colloidal science and thus would create new chances in nanotechnology. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Arregui, Sergio; Marinova, Dessislava; Sanz, Joaquín
2018-01-01
In the case of tuberculosis (TB), the capabilities of epidemic models to produce quantitatively robust forecasts are limited by multiple hindrances. Among these, understanding the complex relationship between disease epidemiology and populations’ age structure has been highlighted as one of the most relevant. TB dynamics depends on age in multiple ways, some of which are traditionally simplified in the literature. That is the case of the heterogeneities in contact intensity among different age strata that are common to all airborne diseases, but still typically neglected in the TB case. Furthermore, while demographic structures of many countries are rapidly aging, demographic dynamics are pervasively ignored when modeling TB spreading. In this work, we present a TB transmission model that incorporates country-specific demographic prospects and empirical contact data around a data-driven description of TB dynamics. Using our model, we find that the inclusion of demographic dynamics is followed by an increase in the burden levels predicted for the next decades in the areas of the world that are most hit by the disease today. Similarly, we show that considering realistic patterns of contacts among individuals in different age strata reshapes the transmission patterns reproduced by the models, a result with potential implications for the design of age-focused epidemiological interventions. PMID:29563223
Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli
Swings, Toon; Van den Bergh, Bram; Wuyts, Sander; Oeyen, Eline; Voordeckers, Karin; Verstrepen, Kevin J; Fauvart, Maarten; Verstraeten, Natalie; Michiels, Jan
2017-01-01
While specific mutations allow organisms to adapt to stressful environments, most changes in an organism's DNA negatively impact fitness. The mutation rate is therefore strictly regulated and often considered a slowly-evolving parameter. In contrast, we demonstrate an unexpected flexibility in cellular mutation rates as a response to changes in selective pressure. We show that hypermutation independently evolves when different Escherichia coli cultures adapt to high ethanol stress. Furthermore, hypermutator states are transitory and repeatedly alternate with decreases in mutation rate. Specifically, population mutation rates rise when cells experience higher stress and decline again once cells are adapted. Interestingly, we identified cellular mortality as the major force driving the quick evolution of mutation rates. Together, these findings show how organisms balance robustness and evolvability and help explain the prevalence of hypermutation in various settings, ranging from emergence of antibiotic resistance in microbes to cancer relapses upon chemotherapy. DOI: http://dx.doi.org/10.7554/eLife.22939.001 PMID:28460660
Computational structural mechanics methods research using an evolving framework
NASA Technical Reports Server (NTRS)
Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.
1990-01-01
Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.
NASA Astrophysics Data System (ADS)
Funnell, M. J.; Peirce, C.; Robinson, A. H.
2017-09-01
Subducting bathymetric anomalies enhance erosion of the overriding forearc crust. The deformation associated with this process is superimposed on pre-existing variable crustal and sedimentary structures developed as a subduction system evolves. Recent attempts to determine the effect and timescale of Louisville Ridge seamount subduction on the Tonga-Kermadec forearc have been limited by simplistic models of inherited overriding crustal structure that neglect along-strike variability. Synthesis of new robustly tested seismic velocity and density models with existing data sets from the region, highlight along-strike variations in the structure of the Tonga-Kermadec subducting and overriding plates. As the subducting plate undergoes bend-faulting and hydration throughout the trench-outer rise region, observed oceanic upper- and mid-crustal velocities are reduced by ∼1.0 km s-1 and upper mantle velocities by ∼0.5 km s-1. In the vicinity of the Louisville Ridge Seamount Chain (LRSC), the trench shallows by 4 km and normal fault throw is reduced by >1 km, suggesting that the subduction of seamounts reduces plate deformation. We find that the extinct Eocene frontal arc, defined by a high velocity (7.0-7.4 km s-1) and density (3.2 g cm-3) lower-crustal anomaly, increases in thickness by ∼6 km, from 12 to >18 km, over 300 km laterally along the Tonga-Kermadec forearc. Coincident variations in bathymetry and free-air gravity anomaly indicate a regional trend of northward-increasing crustal thickness that predates LRSC subduction, and highlight the present-day extent of the Eocene arc between 32°S and ∼18°S. Within this framework of existing forearc crustal structure, the subduction of seamounts of the LRSC promotes erosion of the overriding crust, forming steep, gravitationally unstable, lower-trench slopes. Trench-slope stability is most likely re-established by the collapse of the mid-trench slope and the trenchward side of the extinct Eocene arc, which, within the framework of forearc characterization, implies seamount subduction commenced at ∼22°S.
A Robust Scalable Transportation System Concept
NASA Technical Reports Server (NTRS)
Hahn, Andrew; DeLaurentis, Daniel
2006-01-01
This report documents the 2005 Revolutionary System Concept for Aeronautics (RSCA) study entitled "A Robust, Scalable Transportation System Concept". The objective of the study was to generate, at a high-level of abstraction, characteristics of a new concept for the National Airspace System, or the new NAS, under which transportation goals such as increased throughput, delay reduction, and improved robustness could be realized. Since such an objective can be overwhelmingly complex if pursued at the lowest levels of detail, instead a System-of-Systems (SoS) approach was adopted to model alternative air transportation architectures at a high level. The SoS approach allows the consideration of not only the technical aspects of the NAS", but also incorporates policy, socio-economic, and alternative transportation system considerations into one architecture. While the representations of the individual systems are basic, the higher level approach allows for ways to optimize the SoS at the network level, determining the best topology (i.e. configuration of nodes and links). The final product (concept) is a set of rules of behavior and network structure that not only satisfies national transportation goals, but represents the high impact rules that accomplish those goals by getting the agents to "do the right thing" naturally. The novel combination of Agent Based Modeling and Network Theory provides the core analysis methodology in the System-of-Systems approach. Our method of approach is non-deterministic which means, fundamentally, it asks and answers different questions than deterministic models. The nondeterministic method is necessary primarily due to our marriage of human systems with technological ones in a partially unknown set of future worlds. Our goal is to understand and simulate how the SoS, human and technological components combined, evolve.
Laboratory evolution of copper tolerant yeast strains
2012-01-01
Background Yeast strains endowed with robustness towards copper and/or enriched in intracellular Cu might find application in biotechnology processes, among others in the production of functional foods. Moreover, they can contribute to the study of human diseases related to impairments of copper metabolism. In this study, we investigated the molecular and physiological factors that confer copper tolerance to strains of baker's yeasts. Results We characterized the effects elicited in natural strains of Candida humilis and Saccharomyces cerevisiae by the exposure to copper in the culture broth. We observed that, whereas the growth of Saccharomyces cells was inhibited already at low Cu concentration, C. humilis was naturally robust and tolerated up to 1 g · L-1 CuSO4 in the medium. This resistant strain accumulated over 7 mg of Cu per gram of biomass and escaped severe oxidative stress thanks to high constitutive levels of superoxide dismutase and catalase. Both yeasts were then "evolved" to obtain hyper-resistant cells able to proliferate in high copper medium. While in S. cerevisiae the evolution of robustness towards Cu was paralleled by the increase of antioxidative enzymes, these same activities decreased in evolved hyper-resistant Candida cells. We also characterized in some detail changes in the profile of copper binding proteins, that appeared to be modified by evolution but, again, in a different way in the two yeasts. Conclusions Following evolution, both Candida and Saccharomyces cells were able to proliferate up to 2.5 g · L-1 CuSO4 and to accumulate high amounts of intracellular copper. The comparison of yeasts differing in their robustness, allowed highlighting physiological and molecular determinants of natural and acquired copper tolerance. We observed that different mechanisms contribute to confer metal tolerance: the control of copper uptake, changes in the levels of enzymes involved in oxidative stress response and changes in the copper-binding proteome. However, copper elicits different physiological and molecular reactions in yeasts with different backgrounds. PMID:22214286
From mobile phone data to the spatial structure of cities
Louail, Thomas; Lenormand, Maxime; Cantu Ros, Oliva G.; Picornell, Miguel; Herranz, Ricardo; Frias-Martinez, Enrique; Ramasco, José J.; Barthelemy, Marc
2014-01-01
Pervasive infrastructures, such as cell phone networks, enable to capture large amounts of human behavioral data but also provide information about the structure of cities and their dynamical properties. In this article, we focus on these last aspects by studying phone data recorded during 55 days in 31 Spanish cities. We first define an urban dilatation index which measures how the average distance between individuals evolves during the day, allowing us to highlight different types of city structure. We then focus on hotspots, the most crowded places in the city. We propose a parameter free method to detect them and to test the robustness of our results. The number of these hotspots scales sublinearly with the population size, a result in agreement with previous theoretical arguments and measures on employment datasets. We study the lifetime of these hotspots and show in particular that the hierarchy of permanent ones, which constitute the ‘heart' of the city, is very stable whatever the size of the city. The spatial structure of these hotspots is also of interest and allows us to distinguish different categories of cities, from monocentric and “segregated” where the spatial distribution is very dependent on land use, to polycentric where the spatial mixing between land uses is much more important. These results point towards the possibility of a new, quantitative classification of cities using high resolution spatio-temporal data. PMID:24923248
Globalization to amplify economic climate losses
NASA Astrophysics Data System (ADS)
Otto, C.; Wenz, L.; Levermann, A.
2015-12-01
Economic welfare under enhanced anthropogenic carbon emissions and associated future warming poses a major challenge for a society with an evolving globally connected economy. Unabated climate change will impact economic output for example through heat-stress-related reductions in productivity. Since meteorologically-induced production reductions can propagate along supply chains, structural changes in the economic network may influence climate-related losses. The role of the economic network evolution for climate impacts has been neither quantified nor qualitatively understood. Here we show that since the beginning of the 21st century the structural change of the global supply network has been such that an increase of spillover losses due to unanticipated climatic events has to be expected. We quantify primary, secondary and higher-order losses from reduced labor productivity under past and present economic and climatic conditions and find that indirect losses are significant and increase with rising temperatures. The connectivity of the economic network has increased in such a way as to foster the propagation of production loss. This supply chain connectivity robustly exhibits the characteristic distribution of self-organized criticality which has been shifted towards higher values since 2001. Losses due to this structural evolution dominated over the effect of comparably weak climatic changes during this decade. Our finding suggests that the current form of globalization may amplify losses due to climatic extremes and thus necessitate structural adaptation that requires more foresight than presently prevalent.
Hendy, Jane; Chrysanthaki, Theopisti; Barlow, James; Knapp, Martin; Rogers, Anne; Sanders, Caroline; Bower, Peter; Bowen, Robert; Fitzpatrick, Ray; Bardsley, Martin; Newman, Stanton
2012-11-15
To investigate organisational factors influencing the implementation challenges of redesigning services for people with long term conditions in three locations in England, using remote care (telehealth and telecare). Case-studies of three sites forming the UK Department of Health's Whole Systems Demonstrator (WSD) Programme. Qualitative research techniques were used to obtain data from various sources, including semi-structured interviews, observation of meetings over the course programme and prior to its launch, and document review. Participants were managers and practitioners involved in the implementation of remote care services. The implementation of remote care was nested within a large pragmatic cluster randomised controlled trial (RCT), which formed a core element of the WSD programme. To produce robust benefits evidence, many aspect of the trial design could not be easily adapted to local circumstances. While remote care was successfully rolled-out, wider implementation lessons and levels of organisational learning across the sites were hindered by the requirements of the RCT. The implementation of a complex innovation such as remote care requires it to organically evolve, be responsive and adaptable to the local health and social care system, driven by support from front-line staff and management. This need for evolution was not always aligned with the imperative to gather robust benefits evidence. This tension needs to be resolved if government ambitions for the evidence-based scaling-up of remote care are to be realised.
Pulse register phonation in Diana monkey alarm calls
NASA Astrophysics Data System (ADS)
Riede, Tobias; Zuberbühler, Klaus
2003-05-01
The adult male Diana monkeys (Cercopithecus diana) produce predator-specific alarm calls in response to two of their predators, the crowned eagles and the leopards. The acoustic structure of these alarm calls is remarkable for a number of theoretical and empirical reasons. First, although pulsed phonation has been described in a variety of mammalian vocalizations, very little is known about the underlying production mechanism. Second, Diana monkey alarm calls are based almost exclusively on this vocal production mechanism to an extent that has never been documented in mammalian vocal behavior. Finally, the Diana monkeys' pulsed phonation strongly resembles the pulse register in human speech, where fundamental frequency is mainly controlled by subglottal pressure. Here, we report the results of a detailed acoustic analysis to investigate the production mechanism of Diana monkey alarm calls. Within calls, we found a positive correlation between the fundamental frequency and the pulse amplitude, suggesting that both humans and monkeys control fundamental frequency by subglottal pressure. While in humans pulsed phonation is usually considered pathological or artificial, male Diana monkeys rely exclusively on pulsed phonation, suggesting a functional adaptation. Moreover, we were unable to document any nonlinear phenomena, despite the fact that they occur frequently in the vocal repertoire of humans and nonhumans, further suggesting that the very robust Diana monkey pulse production mechanism has evolved for a particular functional purpose. We discuss the implications of these findings for the structural evolution of Diana monkey alarm calls and suggest that the restricted variability in fundamental frequency and robustness of the source signal gave rise to the formant patterns observed in Diana monkey alarm calls, used to convey predator information.
Trade-offs between robustness and small-world effect in complex networks
Peng, Guan-Sheng; Tan, Suo-Yi; Wu, Jun; Holme, Petter
2016-01-01
Robustness and small-world effect are two crucial structural features of complex networks and have attracted increasing attention. However, little is known about the relation between them. Here we demonstrate that, there is a conflicting relation between robustness and small-world effect for a given degree sequence. We suggest that the robustness-oriented optimization will weaken the small-world effect and vice versa. Then, we propose a multi-objective trade-off optimization model and develop a heuristic algorithm to obtain the optimal trade-off topology for robustness and small-world effect. We show that the optimal network topology exhibits a pronounced core-periphery structure and investigate the structural properties of the optimized networks in detail. PMID:27853301
A kriging metamodel-assisted robust optimization method based on a reverse model
NASA Astrophysics Data System (ADS)
Zhou, Hui; Zhou, Qi; Liu, Congwei; Zhou, Taotao
2018-02-01
The goal of robust optimization methods is to obtain a solution that is both optimum and relatively insensitive to uncertainty factors. Most existing robust optimization approaches use outer-inner nested optimization structures where a large amount of computational effort is required because the robustness of each candidate solution delivered from the outer level should be evaluated in the inner level. In this article, a kriging metamodel-assisted robust optimization method based on a reverse model (K-RMRO) is first proposed, in which the nested optimization structure is reduced into a single-loop optimization structure to ease the computational burden. Ignoring the interpolation uncertainties from kriging, K-RMRO may yield non-robust optima. Hence, an improved kriging-assisted robust optimization method based on a reverse model (IK-RMRO) is presented to take the interpolation uncertainty of kriging metamodel into consideration. In IK-RMRO, an objective switching criterion is introduced to determine whether the inner level robust optimization or the kriging metamodel replacement should be used to evaluate the robustness of design alternatives. The proposed criterion is developed according to whether or not the robust status of the individual can be changed because of the interpolation uncertainties from the kriging metamodel. Numerical and engineering cases are used to demonstrate the applicability and efficiency of the proposed approach.
Artificial selection for structural color on butterfly wings and comparison with natural evolution
Wasik, Bethany R.; Liew, Seng Fatt; Lilien, David A.; Dinwiddie, April J.; Noh, Heeso; Cao, Hui; Monteiro, Antónia
2014-01-01
Brilliant animal colors often are produced from light interacting with intricate nano-morphologies present in biological materials such as butterfly wing scales. Surveys across widely divergent butterfly species have identified multiple mechanisms of structural color production; however, little is known about how these colors evolved. Here, we examine how closely related species and populations of Bicyclus butterflies have evolved violet structural color from brown-pigmented ancestors with UV structural color. We used artificial selection on a laboratory model butterfly, B. anynana, to evolve violet scales from UV brown scales and compared the mechanism of violet color production with that of two other Bicyclus species, Bicyclus sambulos and Bicyclus medontias, which have evolved violet/blue scales independently via natural selection. The UV reflectance peak of B. anynana brown scales shifted to violet over six generations of artificial selection (i.e., in less than 1 y) as the result of an increase in the thickness of the lower lamina in ground scales. Similar scale structures and the same mechanism for producing violet/blue structural colors were found in the other Bicyclus species. This work shows that populations harbor large amounts of standing genetic variation that can lead to rapid evolution of scales’ structural color via slight modifications to the scales’ physical dimensions. PMID:25092295
Artificial selection for structural color on butterfly wings and comparison with natural evolution.
Wasik, Bethany R; Liew, Seng Fatt; Lilien, David A; Dinwiddie, April J; Noh, Heeso; Cao, Hui; Monteiro, Antónia
2014-08-19
Brilliant animal colors often are produced from light interacting with intricate nano-morphologies present in biological materials such as butterfly wing scales. Surveys across widely divergent butterfly species have identified multiple mechanisms of structural color production; however, little is known about how these colors evolved. Here, we examine how closely related species and populations of Bicyclus butterflies have evolved violet structural color from brown-pigmented ancestors with UV structural color. We used artificial selection on a laboratory model butterfly, B. anynana, to evolve violet scales from UV brown scales and compared the mechanism of violet color production with that of two other Bicyclus species, Bicyclus sambulos and Bicyclus medontias, which have evolved violet/blue scales independently via natural selection. The UV reflectance peak of B. anynana brown scales shifted to violet over six generations of artificial selection (i.e., in less than 1 y) as the result of an increase in the thickness of the lower lamina in ground scales. Similar scale structures and the same mechanism for producing violet/blue structural colors were found in the other Bicyclus species. This work shows that populations harbor large amounts of standing genetic variation that can lead to rapid evolution of scales' structural color via slight modifications to the scales' physical dimensions.
Robust Entrainment of Circadian Oscillators Requires Specific Phase Response Curves
Pfeuty, Benjamin; Thommen, Quentin; Lefranc, Marc
2011-01-01
The circadian clocks keeping time in many living organisms rely on self-sustained biochemical oscillations entrained by external cues, such as light, to the 24-h cycle induced by Earth's rotation. However, environmental cues are unreliable due to the variability of habitats, weather conditions, or cue-sensing mechanisms among individuals. A tempting hypothesis is that circadian clocks have evolved so as to be robust to fluctuations in the signal that entrains them. To support this hypothesis, we analyze the synchronization behavior of weakly and periodically forced oscillators in terms of their phase response curve (PRC), which measures phase changes induced by a perturbation applied at different times of the cycle. We establish a general relationship between the robustness of key entrainment properties, such as stability and oscillator phase, on the one hand, and the shape of the PRC as characterized by a specific curvature or the existence of a dead zone, on the other hand. The criteria obtained are applied to computational models of circadian clocks and account for the disparate robustness properties of various forcing schemes. Finally, the analysis of PRCs measured experimentally in several organisms strongly suggests a case of convergent evolution toward an optimal strategy for maintaining a clock that is accurate and robust to environmental fluctuations. PMID:21641300
Yu, Chengzhu; Hansen, John H L
2017-03-01
Human physiology has evolved to accommodate environmental conditions, including temperature, pressure, and air chemistry unique to Earth. However, the environment in space varies significantly compared to that on Earth and, therefore, variability is expected in astronauts' speech production mechanism. In this study, the variations of astronaut voice characteristics during the NASA Apollo 11 mission are analyzed. Specifically, acoustical features such as fundamental frequency and phoneme formant structure that are closely related to the speech production system are studied. For a further understanding of astronauts' vocal tract spectrum variation in space, a maximum likelihood frequency warping based analysis is proposed to detect the vocal tract spectrum displacement during space conditions. The results from fundamental frequency, formant structure, as well as vocal spectrum displacement indicate that astronauts change their speech production mechanism when in space. Moreover, the experimental results for astronaut voice identification tasks indicate that current speaker recognition solutions are highly vulnerable to astronaut voice production variations in space conditions. Future recommendations from this study suggest that successful applications of speaker recognition during extended space missions require robust speaker modeling techniques that could effectively adapt to voice production variation caused by diverse space conditions.
Biophysics of protein evolution and evolutionary protein biophysics
Sikosek, Tobias; Chan, Hue Sun
2014-01-01
The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599
The Nucleus Accumbens and Pavlovian Reward Learning
Day, Jeremy J.
2011-01-01
The ability to form associations between predictive environmental events and rewarding outcomes is a fundamental aspect of learned behavior. This apparently simple ability likely requires complex neural processing evolved to identify, seek, and utilize natural rewards and redirect these activities based on updated sensory information. Emerging evidence from both animal and human research suggests that this type of processing is mediated in part by the nucleus accumbens and a closely associated network of brain structures. The nucleus accumbens is required for a number of reward-related behaviors, and processes specific information about reward availability, value, and context. Additionally, this structure is critical for the acquisition and expression of most Pavlovian stimulus-reward relationships, and cues that predict rewards produce robust changes in neural activity in the nucleus accumbens. While processing within the nucleus accumbens may enable or promote Pavlovian reward learning in natural situations, it has also been implicated in aspects of human drug addiction, including the ability of drug-paired cues to control behavior. This article will provide a critical review of the existing animal and human literature concerning the role of the NAc in Pavlovian learning with non-drug rewards and consider some clinical implications of these findings. PMID:17404375
Makam, Pandeeswar; Gazit, Ehud
2018-05-21
Molecular self-assembly is a ubiquitous process in nature and central to bottom-up nanotechnology. In particular, the organization of peptide building blocks into ordered supramolecular structures has gained much interest due to the unique properties of the products, including biocompatibility, chemical and structural diversity, robustness and ease of large-scale synthesis. In addition, peptides, as short as dipeptides, contain all the molecular information needed to spontaneously form well-ordered structures at both the nano- and the micro-scale. Therefore, peptide supramolecular assembly has been effectively utilized to produce novel materials with tailored properties for various applications in the fields of material science, engineering, medicine, and biology. To further expand the conformational space of peptide assemblies in terms of structural and functional complexity, multicomponent (two or more) peptide supramolecular co-assembly has recently evolved as a promising extended approach, similar to the structural diversity of natural sequence-defined biopolymers (proteins) as well as of synthetic covalent co-polymers. The use of this methodology was recently demonstrated in various applications, such as nanostructure physical dimension control, the creation of non-canonical complex topologies, mechanical strength modulation, the design of light harvesting soft materials, fabrication of electrically conducting devices, induced fluorescence, enzymatic catalysis and tissue engineering. In light of these significant advancements in the field of peptide supramolecular co-assembly in the last few years, in this tutorial review, we provide an updated overview and future prospects of this emerging subject.
ERIC Educational Resources Information Center
Murphy, Joseph
2006-01-01
Over the last quarter century, the American high school, like the larger educational industry in which it is embedded, has been subjected to a good deal of critical analysis. Using a longer lens provided by historical research on the development and growth of the American high school as well as an especially robust theory of organizational change…
ERIC Educational Resources Information Center
Violini, Bob
2014-01-01
As part of the student success agenda, the nation's community colleges have been asked to rethink their approach to education on every level. From the explosion of smartphones and mobile devices on campus to the demand for more robust data analytics and tracking to the increasingly technical nature of global work, technology has evolved from a…
Cluster fusion-fission dynamics in the Singapore stock exchange
NASA Astrophysics Data System (ADS)
Teh, Boon Kin; Cheong, Siew Ann
2015-10-01
In this paper, we investigate how the cross-correlations between stocks in the Singapore stock exchange (SGX) evolve over 2008 and 2009 within overlapping one-month time windows. In particular, we examine how these cross-correlations change before, during, and after the Sep-Oct 2008 Lehman Brothers Crisis. To do this, we extend the complete-linkage hierarchical clustering algorithm, to obtain robust clusters of stocks with stronger intracluster correlations, and weaker intercluster correlations. After we identify the robust clusters in all time windows, we visualize how these change in the form of a fusion-fission diagram. Such a diagram depicts graphically how the cluster sizes evolve, the exchange of stocks between clusters, as well as how strongly the clusters mix. From the fusion-fission diagram, we see a giant cluster growing and disintegrating in the SGX, up till the Lehman Brothers Crisis in September 2008 and the market crashes of October 2008. After the Lehman Brothers Crisis, clusters in the SGX remain small for few months before giant clusters emerge once again. In the aftermath of the crisis, we also find strong mixing of component stocks between clusters. As a result, the correlation between initially strongly-correlated pairs of stocks decay exponentially with average life time of about a month. These observations impact strongly how portfolios and trading strategies should be formulated.
Chen, Bor-Sen; Yeh, Chin-Hsun
2017-12-01
We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.
Robust stability of fractional order polynomials with complicated uncertainty structure
Şenol, Bilal; Pekař, Libor
2017-01-01
The main aim of this article is to present a graphical approach to robust stability analysis for families of fractional order (quasi-)polynomials with complicated uncertainty structure. More specifically, the work emphasizes the multilinear, polynomial and general structures of uncertainty and, moreover, the retarded quasi-polynomials with parametric uncertainty are studied. Since the families with these complex uncertainty structures suffer from the lack of analytical tools, their robust stability is investigated by numerical calculation and depiction of the value sets and subsequent application of the zero exclusion condition. PMID:28662173
NASA Technical Reports Server (NTRS)
Collins, Emmanuel G., Jr.; Richter, Stephen
1990-01-01
One well known deficiency of LQG compensators is that they do not guarantee any measure of robustness. This deficiency is especially highlighted when considering control design for complex systems such as flexible structures. There has thus been a need to generalize LQG theory to incorporate robustness constraints. Here we describe the maximum entropy approach to robust control design for flexible structures, a generalization of LQG theory, pioneered by Hyland, which has proved useful in practice. The design equations consist of a set of coupled Riccati and Lyapunov equations. A homotopy algorithm that is used to solve these design equations is presented.
Hardware Design and Testing of SUPERball, A Modular Tensegrity Robot
NASA Technical Reports Server (NTRS)
Sabelhaus, Andrew P.; Bruce, Jonathan; Caluwaerts, Ken; Chen, Yangxin; Lu, Dizhou; Liu, Yuejia; Agogino, Adrian K.; SunSpiral, Vytas; Agogino, Alice M.
2014-01-01
We are developing a system of modular, autonomous "tensegrity end-caps" to enable the rapid exploration of untethered tensegrity robot morphologies and functions. By adopting a self-contained modular approach, different end-caps with various capabilities (such as peak torques, or motor speeds), can be easily combined into new tensegrity robots composed of rods, cables, and actuators of different scale (such as in length, mass, peak loads, etc). As a first step in developing this concept, we are in the process of designing and testing the end-caps for SUPERball (Spherical Underactuated Planetary Exploration Robot), a project at the Dynamic Tensegrity Robotics Lab (DTRL) within NASA Ames's Intelligent Robotics Group. This work discusses the evolving design concepts and test results that have gone into the structural, mechanical, and sensing aspects of SUPERball. This representative tensegrity end-cap design supports robust and repeatable untethered mobility tests of the SUPERball, while providing high force, high displacement actuation, with a low-friction, compliant cabling system.
Hodge, Jennifer R; Alim, Chidera; Bertrand, Nick G; Lee, Wesley; Price, Samantha A; Tran, Binh; Wainwright, Peter C
2018-07-01
Antipredator defensive traits are thought to trade-off evolutionarily with traits that facilitate predator avoidance. However, complexity and scale have precluded tests of this prediction in many groups, including fishes. Using a macroevolutionary approach, we test this prediction in butterflyfishes, an iconic group of coral reef inhabitants with diverse social behaviours, foraging strategies and antipredator adaptations. We find that several antipredator traits have evolved adaptively, dependent primarily on foraging strategy. We identify a previously unrecognised axis of diversity in butterflyfishes where species with robust morphological defences have riskier foraging strategies and lack sociality, while species with reduced morphological defences feed in familiar territories, have adaptations for quick escapes and benefit from the vigilance provided by sociality. Furthermore, we find evidence for the constrained evolution of fin spines among species that graze solely on corals, highlighting the importance of corals, as both prey and structural refuge, in shaping fish morphology. © 2018 John Wiley & Sons Ltd/CNRS.
Modeling complexity in engineered infrastructure system: Water distribution network as an example
NASA Astrophysics Data System (ADS)
Zeng, Fang; Li, Xiang; Li, Ke
2017-02-01
The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.
Data Publication: The Evolving Lifecyle
NASA Astrophysics Data System (ADS)
Studwell, S.; Elliott, J.; Anderson, A.
2015-12-01
Datasets are recognized as valuable information entities in their own right that, now and in the future, need to be available for citation, discovery, retrieval and reuse. The U.S. Department of Energy's Office of Scientific and Technical Information (OSTI) provides Digital Object Identifiers (DOIs) to DOE-funded data through partnership with DataCite. The Geothermal Data Repository (GDR) has been using OSTI's Data ID Service since summer, 2014 and is a success story for data publishing in several different ways. This presentation attributes the initial success to the insistence of DOE's Geothermal Technologies Office on detailed planning, robust data curation, and submitter participation. OSTI widely disseminates these data products across both U.S. and international platforms and continually enhances the Data ID Service to facilitate better linkage between published literature, supplementary data components, and the underlying datasets within the structure of the GDR repository. Issues of granularity in DOI assignment, the role of new federal government guidelines on public access to digital data, and the challenges still ahead will be addressed.
Finlay, Barbara L; Hinz, Flora; Darlington, Richard B
2011-07-27
The pattern of individual variation in brain component structure in pigs, minks and laboratory mice is very similar to variation across species in the same components, at a reduced scale. This conserved pattern of allometric scaling resembles robotic architectures designed to be robust to changes in computing power and task demands, and may reflect the mechanism by which both growing and evolving brains defend basic sensory, motor and homeostatic functions at multiple scales. Conserved scaling rules also have implications for species-specific sensory and social communication systems, motor competencies and cognitive abilities. The role of relative changes in neuron number in the central nervous system in producing species-specific behaviour is thus highly constrained, while changes in the sensory and motor periphery, and in motivational and attentional systems increase in probability as the principal loci producing important changes in functional neuroanatomy between species. By their nature, these loci require renewed attention to development and life history in the initial organization and production of species-specific behavioural abilities.
Conflict and convention in dynamic networks.
Foley, Michael; Forber, Patrick; Smead, Rory; Riedl, Christoph
2018-03-01
An important way to resolve games of conflict (snowdrift, hawk-dove, chicken) involves adopting a convention: a correlated equilibrium that avoids any conflict between aggressive strategies. Dynamic networks allow individuals to resolve conflict via their network connections rather than changing their strategy. Exploring how behavioural strategies coevolve with social networks reveals new dynamics that can help explain the origins and robustness of conventions. Here, we model the emergence of conventions as correlated equilibria in dynamic networks. Our results show that networks have the tendency to break the symmetry between the two conventional solutions in a strongly biased way. Rather than the correlated equilibrium associated with ownership norms (play aggressive at home, not away), we usually see the opposite host-guest norm (play aggressive away, not at home) evolve on dynamic networks, a phenomenon common to human interaction. We also show that learning to avoid conflict can produce realistic network structures in a way different than preferential attachment models. © 2017 The Author(s).
Dynamic Evolution of Financial Network and its Relation to Economic Crises
NASA Astrophysics Data System (ADS)
Gao, Ya-Chun; Wei, Zong-Wen; Wang, Bing-Hong
2013-02-01
The static topology properties of financial networks have been widely investigated since the work done by Mantegna, yet their dynamic evolution with time is little considered. In this paper, we comprehensively study the dynamic evolution of financial network by a sliding window technique. The vertices and edges of financial network are represented by the stocks from S&P500 components and correlations between pairs of daily returns of price fluctuation, respectively. Furthermore, the duration of stock price fluctuation, spanning from January 4, 1985 to September 14, 2009, makes us to carefully observe the relation between the dynamic topological properties and big financial crashes. The empirical results suggest that the financial network has the robust small-world property when the time evolves, and the topological structure drastically changes when the big financial crashes occur. This correspondence between the dynamic evolution of financial network and big financial crashes may provide a novel view to understand the origin of economic crisis.
Robust fuel- and time-optimal control of uncertain flexible space structures
NASA Technical Reports Server (NTRS)
Wie, Bong; Sinha, Ravi; Sunkel, John; Cox, Ken
1993-01-01
The problem of computing open-loop, fuel- and time-optimal control inputs for flexible space structures in the face of modeling uncertainty is investigated. Robustified, fuel- and time-optimal pulse sequences are obtained by solving a constrained optimization problem subject to robustness constraints. It is shown that 'bang-off-bang' pulse sequences with a finite number of switchings provide a practical tradeoff among the maneuvering time, fuel consumption, and performance robustness of uncertain flexible space structures.
NASA Astrophysics Data System (ADS)
Bailey, Brent Andrew
Structural designs by humans and nature are wholly distinct in their approaches. Engineers model components to verify that all mechanical requirements are satisfied before assembling a product. Nature, on the other hand; creates holistically: each part evolves in conjunction with the others. The present work is a synthesis of these two design approaches; namely, spatial models that evolve. Topology optimization determines the amount and distribution of material within a model; which corresponds to the optimal connectedness and shape of a structure. Smooth designs are obtained by using higher-order B-splines in the definition of the material distribution. Higher-fidelity is achieved using adaptive meshing techniques at the interface between solid and void. Nature is an exemplary basis for mass minimization, as processing material requires both resources and energy. Topological optimization techniques were originally formulated as the maximization of the structural stiffness subject to a volume constraint. This research inverts the optimization problem: the mass is minimized subject to deflection constraints. Active materials allow a structure to interact with its environment in a manner similar to muscles and sensory organs in animals. By specifying the material properties and design requirements, adaptive structures with integrated sensors and actuators can evolve.
Robustness and structure of complex networks
NASA Astrophysics Data System (ADS)
Shao, Shuai
This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks are much more vulnerable to localized attack compared with random attack. In the second part, we extend the tree-like generating function method to incorporating clustering structure in complex networks. We study the robustness of a complex network system, especially a network of networks (NON) with clustering structure in each network. We find that the system becomes less robust as we increase the clustering coefficient of each network. For a partially dependent network system, we also find that the influence of the clustering coefficient on network robustness decreases as we decrease the coupling strength, and the critical coupling strength qc, at which the first-order phase transition changes to second-order, increases as we increase the clustering coefficient.
Active printed materials for complex self-evolving deformations.
Raviv, Dan; Zhao, Wei; McKnelly, Carrie; Papadopoulou, Athina; Kadambi, Achuta; Shi, Boxin; Hirsch, Shai; Dikovsky, Daniel; Zyracki, Michael; Olguin, Carlos; Raskar, Ramesh; Tibbits, Skylar
2014-12-18
We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus.
Active Printed Materials for Complex Self-Evolving Deformations
Raviv, Dan; Zhao, Wei; McKnelly, Carrie; Papadopoulou, Athina; Kadambi, Achuta; Shi, Boxin; Hirsch, Shai; Dikovsky, Daniel; Zyracki, Michael; Olguin, Carlos; Raskar, Ramesh; Tibbits, Skylar
2014-01-01
We propose a new design of complex self-evolving structures that vary over time due to environmental interaction. In conventional 3D printing systems, materials are meant to be stable rather than active and fabricated models are designed and printed as static objects. Here, we introduce a novel approach for simulating and fabricating self-evolving structures that transform into a predetermined shape, changing property and function after fabrication. The new locally coordinated bending primitives combine into a single system, allowing for a global deformation which can stretch, fold and bend given environmental stimulus. PMID:25522053
Conditioning and Robustness of RNA Boltzmann Sampling under Thermodynamic Parameter Perturbations.
Rogers, Emily; Murrugarra, David; Heitsch, Christine
2017-07-25
Understanding how RNA secondary structure prediction methods depend on the underlying nearest-neighbor thermodynamic model remains a fundamental challenge in the field. Minimum free energy (MFE) predictions are known to be "ill conditioned" in that small changes to the thermodynamic model can result in significantly different optimal structures. Hence, the best practice is now to sample from the Boltzmann distribution, which generates a set of suboptimal structures. Although the structural signal of this Boltzmann sample is known to be robust to stochastic noise, the conditioning and robustness under thermodynamic perturbations have yet to be addressed. We present here a mathematically rigorous model for conditioning inspired by numerical analysis, and also a biologically inspired definition for robustness under thermodynamic perturbation. We demonstrate the strong correlation between conditioning and robustness and use its tight relationship to define quantitative thresholds for well versus ill conditioning. These resulting thresholds demonstrate that the majority of the sequences are at least sample robust, which verifies the assumption of sampling's improved conditioning over the MFE prediction. Furthermore, because we find no correlation between conditioning and MFE accuracy, the presence of both well- and ill-conditioned sequences indicates the continued need for both thermodynamic model refinements and alternate RNA structure prediction methods beyond the physics-based ones. Copyright © 2017. Published by Elsevier Inc.
Evolution of ribozymes in the presence of a mineral surface
Stephenson, James D.; Popović, Milena; Bristow, Thomas F.
2016-01-01
Mineral surfaces are often proposed as the sites of critical processes in the emergence of life. Clay minerals in particular are thought to play significant roles in the origin of life including polymerizing, concentrating, organizing, and protecting biopolymers. In these scenarios, the impact of minerals on biopolymer folding is expected to influence evolutionary processes. These processes include both the initial emergence of functional structures in the presence of the mineral and the subsequent transition away from the mineral-associated niche. The initial evolution of function depends upon the number and distribution of sequences capable of functioning in the presence of the mineral, and the transition to new environments depends upon the overlap between sequences that evolve on the mineral surface and sequences that can perform the same functions in the mineral's absence. To examine these processes, we evolved self-cleaving ribozymes in vitro in the presence or absence of Na-saturated montmorillonite clay mineral particles. Starting from a shared population of random sequences, RNA populations were evolved in parallel, along separate evolutionary trajectories. Comparative sequence analysis and activity assays show that the impact of this clay mineral on functional structure selection was minimal; it neither prevented common structures from emerging, nor did it promote the emergence of new structures. This suggests that montmorillonite does not improve RNA's ability to evolve functional structures; however, it also suggests that RNAs that do evolve in contact with montmorillonite retain the same structures in mineral-free environments, potentially facilitating an evolutionary transition away from a mineral-associated niche. PMID:27793980
Disgust: Evolved Function and Structure
ERIC Educational Resources Information Center
Tybur, Joshua M.; Lieberman, Debra; Kurzban, Robert; DeScioli, Peter
2013-01-01
Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and that of information processing. Although there is…
Enabling Rapid and Robust Structural Analysis During Conceptual Design
NASA Technical Reports Server (NTRS)
Eldred, Lloyd B.; Padula, Sharon L.; Li, Wu
2015-01-01
This paper describes a multi-year effort to add a structural analysis subprocess to a supersonic aircraft conceptual design process. The desired capabilities include parametric geometry, automatic finite element mesh generation, static and aeroelastic analysis, and structural sizing. The paper discusses implementation details of the new subprocess, captures lessons learned, and suggests future improvements. The subprocess quickly compares concepts and robustly handles large changes in wing or fuselage geometry. The subprocess can rank concepts with regard to their structural feasibility and can identify promising regions of the design space. The automated structural analysis subprocess is deemed robust and rapid enough to be included in multidisciplinary conceptual design and optimization studies.
Robust Design of Biological Circuits: Evolutionary Systems Biology Approach
Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia
2011-01-01
Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise. PMID:22187523
Robust design of biological circuits: evolutionary systems biology approach.
Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia
2011-01-01
Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise.
Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses
Stephen, Emily P.; Lepage, Kyle Q.; Eden, Uri T.; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S.; Guenther, Frank H.; Kramer, Mark A.
2014-01-01
The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty—both in the functional network edges and the corresponding aggregate measures of network topology—are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here—appropriate for static and dynamic network inference and different statistical measures of coupling—permits the evaluation of confidence in network measures in a variety of settings common to neuroscience. PMID:24678295
Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.
Stephen, Emily P; Lepage, Kyle Q; Eden, Uri T; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S; Guenther, Frank H; Kramer, Mark A
2014-01-01
The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty-both in the functional network edges and the corresponding aggregate measures of network topology-are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here-appropriate for static and dynamic network inference and different statistical measures of coupling-permits the evaluation of confidence in network measures in a variety of settings common to neuroscience.
Light transport and lasing in complex photonic structures
NASA Astrophysics Data System (ADS)
Liew, Seng Fatt
Complex photonic structures refer to composite optical materials with dielectric constant varying on length scales comparable to optical wavelengths. Light propagation in such heterogeneous composites is greatly different from homogeneous media due to scattering of light in all directions. Interference of these scattered light waves gives rise to many fascinating phenomena and it has been a fast growing research area, both for its fundamental physics and for its practical applications. In this thesis, we have investigated the optical properties of photonic structures with different degree of order, ranging from periodic to random. The first part of this thesis consists of numerical studies of the photonic band gap (PBG) effect in structures from 1D to 3D. From these studies, we have observed that PBG effect in a 1D photonic crystal is robust against uncorrelated disorder due to preservation of long-range positional order. However, in higher dimensions, the short-range positional order alone is sufficient to form PBGs in 2D and 3D photonic amorphous structures (PASS). We have identified several parameters including dielectric filling fraction and degree of order that can be tuned to create a broad isotropic PBG. The largest PBG is produced by the dielectric networks due to local uniformity in their dielectric constant distribution. In addition, we also show that deterministic aperiodic structures (DASs) such as the golden-angle spiral and topological defect structures can support a wide PBG and their optical resonances contain unexpected features compared to those in photonic crystals. Another growing research field based on complex photonic structures is the study of structural color in animals and plants. Previous studies have shown that non-iridescent color can be generated from PASs via single or double scatterings. For better understanding of the coloration mechanisms, we have measured the wavelength-dependent scattering length from the biomimetic samples. Our theoretical modeling and analysis explains why single scattering of light is dominant over multiple scattering in similar biological structures and is responsible for color generation. In collaboration with evolutionary biologists, we examine how closely-related species and populations of butterflies have evolved their structural color. We have used artificial selection on a lab model butterfly to evolve violet color from an ultra-violet brown color. The same coloration mechanism is found in other blue/violet species that have evolved their color in nature, which implies the same evolution path for their nanostructure. While the absorption of light is ubiquitous in nature and in applications, the question remains how absorption modifies the transmission in random media. Therefore, we numerically study the effects of optical absorption on the highest transmission states in a two-dimensional disordered waveguide. Our results show that strong absorption turns the highest transmission channel in random media from diffusive to ballistic-like transport. Finally, we have demonstrated lasing mode selection in a nearly circular semiconductor microdisk laser by shaping the spatial profile of the pump beam. Despite of strong mode overlap, selective pumping suppresses the competing lasing modes by either increasing their thresholds or reducing their power slopes. As a result, we can switch both the lasing frequency and the output direction. This powerful technique can have potential application as an on-chip tunable light source.
NASA Astrophysics Data System (ADS)
Marhadi, Kun Saptohartyadi
Structural optimization for damage tolerance under various unforeseen damage scenarios is computationally challenging. It couples non-linear progressive failure analysis with sampling-based stochastic analysis of random damage. The goal of this research was to understand the relationship between alternate load paths available in a structure and its damage tolerance, and to use this information to develop computationally efficient methods for designing damage tolerant structures. Progressive failure of a redundant truss structure subjected to small random variability was investigated to identify features that correlate with robustness and predictability of the structure's progressive failure. The identified features were used to develop numerical surrogate measures that permit computationally efficient deterministic optimization to achieve robustness and predictability of progressive failure. Analysis of damage tolerance on designs with robust progressive failure indicated that robustness and predictability of progressive failure do not guarantee damage tolerance. Damage tolerance requires a structure to redistribute its load to alternate load paths. In order to investigate the load distribution characteristics that lead to damage tolerance in structures, designs with varying degrees of damage tolerance were generated using brute force stochastic optimization. A method based on principal component analysis was used to describe load distributions (alternate load paths) in the structures. Results indicate that a structure that can develop alternate paths is not necessarily damage tolerant. The alternate load paths must have a required minimum load capability. Robustness analysis of damage tolerant optimum designs indicates that designs are tailored to specified damage. A design Optimized under one damage specification can be sensitive to other damages not considered. Effectiveness of existing load path definitions and characterizations were investigated for continuum structures. A load path definition using a relative compliance change measure (U* field) was demonstrated to be the most useful measure of load path. This measure provides quantitative information on load path trajectories and qualitative information on the effectiveness of the load path. The use of the U* description of load paths in optimizing structures for effective load paths was investigated.
Proteins with Novel Structure, Function and Dynamics
NASA Technical Reports Server (NTRS)
Pohorille, Andrew
2014-01-01
Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.
NASA Astrophysics Data System (ADS)
Tadesse, T.; Zaitchik, B. F.; Habib, S.; Funk, C. C.; Senay, G. B.; Dinku, T.; Policelli, F. S.; Block, P.; Baigorria, G. A.; Beyene, S.; Wardlow, B.; Hayes, M. J.
2014-12-01
The development of effective strategies to adapt to changes in the character of droughts and floods in Africa will rely on improved seasonal prediction systems that are robust to an evolving climate baseline and can be integrated into disaster preparedness and response. Many efforts have been made to build models to improve seasonal forecasts in the Greater Horn of Africa region (GHA) using satellite and climate data, but these efforts and models must be improved and translated into future conditions under evolving climate conditions. This has considerable social significance, but is challenged by the nature of climate predictability and the adaptability of coupled natural and human systems facing exposure to climate extremes. To address these issues, work is in progress under a project funded by NASA. The objectives of the project include: 1) Characterize and explain large-scale drivers in the ocean-atmosphere-land system associated with years of extreme flood or drought in the GHA. 2) Evaluate the performance of state-of-the-art seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes. 3) Apply seasonal forecast systems to prediction of socially relevant impacts on crops, flood risk, and economic outcomes, and assess the value of these predictions to decision makers. 4) Evaluate the robustness of seasonal prediction systems to evolving climate conditions. The National Drought Mitigation Center (University of Nebraska-Lincoln, USA) is leading this project in collaboration with the USGS, Johns Hopkins University, University of Wisconsin-Madison, the International Research Institute for Climate and Society, NASA, and GHA local experts. The project is also designed to have active engagement of end users in various sectors, university researchers, and extension agents in GHA through workshops and/or webinars. This project is expected improve and implement new and existing climate- and remote sensing-based agricultural, meteorological, and hydrologic drought and flood monitoring products (or indicators) that can enhance the preparedness for extreme climate events and climate change adaptation and mitigation strategies in the GHA. Even though this project is in its first year, the preliminary results and future plans to carry out the objectives will be presented.
A 45-Amino-Acid Scaffold Mined from the PDB for High-Affinity Ligand Engineering.
Kruziki, Max A; Bhatnagar, Sumit; Woldring, Daniel R; Duong, Vandon T; Hackel, Benjamin J
2015-07-23
Small protein ligands can provide superior physiological distribution compared with antibodies, and improved stability, production, and specific conjugation. Systematic evaluation of the PDB identified a scaffold to push the limits of small size and robust evolution of stable, high-affinity ligands: 45-residue T7 phage gene 2 protein (Gp2) contains an α helix opposite a β sheet with two adjacent loops amenable to mutation. De novo ligand discovery from 10(8) mutants and directed evolution toward four targets yielded target-specific binders with affinities as strong as 200 ± 100 pM, Tms from 65 °C ± 3 °C to 80°C ± 1 °C, and retained activity after thermal denaturation. For cancer targeting, a Gp2 domain for epidermal growth factor receptor was evolved with 18 ± 8 nM affinity, receptor-specific binding, and high thermal stability with refolding. The efficiency of evolving new binding function and the size, affinity, specificity, and stability of evolved domains render Gp2 a uniquely effective ligand scaffold. Copyright © 2015 Elsevier Ltd. All rights reserved.
Evolution of synchronization and desynchronization in digital organisms.
Knoester, David B; McKinley, Philip K
2011-01-01
We present a study in the evolution of temporal behavior, specifically synchronization and desynchronization, through digital evolution and group selection. In digital evolution, a population of self-replicating computer programs exists in a user-defined computational environment and is subject to instruction-level mutations and natural selection. Group selection links the survival of the individual to the survival of its group, thus encouraging cooperation. Previous approaches to engineering synchronization and desynchronization algorithms have taken inspiration from nature: In the well-known firefly model, the only form of communication between agents is in the form of flash messages among neighbors. Here we demonstrate that populations of digital organisms, provided with a similar mechanism and minimal information about their environment, are capable of evolving algorithms for synchronization and desynchronization, and that the evolved behaviors are robust to message loss. We further describe how the evolved behavior for synchronization mimics that of the well-known Ermentrout model for firefly synchronization in biology. In addition to discovering self-organizing behaviors for distributed computing systems, this result indicates that digital evolution may be used to further our understanding of synchronization in biology.
A robust low-rate coding scheme for packet video
NASA Technical Reports Server (NTRS)
Chen, Y. C.; Sayood, Khalid; Nelson, D. J.; Arikan, E. (Editor)
1991-01-01
Due to the rapidly evolving field of image processing and networking, video information promises to be an important part of telecommunication systems. Although up to now video transmission has been transported mainly over circuit-switched networks, it is likely that packet-switched networks will dominate the communication world in the near future. Asynchronous transfer mode (ATM) techniques in broadband-ISDN can provide a flexible, independent and high performance environment for video communication. For this paper, the network simulator was used only as a channel in this simulation. Mixture blocking coding with progressive transmission (MBCPT) has been investigated for use over packet networks and has been found to provide high compression rate with good visual performance, robustness to packet loss, tractable integration with network mechanics and simplicity in parallel implementation.
NASA Technical Reports Server (NTRS)
Dorsey, John T.; Poteet, Carl C.; Chen, Roger R.; Wurster, Kathryn E.
2002-01-01
A technology development program was conducted to evolve an earlier metallic thermal protection system (TPS) panel design, with the goals of: improving operations features, increasing adaptability (ease of attaching to a variety of tank shapes and structural concepts), and reducing weight. The resulting Adaptable Robust Metallic Operable Reusable (ARMOR) TPS system incorporates a high degree of design flexibility (allowing weight and operability to be traded and balanced) and can also be easily integrated with a large variety of tank shapes, airframe structural arrangements and airframe structure/material concepts. An initial attempt has been made to establish a set of performance based TPS design requirements. A set of general (FARtype) requirements have been proposed, focusing on defining categories that must be included for a comprehensive design. Load cases required for TPS design must reflect the full flight envelope, including a comprehensive set of limit loads, However, including additional loads. such as ascent abort trajectories, as ultimate load cases, and on-orbit debris/micro-meteoroid hypervelocity impact, as one of the discrete -source -damage load cases, will have a significant impact on system design and resulting performance, reliability and operability. Although these load cases have not been established, they are of paramount importance for reusable vehicles, and until properly included, all sizing results and assessments of reliability and operability must be considered optimistic at a minimum.
Gersick, Andrew S; Rubenstein, Daniel I
2017-08-19
Though morphologically very similar, equids across the extant species occupy ecological niches that are surprisingly non-overlapping. Occupancy of these distinct niches appears related to subtle physiological and behavioural adaptations which, in turn, correspond to significant differences in the social behaviours and emergent social systems characterizing the different species. Although instances of intraspecific behavioural variation in equids demonstrate that the same body plan can support a range of social structures, each of these morphologically similar species generally shows robust fidelity to its evolved social system. The pattern suggests a subtle relationship between physiological phenotypes and behavioural flexibility. While environmental conditions can vary widely within relatively short temporal or spatial scales, physiological changes and changes to the behaviours that regulate physiological processes, are constrained to longer cycles of adaptation. Physiology is then the limiting variable in the interaction between ecological variation and behavioural and socio-structural flexibility. Behavioural and socio-structural flexibility, in turn, will generate important feedbacks that will govern physiological function, thus creating a coupled web of interactions that can lead to changes in individual and collective behaviour. Longitudinal studies of equid and other large-bodied ungulate populations under environmental stress, such as those discussed here, may offer the best opportunities for researchers to examine, in real time, the interplay between individual behavioural plasticity, socio-structural flexibility, and the physiological and genetic changes that together produce adaptive change.This article is part of the themed issue 'Physiological determinants of social behaviour in animals'. © 2017 The Author(s).
Robust on-off pulse control of flexible space vehicles
NASA Technical Reports Server (NTRS)
Wie, Bong; Sinha, Ravi
1993-01-01
The on-off reaction jet control system is often used for attitude and orbital maneuvering of various spacecraft. Future space vehicles such as the orbital transfer vehicles, orbital maneuvering vehicles, and space station will extensively use reaction jets for orbital maneuvering and attitude stabilization. The proposed robust fuel- and time-optimal control algorithm is used for a three-mass spacing model of flexible spacecraft. A fuel-efficient on-off control logic is developed for robust rest-to-rest maneuver of a flexible vehicle with minimum excitation of structural modes. The first part of this report is concerned with the problem of selecting a proper pair of jets for practical trade-offs among the maneuvering time, fuel consumption, structural mode excitation, and performance robustness. A time-optimal control problem subject to parameter robustness constraints is formulated and solved. The second part of this report deals with obtaining parameter insensitive fuel- and time- optimal control inputs by solving a constrained optimization problem subject to robustness constraints. It is shown that sensitivity to modeling errors can be significantly reduced by the proposed, robustified open-loop control approach. The final part of this report deals with sliding mode control design for uncertain flexible structures. The benchmark problem of a flexible structure is used as an example for the feedback sliding mode controller design with bounded control inputs and robustness to parameter variations is investigated.
Best Practices for Reliable and Robust Spacecraft Structures
NASA Technical Reports Server (NTRS)
Raju, Ivatury S.; Murthy, P. L. N.; Patel, Naresh R.; Bonacuse, Peter J.; Elliott, Kenny B.; Gordon, S. A.; Gyekenyesi, J. P.; Daso, E. O.; Aggarwal, P.; Tillman, R. F.
2007-01-01
A study was undertaken to capture the best practices for the development of reliable and robust spacecraft structures for NASA s next generation cargo and crewed launch vehicles. In this study, the NASA heritage programs such as Mercury, Gemini, Apollo, and the Space Shuttle program were examined. A series of lessons learned during the NASA and DoD heritage programs are captured. The processes that "make the right structural system" are examined along with the processes to "make the structural system right". The impact of technology advancements in materials and analysis and testing methods on reliability and robustness of spacecraft structures is studied. The best practices and lessons learned are extracted from these studies. Since the first human space flight, the best practices for reliable and robust spacecraft structures appear to be well established, understood, and articulated by each generation of designers and engineers. However, these best practices apparently have not always been followed. When the best practices are ignored or short cuts are taken, risks accumulate, and reliability suffers. Thus program managers need to be vigilant of circumstances and situations that tend to violate best practices. Adherence to the best practices may help develop spacecraft systems with high reliability and robustness against certain anomalies and unforeseen events.
2012-01-01
Background To investigate organisational factors influencing the implementation challenges of redesigning services for people with long term conditions in three locations in England, using remote care (telehealth and telecare). Methods Case-studies of three sites forming the UK Department of Health’s Whole Systems Demonstrator (WSD) Programme. Qualitative research techniques were used to obtain data from various sources, including semi-structured interviews, observation of meetings over the course programme and prior to its launch, and document review. Participants were managers and practitioners involved in the implementation of remote care services. Results The implementation of remote care was nested within a large pragmatic cluster randomised controlled trial (RCT), which formed a core element of the WSD programme. To produce robust benefits evidence, many aspect of the trial design could not be easily adapted to local circumstances. While remote care was successfully rolled-out, wider implementation lessons and levels of organisational learning across the sites were hindered by the requirements of the RCT. Conclusions The implementation of a complex innovation such as remote care requires it to organically evolve, be responsive and adaptable to the local health and social care system, driven by support from front-line staff and management. This need for evolution was not always aligned with the imperative to gather robust benefits evidence. This tension needs to be resolved if government ambitions for the evidence-based scaling-up of remote care are to be realised. PMID:23153014
Is countershading camouflage robust to lighting change due to weather?
Penacchio, Olivier; Lovell, P George; Harris, Julie M
2018-02-01
Countershading is a pattern of coloration thought to have evolved in order to implement camouflage. By adopting a pattern of coloration that makes the surface facing towards the sun darker and the surface facing away from the sun lighter, the overall amount of light reflected off an animal can be made more uniformly bright. Countershading could hence contribute to visual camouflage by increasing background matching or reducing cues to shape. However, the usefulness of countershading is constrained by a particular pattern delivering 'optimal' camouflage only for very specific lighting conditions. In this study, we test the robustness of countershading camouflage to lighting change due to weather, using human participants as a 'generic' predator. In a simulated three-dimensional environment, we constructed an array of simple leaf-shaped items and a single ellipsoidal target 'prey'. We set these items in two light environments: strongly directional 'sunny' and more diffuse 'cloudy'. The target object was given the optimal pattern of countershading for one of these two environment types or displayed a uniform pattern. By measuring detection time and accuracy, we explored whether and how target detection depended on the match between the pattern of coloration on the target object and scene lighting. Detection times were longest when the countershading was appropriate to the illumination; incorrectly camouflaged targets were detected with a similar pattern of speed and accuracy to uniformly coloured targets. We conclude that structural changes in light environment, such as caused by differences in weather, do change the effectiveness of countershading camouflage.
A network property necessary for concentration robustness
NASA Astrophysics Data System (ADS)
Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran
2016-10-01
Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.
A network property necessary for concentration robustness.
Eloundou-Mbebi, Jeanne M O; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran
2016-10-19
Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.
A network property necessary for concentration robustness
Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran
2016-01-01
Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications. PMID:27759015
Criteria for robustness of heteroclinic cycles in neural microcircuits
2011-01-01
We introduce a test for robustness of heteroclinic cycles that appear in neural microcircuits modeled as coupled dynamical cells. Robust heteroclinic cycles (RHCs) can appear as robust attractors in Lotka-Volterra-type winnerless competition (WLC) models as well as in more general coupled and/or symmetric systems. It has been previously suggested that RHCs may be relevant to a range of neural activities, from encoding and binding to spatio-temporal sequence generation. The robustness or otherwise of such cycles depends both on the coupling structure and the internal structure of the neurons. We verify that robust heteroclinic cycles can appear in systems of three identical cells, but only if we require perturbations to preserve some invariant subspaces for the individual cells. On the other hand, heteroclinic attractors can appear robustly in systems of four or more identical cells for some symmetric coupling patterns, without restriction on the internal dynamics of the cells. PMID:22656192
Practical robustness measures in multivariable control system analysis. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Lehtomaki, N. A.
1981-01-01
The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.
Epilogue: Systems Approaches and Systems Practice
NASA Astrophysics Data System (ADS)
Reynolds, Martin; Holwell, Sue
Each of the five systems approaches discussed in this volume: system dynamics (SD), the viable systems model (VSM), strategic options development and analysis (SODA), soft systems methodology (SSM) and critical systems heuristics (CSH) has a pedigree. Not in the sense of the sometimes absurd spectacle of animals paraded at dog shows. Rather, their pedigree derives from their systems foundations, their capacity to evolve and their flexibility in use. None of the five approaches has developed out of use in restricted and controlled contexts of either low or high levels of complicatedness. Neither has any one of them evolved as a consequence of being applied only to situations with either presumed stakeholder agreement on purpose, or courteous disagreement amongst stakeholders, or stakeholder coercion. The compilation is not a celebration of abstract ‘methodologies', but of theoretically robust approaches that have a genuine pedigree in practice.
The Department of Energy Nuclear Criticality Safety Program
NASA Astrophysics Data System (ADS)
Felty, James R.
2005-05-01
This paper broadly covers key events and activities from which the Department of Energy Nuclear Criticality Safety Program (NCSP) evolved. The NCSP maintains fundamental infrastructure that supports operational criticality safety programs. This infrastructure includes continued development and maintenance of key calculational tools, differential and integral data measurements, benchmark compilation, development of training resources, hands-on training, and web-based systems to enhance information preservation and dissemination. The NCSP was initiated in response to Defense Nuclear Facilities Safety Board Recommendation 97-2, Criticality Safety, and evolved from a predecessor program, the Nuclear Criticality Predictability Program, that was initiated in response to Defense Nuclear Facilities Safety Board Recommendation 93-2, The Need for Critical Experiment Capability. This paper also discusses the role Dr. Sol Pearlstein played in helping the Department of Energy lay the foundation for a robust and enduring criticality safety infrastructure.
Orion FSW V and V and Kedalion Engineering Lab Insight
NASA Technical Reports Server (NTRS)
Mangieri, Mark L.
2010-01-01
NASA, along with its prime Orion contractor and its subcontractor s are adapting an avionics system paradigm borrowed from the manned commercial aircraft industry for use in manned space flight systems. Integrated Modular Avionics (IMA) techniques have been proven as a robust avionics solution for manned commercial aircraft (B737/777/787, MD 10/90). This presentation will outline current approaches to adapt IMA, along with its heritage FSW V&V paradigms, into NASA's manned space flight program for Orion. NASA's Kedalion engineering analysis lab is on the forefront of validating many of these contemporary IMA based techniques. Kedalion has already validated many of the proposed Orion FSW V&V paradigms using Orion's precursory Flight Test Article (FTA) Pad Abort 1 (PA-1) program. The Kedalion lab will evolve its architectures, tools, and techniques in parallel with the evolving Orion program.
Dynamic model of time-dependent complex networks.
Hill, Scott A; Braha, Dan
2010-10-01
The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by irregular connections that evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present an approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme.
Deng, Meng; Nair, Lakshmi S.; Nukavarapu, Syam P.; Kumbar, Sangamesh G.; Jiang, Tao; Weikel, Arlin L.; Krogman, Nicholas R.; Allcock, Harry R.; Laurencin, Cato T.
2011-01-01
Synthetic biodegradable polymers serve as temporary substrates that accommodate cell infiltration and tissue in-growth in regenerative medicine. To allow tissue in-growth and nutrient transport, traditional three-dimensional (3D) scaffolds must be prefabricated with an interconnected porous structure. Here we demonstrated for the first time a unique polymer erosion process through which polymer matrices evolve from a solid coherent film to an assemblage of microspheres with an interconnected 3D porous structure. This polymer system was developed on the highly versatile platform of polyphosphazene-polyester blends. Co-substituting a polyphosphazene backbone with both hydrophilic glycylglycine dipeptide and hydrophobic 4-phenylphenoxy group generated a polymer with strong hydrogen bonding capacity. Rapid hydrolysis of the polyester component permitted the formation of 3D void space filled with self-assembled polyphosphazene spheres. Characterization of such self-assembled porous structures revealed macropores (10-100 μm) between spheres as well as micro- and nanopores on the sphere surface. A similar degradation pattern was confirmed in vivo using a rat subcutaneous implantation model. 12 weeks of implantation resulted in an interconnected porous structure with 82-87% porosity. Cell infiltration and collagen tissue in-growth between microspheres observed by histology confirmed the formation of an in situ 3D interconnected porous structure. It was determined that the in situ porous structure resulted from unique hydrogen bonding in the blend promoting a three-stage degradation mechanism. The robust tissue in-growth of this dynamic pore forming scaffold attests to the utility of this system as a new strategy in regenerative medicine for developing solid matrices that balance degradation with tissue formation. PMID:21789036
Zhang, Yalei; Chen, Wen; Dai, Chaomeng; Zhou, Chuanlong; Zhou, Xuefei
2015-01-01
The structures of nanoscale zero-valent iron (nZVI) particles evolving during reactions, and the reactions are influenced by the evolved structures. To understand the removal process in detail, it is important to investigate the relationships between the reactions and structural evolution. Using high resolution-transmission electron microscopy (HR-TEM), typical evolved structures (sheet coprecipitation and cavity corrosion) of nZVI in anoxic Co2+ solutions were revealed. The system pH (pH measured in mixture), which controls the stability of coprecipitation and the nZVI corrosion rate, were found to be the determining factors of structural evolutions. X-ray photoelectron spectroscopy (XPS) results indicated that the formation and dissolution of sheet structure impacts on the ratio of Fe(0) on the nZVI surface and the surface Co2+ reduction. The cavity structure provides the possibility of Co migration from the surface to the bulk of nZVI, leading to continuous removal. Subacidity conditions could accelerate the evolution and improve the removal; the results of structurally controlled reactions further indicated that the removal was suspended by the sheet structure and enhanced by cavity structure. The results and discussion in this paper revealed the “structural influence” crucial for the full and dynamical understanding of nZVI reactions. PMID:26355955
Zhang, Yalei; Chen, Wen; Dai, Chaomeng; Zhou, Chuanlong; Zhou, Xuefei
2015-09-10
The structures of nanoscale zero-valent iron (nZVI) particles evolving during reactions, and the reactions are influenced by the evolved structures. To understand the removal process in detail, it is important to investigate the relationships between the reactions and structural evolution. Using high resolution-transmission electron microscopy (HR-TEM), typical evolved structures (sheet coprecipitation and cavity corrosion) of nZVI in anoxic Co(2+) solutions were revealed. The system pH (pH measured in mixture), which controls the stability of coprecipitation and the nZVI corrosion rate, were found to be the determining factors of structural evolutions. X-ray photoelectron spectroscopy (XPS) results indicated that the formation and dissolution of sheet structure impacts on the ratio of Fe(0) on the nZVI surface and the surface Co(2+) reduction. The cavity structure provides the possibility of Co migration from the surface to the bulk of nZVI, leading to continuous removal. Subacidity conditions could accelerate the evolution and improve the removal; the results of structurally controlled reactions further indicated that the removal was suspended by the sheet structure and enhanced by cavity structure. The results and discussion in this paper revealed the "structural influence" crucial for the full and dynamical understanding of nZVI reactions.
NASA Astrophysics Data System (ADS)
Zhang, Yalei; Chen, Wen; Dai, Chaomeng; Zhou, Chuanlong; Zhou, Xuefei
2015-09-01
The structures of nanoscale zero-valent iron (nZVI) particles evolving during reactions, and the reactions are influenced by the evolved structures. To understand the removal process in detail, it is important to investigate the relationships between the reactions and structural evolution. Using high resolution-transmission electron microscopy (HR-TEM), typical evolved structures (sheet coprecipitation and cavity corrosion) of nZVI in anoxic Co2+ solutions were revealed. The system pH (pH measured in mixture), which controls the stability of coprecipitation and the nZVI corrosion rate, were found to be the determining factors of structural evolutions. X-ray photoelectron spectroscopy (XPS) results indicated that the formation and dissolution of sheet structure impacts on the ratio of Fe(0) on the nZVI surface and the surface Co2+ reduction. The cavity structure provides the possibility of Co migration from the surface to the bulk of nZVI, leading to continuous removal. Subacidity conditions could accelerate the evolution and improve the removal; the results of structurally controlled reactions further indicated that the removal was suspended by the sheet structure and enhanced by cavity structure. The results and discussion in this paper revealed the “structural influence” crucial for the full and dynamical understanding of nZVI reactions.
Rings in Evolved Stars: Fingerprints of Their Mass-Loss History
NASA Astrophysics Data System (ADS)
Ramos-Larios, Gerardo; Santamaria, Edgar; Sabin, Laurence; Guerrero, Martin; Marquez-Lugo, Alejandro
2015-08-01
The majority of intermediate mass evolved stars i.e. asymptotic giant branch (AGB) stars, post-AGB and pre-planetary nebulae (PPN) are well known for been characterized by external structures such as knots, arcs, ansae, jets, haloes, shells and even annular enhancements in intensity -features which are commonly referred to as rings. These are well described either as spherical bubbles of periodic isotropic nuclear mass pulsations (Balick, Wilson & Hajian 2001) or projections of spherical shells onto the plane of the sky by Kwok (2001).These interesting structures are part of the AGB wind, suggesting that this wind comes in a series of semi periodic lapses, indicating that the outflow has quasi-periodic oscillations.After an extensive analysis in the Hubble Space Telescope (HST) archives we found new ring-like structures in several evolved stars. Following the image analysis procedure described by Corradi et al. (2004), and using unsharp masking techniques it was possible to enhance the ring structures, and to obtain an effective removal of the underlying halo emission.Our new findings will help first to constrain the physical processes responsible for the rings creation and then to better understand the mass loss activity in these evolved stars.
Robust, nonlinear, high angle-of-attack control design for a supermaneuverable vehicle
NASA Technical Reports Server (NTRS)
Adams, Richard J.
1993-01-01
High angle-of-attack flight control laws are developed for a supermaneuverable fighter aircraft. The methods of dynamic inversion and structured singular value synthesis are combined into an approach which addresses both the nonlinearity and robustness problems of flight at extreme operating conditions. The primary purpose of the dynamic inversion control elements is to linearize the vehicle response across the flight envelope. Structured singular value synthesis is used to design a dynamic controller which provides robust tracking to pilot commands. The resulting control system achieves desired flying qualities and guarantees a large margin of robustness to uncertainties for high angle-of-attack flight conditions. The results of linear simulation and structured singular value stability analysis are presented to demonstrate satisfaction of the design criteria. High fidelity nonlinear simulation results show that the combined dynamics inversion/structured singular value synthesis control law achieves a high level of performance in a realistic environment.
Sustainable infrastructure system modeling under uncertainties and dynamics
NASA Astrophysics Data System (ADS)
Huang, Yongxi
Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches (i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: (1) is the renewable energy an economically viable solution? (2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? (3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the potential risks caused by feedstock seasonality and demand uncertainty. Facility spatiality, time variation of feedstock yields, and demand uncertainty are integrated into a two-stage stochastic programming (SP) framework. In the study of Transitional Energy System Modeling under Uncertainty, a multistage stochastic dynamic programming is established to optimize the process of building and operating fuel production facilities during the transition. Dynamics due to the evolving technologies and societal changes and uncertainty due to demand fluctuations are the major issues to be addressed.
Variable Neural Adaptive Robust Control: A Switched System Approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.
2015-05-01
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less
Galaxies and Their Host Dark Matter Structures
NASA Astrophysics Data System (ADS)
Hahn, ChangHoon
Through their connection with dark matter structures, galaxies act as tracers of the underlying matter distribution in the Universe. Their observed spatial distribution allows us to precisely measure large scale structure and effectively test cosmological models that explain the content, geometry, and history of the Universe. Current observations from galaxy surveys such as the Baryon Oscillation Spectroscopic Survey have already probed vast cosmic volumes with millions of galaxies and ushered in an era of precision cosmology. The next surveys will probe over an order of magnitude more. With this unprecedented statistical power, the bottleneck of scientific discovery is in the methodology. In this dissertation, I address major methodological challenges in constraining cosmology with the large-scale distribution of galaxies. I develop a robust framework for treating systematic effects, which significantly bias galaxy clustering measurements. I apply new innovative approaches to probabilistic parameter inference that challenge and test the in- correct assumptions of the standard approach. Furthermore, I use precise predictions of structure formation from cosmology and observations of galaxies during the last eight billion years to develop detailed models of how galaxies are impacted by their host dark matter structures. These models provide key insight into the galaxy-halo connection, which bridges the gap between cosmology theory and observations. They also answer crucial questions of how galaxies form and evolve. The developments in this dissertation will help unlock the full potential of future observations and allow us to precisely test cosmological models, General Relativity and modified gravity scenarios, and even particle physics theory beyond the Standard Model.
Evolution of a designless nanoparticle network into reconfigurable Boolean logic
NASA Astrophysics Data System (ADS)
Bose, S. K.; Lawrence, C. P.; Liu, Z.; Makarenko, K. S.; van Damme, R. M. J.; Broersma, H. J.; van der Wiel, W. G.
2015-12-01
Natural computers exploit the emergent properties and massive parallelism of interconnected networks of locally active components. Evolution has resulted in systems that compute quickly and that use energy efficiently, utilizing whatever physical properties are exploitable. Man-made computers, on the other hand, are based on circuits of functional units that follow given design rules. Hence, potentially exploitable physical processes, such as capacitive crosstalk, to solve a problem are left out. Until now, designless nanoscale networks of inanimate matter that exhibit robust computational functionality had not been realized. Here we artificially evolve the electrical properties of a disordered nanomaterials system (by optimizing the values of control voltages using a genetic algorithm) to perform computational tasks reconfigurably. We exploit the rich behaviour that emerges from interconnected metal nanoparticles, which act as strongly nonlinear single-electron transistors, and find that this nanoscale architecture can be configured in situ into any Boolean logic gate. This universal, reconfigurable gate would require about ten transistors in a conventional circuit. Our system meets the criteria for the physical realization of (cellular) neural networks: universality (arbitrary Boolean functions), compactness, robustness and evolvability, which implies scalability to perform more advanced tasks. Our evolutionary approach works around device-to-device variations and the accompanying uncertainties in performance. Moreover, it bears a great potential for more energy-efficient computation, and for solving problems that are very hard to tackle in conventional architectures.
NASA Astrophysics Data System (ADS)
Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan
2018-07-01
Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.
Effect of interaction strength on robustness of controlling edge dynamics in complex networks
NASA Astrophysics Data System (ADS)
Pang, Shao-Peng; Hao, Fei
2018-05-01
Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.
Nanobody-derived nanobiotechnology tool kits for diverse biomedical and biotechnology applications.
Wang, Yongzhong; Fan, Zhen; Shao, Lei; Kong, Xiaowei; Hou, Xianjuan; Tian, Dongrui; Sun, Ying; Xiao, Yazhong; Yu, Li
2016-01-01
Owing to peculiar properties of nanobody, including nanoscale size, robust structure, stable and soluble behaviors in aqueous solution, reversible refolding, high affinity and specificity for only one cognate target, superior cryptic cleft accessibility, and deep tissue penetration, as well as a sustainable source, it has been an ideal research tool for the development of sophisticated nanobiotechnologies. Currently, the nanobody has been evolved into versatile research and application tool kits for diverse biomedical and biotechnology applications. Various nanobody-derived formats, including the nanobody itself, the radionuclide or fluorescent-labeled nanobodies, nanobody homo- or heteromultimers, nanobody-coated nanoparticles, and nanobody-displayed bacteriophages, have been successfully demonstrated as powerful nanobiotechnological tool kits for basic biomedical research, targeting drug delivery and therapy, disease diagnosis, bioimaging, and agricultural and plant protection. These applications indicate a special advantage of these nanobody-derived technologies, already surpassing the "me-too" products of other equivalent binders, such as the full-length antibodies, single-chain variable fragments, antigen-binding fragments, targeting peptides, and DNA-based aptamers. In this review, we summarize the current state of the art in nanobody research, focusing on the nanobody structural features, nanobody production approach, nanobody-derived nanobiotechnology tool kits, and the potentially diverse applications in biomedicine and biotechnology. The future trends, challenges, and limitations of the nanobody-derived nanobiotechnology tool kits are also discussed.
ERIC Educational Resources Information Center
Floryan, Mark
2013-01-01
This dissertation presents a novel effort to develop ITS technologies that adapt by observing student behavior. In particular, we define an evolving expert knowledge base (EEKB) that structures a domain's information as a set of nodes and the relationships that exist between those nodes. The structure of this model is not the particularly novel…
Using dynamic mode decomposition to extract cyclic behavior in the stock market
NASA Astrophysics Data System (ADS)
Hua, Jia-Chen; Roy, Sukesh; McCauley, Joseph L.; Gunaratne, Gemunu H.
2016-04-01
The presence of cyclic expansions and contractions in the economy has been known for over a century. The work reported here searches for similar cyclic behavior in stock valuations. The variations are subtle and can only be extracted through analysis of price variations of a large number of stocks. Koopman mode analysis is a natural approach to establish such collective oscillatory behavior. The difficulty is that even non-cyclic and stochastic constituents of a finite data set may be interpreted as a sum of periodic motions. However, deconvolution of these irregular dynamical facets may be expected to be non-robust, i.e., to depend on specific data set. We propose an approach to differentiate robust and non-robust features in a time series; it is based on identifying robust features with reproducible Koopman modes, i.e., those that persist between distinct sub-groupings of the data. Our analysis of stock data discovered four reproducible modes, one of which has period close to the number of trading days/year. To the best of our knowledge these cycles were not reported previously. It is particularly interesting that the cyclic behaviors persisted through the great recession even though phase relationships between stocks within the modes evolved in the intervening period.
The mechanism of folding robustness revealed by the crystal structure of extra-superfolder GFP.
Choi, Jae Young; Jang, Tae-Ho; Park, Hyun Ho
2017-01-01
Stability of green fluorescent protein (GFP) is sometimes important for a proper practical application of this protein. Random mutagenesis and targeted mutagenesis have been used to create better-folded variants of GFP, including recently reported extra-superfolder GFP. Our aim was to determine the crystal structure of extra-superfolder GFP, which is more robustly folded and stable than GFP and superfolder GFP. The structural and structure-based mutagenesis analyses revealed that some of the mutations that created extra-superfolder GFP (F46L, E126K, N149K, and S208L) contribute to folding robustness by stabilizing extra-superfolder GFP with various noncovalent bonds. © 2016 Federation of European Biochemical Societies.
NASA Astrophysics Data System (ADS)
Sharma, Kapil K.; Pandey, S. N.
2016-12-01
In this article, the robustness of tripartite Greenberger-Horne-Zeilinger (GHZ) and W states is investigated against Dzyaloshinskii-Moriya (i.e. DM) interaction. We consider a closed system of three qubits and an environmental qubit. The environmental qubit interacts with any one of the three qubits through DM interaction. The tripartite system is initially prepared in GHZ and W states, respectively. The composite four qubits system evolve with unitary dynamics. We detach the environmental qubit by tracing out from four qubits, and profound impact of DM interaction is studied on the initial entanglement of the system. As a result, we find that the bipartite partitions of W states suffer from entanglement sudden death (i.e. ESD), while tripartite entanglement does not. On the other hand, bipartite partitions and tripartite entanglement in GHZ states do not feel any influence of DM interaction. So, we find that GHZ states have robust character than W states. In this work, we consider generalised GHZ and W states, and three π is used as an entanglement measure. This study can be useful in quantum information processing where unwanted DM interaction takes place.
Cosmological evolution of supermassive black holes in the centres of galaxies
NASA Astrophysics Data System (ADS)
Kapinska, Anna D.
2012-06-01
Radio galaxies and quasars are among the largest and most powerful single objects known and are believed to have had a significant impact on the evolving Universe and its large scale structure. Their jets inject a significant amount of energy into the surrounding medium, hence they can provide useful information in the study of the density and evolution of the intergalactic and intracluster medium. The jet activity is also believed to regulate the growth of massive galaxies via the AGN feedback. In this thesis I explore the intrinsic and extrinsic physical properties of the population of Fanaroff-Riley II (FR II) objects, i.e. their kinetic luminosities, lifetimes, and central densities of their environments. In particular, the radio and kinetic luminosity functions of these powerful radio sources are investigated using the complete, flux limited radio catalogues of 3CRR and BRL. I construct multidimensional Monte Carlo simulations using semi-analytical models of FR II source time evolution to create artificial samples of radio galaxies. Unlike previous studies, I compare radio luminosity functions found with both the observed and simulated data to explore the best-fitting fundamental source parameters. The Monte Carlo method presented here allows one to: (i) set better limits on the predicted fundamental parameters of which confidence intervals estimated over broad ranges are presented, and (ii) generate the most plausible underlying parent populations of these radio sources. Moreover, I allow the source physical properties to co-evolve with redshift, and I find that all the investigated parameters most likely undergo cosmological evolution; however these parameters are strongly degenerate, and independent constraints are necessary to draw more precise conclusions. Furthermore, since it has been suggested that low luminosity FR IIs may be distinct from their powerful equivalents, I attempt to investigate fundamental properties of a sample of low redshift, low radio luminosity density radio galaxies. Based on SDSS-FIRST-NVSS radio sample I construct a low frequency (325 MHz) sample of radio galaxies and attempt to explore the fundamental properties of these low luminosity radio sources. The results are discussed through comparison with the results from the powerful radio sources of the 3CRR and BRL samples. Finally, I investigate the total power injected by populations of these powerful radio sources at various cosmological epochs and discuss the significance of the impact of these sources on the evolving Universe. Remarkably, sets of two degenerate fundamental parameters, the kinetic luminosity and maximum lifetimes of radio sources, despite the degeneracy provide particularly robust estimates of the total power produced by FR IIs during their lifetimes. This can be also used for robust estimations of the quenching of the cooling flows in cluster of galaxies.
Robust control synthesis for uncertain dynamical systems
NASA Technical Reports Server (NTRS)
Byun, Kuk-Whan; Wie, Bong; Sunkel, John
1989-01-01
This paper presents robust control synthesis techniques for uncertain dynamical systems subject to structured parameter perturbation. Both QFT (quantitative feedback theory) and H-infinity control synthesis techniques are investigated. Although most H-infinity-related control techniques are not concerned with the structured parameter perturbation, a new way of incorporating the parameter uncertainty in the robust H-infinity control design is presented. A generic model of uncertain dynamical systems is used to illustrate the design methodologies investigated in this paper. It is shown that, for a certain noncolocated structural control problem, use of both techniques results in nonminimum phase compensation.
NASA Astrophysics Data System (ADS)
Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min
2016-01-01
This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.
How Robustly Does Cannabis Use Associate to College Grades? Findings From Two Cohorts.
Martinez, Julia A; Roth, Madeline G; Johnson, Douglas N; Jones, Jane A
2015-01-01
Along with recent changes in cannabis legalization and decriminalization, there has been an increasing amount of attention aimed at cannabis use and outcomes in college. Although some amount of cannabis use might be expected under theories of collegiate identity development, public health research indicates that cannabis use ultimately associates with negative vocational outcomes. To examine how cannabis use associates with college grade point average specifically, we surveyed n = 1,080 full-time college students and a replication sample of n = 590. Results showed that even after accounting for other measures of student identity formation and drug use, increased cannabis use was robustly associated with lower grade point average. Future research should examine the mechanisms underlying this association. Nevertheless, while laws and attitudes toward cannabis evolve, initiatives to decrease college use should continue. © The Author(s) 2015.
Onboard Image Registration from Invariant Features
NASA Technical Reports Server (NTRS)
Wang, Yi; Ng, Justin; Garay, Michael J.; Burl, Michael C
2008-01-01
This paper describes a feature-based image registration technique that is potentially well-suited for onboard deployment. The overall goal is to provide a fast, robust method for dynamically combining observations from multiple platforms into sensors webs that respond quickly to short-lived events and provide rich observations of objects that evolve in space and time. The approach, which has enjoyed considerable success in mainstream computer vision applications, uses invariant SIFT descriptors extracted at image interest points together with the RANSAC algorithm to robustly estimate transformation parameters that relate one image to another. Experimental results for two satellite image registration tasks are presented: (1) automatic registration of images from the MODIS instrument on Terra to the MODIS instrument on Aqua and (2) automatic stabilization of a multi-day sequence of GOES-West images collected during the October 2007 Southern California wildfires.
The ecology and evolution of avian alarm call signaling systems
NASA Astrophysics Data System (ADS)
Billings, Alexis Chandon
Communication is often set up as a simple dyadic exchange between one sender and one receiver. However, in reality, signaling systems have evolved and are used with many forms and types of information bombarding multiple senders, who in turn send multiple signals of different modalities, through various environmental spaces, finally reaching multiple receivers. In order to understand both the ecology and evolution of a signaling system, we must examine all the facets of the signaling system. My dissertation focused on the alarm call signaling system in birds. Alarm calls are acoustic signals given in response to danger or predators. My first two chapters examine how information about predators alters alarm calls. In chapter one I found that chickadees make distinctions between predators of different hunting strategies and appear to encode information about predators differently if they are heard instead of seen. In my second chapter, I test these findings more robustly in a non-model bird, the Steller's jay. I again found that predator species matters, but that how Steller's jays respond if they saw or heard the predator depends on the predator species. In my third chapter, I tested how habitat has influenced the evolution of mobbing call acoustic structure. I found that habitat is not a major contributor to the variation in acoustic structure seen across species and that other selective pressures such as body size may be more important. In my fourth chapter I present a new framework to understand the evolution of multimodal communication across species. I identify a unique constraint, the need for overlapping sensory systems, thresholds and cognitive abilities between sender and receiver in order for different forms of interspecific communication to evolve. Taken together, these chapters attempt to understand a signaling system from both an ecological and evolutionary perspective by examining each piece of the communication scheme.
A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm
NASA Technical Reports Server (NTRS)
Ortiz, Francisco
2004-01-01
COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.
Irreconcilable difference between quantum walks and adiabatic quantum computing
NASA Astrophysics Data System (ADS)
Wong, Thomas G.; Meyer, David A.
2016-06-01
Continuous-time quantum walks and adiabatic quantum evolution are two general techniques for quantum computing, both of which are described by Hamiltonians that govern their evolutions by Schrödinger's equation. In the former, the Hamiltonian is fixed, while in the latter, the Hamiltonian varies with time. As a result, their formulations of Grover's algorithm evolve differently through Hilbert space. We show that this difference is fundamental; they cannot be made to evolve along each other's path without introducing structure more powerful than the standard oracle for unstructured search. For an adiabatic quantum evolution to evolve like the quantum walk search algorithm, it must interpolate between three fixed Hamiltonians, one of which is complex and introduces structure that is stronger than the oracle for unstructured search. Conversely, for a quantum walk to evolve along the path of the adiabatic search algorithm, it must be a chiral quantum walk on a weighted, directed star graph with structure that is also stronger than the oracle for unstructured search. Thus, the two techniques, although similar in being described by Hamiltonians that govern their evolution, compute by fundamentally irreconcilable means.
The sequence, structure and evolutionary features of HOTAIR in mammals
2011-01-01
Background An increasing number of long noncoding RNAs (lncRNAs) have been identified recently. Different from all the others that function in cis to regulate local gene expression, the newly identified HOTAIR is located between HoxC11 and HoxC12 in the human genome and regulates HoxD expression in multiple tissues. Like the well-characterised lncRNA Xist, HOTAIR binds to polycomb proteins to methylate histones at multiple HoxD loci, but unlike Xist, many details of its structure and function, as well as the trans regulation, remain unclear. Moreover, HOTAIR is involved in the aberrant regulation of gene expression in cancer. Results To identify conserved domains in HOTAIR and study the phylogenetic distribution of this lncRNA, we searched the genomes of 10 mammalian and 3 non-mammalian vertebrates for matches to its 6 exons and the two conserved domains within the 1800 bp exon6 using Infernal. There was just one high-scoring hit for each mammal, but many low-scoring hits were found in both mammals and non-mammalian vertebrates. These hits and their flanking genes in four placental mammals and platypus were examined to determine whether HOTAIR contained elements shared by other lncRNAs. Several of the hits were within unknown transcripts or ncRNAs, many were within introns of, or antisense to, protein-coding genes, and conservation of the flanking genes was observed only between human and chimpanzee. Phylogenetic analysis revealed discrete evolutionary dynamics for orthologous sequences of HOTAIR exons. Exon1 at the 5' end and a domain in exon6 near the 3' end, which contain domains that bind to multiple proteins, have evolved faster in primates than in other mammals. Structures were predicted for exon1, two domains of exon6 and the full HOTAIR sequence. The sequence and structure of two fragments, in exon1 and the domain B of exon6 respectively, were identified to robustly occur in predicted structures of exon1, domain B of exon6 and the full HOTAIR in mammals. Conclusions HOTAIR exists in mammals, has poorly conserved sequences and considerably conserved structures, and has evolved faster than nearby HoxC genes. Exons of HOTAIR show distinct evolutionary features, and a 239 bp domain in the 1804 bp exon6 is especially conserved. These features, together with the absence of some exons and sequences in mouse, rat and kangaroo, suggest ab initio generation of HOTAIR in marsupials. Structure prediction identifies two fragments in the 5' end exon1 and the 3' end domain B of exon6, with sequence and structure invariably occurring in various predicted structures of exon1, the domain B of exon6 and the full HOTAIR. PMID:21496275
STATISTICS AND INTELLIGENCE IN DEVELOPING COUNTRIES: A NOTE.
Kodila-Tedika, Oasis; Asongu, Simplice A; Azia-Dimbu, Florentin
2017-05-01
The purpose of this study is to assess the relationship between intelligence (or human capital) and the statistical capacity of developing countries. The line of inquiry is motivated essentially by the scarce literature on poor statistics in developing countries and an evolving stream of literature on the knowledge economy. A positive association is established between intelligence quotient (IQ) and statistical capacity. The relationship is robust to alternative specifications with varying conditioning information sets and control for outliers. Policy implications are discussed.
Evolved Escherichia coli strains for amplified, functional expression of membrane proteins.
Gul, Nadia; Linares, Daniel M; Ho, Franz Y; Poolman, Bert
2014-01-09
The major barrier to the physical characterization and structure determination of membrane proteins is low protein yield and/or low functionality in recombinant expression. The enteric bacterium Escherichia coli is the most widely employed organism for producing recombinant proteins. Beside several advantages of this expression host, one major drawback is that the protein of interest does not always adopt its native conformation and may end up in large insoluble aggregates. We describe a robust strategy to increase the likelihood of overexpressing membrane proteins in a functional state. The method involves fusion in tandem of green fluorescent protein and the erythromycin resistance protein (23S ribosomal RNA adenine N-6 methyltransferase, ErmC) to the C-terminus of a target membrane protein. The fluorescence of green fluorescent protein is used to report the folding state of the target protein, whereas ErmC is used to select for increased expression. By gradually increasing the erythromycin concentration of the medium and testing different membrane protein targets, we obtained a number of evolved strains of which four (NG2, NG3, NG5 and NG6) were characterized and their genome was fully sequenced. Strikingly, each of the strains carried a mutation in the hns gene, whose product is involved in genome organization and transcriptional silencing. The degree of expression of (membrane) proteins correlates with the severity of the hns mutation, but cells in which hns was deleted showed an intermediate expression performance. We propose that (partial) removal of the transcriptional silencing mechanism changes the levels of proteins essential for the functional overexpression of membrane proteins. © 2013.
Guaranteeing robustness of structural condition monitoring to environmental variability
NASA Astrophysics Data System (ADS)
Van Buren, Kendra; Reilly, Jack; Neal, Kyle; Edwards, Harry; Hemez, François
2017-01-01
Advances in sensor deployment and computational modeling have allowed significant strides to be recently made in the field of Structural Health Monitoring (SHM). One widely used SHM strategy is to perform a vibration analysis where a model of the structure's pristine (undamaged) condition is compared with vibration response data collected from the physical structure. Discrepancies between model predictions and monitoring data can be interpreted as structural damage. Unfortunately, multiple sources of uncertainty must also be considered in the analysis, including environmental variability, unknown model functional forms, and unknown values of model parameters. Not accounting for these sources of uncertainty can lead to false-positives or false-negatives in the structural condition assessment. To manage the uncertainty, we propose a robust SHM methodology that combines three technologies. A time series algorithm is trained using "baseline" data to predict the vibration response, compare predictions to actual measurements collected on a potentially damaged structure, and calculate a user-defined damage indicator. The second technology handles the uncertainty present in the problem. An analysis of robustness is performed to propagate this uncertainty through the time series algorithm and obtain the corresponding bounds of variation of the damage indicator. The uncertainty description and robustness analysis are both inspired by the theory of info-gap decision-making. Lastly, an appropriate "size" of the uncertainty space is determined through physical experiments performed in laboratory conditions. Our hypothesis is that examining how the uncertainty space changes throughout time might lead to superior diagnostics of structural damage as compared to only monitoring the damage indicator. This methodology is applied to a portal frame structure to assess if the strategy holds promise for robust SHM. (Publication approved for unlimited, public release on October-28-2015, LA-UR-15-28442, unclassified.)
The Evolving Market Structure of the U.S. Residential Solar PV Installation
Solar PV Installation Industry, 2000-2016 The Evolving Market Structure of the U.S. Residential Solar PV residential solar photovoltaic (PV) system and that the residential PV installation industry has become more concentrated over time. From 2000 to 2016, the U.S. residential solar photovoltaic (PV) installation industry
Rudall, Paula J.; Bateman, Richard M.
2010-01-01
Recent phylogenetic reconstructions suggest that axially condensed flower-like structures evolved iteratively in seed plants from either simple or compound strobili. The simple-strobilus model of flower evolution, widely applied to the angiosperm flower, interprets the inflorescence as a compound strobilus. The conifer cone and the gnetalean ‘flower’ are commonly interpreted as having evolved from a compound strobilus by extreme condensation and (at least in the case of male conifer cones) elimination of some structures present in the presumed ancestral compound strobilus. These two hypotheses have profoundly different implications for reconstructing the evolution of developmental genetic mechanisms in seed plants. If different flower-like structures evolved independently, there should intuitively be little commonality of patterning genes. However, reproductive units of some early-divergent angiosperms, including the extant genus Trithuria (Hydatellaceae) and the extinct genus Archaefructus (Archaefructaceae), apparently combine features considered typical of flowers and inflorescences. We re-evaluate several disparate strands of comparative data to explore whether flower-like structures could have arisen by co-option of flower-expressed patterning genes into independently evolved condensed inflorescences, or vice versa. We discuss the evolution of the inflorescence in both gymnosperms and angiosperms, emphasising the roles of heterotopy in dictating gender expression and heterochrony in permitting internodal compression. PMID:20047867
Rudall, Paula J; Bateman, Richard M
2010-02-12
Recent phylogenetic reconstructions suggest that axially condensed flower-like structures evolved iteratively in seed plants from either simple or compound strobili. The simple-strobilus model of flower evolution, widely applied to the angiosperm flower, interprets the inflorescence as a compound strobilus. The conifer cone and the gnetalean 'flower' are commonly interpreted as having evolved from a compound strobilus by extreme condensation and (at least in the case of male conifer cones) elimination of some structures present in the presumed ancestral compound strobilus. These two hypotheses have profoundly different implications for reconstructing the evolution of developmental genetic mechanisms in seed plants. If different flower-like structures evolved independently, there should intuitively be little commonality of patterning genes. However, reproductive units of some early-divergent angiosperms, including the extant genus Trithuria (Hydatellaceae) and the extinct genus Archaefructus (Archaefructaceae), apparently combine features considered typical of flowers and inflorescences. We re-evaluate several disparate strands of comparative data to explore whether flower-like structures could have arisen by co-option of flower-expressed patterning genes into independently evolved condensed inflorescences, or vice versa. We discuss the evolution of the inflorescence in both gymnosperms and angiosperms, emphasising the roles of heterotopy in dictating gender expression and heterochrony in permitting internodal compression.
MacDonald, G; Mackenzie, J A; Nolan, M; Insall, R H
2016-03-15
In this paper, we devise a moving mesh finite element method for the approximate solution of coupled bulk-surface reaction-diffusion equations on an evolving two dimensional domain. Fundamental to the success of the method is the robust generation of bulk and surface meshes. For this purpose, we use a novel moving mesh partial differential equation (MMPDE) approach. The developed method is applied to model problems with known analytical solutions; these experiments indicate second-order spatial and temporal accuracy. Coupled bulk-surface problems occur frequently in many areas; in particular, in the modelling of eukaryotic cell migration and chemotaxis. We apply the method to a model of the two-way interaction of a migrating cell in a chemotactic field, where the bulk region corresponds to the extracellular region and the surface to the cell membrane.
Using Evolved Fuzzy Neural Networks for Injury Detection from Isokinetic Curves
NASA Astrophysics Data System (ADS)
Couchet, Jorge; Font, José María; Manrique, Daniel
In this paper we propose an evolutionary fuzzy neural networks system for extracting knowledge from a set of time series containing medical information. The series represent isokinetic curves obtained from a group of patients exercising the knee joint on an isokinetic dynamometer. The system has two parts: i) it analyses the time series input in order generate a simplified model of an isokinetic curve; ii) it applies a grammar-guided genetic program to obtain a knowledge base represented by a fuzzy neural network. Once the knowledge base has been generated, the system is able to perform knee injuries detection. The results suggest that evolved fuzzy neural networks perform better than non-evolutionary approaches and have a high accuracy rate during both the training and testing phases. Additionally, they are robust, as the system is able to self-adapt to changes in the problem without human intervention.
Autonomous Evolution of Dynamic Gaits with Two Quadruped Robots
NASA Technical Reports Server (NTRS)
Hornby, Gregory S.; Takamura, Seichi; Yamamoto, Takashi; Fujita, Masahiro
2004-01-01
A challenging task that must be accomplished for every legged robot is creating the walking and running behaviors needed for it to move. In this paper we describe our system for autonomously evolving dynamic gaits on two of Sony's quadruped robots. Our evolutionary algorithm runs on board the robot and uses the robot's sensors to compute the quality of a gait without assistance from the experimenter. First we show the evolution of a pace and trot gait on the OPEN-R prototype robot. With the fastest gait, the robot moves at over 10/min/min., which is more than forty body-lengths/min. While these first gaits are somewhat sensitive to the robot and environment in which they are evolved, we then show the evolution of robust dynamic gaits, one of which is used on the ERS-110, the first consumer version of AIBO.
Robust biological parametric mapping: an improved technique for multimodal brain image analysis
NASA Astrophysics Data System (ADS)
Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.
2011-03-01
Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.
Linear, multivariable robust control with a mu perspective
NASA Technical Reports Server (NTRS)
Packard, Andy; Doyle, John; Balas, Gary
1993-01-01
The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.
Stability and the Evolvability of Function in a Model Protein
Bloom, Jesse D.; Wilke, Claus O.; Arnold, Frances H.; Adami, Christoph
2004-01-01
Functional proteins must fold with some minimal stability to a structure that can perform a biochemical task. Here we use a simple model to investigate the relationship between the stability requirement and the capacity of a protein to evolve the function of binding to a ligand. Although our model contains no built-in tradeoff between stability and function, proteins evolved function more efficiently when the stability requirement was relaxed. Proteins with both high stability and high function evolved more efficiently when the stability requirement was gradually increased than when there was constant selection for high stability. These results show that in our model, the evolution of function is enhanced by allowing proteins to explore sequences corresponding to marginally stable structures, and that it is easier to improve stability while maintaining high function than to improve function while maintaining high stability. Our model also demonstrates that even in the absence of a fundamental biophysical tradeoff between stability and function, the speed with which function can evolve is limited by the stability requirement imposed on the protein. PMID:15111394
Genetic Architecture Promotes the Evolution and Maintenance of Cooperation
Frénoy, Antoine; Taddei, François; Misevic, Dusan
2013-01-01
When cooperation has a direct cost and an indirect benefit, a selfish behavior is more likely to be selected for than an altruistic one. Kin and group selection do provide evolutionary explanations for the stability of cooperation in nature, but we still lack the full understanding of the genomic mechanisms that can prevent cheater invasion. In our study we used Aevol, an agent-based, in silico genomic platform to evolve populations of digital organisms that compete, reproduce, and cooperate by secreting a public good for tens of thousands of generations. We found that cooperating individuals may share a phenotype, defined as the amount of public good produced, but have very different abilities to resist cheater invasion. To understand the underlying genetic differences between cooperator types, we performed bio-inspired genomics analyses of our digital organisms by recording and comparing the locations of metabolic and secretion genes, as well as the relevant promoters and terminators. Association between metabolic and secretion genes (promoter sharing, overlap via frame shift or sense-antisense encoding) was characteristic for populations with robust cooperation and was more likely to evolve when secretion was costly. In mutational analysis experiments, we demonstrated the potential evolutionary consequences of the genetic association by performing a large number of mutations and measuring their phenotypic and fitness effects. The non-cooperating mutants arising from the individuals with genetic association were more likely to have metabolic deleterious mutations that eventually lead to selection eliminating such mutants from the population due to the accompanying fitness decrease. Effectively, cooperation evolved to be protected and robust to mutations through entangled genetic architecture. Our results confirm the importance of second-order selection on evolutionary outcomes, uncover an important genetic mechanism for the evolution and maintenance of cooperation, and suggest promising methods for preventing gene loss in synthetically engineered organisms. PMID:24278000
NASA Astrophysics Data System (ADS)
Zhang, Langwen; Xie, Wei; Wang, Jingcheng
2017-11-01
In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.
NASA Technical Reports Server (NTRS)
Wie, Bong; Liu, Qiang
1992-01-01
Both feedback and feedforward control approaches for uncertain dynamical systems (in particular, with uncertainty in structural mode frequency) are investigated. The control objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant uncertainty. Preshaping of an ideal, time optimal control input using a tapped-delay filter is shown to provide a fast settling time with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. It is shown that a properly designed, feedback controller performs well, as compared with a time optimal open loop controller with special preshaping for performance robustness. Also included are two separate papers by the same authors on this subject.
A model for the emergence of cooperation, interdependence, and structure in evolving networks.
Jain, S; Krishna, S
2001-01-16
Evolution produces complex and structured networks of interacting components in chemical, biological, and social systems. We describe a simple mathematical model for the evolution of an idealized chemical system to study how a network of cooperative molecular species arises and evolves to become more complex and structured. The network is modeled by a directed weighted graph whose positive and negative links represent "catalytic" and "inhibitory" interactions among the molecular species, and which evolves as the least populated species (typically those that go extinct) are replaced by new ones. A small autocatalytic set, appearing by chance, provides the seed for the spontaneous growth of connectivity and cooperation in the graph. A highly structured chemical organization arises inevitably as the autocatalytic set enlarges and percolates through the network in a short analytically determined timescale. This self organization does not require the presence of self-replicating species. The network also exhibits catastrophes over long timescales triggered by the chance elimination of "keystone" species, followed by recoveries.
A model for the emergence of cooperation, interdependence, and structure in evolving networks
NASA Astrophysics Data System (ADS)
Jain, Sanjay; Krishna, Sandeep
2001-01-01
Evolution produces complex and structured networks of interacting components in chemical, biological, and social systems. We describe a simple mathematical model for the evolution of an idealized chemical system to study how a network of cooperative molecular species arises and evolves to become more complex and structured. The network is modeled by a directed weighted graph whose positive and negative links represent "catalytic" and "inhibitory" interactions among the molecular species, and which evolves as the least populated species (typically those that go extinct) are replaced by new ones. A small autocatalytic set, appearing by chance, provides the seed for the spontaneous growth of connectivity and cooperation in the graph. A highly structured chemical organization arises inevitably as the autocatalytic set enlarges and percolates through the network in a short analytically determined timescale. This self organization does not require the presence of self-replicating species. The network also exhibits catastrophes over long timescales triggered by the chance elimination of "keystone" species, followed by recoveries.
Solving a real-world problem using an evolving heuristically driven schedule builder.
Hart, E; Ross, P; Nelson, J
1998-01-01
This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be successfully solved by division into two subproblems and solving each using a separate genetic algorithm (GA). We address the problem of whether this produces locally optimal solutions and how to overcome this. We extend the traditional approach of evolving a "permutation + schedule builder" by concentrating on evolving the schedule builder itself. This results in a unique schedule builder being built for each daily scheduling problem, each individually tailored to deal with the particular features of that problem. This results in a robust, fast, and flexible system that can cope with most of the circumstances imaginable at the factory. We also compare the performance of a GA approach to several other evolutionary methods and show that population-based methods are superior to both hill-climbing and simulated annealing in the quality of solutions produced. Population-based methods also have the distinct advantage of producing multiple, equally fit solutions, which is of particular importance when considering the practical aspects of the problem.
Zagrijchuk, Elizaveta A.; Sabirov, Marat A.; Holloway, David M.; Spirov, Alexander V.
2014-01-01
Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes. PMID:24712536
The emotion system promotes diversity and evolvability
Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J.; Aksnes, Dag L.; Mangel, Marc; Jørgensen, Christian
2014-01-01
Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels. PMID:25100697
The emotion system promotes diversity and evolvability.
Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J; Aksnes, Dag L; Mangel, Marc; Jørgensen, Christian
2014-09-22
Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels.
Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark
2016-01-01
In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.
Evolving effective behaviours to interact with tag-based populations
NASA Astrophysics Data System (ADS)
Yucel, Osman; Crawford, Chad; Sen, Sandip
2015-07-01
Tags and other characteristics, externally perceptible features that are consistent among groups of animals or humans, can be used by others to determine appropriate response strategies in societies. This usage of tags can be extended to artificial environments, where agents can significantly reduce cognitive effort spent on appropriate strategy choice and behaviour selection by reusing strategies for interacting with new partners based on their tags. Strategy selection mechanisms developed based on this idea have successfully evolved stable cooperation in games such as the Prisoner's Dilemma game but relies upon payoff sharing and matching methods that limit the applicability of the tag framework. Our goal is to develop a general classification and behaviour selection approach based on the tag framework. We propose and evaluate alternative tag matching and adaptation schemes for a new, incoming individual to select appropriate behaviour against any population member of an existing, stable society. Our proposed approach allows agents to evolve both the optimal tag for the environment as well as appropriate strategies for existing agent groups. We show that these mechanisms will allow for robust selection of optimal strategies by agents entering a stable society and analyse the various environments where this approach is effective.
NASA Astrophysics Data System (ADS)
Wang, Chunbai; Mitra, Ambar K.
2016-01-01
Any boundary surface evolving in viscous fluid is driven with surface capillary currents. By step function defined for the fluid-structure interface, surface currents are found near a flat wall in a logarithmic form. The general flat-plate boundary layer is demonstrated through the interface kinematics. The dynamics analysis elucidates the relationship of the surface currents with the adhering region as well as the no-slip boundary condition. The wall skin friction coefficient, displacement thickness, and the logarithmic velocity-defect law of the smooth flat-plate boundary-layer flow are derived with the advent of the forced evolving boundary method. This fundamental theory has wide applications in applied science and engineering.
Reetz, Manfred T.
2004-01-01
A fundamentally new approach to asymmetric catalysis in organic chemistry is described based on the in vitro evolution of enantioselective enzymes. It comprises the appropriate combination of gene mutagenesis and expression coupled with an efficient high-throughput screening system for evaluating enantioselectivity (enantiomeric excess assay). Several such cycles lead to a “Darwinistic” process, which is independent of any knowledge concerning the structure or the mechanism of the enzyme being evolved. The challenge is to choose the optimal mutagenesis methods to navigate efficiently in protein sequence space. As a first example, the combination of error-prone mutagenesis, saturation mutagenesis, and DNA-shuffling led to a dramatic enhancement of enantioselectivity of a lipase acting as a catalyst in the kinetic resolution of a chiral ester. Mutations at positions remote from the catalytically active center were identified, a surprising finding, which was explained on the basis of a novel relay mechanism. The scope and limitations of the method are discussed, including the prospect of directed evolution of stereoselective hybrid catalysts composed of robust protein hosts in which transition metal centers have been implanted. PMID:15079053
Dynamic pricing of network goods with boundedly rational consumers.
Radner, Roy; Radunskaya, Ami; Sundararajan, Arun
2014-01-07
We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller's optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product's user base evolving over time and consumers basing their choices on a mixture of a myopic and a "stubborn" expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice.
Determinant factors of industrial symbiosis: greening Pasir Gudang industrial park
NASA Astrophysics Data System (ADS)
Teh, B. T.; Ho, C. S.; Matsuoka, Y.; Chau, L. W.; Gomi, K.
2014-02-01
Green industry has been identified as an important element in attaining greater sustainability. It calls for harmonizing robust economic growth with environment protection. Industries, particularly in developing and transitional nations such as Malaysia, are in need of a reform. Many experts and international organizations suggest the concept of industrial symbiosis. Mainly, there are successful cases of industrial symbiosis practices around the world. However, there are numerous cases of failure too. As industrial symbiosis is an emerging new approach, with a short history of two decades, a lot of researches are generally focused on narrow context and technical details. There is a lack of concerted efforts to look into the drivers and barriers of industrial symbiosis across different cases. This paper aims to examine the factors influencing the development of industrial symbiosis from various countries to supports such networks to evolve in Pasir Gudang. The findings show institution, law and regulation, finance, awareness and capacity building, technology, research and development, information, collaboration, market, geography proximity, environmental issues and industry structure affect the formation of industrial symbiosis.
Isoform switching facilitates period control in the Neurospora crassa circadian clock.
Akman, Ozgur E; Locke, James C W; Tang, Sanyi; Carré, Isabelle; Millar, Andrew J; Rand, David A
2008-01-01
A striking and defining feature of circadian clocks is the small variation in period over a physiological range of temperatures. This is referred to as temperature compensation, although recent work has suggested that the variation observed is a specific, adaptive control of period. Moreover, given that many biological rate constants have a Q(10) of around 2, it is remarkable that such clocks remain rhythmic under significant temperature changes. We introduce a new mathematical model for the Neurospora crassa circadian network incorporating experimental work showing that temperature alters the balance of translation between a short and long form of the FREQUENCY (FRQ) protein. This is used to discuss period control and functionality for the Neurospora system. The model reproduces a broad range of key experimental data on temperature dependence and rhythmicity, both in wild-type and mutant strains. We present a simple mechanism utilising the presence of the FRQ isoforms (isoform switching) by which period control could have evolved, and argue that this regulatory structure may also increase the temperature range where the clock is robustly rhythmic.
Choice Shift in Opinion Network Dynamics
NASA Astrophysics Data System (ADS)
Gabbay, Michael
Choice shift is a phenomenon associated with small group dynamics whereby group discussion causes group members to shift their opinions in a more extreme direction so that the mean post-discussion opinion exceeds the mean pre-discussion opinion. Also known as group polarization, choice shift is a robust experimental phenomenon and has been well-studied within social psychology. In opinion network models, shifts toward extremism are typically produced by the presence of stubborn agents at the extremes of the opinion axis, whose opinions are much more resistant to change than moderate agents. However, we present a model in which choice shift can arise without the assumption of stubborn agents; the model evolves member opinions and uncertainties using coupled nonlinear differential equations. In addition, we briefly describe the results of a recent experiment conducted involving online group discussion concerning the outcome of National Football League games are described. The model predictions concerning the effects of network structure, disagreement level, and team choice (favorite or underdog) are in accord with the experimental results. This research was funded by the Office of Naval Research and the Defense Threat Reduction Agency.
1H magic-angle spinning NMR evolves as a powerful new tool for membrane proteins
NASA Astrophysics Data System (ADS)
Schubeis, Tobias; Le Marchand, Tanguy; Andreas, Loren B.; Pintacuda, Guido
2018-02-01
Building on a decade of continuous advances of the community, the recent development of very fast (60 kHz and above) magic-angle spinning (MAS) probes has revolutionised the field of solid-state NMR. This new spinning regime reduces the 1H-1H dipolar couplings, so that direct detection of the larger magnetic moment available from 1H is now possible at high resolution, not only in deuterated molecules but also in fully-protonated substrates. Such capabilities allow rapid "fingerprinting" of samples with a ten-fold reduction of the required sample amounts with respect to conventional approaches, and permit extensive, robust and expeditious assignment of small-to-medium sized proteins (up to ca. 300 residues), and the determination of inter-nuclear proximities, relative orientations of secondary structural elements, protein-cofactor interactions, local and global dynamics. Fast MAS and 1H detection techniques have nowadays been shown to be applicable to membrane-bound systems. This paper reviews the strategies underlying this recent leap forward in sensitivity and resolution, describing its potential for the detailed characterization of membrane proteins.
Dynamic pricing of network goods with boundedly rational consumers
Radner, Roy; Radunskaya, Ami; Sundararajan, Arun
2014-01-01
We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller’s optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product’s user base evolving over time and consumers basing their choices on a mixture of a myopic and a “stubborn” expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice. PMID:24367101
Natural selection promotes antigenic evolvability.
Graves, Christopher J; Ros, Vera I D; Stevenson, Brian; Sniegowski, Paul D; Brisson, Dustin
2013-01-01
The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.
Natural Selection Promotes Antigenic Evolvability
Graves, Christopher J.; Ros, Vera I. D.; Stevenson, Brian; Sniegowski, Paul D.; Brisson, Dustin
2013-01-01
The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed ‘cassettes’ that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections. PMID:24244173
Tetrametallic molecular catalysts for photochemical water oxidation.
Sartorel, Andrea; Bonchio, Marcella; Campagna, Sebastiano; Scandola, Franco
2013-03-21
Among molecular water oxidation catalysts (WOCs), those featuring a reactive set of four multi-redox transition metals can leverage an extraordinary interplay of electronic and structural properties. These are of particular interest, owing to their close structural, and possibly functional, relationship to the oxygen evolving complex of natural photosynthesis. In this review, special attention is given to two classes of tetrametallic molecular WOCs: (i) M(4)O(4) cubane-type structures stabilized by simple organic ligands, and (ii) systems in which a tetranuclear metal core is stabilized by coordination of two polyoxometalate (POM) ligands. Recent work in this rapidly evolving field is reviewed, with particular emphasis on photocatalytic aspects. Special attention is given to studies addressing the mechanistic complexity of these systems, sometimes overlooked in the rush for oxygen evolving performance. The complementary role of molecular WOCs and their relationship with bulk oxides and heterogeneous catalysis are discussed.
Ni, Xuan; Yang, Rui; Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso
2010-12-01
Microscopic models based on evolutionary games on spatially extended scales have recently been developed to address the fundamental issue of species coexistence. In this pursuit almost all existing works focus on the relevant dynamical behaviors originated from a single but physically reasonable initial condition. To gain comprehensive and global insights into the dynamics of coexistence, here we explore the basins of coexistence and extinction and investigate how they evolve as a basic parameter of the system is varied. Our model is cyclic competitions among three species as described by the classical rock-paper-scissors game, and we consider both discrete lattice and continuous space, incorporating species mobility and intraspecific competitions. Our results reveal that, for all cases considered, a basin of coexistence always emerges and persists in a substantial part of the parameter space, indicating that coexistence is a robust phenomenon. Factors such as intraspecific competition can, in fact, promote coexistence by facilitating the emergence of the coexistence basin. In addition, we find that the extinction basins can exhibit quite complex structures in terms of the convergence time toward the final state for different initial conditions. We have also developed models based on partial differential equations, which yield basin structures that are in good agreement with those from microscopic stochastic simulations. To understand the origin and emergence of the observed complicated basin structures is challenging at the present due to the extremely high dimensional nature of the underlying dynamical system. © 2010 American Institute of Physics.
Reactome diagram viewer: data structures and strategies to boost performance.
Fabregat, Antonio; Sidiropoulos, Konstantinos; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning
2018-04-01
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community. The pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partitioning data structure minimizes CPU workload, enabling the introduction of new features that further enhance user experience. Through the use of highly optimized data structures and algorithms, Reactome has boosted the performance and usability of the new pathway diagram viewer, providing a robust, scalable and easy-to-integrate solution to pathway visualization. As graph-based visualization of complex data is a frequent challenge in bioinformatics, many of the individual strategies presented here are applicable to a wide range of web-based bioinformatics resources. Reactome is available online at: https://reactome.org. The diagram viewer is part of the Reactome pathway browser (https://reactome.org/PathwayBrowser/) and also available as a stand-alone widget at: https://reactome.org/dev/diagram/. The source code is freely available at: https://github.com/reactome-pwp/diagram. fabregat@ebi.ac.uk or hhe@ebi.ac.uk. Supplementary data are available at Bioinformatics online.
Structural basis for inhibition of TLR2 by staphylococcal superantigen-like protein 3 (SSL3)
Koymans, Kirsten J.; Feitsma, Louris J.; Brondijk, T. Harma C.; Aerts, Piet C.; Lukkien, Eddie; Lössl, Philip; van Kessel, Kok P. M.; de Haas, Carla J. C.; van Strijp, Jos A. G.; Huizinga, Eric G.
2015-01-01
Toll-like receptors (TLRs) are crucial in innate recognition of invading micro-organisms and their subsequent clearance. Bacteria are not passive bystanders and have evolved complex evasion mechanisms. Staphylococcus aureus secretes a potent TLR2 antagonist, staphylococcal superantigen-like protein 3 (SSL3), which prevents receptor stimulation by pathogen-associated lipopeptides. Here, we present crystal structures of SSL3 and its complex with TLR2. The structure reveals that formation of the specific inhibitory complex is predominantly mediated by hydrophobic contacts between SSL3 and TLR2 and does not involve interaction of TLR2–glycans with the conserved LewisX binding site of SSL3. In the complex, SSL3 partially covers the entrance to the lipopeptide binding pocket in TLR2, reducing its size by ∼50%. We show that this is sufficient to inhibit binding of agonist Pam2CSK4 effectively, yet allows SSL3 to bind to an already formed TLR2–Pam2CSK4 complex. The binding site of SSL3 overlaps those of TLR2 dimerization partners TLR1 and TLR6 extensively. Combined, our data reveal a robust dual mechanism in which SSL3 interferes with TLR2 activation at two stages: by binding to TLR2, it blocks ligand binding and thus inhibits activation. Second, by interacting with an already formed TLR2–lipopeptide complex, it prevents TLR heterodimerization and downstream signaling. PMID:26283364
Self-assembly of amorphous biophotonic nanostructures by phase separation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dufresne, Eric R.; Noh, Heeso; Saranathan, Vinodkumar
2009-04-23
Some of the most vivid colors in the animal kingdom are created not by pigments, but by wavelength-selective scattering of light from nanostructures. Here we investigate quasi-ordered nanostructures of avian feather barbs which produce vivid non-iridescent colors. These {beta}-keratin and air nanostructures are found in two basic morphologies: tortuous channels and amorphous packings of spheres. Each class of nanostructure is isotropic and has a pronounced characteristic length scale of variation in composition. These local structural correlations lead to strong backscattering over a narrow range of optical frequencies and little variation with angle of incidence. Such optical properties play important rolesmore » in social and sexual communication. To be effective, birds need to precisely control the development of these nanoscale structures, yet little is known about how they grow. We hypothesize that multiple lineages of birds have convergently evolved to exploit phase separation and kinetic arrest to self-assemble spongy color-producing nanostructures in feather barbs. Observed avian nanostructures are strikingly similar to those self-assembled during the phase separation of fluid mixtures; the channel and sphere morphologies are characteristic of phase separation by spinodal decomposition and nucleation and growth, respectively. These unstable structures are locked-in by the kinetic arrest of the {beta}-keratin matrix, likely through the entanglement or cross-linking of supermolecular {beta}-keratin fibers. Using the power of self-assembly, birds can robustly realize a diverse range of nanoscopic morphologies with relatively small physical and chemical changes during feather development.« less
NASA Technical Reports Server (NTRS)
Stoica, A.; Keymeulen, D.; Zebulum, R. S.; Ferguson, M. I.; Guo, X.
2002-01-01
This paper comments on some directions of growth for evolvable hardware, proposes research directions that address the scalability problem and gives examples of results in novel areas approached by EHW.
A Robust Bayesian Approach for Structural Equation Models with Missing Data
ERIC Educational Resources Information Center
Lee, Sik-Yum; Xia, Ye-Mao
2008-01-01
In this paper, normal/independent distributions, including but not limited to the multivariate t distribution, the multivariate contaminated distribution, and the multivariate slash distribution, are used to develop a robust Bayesian approach for analyzing structural equation models with complete or missing data. In the context of a nonlinear…
The Robustness of LISREL Estimates in Structural Equation Models with Categorical Variables.
ERIC Educational Resources Information Center
Ethington, Corinna A.
1987-01-01
This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical variables. The analysis of mixed matrices produced estimates that closely approximated the model parameters except where dichotomous variables were…
Spectroscopic confirmation of a galaxy cluster associated with 7C 1756+6520 at z = 1.416
NASA Astrophysics Data System (ADS)
Galametz, A.; Stern, D.; Stanford, S. A.; De Breuck, C.; Vernet, J.; Griffith, R. L.; Harrison, F. A.
2010-06-01
We present spectroscopic follow-up of an overdensity of galaxies photometrically selected to be at 1.4 < z < 2.5 found in the vicinity of the radio galaxy 7C 1756+6520 at z = 1.4156. Using the DEIMOS optical multi-object spectrograph on the Keck 2 telescope, we observed a total of 129 BzK-selected sources, comprising 82 blue, star-forming galaxy candidates (sBzK) and 47 red, passively-evolving galaxy candidates (pBzK*), as well as 11 mid-infrared selected AGN candidates. We obtain robust spectroscopic redshifts for 36 blue galaxies, 7 red galaxies and 9 AGN candidates. Assuming all foreground interlopers were identified, we find that only 16% (9%) of the sBzK (pBzK*) galaxies are at z < 1.4. Therefore, the BzK criteria are shown to be relatively robust at identifying galaxies at moderate redshifts. Twenty-one galaxies, including the radio galaxy, four additional AGN candidates and three red galaxy candidates are found with 1.4156 ± 0.025, forming a large scale structure at the redshift of the radio galaxy. Of these, eight have projected offsets <2 Mpc relative to the radio galaxy position and have velocity offsets <1000 km s-1 relative to the radio galaxy redshift. This confirms that 7C 1756+6520 is associated with a high-redshift galaxy cluster. A second compact group of four galaxies is found at z ~ 1.437, forming a sub-group offset by Δv ~ 3000 km s-1 and approximately 1.'5 east of the radio galaxy.
Is countershading camouflage robust to lighting change due to weather?
2018-01-01
Countershading is a pattern of coloration thought to have evolved in order to implement camouflage. By adopting a pattern of coloration that makes the surface facing towards the sun darker and the surface facing away from the sun lighter, the overall amount of light reflected off an animal can be made more uniformly bright. Countershading could hence contribute to visual camouflage by increasing background matching or reducing cues to shape. However, the usefulness of countershading is constrained by a particular pattern delivering ‘optimal’ camouflage only for very specific lighting conditions. In this study, we test the robustness of countershading camouflage to lighting change due to weather, using human participants as a ‘generic’ predator. In a simulated three-dimensional environment, we constructed an array of simple leaf-shaped items and a single ellipsoidal target ‘prey’. We set these items in two light environments: strongly directional ‘sunny’ and more diffuse ‘cloudy’. The target object was given the optimal pattern of countershading for one of these two environment types or displayed a uniform pattern. By measuring detection time and accuracy, we explored whether and how target detection depended on the match between the pattern of coloration on the target object and scene lighting. Detection times were longest when the countershading was appropriate to the illumination; incorrectly camouflaged targets were detected with a similar pattern of speed and accuracy to uniformly coloured targets. We conclude that structural changes in light environment, such as caused by differences in weather, do change the effectiveness of countershading camouflage. PMID:29515822
Martin, Sébastien; Troccaz, Jocelyne; Daanenc, Vincent
2010-04-01
The authors present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. The approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves toward the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. During the evolution of the surface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. The proposed method is evaluated on 36 exams that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.
Kappenman, Emily S; Keil, Andreas
2017-01-01
In recent years, the psychological and behavioral sciences have increased efforts to strengthen methodological practices and publication standards, with the ultimate goal of enhancing the value and reproducibility of published reports. These issues are especially important in the multidisciplinary field of psychophysiology, which yields rich and complex data sets with a large number of observations. In addition, the technological tools and analysis methods available in the field of psychophysiology are continually evolving, widening the array of techniques and approaches available to researchers. This special issue presents articles detailing rigorous and systematic evaluations of tasks, measures, materials, analysis approaches, and statistical practices in a variety of subdisciplines of psychophysiology. These articles highlight challenges in conducting and interpreting psychophysiological research and provide data-driven, evidence-based recommendations for overcoming those challenges to produce robust, reproducible results in the field of psychophysiology. © 2016 Society for Psychophysiological Research.
Effector-triggered immunity: from pathogen perception to robust defense.
Cui, Haitao; Tsuda, Kenichi; Parker, Jane E
2015-01-01
In plant innate immunity, individual cells have the capacity to sense and respond to pathogen attack. Intracellular recognition mechanisms have evolved to intercept perturbations by pathogen virulence factors (effectors) early in host infection and convert it to rapid defense. One key to resistance success is a polymorphic family of intracellular nucleotide-binding/leucine-rich-repeat (NLR) receptors that detect effector interference in different parts of the cell. Effector-activated NLRs connect, in various ways, to a conserved basal resistance network in order to transcriptionally boost defense programs. Effector-triggered immunity displays remarkable robustness against pathogen disturbance, in part by employing compensatory mechanisms within the defense network. Also, the mobility of some NLRs and coordination of resistance pathways across cell compartments provides flexibility to fine-tune immune outputs. Furthermore, a number of NLRs function close to the nuclear chromatin by balancing actions of defense-repressing and defense-activating transcription factors to program cells dynamically for effective disease resistance.
Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics.
Kaneko, Kunihiko; Furusawa, Chikara
2018-05-20
We present a macroscopic theory to characterize the plasticity, robustness, and evolvability of biological responses and their fluctuations. First, linear approximation in intracellular reaction dynamics is used to demonstrate proportional changes in the expression of all cellular components in response to a given environmental stress, with the proportion coefficient determined by the change in growth rate as a consequence of the steady growth of cells. We further demonstrate that this relationship is supported through adaptation experiments of bacteria, perhaps too well as this proportionality is held even across cultures of different types of conditions. On the basis of simulations of cell models, we further show that this global proportionality is a consequence of evolution in which expression changes in response to environmental or genetic perturbations are constrained along a unique one-dimensional curve, which is a result of evolutionary robustness. It then follows that the expression changes induced by environmental changes are proportionally reduced across different components of a cell by evolution, which is akin to the Le Chatelier thermodynamics principle. Finally, with the aid of a fluctuation-response relationship, this proportionality is shown to hold between fluctuations caused by genetic changes and those caused by noise. Overall, these results and support from the theoretical and experimental literature suggest a formulation of cellular systems akin to thermodynamics, in which a macroscopic potential is given by the growth rate (or fitness) represented as a function of environmental and evolutionary changes.
Space Launch Systems Block 1B Preliminary Navigation System Design
NASA Technical Reports Server (NTRS)
Oliver, T. Emerson; Park, Thomas; Anzalone, Evan; Smith, Austin; Strickland, Dennis; Patrick, Sean
2018-01-01
NASA is currently building the Space Launch Systems (SLS) Block 1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. In parallel, NASA is also designing the Block 1B launch vehicle. The Block 1B vehicle is an evolution of the Block 1 vehicle and extends the capability of the NASA launch vehicle. This evolution replaces the Interim Cryogenic Propulsive Stage (ICPS) with the Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability, increased robustness for manned missions, and the capability to execute more demanding missions so must the SLS Integrated Navigation System evolved to support those missions. This paper describes the preliminary navigation systems design for the SLS Block 1B vehicle. The evolution of the navigation hard-ware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1B vehicle navigation system is de-signed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. Additionally, the Block 1B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and robust algorithm design, including Fault Detection, Isolation, and Recovery (FDIR) logic.
Passive dynamics is a good basis for robot design and control, not!
NASA Astrophysics Data System (ADS)
Ruina, Andy
Many airplanes can, or nearly can, glide stably without control. So, it seems natural that the first successful powered flight followed from mastery of gliding. Many bicycles can, or nearly can, balance themselves when in motion. Bicycle design seems to have evolved to gain this feature. Also, we can make toys and 'robots' that, like a stable glider or coasting bicycle, stably walk without motors or control in a remarkably human-like way. Again, it seems to make sense to use `passive-dynamics' as a core for developing the control of walking robots and to gain understanding of the control of walking people. That's what I used to think. But, so far, this has not led to robust walking robots. What about human evolution? We didn't evolve dynamic bodies and then learn to control them. Rather, people had elaborate control systems way back when we were fish and even worms. However: if control is paramount, why is it that uncontrolled passive-dynamic walkers walk so much like humans? It seems that energy optimal, yet robust, control, perhaps a proxy for evolutionary development, arrives at solutions that have some features in common with passive-dynamics. Rather than thinking of good powered walking as passive walking with a small amount of control added, I now think of good powered walking, human or robotic, as highly controlled, while optimized for, in part, minimal actuator use. Thus, much of the motor effort, always at the ready, is usually titrated out.
Salvi, Daniele; Macali, Armando; Mariottini, Paolo
2014-01-01
The bivalve family Ostreidae has a worldwide distribution and includes species of high economic importance. Phylogenetics and systematic of oysters based on morphology have proved difficult because of their high phenotypic plasticity. In this study we explore the phylogenetic information of the DNA sequence and secondary structure of the nuclear, fast-evolving, ITS2 rRNA and the mitochondrial 16S rRNA genes from the Ostreidae and we implemented a multi-locus framework based on four loci for oyster phylogenetics and systematics. Sequence-structure rRNA models aid sequence alignment and improved accuracy and nodal support of phylogenetic trees. In agreement with previous molecular studies, our phylogenetic results indicate that none of the currently recognized subfamilies, Crassostreinae, Ostreinae, and Lophinae, is monophyletic. Single gene trees based on Maximum likelihood (ML) and Bayesian (BA) methods and on sequence-structure ML were congruent with multilocus trees based on a concatenated (ML and BA) and coalescent based (BA) approaches and consistently supported three main clades: (i) Crassostrea, (ii) Saccostrea, and (iii) an Ostreinae-Lophinae lineage. Therefore, the subfamily Crassotreinae (including Crassostrea), Saccostreinae subfam. nov. (including Saccostrea and tentatively Striostrea) and Ostreinae (including Ostreinae and Lophinae taxa) are recognized. Based on phylogenetic and biogeographical evidence the Asian species of Crassostrea from the Pacific Ocean are assigned to Magallana gen. nov., whereas an integrative taxonomic revision is required for the genera Ostrea and Dendostrea. This study pointed out the suitability of the ITS2 marker for DNA barcoding of oyster and the relevance of using sequence-structure rRNA models and features of the ITS2 folding in molecular phylogenetics and taxonomy. The multilocus approach allowed inferring a robust phylogeny of Ostreidae providing a broad molecular perspective on their systematics. PMID:25250663
Salvi, Daniele; Macali, Armando; Mariottini, Paolo
2014-01-01
The bivalve family Ostreidae has a worldwide distribution and includes species of high economic importance. Phylogenetics and systematic of oysters based on morphology have proved difficult because of their high phenotypic plasticity. In this study we explore the phylogenetic information of the DNA sequence and secondary structure of the nuclear, fast-evolving, ITS2 rRNA and the mitochondrial 16S rRNA genes from the Ostreidae and we implemented a multi-locus framework based on four loci for oyster phylogenetics and systematics. Sequence-structure rRNA models aid sequence alignment and improved accuracy and nodal support of phylogenetic trees. In agreement with previous molecular studies, our phylogenetic results indicate that none of the currently recognized subfamilies, Crassostreinae, Ostreinae, and Lophinae, is monophyletic. Single gene trees based on Maximum likelihood (ML) and Bayesian (BA) methods and on sequence-structure ML were congruent with multilocus trees based on a concatenated (ML and BA) and coalescent based (BA) approaches and consistently supported three main clades: (i) Crassostrea, (ii) Saccostrea, and (iii) an Ostreinae-Lophinae lineage. Therefore, the subfamily Crassostreinae (including Crassostrea), Saccostreinae subfam. nov. (including Saccostrea and tentatively Striostrea) and Ostreinae (including Ostreinae and Lophinae taxa) are recognized [corrected]. Based on phylogenetic and biogeographical evidence the Asian species of Crassostrea from the Pacific Ocean are assigned to Magallana gen. nov., whereas an integrative taxonomic revision is required for the genera Ostrea and Dendostrea. This study pointed out the suitability of the ITS2 marker for DNA barcoding of oyster and the relevance of using sequence-structure rRNA models and features of the ITS2 folding in molecular phylogenetics and taxonomy. The multilocus approach allowed inferring a robust phylogeny of Ostreidae providing a broad molecular perspective on their systematics.
On robust parameter estimation in brain-computer interfacing
NASA Astrophysics Data System (ADS)
Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert
2017-12-01
Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.
Is there a self-organization principle of river deltas?
NASA Astrophysics Data System (ADS)
Tejedor, Alejandro; Longjas, Anthony; Foufoula-Georgiou, Efi
2017-04-01
River deltas are known to possess a complex topological and flux-partitioning structure which has recently been quantified using spectral graph theory [Tejedor et al., 2015a,b]. By analysis of real and simulated deltas it has also been shown that there is promise in formalizing relationships between this topo-dynamic delta structure and the underlying delta forming processes [e.g., Tejedor et al., 2016]. The question we pose here is whether there exists a first order organizational principle behind the self-organization of river deltas and whether this principle can be unraveled from the co-evolving topo-dynamic structure encoded in the delta planform. To answer this question, we introduce a new metric, the nonlocal Entropy Rate (nER) that captures the information content of a delta network in terms of the degree of uncertainty in delivering fluxes from any point of the network to the shoreline. We hypothesize that if the "guiding principle" of undisturbed deltas is to efficiently and robustly build land by increasing the diversity of their flux pathways over the delta plane, then they would exhibit maximum nonlocal Entropy Rate at states at which geometry and flux dynamics are at equilibrium. At the same time, their nER would be non-optimal at transient states, such as before and after major avulsions during which topology and dynamics adjust to each other to reach a new equilibrium state. We will present our results for field and simulated deltas, which confirm this hypothesis and open up new ways of thinking about self-organization, complexity and robustness in river deltas. One particular connection of interest might have important implications since entropy rate and resilience are related by the fluctuation theorem [Demetrius and Manke, 2005], and therefore our results suggest that deltas might in fact self-organize to maximize their resilience to structural and dynamic perturbations. References: Tejedor, A., A. Longjas, I. Zaliapin, and E. Foufoula-Georgiou (2015), Water Resour. Res., 51, 3998-4018. Tejedor, A., A. Longjas, I. Zaliapin, and E. Foufoula-Georgiou (2015), Water Resour. Res., 51, 4019-4045. Tejedor, A., A. Longjas, R. Caldwell, D. A. Edmonds, I. Zaliapin, and E. Foufoula-Georgiou (2016), Geophys. Res. Lett., 43, 3280-3287. Demetrius, L., and T. Manke (2005), Phys. A Stat. Mech. Appl., 346, 682-696.
VCD Robustness of the Amide-I and Amide-II Vibrational Modes of Small Peptide Models.
Góbi, Sándor; Magyarfalvi, Gábor; Tarczay, György
2015-09-01
The rotational strengths and the robustness values of amide-I and amide-II vibrational modes of For(AA)n NHMe (where AA is Val, Asn, Asp, or Cys, n = 1-5 for Val and Asn; n = 1 for Asp and Cys) model peptides with α-helix and β-sheet backbone conformations were computed by density functional methods. The robustness results verify empirical rules drawn from experiments and from computed rotational strengths linking amide-I and amide-II patterns in the vibrational circular dichroism (VCD) spectra of peptides with their backbone structures. For peptides with at least three residues (n ≥ 3) these characteristic patterns from coupled amide vibrational modes have robust signatures. For shorter peptide models many vibrational modes are nonrobust, and the robust modes can be dependent on the residues or on their side chain conformations in addition to backbone conformations. These robust VCD bands, however, provide information for the detailed structural analysis of these smaller systems. © 2015 Wiley Periodicals, Inc.
Airborne Transducer Integrity under Operational Environment for Structural Health Monitoring
Salmanpour, Mohammad Saleh; Sharif Khodaei, Zahra; Aliabadi, Mohammad Hossein
2016-01-01
This paper investigates the robustness of permanently mounted transducers used in airborne structural health monitoring systems, when exposed to the operational environment. Typical airliners operate in a range of conditions, hence, structural health monitoring (SHM) transducer robustness and integrity must be demonstrated for these environments. A set of extreme temperature, altitude and vibration environment test profiles are developed using the existing Radio Technical Commission for Aeronautics (RTCA)/DO-160 test methods. Commercially available transducers and manufactured versions bonded to carbon fibre reinforced polymer (CFRP) composite materials are tested. It was found that the DuraAct transducer is robust to environmental conditions tested, while the other transducer types degrade under the same conditions. PMID:27973450
Robust multi-model control of an autonomous wind power system
NASA Astrophysics Data System (ADS)
Cutululis, Nicolas Antonio; Ceanga, Emil; Hansen, Anca Daniela; Sørensen, Poul
2006-09-01
This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright
Ludwig, Martha
2012-01-01
The Neurachninae is the only grass lineage known to contain C3, C4, and C3–C4 intermediate species, and as such has been suggested as a model system for studies of photosynthetic pathway evolution in the Poaceae; however, a lack of a robust phylogenetic framework has hindered this possibility. In this study, plastid and nuclear markers were used to reconstruct evolutionary relationships among Neurachninae species. In addition, photosynthetic types were determined with carbon isotope ratios, and genome sizes with flow cytometry. A high frequency of autopolyploidy was found in the Neurachninae, including in Neurachne munroi F.Muell. and Paraneurachne muelleri S.T.Blake, which independently evolved C4 photosynthesis. Phylogenetic analyses also showed that following their separate C4 origins, these two taxa exchanged a gene encoding the C4 form of phosphoenolpyruvate carboxylase. The C3–C4 intermediate Neurachne minor S.T.Blake is phylogenetically distinct from the two C4 lineages, indicating that intermediacy in this species evolved separately from transitional stages preceding C4 origins. The Neurachninae shows a substantial capacity to evolve new photosynthetic pathways repeatedly. Enablers of these transitions might include anatomical pre-conditions in the C3 ancestor, and frequent autopolyploidization. Transfer of key C4 genetic elements between independently evolved C4 taxa may have also facilitated a rapid adaptation of photosynthesis in these grasses that had to survive in the harsh climate appearing during the late Pliocene in Australia. PMID:23077201
Christin, Pascal-Antoine; Wallace, Mark J; Clayton, Harmony; Edwards, Erika J; Furbank, Robert T; Hattersley, Paul W; Sage, Rowan F; Macfarlane, Terry D; Ludwig, Martha
2012-10-01
The Neurachninae is the only grass lineage known to contain C(3), C(4), and C(3)-C(4) intermediate species, and as such has been suggested as a model system for studies of photosynthetic pathway evolution in the Poaceae; however, a lack of a robust phylogenetic framework has hindered this possibility. In this study, plastid and nuclear markers were used to reconstruct evolutionary relationships among Neurachninae species. In addition, photosynthetic types were determined with carbon isotope ratios, and genome sizes with flow cytometry. A high frequency of autopolyploidy was found in the Neurachninae, including in Neurachne munroi F.Muell. and Paraneurachne muelleri S.T.Blake, which independently evolved C(4) photosynthesis. Phylogenetic analyses also showed that following their separate C(4) origins, these two taxa exchanged a gene encoding the C(4) form of phosphoenolpyruvate carboxylase. The C(3)-C(4) intermediate Neurachne minor S.T.Blake is phylogenetically distinct from the two C(4) lineages, indicating that intermediacy in this species evolved separately from transitional stages preceding C(4) origins. The Neurachninae shows a substantial capacity to evolve new photosynthetic pathways repeatedly. Enablers of these transitions might include anatomical pre-conditions in the C(3) ancestor, and frequent autopolyploidization. Transfer of key C(4) genetic elements between independently evolved C(4) taxa may have also facilitated a rapid adaptation of photosynthesis in these grasses that had to survive in the harsh climate appearing during the late Pliocene in Australia.
The Robustness of LISREL Estimates in Structural Equation Models with Categorical Variables.
ERIC Educational Resources Information Center
Ethington, Corinna A.
This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…
NASA Astrophysics Data System (ADS)
Andrews, Stephen K.; Kelvin, Lee S.; Driver, Simon P.; Robotham, Aaron S. G.
2014-01-01
The 2MASS, UKIDSS-LAS, and VISTA VIKING surveys have all now observed the GAMA 9hr region in the Ks band. Here we compare the detection rates, photometry, basic size measurements, and single-component GALFIT structural measurements for a sample of 37 591 galaxies. We explore the sensitivity limits where the data agree for a variety of issues including: detection, star-galaxy separation, photometric measurements, size and ellipticity measurements, and Sérsic measurements. We find that 2MASS fails to detect at least 20% of the galaxy population within all magnitude bins, however for those that are detected we find photometry is robust (± 0.2 mag) to 14.7 AB mag and star-galaxy separation to 14.8 AB mag. For UKIDSS-LAS we find incompleteness starts to enter at a flux limit of 18.9 AB mag, star-galaxy separation is robust to 16.3 AB mag, and structural measurements are robust to 17.7 AB mag. VISTA VIKING data are complete to approximately 20.0 AB mag and structural measurements appear robust to 18.8 AB mag.
Complex network view of evolving manifolds
NASA Astrophysics Data System (ADS)
da Silva, Diamantino C.; Bianconi, Ginestra; da Costa, Rui A.; Dorogovtsev, Sergey N.; Mendes, José F. F.
2018-03-01
We study complex networks formed by triangulations and higher-dimensional simplicial complexes representing closed evolving manifolds. In particular, for triangulations, the set of possible transformations of these networks is restricted by the condition that at each step, all the faces must be triangles. Stochastic application of these operations leads to random networks with different architectures. We perform extensive numerical simulations and explore the geometries of growing and equilibrium complex networks generated by these transformations and their local structural properties. This characterization includes the Hausdorff and spectral dimensions of the resulting networks, their degree distributions, and various structural correlations. Our results reveal a rich zoo of architectures and geometries of these networks, some of which appear to be small worlds while others are finite dimensional with Hausdorff dimension equal or higher than the original dimensionality of their simplices. The range of spectral dimensions of the evolving triangulations turns out to be from about 1.4 to infinity. Our models include simplicial complexes representing manifolds with evolving topologies, for example, an h -holed torus with a progressively growing number of holes. This evolving graph demonstrates features of a small-world network and has a particularly heavy-tailed degree distribution.
Evolving phenotypic networks in silico.
François, Paul
2014-11-01
Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.
Accatino, F; Sabatier, R; De Michele, C; Ward, D; Wiegand, K; Meyer, K M
2014-08-01
Rangelands provide the main forage resource for livestock in many parts of the world, but maintaining long-term productivity and providing sufficient income for the rancher remains a challenge. One key issue is to maintain the rangeland in conditions where the rancher has the greatest possibility to adapt his/her management choices to a highly fluctuating and uncertain environment. In this study, we address management robustness and adaptability, which increase the resilience of a rangeland. After reviewing how the concept of resilience evolved in parallel to modelling views on rangelands, we present a dynamic model of rangelands to which we applied the mathematical framework of viability theory to quantify the management adaptability of the system in a stochastic environment. This quantification is based on an index that combines the robustness of the system to rainfall variability and the ability of the rancher to adjust his/her management through time. We evaluated the adaptability for four possible scenarios combining two rainfall regimes (high or low) with two herding strategies (grazers only or mixed herd). Results show that pure grazing is viable only for high-rainfall regimes, and that the use of mixed-feeder herds increases the adaptability of the management. The management is the most adaptive with mixed herds and in rangelands composed of an intermediate density of trees and grasses. In such situations, grass provides high quantities of biomass and woody plants ensure robustness to droughts. Beyond the implications for management, our results illustrate the relevance of viability theory for addressing the issue of robustness and adaptability in non-equilibrium environments.
Recovery Schemes for Primitive Variables in General-relativistic Magnetohydrodynamics
NASA Astrophysics Data System (ADS)
Siegel, Daniel M.; Mösta, Philipp; Desai, Dhruv; Wu, Samantha
2018-05-01
General-relativistic magnetohydrodynamic (GRMHD) simulations are an important tool to study a variety of astrophysical systems such as neutron star mergers, core-collapse supernovae, and accretion onto compact objects. A conservative GRMHD scheme numerically evolves a set of conservation equations for “conserved” quantities and requires the computation of certain primitive variables at every time step. This recovery procedure constitutes a core part of any conservative GRMHD scheme and it is closely tied to the equation of state (EOS) of the fluid. In the quest to include nuclear physics, weak interactions, and neutrino physics, state-of-the-art GRMHD simulations employ finite-temperature, composition-dependent EOSs. While different schemes have individually been proposed, the recovery problem still remains a major source of error, failure, and inefficiency in GRMHD simulations with advanced microphysics. The strengths and weaknesses of the different schemes when compared to each other remain unclear. Here we present the first systematic comparison of various recovery schemes used in different dynamical spacetime GRMHD codes for both analytic and tabulated microphysical EOSs. We assess the schemes in terms of (i) speed, (ii) accuracy, and (iii) robustness. We find large variations among the different schemes and that there is not a single ideal scheme. While the computationally most efficient schemes are less robust, the most robust schemes are computationally less efficient. More robust schemes may require an order of magnitude more calls to the EOS, which are computationally expensive. We propose an optimal strategy of an efficient three-dimensional Newton–Raphson scheme and a slower but more robust one-dimensional scheme as a fall-back.
NASA Astrophysics Data System (ADS)
Ji, Yinghua; Ju-Ju, Hu; Jian-Hua, Huang; Qiang, Ke
Due to the influence of decoherence, the quantum state probably evolves from the initial pure state to the mixed state, resulting in loss of fidelity, coherence and purity, which is deteriorating for quantum information transmission. Thus, in quantum engineering, quantum control should not only realize the transfer and track of quantum states through manipulation of the external electromagnetic field but also enhance the robustness against decoherence. In this paper, we aim to design a control law to steer the system into the sliding mode domain and maintain it in that domain when bounded uncertainties exist in the system Hamiltonian. We first define the required control performance by fidelity, degree of coherence and purity in terms of the uncertainty of the Hamiltonian in Markovian open quantum system. By characterizing the required robustness using a sliding mode domain, a sampled-data design method is introduced for decoherence control in the quantum system. Furthermore, utilizing the sampled data, a control scheme has been designed on the basis of sliding mode control, and the choice of sampling operator and driving of quantum state during the sampling by the Lyapunov control method are discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Newpower, M; Ge, S; Mohan, R
Purpose: To report an approach to quantify the normal tissue sparing for 4D robustly-optimized versus PTV-optimized IMPT plans. Methods: We generated two sets of 90 DVHs from a patient’s 10-phase 4D CT set; one by conventional PTV-based optimization done in the Eclipse treatment planning system, and the other by an in-house robust optimization algorithm. The 90 DVHs were created for the following scenarios in each of the ten phases of the 4DCT: ± 5mm shift along x, y, z; ± 3.5% range uncertainty and a nominal scenario. A Matlab function written by Gay and Niemierko was modified to calculate EUDmore » for each DVH for the following structures: esophagus, heart, ipsilateral lung and spinal cord. An F-test determined whether or not the variances of each structure’s DVHs were statistically different. Then a t-test determined if the average EUDs for each optimization algorithm were statistically significantly different. Results: T-test results showed each structure had a statistically significant difference in average EUD when comparing robust optimization versus PTV-based optimization. Under robust optimization all structures except the spinal cord received lower EUDs than PTV-based optimization. Using robust optimization the average EUDs decreased 1.45% for the esophagus, 1.54% for the heart and 5.45% for the ipsilateral lung. The average EUD to the spinal cord increased 24.86% but was still well below tolerance. Conclusion: This work has helped quantify a qualitative relationship noted earlier in our work: that robust optimization leads to plans with greater normal tissue sparing compared to PTV-based optimization. Except in the case of the spinal cord all structures received a lower EUD under robust optimization and these results are statistically significant. While the average EUD to the spinal cord increased to 25.06 Gy under robust optimization it is still well under the TD50 value of 66.5 Gy from Emami et al. Supported in part by the NCI U19 CA021239.« less
Foam structure :from soap froth to solid foams.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kraynik, Andrew Michael
2003-01-01
The properties of solid foams depend on their structure, which usually evolves in the fluid state as gas bubbles expand to form polyhedral cells. The characteristic feature of foam structure-randomly packed cells of different sizes and shapes-is examined in this article by considering soap froth. This material can be modeled as a network of minimal surfaces that divide space into polyhedral cells. The cell-level geometry of random soap froth is calculated with Brakke's Surface Evolver software. The distribution of cell volumes ranges from monodisperse to highly polydisperse. Topological and geometric properties, such as surface area and edge length, of themore » entire foam and individual cells, are discussed. The shape of struts in solid foams is related to Plateau borders in liquid foams and calculated for different volume fractions of material. The models of soap froth are used as templates to produce finite element models of open-cell foams. Three-dimensional images of open-cell foams obtained with x-ray microtomography allow virtual reconstruction of skeletal structures that compare well with the Surface Evolver simulations of soap-froth geometry.« less
Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei
2015-01-01
Molecular biologists have long recognized carcinogenesis as an evolutionary process that involves natural selection. Cancer is driven by the somatic evolution of cell lineages. In this study, the evolution of somatic cancer cell lineages during carcinogenesis was modeled as an equilibrium point (ie, phenotype of attractor) shifting, the process of a nonlinear stochastic evolutionary biological network. This process is subject to intrinsic random fluctuations because of somatic genetic and epigenetic variations, as well as extrinsic disturbances because of carcinogens and stressors. In order to maintain the normal function (ie, phenotype) of an evolutionary biological network subjected to random intrinsic fluctuations and extrinsic disturbances, a network robustness scheme that incorporates natural selection needs to be developed. This can be accomplished by selecting certain genetic and epigenetic variations to modify the network structure to attenuate intrinsic fluctuations efficiently and to resist extrinsic disturbances in order to maintain the phenotype of the evolutionary biological network at an equilibrium point (attractor). However, during carcinogenesis, the remaining (or neutral) genetic and epigenetic variations accumulate, and the extrinsic disturbances become too large to maintain the normal phenotype at the desired equilibrium point for the nonlinear evolutionary biological network. Thus, the network is shifted to a cancer phenotype at a new equilibrium point that begins a new evolutionary process. In this study, the natural selection scheme of an evolutionary biological network of carcinogenesis was derived from a robust negative feedback scheme based on the nonlinear stochastic Nash game strategy. The evolvability and phenotypic robustness criteria of the evolutionary cancer network were also estimated by solving a Hamilton–Jacobi inequality – constrained optimization problem. The simulation revealed that the phenotypic shift of the lung cancer-associated cell network takes 54.5 years from a normal state to stage I cancer, 1.5 years from stage I to stage II cancer, and 2.5 years from stage II to stage III cancer, with a reasonable match for the statistical result of the average age of lung cancer. These results suggest that a robust negative feedback scheme, based on a stochastic evolutionary game strategy, plays a critical role in an evolutionary biological network of carcinogenesis under a natural selection scheme. PMID:26244004
NASA Astrophysics Data System (ADS)
Babaee, Hessam; Choi, Minseok; Sapsis, Themistoklis P.; Karniadakis, George Em
2017-09-01
We develop a new robust methodology for the stochastic Navier-Stokes equations based on the dynamically-orthogonal (DO) and bi-orthogonal (BO) methods [1-3]. Both approaches are variants of a generalized Karhunen-Loève (KL) expansion in which both the stochastic coefficients and the spatial basis evolve according to system dynamics, hence, capturing the low-dimensional structure of the solution. The DO and BO formulations are mathematically equivalent [3], but they exhibit computationally complimentary properties. Specifically, the BO formulation may fail due to crossing of the eigenvalues of the covariance matrix, while both BO and DO become unstable when there is a high condition number of the covariance matrix or zero eigenvalues. To this end, we combine the two methods into a robust hybrid framework and in addition we employ a pseudo-inverse technique to invert the covariance matrix. The robustness of the proposed method stems from addressing the following issues in the DO/BO formulation: (i) eigenvalue crossing: we resolve the issue of eigenvalue crossing in the BO formulation by switching to the DO near eigenvalue crossing using the equivalence theorem and switching back to BO when the distance between eigenvalues is larger than a threshold value; (ii) ill-conditioned covariance matrix: we utilize a pseudo-inverse strategy to invert the covariance matrix; (iii) adaptivity: we utilize an adaptive strategy to add/remove modes to resolve the covariance matrix up to a threshold value. In particular, we introduce a soft-threshold criterion to allow the system to adapt to the newly added/removed mode and therefore avoid repetitive and unnecessary mode addition/removal. When the total variance approaches zero, we show that the DO/BO formulation becomes equivalent to the evolution equation of the Optimally Time-Dependent modes [4]. We demonstrate the capability of the proposed methodology with several numerical examples, namely (i) stochastic Burgers equation: we analyze the performance of the method in the presence of eigenvalue crossing and zero eigenvalues; (ii) stochastic Kovasznay flow: we examine the method in the presence of a singular covariance matrix; and (iii) we examine the adaptivity of the method for an incompressible flow over a cylinder where for large stochastic forcing thirteen DO/BO modes are active.
Topological order following a quantum quench
NASA Astrophysics Data System (ADS)
Tsomokos, Dimitris I.; Hamma, Alioscia; Zhang, Wen; Haas, Stephan; Fazio, Rosario
2009-12-01
We determine the conditions under which topological order survives a rapid quantum quench. Specifically, we consider the case where a quantum spin system is prepared in the ground state of the toric code model and, after the quench, it evolves with a Hamiltonian that does not support topological order. We provide analytical results supported by numerical evidence for a variety of quench Hamiltonians. The robustness of topological order under nonequilibrium situations is tested by studying the topological entropy and a dynamical measure, which makes use of the similarity between partial density matrices obtained from different topological sectors.
'Bioengineered Bugs' - a patho-biotechnology approach to probiotic research and applications.
Sleator, Roy D; Hill, Colin
2008-01-01
Given the increasing commercial and clinical relevance of probiotic cultures, improving their stress tolerance profile and ability to overcome the physiochemical defences of the host is an important biological goal. Pathogenic bacteria have evolved sophisticated strategies to overcome host defences, interact with the immune system and modulate essential host systems. The 'Patho-biotechnology' concept promotes the exploitation of these valuable traits for the design of more technologically robust and effective probiotic cultures with potentially improved biotechnological and clinical applications, as well as the development of novel vaccine and drug delivery platforms.
Sudden death of distillability in qutrit-qutrit systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Song Wei; Zhu Shiliang; Chen Lin
2009-07-15
We introduce the concept of distillability sudden death, i.e., free entangled states can evolve into nondistillable (bound entangled or separable) states in finite time under local noise. We describe the phenomenon through a specific model of local dephasing noise and compare the behavior of states in terms of the Bures fidelity. Then we propose a few methods to avoid distillability sudden death of states under (general) local dephasing noise so that free entangled states can be robust against decoherence. Moreover, we find that bound entangled states are unstable in the limit of infinite time.
NASA Astrophysics Data System (ADS)
Shahzad, Muhammad A.
1999-02-01
With the emergence of data warehousing, Decision support systems have evolved to its best. At the core of these warehousing systems lies a good database management system. Database server, used for data warehousing, is responsible for providing robust data management, scalability, high performance query processing and integration with other servers. Oracle being the initiator in warehousing servers, provides a wide range of features for facilitating data warehousing. This paper is designed to review the features of data warehousing - conceptualizing the concept of data warehousing and, lastly, features of Oracle servers for implementing a data warehouse.
DOT National Transportation Integrated Search
2014-06-01
Rivers and streams evolve all the time. As a result, no stream channel is absolutely stable. Channels evolve at various speeds both vertically (degradation/aggradation) and horizontally (meander : migration). They also respond to man-made changes ran...
Langtimm, Catherine A.; Kendall, William L.; Beck, Cathy A.; Kochman, Howard I.; Teague, Amy L.; Meigs-Friend, Gaia; Peñaloza, Claudia L.
2016-11-30
This report provides supporting details and evidence for the rationale, validity and efficacy of a new mark-recapture model, the Barker Robust Design, to estimate regional manatee survival rates used to parameterize several components of the 2012 version of the Manatee Core Biological Model (CBM) and Threats Analysis (TA). The CBM and TA provide scientific analyses on population viability of the Florida manatee subspecies (Trichechus manatus latirostris) for U.S. Fish and Wildlife Service’s 5-year reviews of the status of the species as listed under the Endangered Species Act. The model evaluation is presented in a standardized reporting framework, modified from the TRACE (TRAnsparent and Comprehensive model Evaluation) protocol first introduced for environmental threat analyses. We identify this new protocol as TRACE-MANATEE SURVIVAL and this model evaluation specifically as TRACE-MANATEE SURVIVAL, Barker RD version 1. The longer-term objectives of the manatee standard reporting format are to (1) communicate to resource managers consistent evaluation information over sequential modeling efforts; (2) build understanding and expertise on the structure and function of the models; (3) document changes in model structures and applications in response to evolving management objectives, new biological and ecological knowledge, and new statistical advances; and (4) provide greater transparency for management and research review.
NASA Astrophysics Data System (ADS)
Maalek, R.; Lichti, D. D.; Ruwanpura, J.
2015-08-01
The application of terrestrial laser scanners (TLSs) on construction sites for automating construction progress monitoring and controlling structural dimension compliance is growing markedly. However, current research in construction management relies on the planned building information model (BIM) to assign the accumulated point clouds to their corresponding structural elements, which may not be reliable in cases where the dimensions of the as-built structure differ from those of the planned model and/or the planned model is not available with sufficient detail. In addition outliers exist in construction site datasets due to data artefacts caused by moving objects, occlusions and dust. In order to overcome the aforementioned limitations, a novel method for robust classification and segmentation of planar and linear features is proposed to reduce the effects of outliers present in the LiDAR data collected from construction sites. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a robust clustering method. A method is also proposed to robustly extract the points belonging to the flat-slab floors and/or ceilings without performing the aforementioned stages in order to preserve computational efficiency. The applicability of the proposed method is investigated in two scenarios, namely, a laboratory with 30 million points and an actual construction site with over 150 million points. The results obtained by the two experiments validate the suitability of the proposed method for robust segmentation of planar and linear features in contaminated datasets, such as those collected from construction sites.
Validity Generalization of the WISC-R Factor Structure with 10 1/2-Year-Old Children.
ERIC Educational Resources Information Center
Shiek, David A.; Miller, John E.
1978-01-01
Investigated robustness of the Wechsler Intelligence Scale for Children-Revised (WISC-R) factor structure. Comparisons of the loadings obtained with generalization sample and 10 1/2-year-old national standardization sample suggest high degree of similarity in composition, magnitude, and pattern. Findings highly support robustness of WISC-R's…
A robust background regression based score estimation algorithm for hyperspectral anomaly detection
NASA Astrophysics Data System (ADS)
Zhao, Rui; Du, Bo; Zhang, Liangpei; Zhang, Lefei
2016-12-01
Anomaly detection has become a hot topic in the hyperspectral image analysis and processing fields in recent years. The most important issue for hyperspectral anomaly detection is the background estimation and suppression. Unreasonable or non-robust background estimation usually leads to unsatisfactory anomaly detection results. Furthermore, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection. In order to implement robust background estimation, as well as to explore the intrinsic data structure of the hyperspectral image, we propose a robust background regression based score estimation algorithm (RBRSE) for hyperspectral anomaly detection. The Robust Background Regression (RBR) is actually a label assignment procedure which segments the hyperspectral data into a robust background dataset and a potential anomaly dataset with an intersection boundary. In the RBR, a kernel expansion technique, which explores the nonlinear structure of the hyperspectral data in a reproducing kernel Hilbert space, is utilized to formulate the data as a density feature representation. A minimum squared loss relationship is constructed between the data density feature and the corresponding assigned labels of the hyperspectral data, to formulate the foundation of the regression. Furthermore, a manifold regularization term which explores the manifold smoothness of the hyperspectral data, and a maximization term of the robust background average density, which suppresses the bias caused by the potential anomalies, are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation method is undertaken on the robust background and potential anomaly datasets, to implement the detection output. The experimental results show that RBRSE achieves superior ROC curves, AUC values, and background-anomaly separation than some of the other state-of-the-art anomaly detection methods, and is easy to implement in practice.
Bar formation as driver of gas inflows in isolated disc galaxies
NASA Astrophysics Data System (ADS)
Fanali, R.; Dotti, M.; Fiacconi, D.; Haardt, F.
2015-12-01
Stellar bars are a common feature in massive disc galaxies. On a theoretical ground, the response of gas to a bar is generally thought to cause nuclear starbursts and, possibly, AGN activity once the perturbed gas reaches the central supermassive black hole. By means of high-resolution numerical simulations, we detail the purely dynamical effects that a forming bar exerts on the gas of an isolated disc galaxy. The galaxy is initially unstable to the formation of non-axisymmetric structures, and within ˜1 Gyr it develops spiral arms that eventually evolve into a central stellar bar on kpc scale. A first major episode of gas inflow occurs during the formation of the spiral arms while at later times, when the stellar bar is establishing, a low-density region is carved between the bar corotational and inner Lindblad resonance radii. The development of such `dead zone' inhibits further massive gas inflows. Indeed, the gas inflow reaches its maximum during the relatively fast bar-formation phase and not, as often assumed, when the bar is fully formed. We conclude that the low efficiency of long-lived, evolved bars in driving gas towards galactic nuclei is the reason why observational studies have failed to establish an indisputable link between bars and AGNs. On the other hand, the high efficiency in driving strong gas inflows of the intrinsically transient process of bar formation suggests that the importance of bars as drivers of AGN activity in disc galaxies has been overlooked so far. We finally prove that our conclusions are robust against different numerical implementations of the hydrodynamics routinely used in galaxy evolution studies.
Santos, José; Monteagudo, Ángel
2017-03-27
The canonical code, although prevailing in complex genomes, is not universal. It was shown the canonical genetic code superior robustness compared to random codes, but it is not clearly determined how it evolved towards its current form. The error minimization theory considers the minimization of point mutation adverse effect as the main selection factor in the evolution of the code. We have used simulated evolution in a computer to search for optimized codes, which helps to obtain information about the optimization level of the canonical code in its evolution. A genetic algorithm searches for efficient codes in a fitness landscape that corresponds with the adaptability of possible hypothetical genetic codes. The lower the effects of errors or mutations in the codon bases of a hypothetical code, the more efficient or optimal is that code. The inclusion of the fitness sharing technique in the evolutionary algorithm allows the extent to which the canonical genetic code is in an area corresponding to a deep local minimum to be easily determined, even in the high dimensional spaces considered. The analyses show that the canonical code is not in a deep local minimum and that the fitness landscape is not a multimodal fitness landscape with deep and separated peaks. Moreover, the canonical code is clearly far away from the areas of higher fitness in the landscape. Given the non-presence of deep local minima in the landscape, although the code could evolve and different forces could shape its structure, the fitness landscape nature considered in the error minimization theory does not explain why the canonical code ended its evolution in a location which is not an area of a localized deep minimum of the huge fitness landscape.
Transient ensemble dynamics in time-independent galactic potentials
NASA Astrophysics Data System (ADS)
Mahon, M. Elaine; Abernathy, Robert A.; Bradley, Brendan O.; Kandrup, Henry E.
1995-07-01
This paper summarizes a numerical investigation of the short-time, possibly transient, behaviour of ensembles of stochastic orbits evolving in fixed non-integrable potentials, with the aim of deriving insights into the structure and evolution of galaxies. The simulations involved three different two-dimensional potentials, quite different in appearance. However, despite these differences, ensembles in all three potentials exhibit similar behaviour. This suggests that the conclusions inferred from the simulations are robust, relying only on basic topological properties, e.g., the existence of KAM tori and cantori. Generic ensembles of initial conditions, corresponding to stochastic orbits, exhibit a rapid coarse-grained approach towards a near-invariant distribution on a time-scale <
Chattaway, Marie Anne; Jenkins, Claire; Rajendram, Dunstan; Cravioto, Alejandro; Talukder, Kaisar Ali; Dallman, Tim; Underwood, Anthony; Platt, Steve; Okeke, Iruka N; Wain, John
2014-01-01
Enteroaggregative E. coli (EAEC) is an established diarrhoeagenic pathotype. The association with virulence gene content and ability to cause disease has been studied but little is known about the population structure of EAEC and how this pathotype evolved. Analysis by Multi Locus Sequence Typing of 564 EAEC isolates from cases and controls in Bangladesh, Nigeria and the UK spanning the past 29 years, revealed multiple successful lineages of EAEC. The population structure of EAEC indicates some clusters are statistically associated with disease or carriage, further highlighting the heterogeneous nature of this group of organisms. Different clusters have evolved independently as a result of both mutational and recombination events; the EAEC phenotype is distributed throughout the population of E. coli.
A closed-form solution to tensor voting: theory and applications.
Wu, Tai-Pang; Yeung, Sai-Kit; Jia, Jiaya; Tang, Chi-Keung; Medioni, Gérard
2012-08-01
We prove a closed-form solution to tensor voting (CFTV): Given a point set in any dimensions, our closed-form solution provides an exact, continuous, and efficient algorithm for computing a structure-aware tensor that simultaneously achieves salient structure detection and outlier attenuation. Using CFTV, we prove the convergence of tensor voting on a Markov random field (MRF), thus termed as MRFTV, where the structure-aware tensor at each input site reaches a stationary state upon convergence in structure propagation. We then embed structure-aware tensor into expectation maximization (EM) for optimizing a single linear structure to achieve efficient and robust parameter estimation. Specifically, our EMTV algorithm optimizes both the tensor and fitting parameters and does not require random sampling consensus typically used in existing robust statistical techniques. We performed quantitative evaluation on its accuracy and robustness, showing that EMTV performs better than the original TV and other state-of-the-art techniques in fundamental matrix estimation for multiview stereo matching. The extensions of CFTV and EMTV for extracting multiple and nonlinear structures are underway.
A Maltose-Binding Protein Fusion Construct Yields a Robust Crystallography Platform for MCL1
Clifton, Matthew C.; Dranow, David M.; Leed, Alison; Fulroth, Ben; Fairman, James W.; Abendroth, Jan; Atkins, Kateri A.; Wallace, Ellen; Fan, Dazhong; Xu, Guoping; Ni, Z. J.; Daniels, Doug; Van Drie, John; Wei, Guo; Burgin, Alex B.; Golub, Todd R.; Hubbard, Brian K.; Serrano-Wu, Michael H.
2015-01-01
Crystallization of a maltose-binding protein MCL1 fusion has yielded a robust crystallography platform that generated the first apo MCL1 crystal structure, as well as five ligand-bound structures. The ability to obtain fragment-bound structures advances structure-based drug design efforts that, despite considerable effort, had previously been intractable by crystallography. In the ligand-independent crystal form we identify inhibitor binding modes not observed in earlier crystallographic systems. This MBP-MCL1 construct dramatically improves the structural understanding of well-validated MCL1 ligands, and will likely catalyze the structure-based optimization of high affinity MCL1 inhibitors. PMID:25909780
Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rossi, R; Gallagher, B; Neville, J
Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less
Tonnabel, Jeanne; Mignot, Agnès; Douzery, Emmanuel J P; Rebelo, Anthony G; Schurr, Frank M; Midgley, Jeremy; Illing, Nicola; Justy, Fabienne; Orcel, Denis; Olivieri, Isabelle
2014-10-01
Natural selection is expected to cause convergence of life histories among taxa as well as correlated evolution of different life-history traits. Here, we quantify the extent of convergence of five key life-history traits (adult fire survival, seed storage, degree of sexual dimorphism, pollination mode, and seed-dispersal mode) and test hypotheses about their correlated evolution in the genus Leucadendron (Proteaceae) from the fire-prone South African fynbos. We reconstructed a new molecular phylogeny of this highly diverse genus that involves more taxa and molecular markers than previously. This reconstruction identifies new clades that were not detected by previous molecular study and morphological classifications. Using this new phylogeny and robust methods that account for phylogenetic uncertainty, we show that the five life-history traits studied were labile during the evolutionary history of the genus. This diversity allowed us to tackle major questions about the correlated evolution of life-history strategies. We found that species with longer seed-dispersal distances tended to evolve lower pollen-dispersal distance, that insect-pollinated species evolved decreased sexual dimorphism, and that species with a persistent soil seed-bank evolved toward reduced fire-survival ability of adults. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
Collapse of cooperation in evolving games.
Stewart, Alexander J; Plotkin, Joshua B
2014-12-09
Game theory provides a quantitative framework for analyzing the behavior of rational agents. The Iterated Prisoner's Dilemma in particular has become a standard model for studying cooperation and cheating, with cooperation often emerging as a robust outcome in evolving populations. Here we extend evolutionary game theory by allowing players' payoffs as well as their strategies to evolve in response to selection on heritable mutations. In nature, many organisms engage in mutually beneficial interactions and individuals may seek to change the ratio of risk to reward for cooperation by altering the resources they commit to cooperative interactions. To study this, we construct a general framework for the coevolution of strategies and payoffs in arbitrary iterated games. We show that, when there is a tradeoff between the benefits and costs of cooperation, coevolution often leads to a dramatic loss of cooperation in the Iterated Prisoner's Dilemma. The collapse of cooperation is so extreme that the average payoff in a population can decline even as the potential reward for mutual cooperation increases. Depending upon the form of tradeoffs, evolution may even move away from the Iterated Prisoner's Dilemma game altogether. Our work offers a new perspective on the Prisoner's Dilemma and its predictions for cooperation in natural populations; and it provides a general framework to understand the coevolution of strategies and payoffs in iterated interactions.
Artificial Metamorphosis: Evolutionary Design of Transforming, Soft-Bodied Robots.
Joachimczak, Michał; Suzuki, Reiji; Arita, Takaya
2016-01-01
We show how the concept of metamorphosis, together with a biologically inspired model of multicellular development, can be used to evolve soft-bodied robots that are adapted to two very different tasks, such as being able to move in an aquatic and in a terrestrial environment. Each evolved solution defines two pairs of morphologies and controllers, together with a process of transforming one pair into the other. Animats develop from a single cell and grow through cellular divisions and deaths until they reach an initial larval form adapted to a first environment. To obtain the adult form adapted to a second environment, the larva undergoes metamorphosis, during which new cells are added or removed and its controller is modified. Importantly, our approach assumes nothing about what morphologies or methods of locomotion are preferred. Instead, it successfully searches the vast space of possible designs and comes up with complex, surprising, lifelike solutions that are reminiscent of amphibian metamorphosis. We analyze obtained solutions and investigate whether the morphological changes during metamorphosis are indeed adaptive. We then compare the effectiveness of three different types of selective pressures used to evolve metamorphic individuals. Finally, we investigate potential advantages of using metamorphosis to automatically produce soft-bodied designs by comparing the performance of metamorphic individuals with their specialized counterparts and designs that are robust to both environments.
Unraveling the genetic basis of xylose consumption in engineered Saccharomyces cerevisiae strains.
Dos Santos, Leandro Vieira; Carazzolle, Marcelo Falsarella; Nagamatsu, Sheila Tiemi; Sampaio, Nádia Maria Vieira; Almeida, Ludimila Dias; Pirolla, Renan Augusto Siqueira; Borelli, Guilherme; Corrêa, Thamy Lívia Ribeiro; Argueso, Juan Lucas; Pereira, Gonçalo Amarante Guimarães
2016-12-21
The development of biocatalysts capable of fermenting xylose, a five-carbon sugar abundant in lignocellulosic biomass, is a key step to achieve a viable production of second-generation ethanol. In this work, a robust industrial strain of Saccharomyces cerevisiae was modified by the addition of essential genes for pentose metabolism. Subsequently, taken through cycles of adaptive evolution with selection for optimal xylose utilization, strains could efficiently convert xylose to ethanol with a yield of about 0.46 g ethanol/g xylose. Though evolved independently, two strains carried shared mutations: amplification of the xylose isomerase gene and inactivation of ISU1, a gene encoding a scaffold protein involved in the assembly of iron-sulfur clusters. In addition, one of evolved strains carried a mutation in SSK2, a member of MAPKKK signaling pathway. In validation experiments, mutating ISU1 or SSK2 improved the ability to metabolize xylose of yeast cells without adaptive evolution, suggesting that these genes are key players in a regulatory network for xylose fermentation. Furthermore, addition of iron ion to the growth media improved xylose fermentation even by non-evolved cells. Our results provide promising new targets for metabolic engineering of C5-yeasts and point to iron as a potential new additive for improvement of second-generation ethanol production.
Unraveling the genetic basis of xylose consumption in engineered Saccharomyces cerevisiae strains
dos Santos, Leandro Vieira; Carazzolle, Marcelo Falsarella; Nagamatsu, Sheila Tiemi; Sampaio, Nádia Maria Vieira; Almeida, Ludimila Dias; Pirolla, Renan Augusto Siqueira; Borelli, Guilherme; Corrêa, Thamy Lívia Ribeiro; Argueso, Juan Lucas; Pereira, Gonçalo Amarante Guimarães
2016-01-01
The development of biocatalysts capable of fermenting xylose, a five-carbon sugar abundant in lignocellulosic biomass, is a key step to achieve a viable production of second-generation ethanol. In this work, a robust industrial strain of Saccharomyces cerevisiae was modified by the addition of essential genes for pentose metabolism. Subsequently, taken through cycles of adaptive evolution with selection for optimal xylose utilization, strains could efficiently convert xylose to ethanol with a yield of about 0.46 g ethanol/g xylose. Though evolved independently, two strains carried shared mutations: amplification of the xylose isomerase gene and inactivation of ISU1, a gene encoding a scaffold protein involved in the assembly of iron-sulfur clusters. In addition, one of evolved strains carried a mutation in SSK2, a member of MAPKKK signaling pathway. In validation experiments, mutating ISU1 or SSK2 improved the ability to metabolize xylose of yeast cells without adaptive evolution, suggesting that these genes are key players in a regulatory network for xylose fermentation. Furthermore, addition of iron ion to the growth media improved xylose fermentation even by non-evolved cells. Our results provide promising new targets for metabolic engineering of C5-yeasts and point to iron as a potential new additive for improvement of second-generation ethanol production. PMID:28000736
1994-06-01
the peaceful settlement of international disputes. Although peacekeeping was not explicitly provided for in the Charter, it has evolved since 1945...Prior to 1919, the justifications for resort to war had evolved from moral grounds to a legal basis. 3 The emergence of the state as a political structure...course overlapping and, importantly, as Professor Scheffer has noted, they are " evolving and reflect, with respect to the use of force under UN
Sochan, Anne M
2011-07-01
How should nursing knowledge advance? This exploration contextualizes its evolution past and present. In addressing how it evolved in the past, a probable historical evolution of its development draws on the perspectives of Frank & Gills's World System Theory, Kuhn's treatise on Scientific Revolutions, and Foucault's notions of Discontinuities in scientific knowledge development. By describing plausible scenarios of how nursing knowledge evolved, I create a case for why nursing knowledge developers should adopt a post-structural stance in prioritizing their research agenda(s). Further, by adopting a post-structural stance, I create a case on how nurses can advance their disciplinary knowledge using an engaging post-colonial strategy. Given an interrupted history caused by influence(s) constraining nursing's knowledge development by power structures external, and internal, to nursing, knowledge development can evolve in the future by drawing on post-structural interpretation, and post-colonial strategy. The post-structural writings of Deleuze & Guattari's understanding of 'Nomadology' as a subtle means to resist being constrained by existing knowledge development structures, might be a useful stance to understanding the urgency of why nursing knowledge should advance addressing the structural influences on its development. Furthermore, Bhabha's post-colonial elucidation of 'Hybridity' as an equally discreet means to change the culture of those constraining structures is an appropriate strategy to enact how nursing knowledge developers can engage with existing power structures, and simultaneously influence that engagement. Taken together, 'post-structural stance' and 'post-colonial strategy' can refocus nursing scholarship to learn from its past, in order to develop relevant disciplinary knowledge in its future. © 2011 Blackwell Publishing Ltd.
Constructing Robust Cooperative Networks using a Multi-Objective Evolutionary Algorithm
Wang, Shuai; Liu, Jing
2017-01-01
The design and construction of network structures oriented towards different applications has attracted much attention recently. The existing studies indicated that structural heterogeneity plays different roles in promoting cooperation and robustness. Compared with rewiring a predefined network, it is more flexible and practical to construct new networks that satisfy the desired properties. Therefore, in this paper, we study a method for constructing robust cooperative networks where the only constraint is that the number of nodes and links is predefined. We model this network construction problem as a multi-objective optimization problem and propose a multi-objective evolutionary algorithm, named MOEA-Netrc, to generate the desired networks from arbitrary initializations. The performance of MOEA-Netrc is validated on several synthetic and real-world networks. The results show that MOEA-Netrc can construct balanced candidates and is insensitive to the initializations. MOEA-Netrc can find the Pareto fronts for networks with different levels of cooperation and robustness. In addition, further investigation of the robustness of the constructed networks revealed the impact on other aspects of robustness during the construction process. PMID:28134314
Martínez-Castilla, León P.; Rodríguez-Sotres, Rogelio
2010-01-01
Background Despite the remarkable progress of bioinformatics, how the primary structure of a protein leads to a three-dimensional fold, and in turn determines its function remains an elusive question. Alignments of sequences with known function can be used to identify proteins with the same or similar function with high success. However, identification of function-related and structure-related amino acid positions is only possible after a detailed study of every protein. Folding pattern diversity seems to be much narrower than sequence diversity, and the amino acid sequences of natural proteins have evolved under a selective pressure comprising structural and functional requirements acting in parallel. Principal Findings The approach described in this work begins by generating a large number of amino acid sequences using ROSETTA [Dantas G et al. (2003) J Mol Biol 332:449–460], a program with notable robustness in the assignment of amino acids to a known three-dimensional structure. The resulting sequence-sets showed no conservation of amino acids at active sites, or protein-protein interfaces. Hidden Markov models built from the resulting sequence sets were used to search sequence databases. Surprisingly, the models retrieved from the database sequences belonged to proteins with the same or a very similar function. Given an appropriate cutoff, the rate of false positives was zero. According to our results, this protocol, here referred to as Rd.HMM, detects fine structural details on the folding patterns, that seem to be tightly linked to the fitness of a structural framework for a specific biological function. Conclusion Because the sequence of the native protein used to create the Rd.HMM model was always amongst the top hits, the procedure is a reliable tool to score, very accurately, the quality and appropriateness of computer-modeled 3D-structures, without the need for spectroscopy data. However, Rd.HMM is very sensitive to the conformational features of the models' backbone. PMID:20830209
The Evolving Market Structure of the U.S. Residential Solar PV Installation Industry, 2000-2016
DOE Office of Scientific and Technical Information (OSTI.GOV)
OShaughnessy, Eric J
Market structure refers to the number of firms and the distribution of market shares among firms within an industry. In The Evolving Market Structure of the U.S. Residential Solar PV Installation Industry, 2000-2016, we examine market structure in the context of residential solar PV. We find that over 8,000 companies have installed at least one residential PV system, with about 2,900 companies active in 2016. The majority of residential PV installers are relatively small companies, with about half of installers installing fewer than five systems. At the same time, a subset of high-volume installers accumulated market share, especially beginning aroundmore » 2010 with the emergence of alternative customer financing options.« less
Robust Learning of High-dimensional Biological Networks with Bayesian Networks
NASA Astrophysics Data System (ADS)
Nägele, Andreas; Dejori, Mathäus; Stetter, Martin
Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.
Slater, Michael D.; Hayes, Andrew F.
2010-01-01
Prior research has found strong evidence of a prospective association between R movie exposure and teen smoking. Using parallel process latent-growth modeling, the present study examines prospective associations between viewing of music video channels on television (e.g., MTV and VH-1) and changes over time in smoking and association with smoking peers. Results showed that baseline viewing of music-oriented channels such as MTV and VH-1 robustly predicted increasing trajectories of smoking and of associating with smoking peers, even after application of a variety of controls including parent reports of monitoring behavior. These results are consistent with the arguments from the reinforcing spirals model that such media use serves as a means of developing emergent adolescent social identities consistent with associating with smoking peers and acquiring smoking and other risk behaviors; evidence also suggests that media choice in reinforcing spiral processes are dynamic and evolve as social identity evolves. PMID:21318085
Closed loop deep brain stimulation: an evolving technology.
Hosain, Md Kamal; Kouzani, Abbas; Tye, Susannah
2014-12-01
Deep brain stimulation is an effective and safe medical treatment for a variety of neurological and psychiatric disorders including Parkinson's disease, essential tremor, dystonia, and treatment resistant obsessive compulsive disorder. A closed loop deep brain stimulation (CLDBS) system automatically adjusts stimulation parameters by the brain response in real time. The CLDBS continues to evolve due to the advancement in the brain stimulation technologies. This paper provides a study on the existing systems developed for CLDBS. It highlights the issues associated with CLDBS systems including feedback signal recording and processing, stimulation parameters setting, control algorithm, wireless telemetry, size, and power consumption. The benefits and limitations of the existing CLDBS systems are also presented. Whilst robust clinical proof of the benefits of the technology remains to be achieved, it has the potential to offer several advantages over open loop DBS. The CLDBS can improve efficiency and efficacy of therapy, eliminate lengthy start-up period for programming and adjustment, provide a personalized treatment, and make parameters setting automatic and adaptive.
Evolution of the Radiological Protection System and its Implementation.
Lazo, Edward
2016-02-01
The International System of Radiological Protection, developed, maintained, and elaborated by the International Commission on Radiological Protection (ICRP) has, for the past 50 y, provided a robust framework for developing radiological protection policy, regulation, and application. It has, however, been evolving as a result of experience with its implementation, modernization of social awareness of a shrinking world where the Internet links everyone instantly, and increasing public interest in safety-related decisions. These currents have gently pushed the ICRP in recent years to focus more sharply on particular aspects of its system: optimization, prevailing circumstances, the use of effective dose and aspects of an individual's risk, and consideration of the independent implementation of the international system's elements. This paper will present these issues and their relevance to the ICRP system of protection and its evolution. The broader framework of radiological protection (e.g., science, philosophy, policy, regulation, implementation), of which the ICRP is an important element, will provide a global, equally evolving context for this characterization of the changing ICRP system of radiological protection.
Behavioral resilience in the post-genomic era: emerging models linking genes with environment
Rende, Richard
2012-01-01
One of the most important deliverables of the post-genomic era has been a new and nuanced appreciation of how the environment shapes—and holds potential to alter—the expression of susceptibility genes for behavioral dimensions and disorders. This paper will consider three themes that have emerged from cutting-edge research studies that utilize newer molecular genetic approaches as well as tried-and-true genetic epidemiological methodologies, with particular reference to evolving perspectives on resilience and plasticity. These themes are: (1) evidence for replicable and robust shared environmental effects on a number of clinically relevant behaviors in childhood and adolescence; (2) evolving research on gene-environment interaction; and (3) a newer focus on differential susceptibility and plasticity. The net sum of these themes is that consideration of genetic effects on behavioral dimensions and disorders needs to be connected to thinking about the role of environment as a potent source for promoting resilience and change. PMID:22461772
An analysis of parameter sensitivities of preference-inspired co-evolutionary algorithms
NASA Astrophysics Data System (ADS)
Wang, Rui; Mansor, Maszatul M.; Purshouse, Robin C.; Fleming, Peter J.
2015-10-01
Many-objective optimisation problems remain challenging for many state-of-the-art multi-objective evolutionary algorithms. Preference-inspired co-evolutionary algorithms (PICEAs) which co-evolve the usual population of candidate solutions with a family of decision-maker preferences during the search have been demonstrated to be effective on such problems. However, it is unknown whether PICEAs are robust with respect to the parameter settings. This study aims to address this question. First, a global sensitivity analysis method - the Sobol' variance decomposition method - is employed to determine the relative importance of the parameters controlling the performance of PICEAs. Experimental results show that the performance of PICEAs is controlled for the most part by the number of function evaluations. Next, we investigate the effect of key parameters identified from the Sobol' test and the genetic operators employed in PICEAs. Experimental results show improved performance of the PICEAs as more preferences are co-evolved. Additionally, some suggestions for genetic operator settings are provided for non-expert users.
Slater, Michael D; Hayes, Andrew F
2010-12-01
Prior research has found strong evidence of a prospective association between R movie exposure and teen smoking. Using parallel process latent-growth modeling, the present study examines prospective associations between viewing of music video channels on television (e.g., MTV and VH-1) and changes over time in smoking and association with smoking peers. Results showed that baseline viewing of music-oriented channels such as MTV and VH-1 robustly predicted increasing trajectories of smoking and of associating with smoking peers, even after application of a variety of controls including parent reports of monitoring behavior. These results are consistent with the arguments from the reinforcing spirals model that such media use serves as a means of developing emergent adolescent social identities consistent with associating with smoking peers and acquiring smoking and other risk behaviors; evidence also suggests that media choice in reinforcing spiral processes are dynamic and evolve as social identity evolves.
NASA Astrophysics Data System (ADS)
Gobbato, Maurizio; Kosmatka, John B.; Conte, Joel P.
2014-04-01
Fatigue-induced damage is one of the most uncertain and highly unpredictable failure mechanisms for a large variety of mechanical and structural systems subjected to cyclic and random loads during their service life. A health monitoring system capable of (i) monitoring the critical components of these systems through non-destructive evaluation (NDE) techniques, (ii) assessing their structural integrity, (iii) recursively predicting their remaining fatigue life (RFL), and (iv) providing a cost-efficient reliability-based inspection and maintenance plan (RBIM) is therefore ultimately needed. In contribution to these objectives, the first part of the paper provides an overview and extension of a comprehensive reliability-based fatigue damage prognosis methodology — previously developed by the authors — for recursively predicting and updating the RFL of critical structural components and/or sub-components in aerospace structures. In the second part of the paper, a set of experimental fatigue test data, available in the literature, is used to provide a numerical verification and an experimental validation of the proposed framework at the reliability component level (i.e., single damage mechanism evolving at a single damage location). The results obtained from this study demonstrate (i) the importance and the benefits of a nearly continuous NDE monitoring system, (ii) the efficiency of the recursive Bayesian updating scheme, and (iii) the robustness of the proposed framework in recursively updating and improving the RFL estimations. This study also demonstrates that the proposed methodology can lead to either an extent of the RFL (with a consequent economical gain without compromising the minimum safety requirements) or an increase of safety by detecting a premature fault and therefore avoiding a very costly catastrophic failure.
A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures
2014-01-01
Background Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information. Results We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0. Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure. Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets. Conclusions Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at http://www.cs.ubc.ca/~hjabbari/software.php. PMID:24884954
Dissipative controller designs for second-order dynamic systems
NASA Technical Reports Server (NTRS)
Morris, K. A.; Juang, J. N.
1990-01-01
The passivity theorem may be used to design robust controllers for structures with positive transfer functions. This result is extended to more general configurations using dissipative system theory. A stability theorem for robust, model-independent controllers of structures which lack collocated rate sensors and actuators is given. The theory is illustrated for non-square systems and systems with displacement sensors.
Analysis and Synthesis of Robust Data Structures
1990-08-01
1.3.2 Multiversion Software. .. .. .. .. .. .... .. ... .. ...... 5 1.3.3 Robust Data Structure .. .. .. .. .. .. .. .. .. ... .. ..... 6 1.4...context are 0 multiversion software, which is an adaptation oi N-modulo redundancy (NMR) tech- nique. * recovery blocks, which is an adaptation of...implementations using these features for such a hybrid approach. 1.3.2 Multiversion Software Avizienis [AC77] was the first to adapt NMR technique into
Harnessing Sparse and Low-Dimensional Structures for Robust Clustering of Imagery Data
ERIC Educational Resources Information Center
Rao, Shankar Ramamohan
2009-01-01
We propose a robust framework for clustering data. In practice, data obtained from real measurement devices can be incomplete, corrupted by gross errors, or not correspond to any assumed model. We show that, by properly harnessing the intrinsic low-dimensional structure of the data, these kinds of practical problems can be dealt with in a uniform…
Bao, Yihai; Main, Joseph A; Noh, Sam-Young
2017-08-01
A computational methodology is presented for evaluating structural robustness against column loss. The methodology is illustrated through application to reinforced concrete (RC) frame buildings, using a reduced-order modeling approach for three-dimensional RC framing systems that includes the floor slabs. Comparisons with high-fidelity finite-element model results are presented to verify the approach. Pushdown analyses of prototype buildings under column loss scenarios are performed using the reduced-order modeling approach, and an energy-based procedure is employed to account for the dynamic effects associated with sudden column loss. Results obtained using the energy-based approach are found to be in good agreement with results from direct dynamic analysis of sudden column loss. A metric for structural robustness is proposed, calculated by normalizing the ultimate capacities of the structural system under sudden column loss by the applicable service-level gravity loading and by evaluating the minimum value of this normalized ultimate capacity over all column removal scenarios. The procedure is applied to two prototype 10-story RC buildings, one employing intermediate moment frames (IMFs) and the other employing special moment frames (SMFs). The SMF building, with its more stringent seismic design and detailing, is found to have greater robustness.
Evolution of hormone signaling in elasmobranchs by exploitation of promiscuous receptors.
Carroll, Sean Michael; Bridgham, Jamie T; Thornton, Joseph W
2008-12-01
Specific interactions among proteins, nucleic acids, and metabolites drive virtually all cellular functions and underlie phenotypic complexity and diversity. Despite the fundamental importance of interactions, the mechanisms and dynamics by which they evolve are poorly understood. Here we describe novel interactions between a lineage-specific hormone and its receptors in elasmobranchs, a subclass of cartilaginous fishes, and infer how these associations evolved using phylogenetic and protein structural analyses. The hormone 1alpha-hydroxycorticosterone (1alpha-B) is a physiologically important steroid synthesized only in elasmobranchs. We show that 1alpha-B modulates gene expression in vitro by activating two paralogous intracellular transcription factors, the mineralocorticoid receptor (MR) and glucocorticoid receptor (GR), in the little skate Leucoraja erinacea; MR serves as a high-sensitivity and GR as a low-sensitivity receptor. Using functional analysis of extant and resurrected ancestral proteins, we show that receptor sensitivity to 1alpha-B evolved millions of years before the hormone itself evolved. The 1alpha-B differs from more ancient corticosteroids only by the addition of a hydroxyl group; the three-dimensional structure of the ancestral receptor shows that the ligand pocket contained ample unoccupied space to accommodate this moiety. Our findings indicate that the interactions between 1alpha-B and elasmobranch GR and MR proteins evolved by molecular exploitation: a novel hormone recruited into new functional partnerships two ancient receptors that had previously interacted with other ligands. The ancestral receptor's promiscuous capacity to fortuitously bind compounds that are slight structural variants of its original ligands set the stage for the evolution of this new interaction.
No evidence for a significant AGN contribution to cosmic hydrogen reionization
NASA Astrophysics Data System (ADS)
Parsa, Shaghayegh; Dunlop, James S.; McLure, Ross J.
2018-03-01
We reinvestigate a claimed sample of 22 X-ray detected active galactic nuclei (AGN) at redshifts z > 4, which has reignited the debate as to whether young galaxies or AGN reionized the Universe. These sources lie within the Great Observatories Origins Deep Survey-South (GOODS-S)/Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) field, and we examine both the robustness of the claimed X-ray detections (within the Chandra 4Ms imaging) and perform an independent analysis of the photometric redshifts of the optical/infrared counterparts. We confirm the reality of only 15 of the 22 reported X-ray detections, and moreover find that only 12 of the 22 optical/infrared counterpart galaxies actually lie robustly at z > 4. Combining these results we find convincing evidence for only seven X-ray AGN at z > 4 in the GOODS-S field, of which only one lies at z > 5. We recalculate the evolving far-ultraviolet (1500 Å) luminosity density produced by AGN at high redshift, and find that it declines rapidly from z ≃ 4 to z ≃ 6, in agreement with several other recent studies of the evolving AGN luminosity function. The associated rapid decline in inferred hydrogen ionizing emissivity contributed by AGN falls an order-of-magnitude short of the level required to maintain hydrogen ionization at z ≃ 6. We conclude that all available evidence continues to favour a scenario in which young galaxies reionized the Universe, with AGN making, at most, a very minor contribution to cosmic hydrogen reionization.
Electrically tunable robust edge states in graphene-based topological photonic crystal slabs
NASA Astrophysics Data System (ADS)
Song, Zidong; Liu, HongJun; Huang, Nan; Wang, ZhaoLu
2018-03-01
Topological photonic crystals are optical structures supporting topologically protected unidirectional edge states that exhibit robustness against defects. Here, we propose a graphene-based all-dielectric photonic crystal slab structure that supports two-dimensionally confined topological edge states. These topological edge states can be confined in the out-of-plane direction by two parallel graphene sheets. In the structure, the excitation frequency range of topological edge states can be dynamically and continuously tuned by varying bias voltage across the two parallel graphene sheets. Utilizing this kind of architecture, we construct Z-shaped channels to realize topological edge transmission with diffrerent frequencies. The proposal provides a new degree of freedom to dynamically control topological edge states and potential applications for robust integrated photonic devices and optical communication systems.
Li, Dan; Hu, Nan; Yu, Yueyi; Zhou, Aihong; Li, Fangyu; Jia, Jianping
2017-01-01
Despite its popularity, the latent structure of 22-item Zarit Burden Interview (ZBI) remains unclear. There has been no study exploring how caregiver multidimensional burden changed. The aim of the work was to validate the latent structure of ZBI and to investigate how multidimensional burden evolves with increasing global burden. We studied 1,132 dyads of dementia patients and their informal caregivers. The caregivers completed the ZBI and a questionnaire regarding caregiving. The total sample was randomly split into two equal subsamples. Exploratory factor analysis (EFA) was performed in the first subsample. In the second subsample, confirmatory factor analysis (CFA) was conducted to validate models generated from EFA. The mean of weighted factor score was calculated to assess the change of dimension burden against the increasing ZBI total score. The result of EFA and CFA supported that a five-factor structure, including role strain, personal strain, incompetency, dependency, and guilt, had the best goodness-of-fit. The trajectories of multidimensional burden suggested that three different dimensions (guilt, role strain and personal strain) became the main subtype of burden in sequence as the ZBI total score increased from mild to moderate. Factor dependency contributed prominently to the total burden in severe stage. The five-factor ZBI is a psychometrically robust measure for assessing multidimensional burden in Chinese caregivers. The changes of multidimensional burden have deepened our understanding of the psychological characteristics of caregiving beyond a single total score and may be useful for developing interventions to reduce caregiver burden.
Evolving Systems: An Outcome of Fondest Hopes and Wildest Dreams
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Balas, Mark J.
2012-01-01
New theory is presented for evolving systems, which are autonomously controlled subsystems that self-assemble into a new evolved system with a higher purpose. Evolving systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control that operates through one specific component to maintain stability during the evolution. In addition, this control must often overcome persistent disturbances that occur while the evolution is in progress. Theoretical results will be presented for Adaptive Key Component control for persistent disturbance rejection. An illustrative example will demonstrate the Adaptive Key Component controller on a system composed of rigid body and flexible body modes.
Monkey Lipsmacking Develops Like the Human Speech Rhythm
ERIC Educational Resources Information Center
Morrill, Ryan J.; Paukner, Annika; Ferrari, Pier F.; Ghazanfar, Asif A.
2012-01-01
Across all languages studied to date, audiovisual speech exhibits a consistent rhythmic structure. This rhythm is critical to speech perception. Some have suggested that the speech rhythm evolved "de novo" in humans. An alternative account--the one we explored here--is that the rhythm of speech evolved through the modification of rhythmic facial…
The Evolving Market Structure of the U.S. Residential Solar PV Installation Industry, 2000-2016
DOE Office of Scientific and Technical Information (OSTI.GOV)
OShaughnessy, Eric J.
This study uses data on over 900,000 solar PV installations to summarize the evolving market structure of the U.S. residential solar PV installation industry. Over 8,000 companies have installed residential PV systems in the United States. The vast majority of these installers are small local companies. At the same time, a subset of national-scale high-volume PV installation companies hold high market shares. This study examines the factors behind these trends in market concentration, including the role of customer financing options.
Jurgenson, E. D.; Maris, P.; Furnstahl, R. J.; ...
2013-05-13
The similarity renormalization group (SRG) is used to soften interactions for ab initio nuclear structure calculations by decoupling low- and high-energy Hamiltonian matrix elements. The substantial contribution of both initial and SRG-induced three-nucleon forces requires their consistent evolution in a three-particle basis space before applying them to larger nuclei. While, in principle, the evolved Hamiltonians are unitarily equivalent, in practice the need for basis truncation introduces deviations, which must be monitored. Here we present benchmark no-core full configuration calculations with SRG-evolved interactions in p-shell nuclei over a wide range of softening. As a result, these calculations are used to assessmore » convergence properties, extrapolation techniques, and the dependence of energies, including four-body contributions, on the SRG resolution scale.« less
A Systems Approach to Lower Cost Missions: Following the Rideshare Paradigm
NASA Technical Reports Server (NTRS)
Herrell, L.
2009-01-01
Small-satellite rideshare capabilities and opportunities for low-cost access to space have been evolving over the past 10 years. Small space launch vehicle technology is rapidly being developed and demonstrated, including the Minotaur series and the Space X Falcon, among others, along with the lower cost launch facilities at Alaska's Kodiak Launch Complex, NASA's Wallops Flight Facility, and the Reagan Test Site in the Pacific. Demonstrated capabilities for the launch of multiple payloads have increased (and continue to increase) significantly. This will allow more efficient and cost-effective use of the various launch opportunities, including utilizing the excess capacity of the emerging Evolved Expendable Launch Vehicle (EELV)-based missions. The definition of standardized interfaces and processes, along with various user guides and payload implementation plans, has been developed and continues to be refined. Top-level agency policies for the support of low-cost access to space for small experimental payloads, such as the DoD policy structure on auxiliary payloads, have been defined and provide the basis for the continued refinement and implementation of these evolving technologies. Most importantly, the coordination and cooperative interfaces between the various stakeholders continues to evolve. The degree of this coordination and technical interchange is demonstrated by the wide stakeholder participation at the recent 2008 Small Payload Rideshare Workshop, held at NASA's Wallops Flight Facility. This annual workshop has been the major platform for coordination and technical interchange within the rideshare community and with the various sponsoring agencies. These developments have provided the foundation for a robust low-cost small payload rideshare capability. However, the continued evolution, sustainment, and utilization of these capabilities will require continued stakeholder recognition, support, and nourishing. Ongoing, coordinated effort, partnering, and support between stakeholders is essential to acquire the improved organizational processes and efficiencies required to meet the needs of the growing small payload community for low-cost access to space. Further, a mix of capabilities developed within the space community for Operationally Responsive Space, an international committee investigating space systems cross-compatibility, and an industry-based organization seeking small satellite "standardization" all work toward a new paradigm: sharing or leveraging resources amongst multiple users. The challenge: where are those users, and what is the best way to leverage them? What is leveraged-mass, power, cost-sharing? And how does one sort through these options? What policies may prevent the use of some options? Who are the "other users" that might share or leverage capabilities? This paper presents a systematic look at both the users and the launch options, and suggests a way forward.
A General Framework of Persistence Strategies for Biological Systems Helps Explain Domains of Life
Yafremava, Liudmila S.; Wielgos, Monica; Thomas, Suravi; Nasir, Arshan; Wang, Minglei; Mittenthal, Jay E.; Caetano-Anollés, Gustavo
2012-01-01
The nature and cause of the division of organisms in superkingdoms is not fully understood. Assuming that environment shapes physiology, here we construct a novel theoretical framework that helps identify general patterns of organism persistence. This framework is based on Jacob von Uexküll’s organism-centric view of the environment and James G. Miller’s view of organisms as matter-energy-information processing molecular machines. Three concepts describe an organism’s environmental niche: scope, umwelt, and gap. Scope denotes the entirety of environmental events and conditions to which the organism is exposed during its lifetime. Umwelt encompasses an organism’s perception of these events. The gap is the organism’s blind spot, the scope that is not covered by umwelt. These concepts bring organisms of different complexity to a common ecological denominator. Ecological and physiological data suggest organisms persist using three strategies: flexibility, robustness, and economy. All organisms use umwelt information to flexibly adapt to environmental change. They implement robustness against environmental perturbations within the gap generally through redundancy and reliability of internal constituents. Both flexibility and robustness improve survival. However, they also incur metabolic matter-energy processing costs, which otherwise could have been used for growth and reproduction. Lineages evolve unique tradeoff solutions among strategies in the space of what we call “a persistence triangle.” Protein domain architecture and other evidence support the preferential use of flexibility and robustness properties. Archaea and Bacteria gravitate toward the triangle’s economy vertex, with Archaea biased toward robustness. Eukarya trade economy for survivability. Protista occupy a saddle manifold separating akaryotes from multicellular organisms. Plants and the more flexible Fungi share an economic stratum, and Metazoa are locked in a positive feedback loop toward flexibility. PMID:23443991
Recent advances on the functional and evolutionary morphology of the amniote respiratory apparatus.
Lambertz, Markus
2016-02-01
Increased organismic complexity in metazoans was achieved via the specialization of certain parts of the body involved in different faculties (structure-function complexes). One of the most basic metabolic demands of animals in general is a sufficient supply of all tissues with oxygen. Specialized structures for gas exchange (and transport) consequently evolved many times and in great variety among bilaterians. This review focuses on some of the latest advancements that morphological research has added to our understanding of how the respiratory apparatus of the primarily terrestrial vertebrates (amniotes) works and how it evolved. Two main components of the respiratory apparatus, the lungs as the "exchanger" and the ventilatory apparatus as the "active pump," are the focus of this paper. Specific questions related to the exchanger concern the structure of the lungs of the first amniotes and the efficiency of structurally simple snake lungs in health and disease, as well as secondary functions of the lungs in heat exchange during the evolution of sauropod dinosaurs. With regard to the active pump, I discuss how the unique ventilatory mechanism of turtles evolved and how understanding the avian ventilatory strategy affects animal welfare issues in the poultry industry. © 2016 New York Academy of Sciences.
Marchal, Marie; Goldschmidt, Felix; Derksen-Müller, Selina N; Panke, Sven; Ackermann, Martin; Johnson, David R
2017-04-24
While mutualistic interactions between different genotypes are pervasive in nature, their evolutionary origin is not clear. The dilemma is that, for mutualistic interactions to emerge and persist, an investment into the partner genotype must pay off: individuals of a first genotype that invest resources to promote the growth of a second genotype must receive a benefit that is not equally accessible to individuals that do not invest. One way for exclusive benefits to emerge is through spatial structure (i.e., physical barriers to the movement of individuals and resources). Here we propose that organisms can evolve their own spatial structure based on physical attachment between individuals, and we hypothesize that attachment evolves when spatial proximity to members of another species is advantageous. We tested this hypothesis using experimental evolution with combinations of E. coli strains that depend on each other to grow. We found that attachment between cells repeatedly evolved within 8 weeks of evolution and observed that many different types of mutations potentially contributed to increased attachment. We postulate a general principle by which passive beneficial interactions between organisms select for attachment, and attachment then provides spatial structure that could be conducive for the evolution of active mutualistic interactions.
Robustness and percolation of holes in complex networks
NASA Astrophysics Data System (ADS)
Zhou, Andu; Maletić, Slobodan; Zhao, Yi
2018-07-01
Efficient robustness and fault tolerance of complex network is significantly influenced by its connectivity, commonly modeled by the structure of pairwise relations between network elements, i.e., nodes. Nevertheless, aggregations of nodes build higher-order structures embedded in complex network, which may be more vulnerable when the fraction of nodes is removed. The structure of higher-order aggregations of nodes can be naturally modeled by simplicial complexes, whereas the removal of nodes affects the values of topological invariants, like the number of higher-dimensional holes quantified with Betti numbers. Following the methodology of percolation theory, as the fraction of nodes is removed, new holes appear, which have the role of merger between already present holes. In the present article, relationship between the robustness and homological properties of complex network is studied, through relating the graph-theoretical signatures of robustness and the quantities derived from topological invariants. The simulation results of random failures and intentional attacks on networks suggest that the changes of graph-theoretical signatures of robustness are followed by differences in the distribution of number of holes per cluster under different attack strategies. In the broader sense, the results indicate the importance of topological invariants research for obtaining further insights in understanding dynamics taking place over complex networks.
Robust control of seismically excited cable stayed bridges with MR dampers
NASA Astrophysics Data System (ADS)
YeganehFallah, Arash; Khajeh Ahamd Attari, Nader
2017-03-01
In recent decades active and semi-active structural control are becoming attractive alternatives for enhancing performance of civil infrastructures subjected to seismic and winds loads. However, in order to have reliable active and semi-active control, there is a need to include information of uncertainties in design of the controller. In real world for civil structures, parameters such as loading places, stiffness, mass and damping are time variant and uncertain. These uncertainties in many cases model as parametric uncertainties. The motivation of this research is to design a robust controller for attenuating the vibrational responses of civil infrastructures, regarding their dynamical uncertainties. Uncertainties in structural dynamic’s parameters are modeled as affine uncertainties in state space modeling. These uncertainties are decoupled from the system through Linear Fractional Transformation (LFT) and are assumed to be unknown input to the system but norm bounded. The robust H ∞ controller is designed for the decoupled system to regulate the evaluation outputs and it is robust to effects of uncertainties, disturbance and sensors noise. The cable stayed bridge benchmark which is equipped with MR damper is considered for the numerical simulation. The simulated results show that the proposed robust controller can effectively mitigate undesired uncertainties effects on systems’ responds under seismic loading.
Kaiser, Gary W.; Longrich, Nicholas R.
2017-01-01
Mesozoic bird fossils from the Pacific Coast of North America are rare, but small numbers are known from the Late Cretaceous aged sediments of Hornby Island, British Columbia. Most are unassociated fragments that offer little information, but additional preparation of a large coracoid has revealed more details of its structure, as well as three associated wing bones. Phylogenetic analysis suggests that Maaqwi cascadensis, gen. et sp. nov. represents a derived crown or near-crown member of Ornithurae, and specifically suggests affinities with Vegaviidae. M. cascadensis is characterized by large size, and regressions based on dimensions of the coracoid suggest a large bird, with an estimated body mass of approximately 1.5 kilograms. The bones are robust, with thick walls, suggesting that M. cascadensis was a bird adapted for diving, similar to modern loons and grebes. The wings are short, while the coracoid is unusually short and broad, similar to modern loons. Along with the Ichthyornithes and Hesperornithes, M. cascadensis and Vegaviidae appear to represent a third clade of bird that evolved to exploit marine habitats in the Late Cretaceous, one specialized for foot-propelled diving and rapid cruising flight over water. PMID:29220405
Vaden, Rachel M.; Oswald, Nathaniel W.; Potts, Malia B.; MacMillan, John B.; White, Michael A.
2017-01-01
Chemicals found in nature have evolved over geological time scales to productively interact with biological molecules, and thus represent an effective resource for pharmaceutical development. Marine-derived bacteria are rich sources of chemically diverse, bioactive secondary metabolites, but harnessing this diversity for biomedical benefit is limited by challenges associated with natural product purification and determination of biochemical mechanism. Using Functional Signature Ontology (FUSION), we report the parallel isolation and characterization of a marine-derived natural product, N6,N6-dimethyladenosine, that robustly inhibits AKT signaling in a variety of non-small cell lung cancer cell lines. Upon validation of the elucidated structure by comparison with a commercially available sample, experiments were initiated to understand the small molecule’s breadth of effect in a biological setting. One such experiment, a reverse phase protein array (RPPA) analysis of >50 kinases, indicated a specific cellular response to treatment. In all, leveraging the FUSION platform allowed for the rapid generation and validation of a biological mechanism of action hypothesis for an unknown natural product and permitted accelerated purification of the bioactive component from a chemically complex fraction. PMID:28294973
Homophyly/Kinship Model: Naturally Evolving Networks
NASA Astrophysics Data System (ADS)
Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi
2015-10-01
It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.
Predicting the evolution of complex networks via similarity dynamics
NASA Astrophysics Data System (ADS)
Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping
2017-01-01
Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.
NASA Astrophysics Data System (ADS)
Dargent, J.; Aunai, N.; Belmont, G.; Dorville, N.; Lavraud, B.; Hesse, M.
2016-06-01
> Tangential current sheets are ubiquitous in space plasmas and yet hard to describe with a kinetic equilibrium. In this paper, we use a semi-analytical model, the BAS model, which provides a steady ion distribution function for a tangential asymmetric current sheet and we prove that an ion kinetic equilibrium produced by this model remains steady in a fully kinetic particle-in-cell simulation even if the electron distribution function does not satisfy the time independent Vlasov equation. We then apply this equilibrium to look at the dependence of magnetic reconnection simulations on their initial conditions. We show that, as the current sheet evolves from a symmetric to an asymmetric upstream plasma, the reconnection rate is impacted and the X line and the electron flow stagnation point separate from one another and start to drift. For the simulated systems, we investigate the overall evolution of the reconnection process via the classical signatures discussed in the literature and searched in the Magnetospheric MultiScale data. We show that they seem robust and do not depend on the specific details of the internal structure of the initial current sheet.
Homophyly/Kinship Model: Naturally Evolving Networks
Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi
2015-01-01
It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network. PMID:26478264
Channel-Forming Bacterial Toxins in Biosensing and Macromolecule Delivery
Gurnev, Philip A.; Nestorovich, Ekaterina M.
2014-01-01
To intoxicate cells, pore-forming bacterial toxins are evolved to allow for the transmembrane traffic of different substrates, ranging from small inorganic ions to cell-specific polypeptides. Recent developments in single-channel electrical recordings, X-ray crystallography, protein engineering, and computational methods have generated a large body of knowledge about the basic principles of channel-mediated molecular transport. These discoveries provide a robust framework for expansion of the described principles and methods toward use of biological nanopores in the growing field of nanobiotechnology. This article, written for a special volume on “Intracellular Traffic and Transport of Bacterial Protein Toxins”, reviews the current state of applications of pore-forming bacterial toxins in small- and macromolecule-sensing, targeted cancer therapy, and drug delivery. We discuss the electrophysiological studies that explore molecular details of channel-facilitated protein and polymer transport across cellular membranes using both natural and foreign substrates. The review focuses on the structurally and functionally different bacterial toxins: gramicidin A of Bacillus brevis, α-hemolysin of Staphylococcus aureus, and binary toxin of Bacillus anthracis, which have found their “second life” in a variety of developing medical and technological applications. PMID:25153255
Robust space-time extraction of ventricular surface evolution using multiphase level sets
NASA Astrophysics Data System (ADS)
Drapaca, Corina S.; Cardenas, Valerie; Studholme, Colin
2004-05-01
This paper focuses on the problem of accurately extracting the CSF-tissue boundary, particularly around the ventricular surface, from serial structural MRI of the brain acquired in imaging studies of aging and dementia. This is a challenging problem because of the common occurrence of peri-ventricular lesions which locally alter the appearance of white matter. We examine a level set approach which evolves a four dimensional description of the ventricular surface over time. This has the advantage of allowing constraints on the contour in the temporal dimension, improving the consistency of the extracted object over time. We follow the approach proposed by Chan and Vese which is based on the Mumford and Shah model and implemented using the Osher and Sethian level set method. We have extended this to the 4 dimensional case to propagate a 4D contour toward the tissue boundaries through the evolution of a 5D implicit function. For convergence we use region-based information provided by the image rather than the gradient of the image. This is adapted to allow intensity contrast changes between time frames in the MRI sequence. Results on time sequences of 3D brain MR images are presented and discussed.
Carbon dot-Au(i)Ag(0) assembly for the construction of an artificial light harvesting system.
Jana, Jayasmita; Aditya, Teresa; Pal, Tarasankar
2018-03-06
Artificial light harvesting systems (LHS) with inorganic counterparts are considered to be robust as well as mechanistically simple, where the system follows the donor-acceptor principle with an unchanged structural pattern. Plasmonic gold or silver nanoparticles are mostly chosen as inorganic counterparts to design artificial LHS. To capitalize on its electron accepting capability, Au(i) has been considered in this work for the synergistic stabilization of a system with intriguingly fluorescing silver(0) clusters produced in situ. Thus a stable fluorescent Au(i)Ag(0) assembly is generated with electron accepting capabilities. On the other hand, carbon dots have evolved as new fluorescent probes due to their unique physicochemical properties. Utilizing the simple electronic behavior of carbon dots, an electronic interaction between the fluorescent Au(i)Ag(0) and a carbon dot has been investigated for the construction of a new artificial light harvesting system. This coinage metal assembly allows surface energy transfer where it acts as an acceptor, while the carbon dot behaves as a good donor. The energy transfer efficiency has been calculated experimentally to be significant (81.3%) and the Au(i)Ag(0)-carbon dot assembly paves the way for efficient artificial LHS.
Adaptive inferential sensors based on evolving fuzzy models.
Angelov, Plamen; Kordon, Arthur
2010-04-01
A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can address the challenges of the modern advanced process industry.
Evolution and coevolution of developmental programs
NASA Astrophysics Data System (ADS)
Jacob, Christian
1999-09-01
The developmental processes of single organisms, such as growth and structure formation, can be described by parallel rewrite systems in the form of Lindenmayer systems, which also allow one to generate geometrical structures in 3D space using turtle interpretation. We present examples of L-systems for growth programs of plant-like structures. Evolution-based programming techniques are applied to design L-systems by Genetic L-system Programming (GLP), demonstrating how developmental programs for plants, exhibiting specific morphogenetic properties can be interactively bred or automatically evolved. Finally, we demonstrate coevolutionary effects among plant populations consisting of different species, interacting with each other, competing for resources like sunlight and nutrients, and evolving successful reproduction strategies in their specific environments.
Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen
2012-08-01
Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: first, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction-this not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide the reader reproducible experiments that demonstrate the capability of the proposed segmentation tool on several public available data sets. Copyright © 2012 Elsevier B.V. All rights reserved.
A 3D Interactive Multi-object Segmentation Tool using Local Robust Statistics Driven Active Contours
Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen
2012-01-01
Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: First, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction — This not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide the reader reproducible experiments that demonstrate the capability of the proposed segmentation tool on several public available data sets. PMID:22831773
The impact behaviour of silk cocoons.
Chen, Fujia; Hesselberg, Thomas; Porter, David; Vollrath, Fritz
2013-07-15
Silk cocoons, constructed by silkmoths (Lepidoptera), are protective structural composites. Some cocoons appear to have evolved towards structural and material optimisation in order to sustain impact strikes from predators and hinder parasite ingress. This study investigates the protective properties of silk cocoons with different morphologies by evaluating their impact resistance and damage tolerance. Finite element analysis was used to analyse empirical observations of the quasi-static impact response of the silk cocoons, and to evaluate the separate benefits of the structures and materials through the deformation and damage mechanism. We use design principles from composite engineering in order to understand the structure-property-function relationship of silkworm cocoons. Understanding the highly evolved survival strategies of the organisms building natural cocoons will hopefully lead to inspiration that in turn could lead to improved composite design.
Askerka, Mikhail; Wang, Jimin; Brudvig, Gary W.; ...
2014-10-27
The S 1 → S 2 transition of the oxygen-evolving complex (OEC) of photosystem II does not involve the transfer of a proton to the lumen and occurs at cryogenic temperatures. Therefore, it is commonly thought to involve only Mn oxidation without any significant change in the structure of the OEC. Here, we analyze structural changes upon the S 1 → S 2 transition, as revealed by quantum mechanics/molecular mechanics methods and the isomorphous difference Fourier method applied to serial femtosecond X-ray diffraction data. Lastly, we find that the main structural change in the OEC is in the position ofmore » the dangling Mn and its coordination environment.« less
1990-01-01
robustness of feedback systems with structured uncertainty. Theorem: Robust Stability Fu(G,A) stable V AA iff suP (Gll(JW))Sl. Theorem: Robust ...through a gain KR. The addition of other dynamics and feedback paths creates stabilization problems for this simple roll attitude feedback control...characteristics are most useful to the designer when examined in the frequency domain. Both relative stability and robustness can be determined from an
NASA Astrophysics Data System (ADS)
Jin, Shi; Wang, Xuelei
2003-04-01
Chemical vapor infiltration (CVI) process is an important technology to fabricate ceramic matrix composites (CMC's). In this paper, a three-dimension numerical model is presented to describe pore microstructure evolution during the CVI process. We extend the two-dimension model proposed in [S. Jin, X.L. Wang, T.L. Starr, J. Mater. Res. 14 (1999) 3829; S. Jin. X.L. Wang, T.L. Starr, X.F. Chen, J. Comp. Phys. 162 (2000) 467], where the fiber surface is modeled as an evolving interface, to the three space dimension. The 3D method keeps all the virtue of the 2D model: robust numerical capturing of topological changes of the interface such as the merging, and fast detection of the inaccessible pores. For models in the kinetic limit, where the moving speed of the interface is constant, some numerical examples are presented to show that this three-dimension model will effectively track the change of porosity, close-off time, location and shape of all pores.
Zhou, Haiqing; Yu, Fang; Huang, Yufeng; ...
2016-09-16
With the massive consumption of fossil fuels and its detrimental impact on the environment, methods of generating clean power are urgent. Hydrogen is an ideal carrier for renewable energy; however, hydrogen generation is inefficient because of the lack of robust catalysts that are substantially cheaper than platinum. Therefore, robust and durable earth-abundant and cost-effective catalysts are desirable for hydrogen generation from water splitting via hydrogen evolution reaction. In this paper, we report an active and durable earth-abundant transition metal dichalcogenide-based hybrid catalyst that exhibits high hydrogen evolution activity approaching the state-of-the-art platinum catalysts, and superior to those of most transitionmore » metal dichalcogenides (molybdenum sulfide, cobalt diselenide and so on). Our material is fabricated by growing ternary molybdenum sulfoselenide particles on self-standing porous nickel diselenide foam. This advance provides a different pathway to design cheap, efficient and sizable hydrogen-evolving electrode by simultaneously tuning the number of catalytic edge sites, porosity, heteroatom doping and electrical conductivity.« less
NASA Astrophysics Data System (ADS)
Zhou, Haiqing; Yu, Fang; Huang, Yufeng; Sun, Jingying; Zhu, Zhuan; Nielsen, Robert J.; He, Ran; Bao, Jiming; Goddard, William A., III; Chen, Shuo; Ren, Zhifeng
2016-09-01
With the massive consumption of fossil fuels and its detrimental impact on the environment, methods of generating clean power are urgent. Hydrogen is an ideal carrier for renewable energy; however, hydrogen generation is inefficient because of the lack of robust catalysts that are substantially cheaper than platinum. Therefore, robust and durable earth-abundant and cost-effective catalysts are desirable for hydrogen generation from water splitting via hydrogen evolution reaction. Here we report an active and durable earth-abundant transition metal dichalcogenide-based hybrid catalyst that exhibits high hydrogen evolution activity approaching the state-of-the-art platinum catalysts, and superior to those of most transition metal dichalcogenides (molybdenum sulfide, cobalt diselenide and so on). Our material is fabricated by growing ternary molybdenum sulfoselenide particles on self-standing porous nickel diselenide foam. This advance provides a different pathway to design cheap, efficient and sizable hydrogen-evolving electrode by simultaneously tuning the number of catalytic edge sites, porosity, heteroatom doping and electrical conductivity.
2010-01-01
Background The species-specificity of male genitalia has been well documented in many insect groups and sexual selection has been proposed as the evolutionary force driving the often rapid, morphological divergence. The internal female genitalia, in sharp contrast, remain poorly studied. Here, we present the first comparative study of the internal reproductive system of Sepsidae. We test the species-specificity of the female genitalia by comparing recently diverged sister taxa. We also compare the rate of change in female morphological characters with the rate of fast-evolving, molecular and behavioral characters. Results We describe the ectodermal parts of the female reproductive tract for 41 species representing 21 of the 37 described genera and define 19 morphological characters with discontinuous variation found in eight structures that are part of the reproductive tract. Using a well-resolved molecular phylogeny based on 10 genes, we reconstruct the evolution of these characters across the family [120 steps; Consistency Index (CI): 0.41]. Two structures, in particular, evolve faster than the rest. The first is the ventral receptacle, which is a secondary sperm storage organ. It accounts for more than half of all the evolutionary changes observed (7 characters; 61 steps; CI: 0.46). It is morphologically diverse across genera, can be bi-lobed or multi-chambered (up to 80 chambers), and is strongly sclerotized in one clade. The second structure is the dorsal sclerite, which is present in all sepsids except Orygma luctuosum and Ortalischema albitarse. It is associated with the opening of the spermathecal ducts and is often distinct even among sister species (4 characters; 16 steps; CI: 0.56). Conclusions We find the internal female genitalia are diverse in Sepsidae and diagnostic for all species. In particular, fast-evolving structures like the ventral receptacle and dorsal sclerite are likely involved in post-copulatory sexual selection. In comparison to behavioral and molecular data, the female structures are evolving 2/3 as fast as the non-constant third positions of the COI barcoding gene. They display less convergent evolution in characters (CI = 0.54) than the third positions or sepsid mating behavior (CICOI = 0.36; CIBEHAV = 0.45). PMID:20831809
Mauer, Michael; Caramori, Maria Luiza; Fioretto, Paola; Najafian, Behzad
2015-06-01
Studies of structural-functional relationships have improved understanding of the natural history of diabetic nephropathy (DN). However, in order to consider structural end points for clinical trials, the robustness of the resultant models needs to be verified. This study examined whether structural-functional relationship models derived from a large cohort of type 1 diabetic (T1D) patients with a wide range of renal function are robust. The predictability of models derived from multiple regression analysis and piecewise linear regression analysis was also compared. T1D patients (n = 161) with research renal biopsies were divided into two equal groups matched for albumin excretion rate (AER). Models to explain AER and glomerular filtration rate (GFR) by classical DN lesions in one group (T1D-model, or T1D-M) were applied to the other group (T1D-test, or T1D-T) and regression analyses were performed. T1D-M-derived models explained 70 and 63% of AER variance and 32 and 21% of GFR variance in T1D-M and T1D-T, respectively, supporting the substantial robustness of the models. Piecewise linear regression analyses substantially improved predictability of the models with 83% of AER variance and 66% of GFR variance explained by classical DN glomerular lesions alone. These studies demonstrate that DN structural-functional relationship models are robust, and if appropriate models are used, glomerular lesions alone explain a major proportion of AER and GFR variance in T1D patients. © The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
Robust controller design for flexible structures using normalized coprime factor plant descriptions
NASA Technical Reports Server (NTRS)
Armstrong, Ernest S.
1993-01-01
Stabilization is a fundamental requirement in the design of feedback compensators for flexible structures. The search for the largest neighborhood around a given design plant for which a single controller produces closed-loop stability can be formulated as an H(sub infinity) control problem. The use of normalized coprime factor plant descriptions, in which the plant perturbations are defined as additive modifications to the coprime factors, leads to a closed-form expression for the maximum neighborhood boundary allowing optimal and suboptimal H(sub infinity) compensators to be computed directly without the usual gamma iteration. A summary of the theory on robust stabilization using normalized coprime factor plant descriptions is presented, and the application of the theory to the computation of robustly stable compensators for the phase version of the Control-Structures Interaction (CSI) Evolutionary Model is described. Results from the application indicate that the suboptimal version of the theory has the potential of providing the bases for the computation of low-authority compensators that are robustly stable to expected variations in design model parameters and additive unmodeled dynamics.
Robust pattern decoding in shape-coded structured light
NASA Astrophysics Data System (ADS)
Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai
2017-09-01
Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.
The origin of conodonts and of vertebrate mineralized skeletons
Murdock, Duncan J.E.; Dong, Xi-Ping; Repetski, John E.; Marone, Federica; Stampanoni, Marco; Donoghue, Philip C.J.
2013-01-01
Conodonts are an extinct group of jawless vertebrates whose tooth-like elements are the earliest instance of a mineralized skeleton in the vertebrate lineage, inspiring the ‘inside-out’ hypothesis that teeth evolved independently of the vertebrate dermal skeleton and before the origin of jaws. However, these propositions have been based on evidence from derived euconodonts. Here we test hypotheses of a paraconodont ancestry of euconodonts using synchrotron radiation X-ray tomographic microscopy to characterize and compare the microstructure of morphologically similar euconodont and paraconodont elements. Paraconodonts exhibit a range of grades of structural differentiation, including tissues and a pattern of growth common to euconodont basal bodies. The different grades of structural differentiation exhibited by paraconodonts demonstrate the stepwise acquisition of euconodont characters, resolving debate over the relationship between these two groups. By implication, the putative homology of euconodont crown tissue and vertebrate enamel must be rejected as these tissues have evolved independently and convergently. Thus, the precise ontogenetic, structural and topological similarities between conodont elements and vertebrate odontodes appear to be a remarkable instance of convergence. The last common ancestor of conodonts and jawed vertebrates probably lacked mineralized skeletal tissues. The hypothesis that teeth evolved before jaws and the inside-out hypothesis of dental evolution must be rejected; teeth seem to have evolved through the extension of odontogenic competence from the external dermis to internal epithelium soon after the origin of jaws.
Park, Kwangwook; Kang, Seokjin; Ravindran, Sooraj; ...
2016-12-26
Double-hetero structure lateral composition modulated (LCM) GaInP and sandwiched LCM GaInP having the same active layer thickness were grown and their optical properties were compared. Sandwiched LCM GaInP showed robust optical properties due to periodic potential nature of the LCM structure, and the periodicity was undistorted even for thickness far beyond the critical layer thickness. A thick LCM GaInP structure with undistorted potential that could preserve the properties of native LCM structure was possible by stacking thin LCM GaInP structures interspaced with strain compensating GaInP layers. Furthermore, the sandwiched structure could be beneficial in realizing the LCM structure embedded highmore » efficiency solar cells.« less
Microgravity Vibration Control and Civil Applications
NASA Technical Reports Server (NTRS)
Whorton, Mark Stephen; Alhorn, Dean Carl
1998-01-01
Controlling vibration of structures is essential for both space structures as well as terrestrial structures. Due to the ambient acceleration levels anticipated for the International Space Station, active vibration isolation is required to provide a quiescent acceleration environment for many science experiments. An overview is given of systems developed and flight tested in orbit for microgravity vibration isolation. Technology developed for vibration control of flexible space structures may also be applied to control of terrestrial structures such as buildings and bridges subject to wind loading or earthquake excitation. Recent developments in modern robust control for flexible space structures are shown to provide good structural vibration control while maintaining robustness to model uncertainties. Results of a mixed H-2/H-infinity control design are provided for a benchmark problem in structural control for earthquake resistant buildings.
Inter-computer communication architecture for a mixed redundancy distributed system
NASA Technical Reports Server (NTRS)
Lala, Jaynarayan H.; Adams, Stuart J.
1987-01-01
The triply redundant intercomputer network for the Advanced Information Processing System (AIPS), an architecture developed to serve as the core avionics system for a broad range of aerospace vehicles, is discussed. The AIPS intercomputer network provides a high-speed, Byzantine-fault-resilient communication service between processing sites, even in the presence of arbitrary failures of simplex and duplex processing sites on the IC network. The IC network contention poll has evolved from the Laning Poll. An analysis of the failure modes and effects and a simulation of the AIPS contention poll, demonstrate the robustness of the system.
High-performance thin layer chromatography to assess pharmaceutical product quality.
Kaale, Eliangiringa; Manyanga, Vicky; Makori, Narsis; Jenkins, David; Michael Hope, Samuel; Layloff, Thomas
2014-06-01
To assess the sustainability, robustness and economic advantages of high-performance thin layer chromatography (HPTLC) for quality control of pharmaceutical products. We compared three laboratories where three lots of cotrimoxazole tablets were assessed using different techniques for quantifying the active ingredient. The average assay relative standard deviation for the three lots was 1.2 with a range of 0.65-2.0. High-performance thin layer chromatography assessments are yielding valid results suitable for assessing product quality. The local pharmaceutical manufacturer had evolved the capacity to produce very high quality products. © 2014 John Wiley & Sons Ltd.
A New Look at NASA: Strategic Research In Information Technology
NASA Technical Reports Server (NTRS)
Alfano, David; Tu, Eugene (Technical Monitor)
2002-01-01
This viewgraph presentation provides information on research undertaken by NASA to facilitate the development of information technologies. Specific ideas covered here include: 1) Bio/nano technologies: biomolecular and nanoscale systems and tools for assembly and computing; 2) Evolvable hardware: autonomous self-improving, self-repairing hardware and software for survivable space systems in extreme environments; 3) High Confidence Software Technologies: formal methods, high-assurance software design, and program synthesis; 4) Intelligent Controls and Diagnostics: Next generation machine learning, adaptive control, and health management technologies; 5) Revolutionary computing: New computational models to increase capability and robustness to enable future NASA space missions.
Quantifying Disease Progression in Amyotrophic Lateral Sclerosis
Simon, Neil G; Turner, Martin R; Vucic, Steve; Al-Chalabi, Ammar; Shefner, Jeremy; Lomen-Hoerth, Catherine; Kiernan, Matthew C
2014-01-01
Amyotrophic lateral sclerosis (ALS) exhibits characteristic variability of onset and rate of disease progression, with inherent clinical heterogeneity making disease quantitation difficult. Recent advances in understanding pathogenic mechanisms linked to the development of ALS impose an increasing need to develop strategies to predict and more objectively measure disease progression. This review explores phenotypic and genetic determinants of disease progression in ALS, and examines established and evolving biomarkers that may contribute to robust measurement in longitudinal clinical studies. With targeted neuroprotective strategies on the horizon, developing efficiencies in clinical trial design may facilitate timely entry of novel treatments into the clinic. PMID:25223628
A numerical code for a three-dimensional magnetospheric MHD equilibrium model
NASA Technical Reports Server (NTRS)
Voigt, G.-H.
1992-01-01
Two dimensional and three dimensional MHD equilibrium models were begun for Earth's magnetosphere. The original proposal was motivated by realizing that global, purely data based models of Earth's magnetosphere are inadequate for studying the underlying plasma physical principles according to which the magnetosphere evolves on the quasi-static convection time scale. Complex numerical grid generation schemes were established for a 3-D Poisson solver, and a robust Grad-Shafranov solver was coded for high beta MHD equilibria. Thus, the effects were calculated of both the magnetopause geometry and boundary conditions on the magnetotail current distribution.
Self-organization, embodiment, and biologically inspired robotics.
Pfeifer, Rolf; Lungarella, Max; Iida, Fumiya
2007-11-16
Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.
CFD Analysis of Turbo Expander for Cryogenic Refrigeration and Liquefaction Cycles
NASA Astrophysics Data System (ADS)
Verma, Rahul; Sam, Ashish Alex; Ghosh, Parthasarathi
Computational Fluid Dynamics analysis has emerged as a necessary tool for designing of turbomachinery. It helps to understand the various sources of inefficiency through investigation of flow physics of the turbine. In this paper, 3D turbulent flow analysis of a cryogenic turboexpander for small scale air separation was performed using Ansys CFX®. The turboexpander has been designed following assumptions based on meanlineblade generation procedure provided in open literature and good engineering judgement. Through analysis of flow field, modifications and further analysis required to evolve a more robust design procedure, have been suggested.
Review of current status of smart structures and integrated systems
NASA Astrophysics Data System (ADS)
Chopra, Inderjit
1996-05-01
A smart structure involves distributed actuators and sensors, and one or more microprocessors that analyze the responses from the sensors and use distributed-parameter control theory to command the actuators to apply localized strains to minimize system response. A smart structure has the capability to respond to a changing external environment (such as loads or shape change) as well as to a changing internal environment (such as damage or failure). It incorporates smart actuators that allow the alteration of system characteristics (such as stiffness or damping) as well as of system response (such as strain or shape) in a controlled manner. Many types of actuators and sensors are being considered, such as piezoelectric materials, shape memory alloys, electrostrictive materials, magnetostrictive materials, electro- rheological fluids and fiber optics. These can be integrated with main load-carrying structures by surface bonding or embedding without causing any significant changes in the mass or structural stiffness of the system. Numerous applications of smart structures technology to various physical systems are evolving to actively control vibration, noise, aeroelastic stability, damping, shape and stress distribution. Applications range from space systems, fixed-wing and rotary-wing aircraft, automotive, civil structures and machine tools. Much of the early development of smart structures methodology was driven by space applications such as vibration and shape control of large flexible space structures, but now wider applications are envisaged for aeronautical and other systems. Embedded or surface-bonded smart actuators on an airplane wing or helicopter blade will induce alteration of twist/camber of airfoil (shape change), that in turn will cause variation of lift distribution and may help to control static and dynamic aeroelastic problems. Applications of smart structures technology to aerospace and other systems are expanding rapidly. Major barriers are: actuator stroke, reliable data base of smart material characteristics, non-availability of robust distributed parameter control strategies, and non-existent mathematical modeling of smart systems. The objective of this paper is to review the state-of-the-art of smart actuators and sensors and integrated systems and point out the needs for future research.
Robust Control Design for Systems With Probabilistic Uncertainty
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.
2005-01-01
This paper presents a reliability- and robustness-based formulation for robust control synthesis for systems with probabilistic uncertainty. In a reliability-based formulation, the probability of violating design requirements prescribed by inequality constraints is minimized. In a robustness-based formulation, a metric which measures the tendency of a random variable/process to cluster close to a target scalar/function is minimized. A multi-objective optimization procedure, which combines stability and performance requirements in time and frequency domains, is used to search for robustly optimal compensators. Some of the fundamental differences between the proposed strategy and conventional robust control methods are: (i) unnecessary conservatism is eliminated since there is not need for convex supports, (ii) the most likely plants are favored during synthesis allowing for probabilistic robust optimality, (iii) the tradeoff between robust stability and robust performance can be explored numerically, (iv) the uncertainty set is closely related to parameters with clear physical meaning, and (v) compensators with improved robust characteristics for a given control structure can be synthesized.
Robust detection-isolation-accommodation for sensor failures
NASA Technical Reports Server (NTRS)
Weiss, J. L.; Pattipati, K. R.; Willsky, A. S.; Eterno, J. S.; Crawford, J. T.
1985-01-01
The results of a one year study to: (1) develop a theory for Robust Failure Detection and Identification (FDI) in the presence of model uncertainty, (2) develop a design methodology which utilizes the robust FDI ththeory, (3) apply the methodology to a sensor FDI problem for the F-100 jet engine, and (4) demonstrate the application of the theory to the evaluation of alternative FDI schemes are presented. Theoretical results in statistical discrimination are used to evaluate the robustness of residual signals (or parity relations) in terms of their usefulness for FDI. Furthermore, optimally robust parity relations are derived through the optimization of robustness metrics. The result is viewed as decentralization of the FDI process. A general structure for decentralized FDI is proposed and robustness metrics are used for determining various parameters of the algorithm.
Truong, Cong-Doan; Kwon, Yung-Keun
2017-12-21
Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis. Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.
Suplatov, Dmitry; Sharapova, Yana; Timonina, Daria; Kopylov, Kirill; Švedas, Vytas
2018-04-01
The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e.g. a substrate or a crystallographic water molecule), and long-range correlations, annotate and rank binding sites on the protein surface by the presence of statistically significant co-evolving positions. The results of the visualCMAT are organized for a convenient visual analysis and can be downloaded to a local computer as a content-rich all-in-one PyMol session file with multiple layers of annotation corresponding to bioinformatic, statistical and structural analyses of the predicted co-evolution, or further studied online using the built-in interactive analysis tools. The online interactivity is implemented in HTML5 and therefore neither plugins nor Java are required. The visualCMAT web-server is integrated with the Mustguseal web-server capable of constructing large structure-guided sequence alignments of protein families and superfamilies using all available information about their structures and sequences in public databases. The visualCMAT web-server can be used to understand the relationship between structure and function in proteins, implemented at selecting hotspots and compensatory mutations for rational design and directed evolution experiments to produce novel enzymes with improved properties, and employed at studying the mechanism of selective ligand's binding and allosteric communication between topologically independent sites in protein structures. The web-server is freely available at https://biokinet.belozersky.msu.ru/visualcmat and there are no login requirements.
Bao, Yihai; Main, Joseph A.; Noh, Sam-Young
2017-01-01
A computational methodology is presented for evaluating structural robustness against column loss. The methodology is illustrated through application to reinforced concrete (RC) frame buildings, using a reduced-order modeling approach for three-dimensional RC framing systems that includes the floor slabs. Comparisons with high-fidelity finite-element model results are presented to verify the approach. Pushdown analyses of prototype buildings under column loss scenarios are performed using the reduced-order modeling approach, and an energy-based procedure is employed to account for the dynamic effects associated with sudden column loss. Results obtained using the energy-based approach are found to be in good agreement with results from direct dynamic analysis of sudden column loss. A metric for structural robustness is proposed, calculated by normalizing the ultimate capacities of the structural system under sudden column loss by the applicable service-level gravity loading and by evaluating the minimum value of this normalized ultimate capacity over all column removal scenarios. The procedure is applied to two prototype 10-story RC buildings, one employing intermediate moment frames (IMFs) and the other employing special moment frames (SMFs). The SMF building, with its more stringent seismic design and detailing, is found to have greater robustness. PMID:28890599
Evolving mobile robots able to display collective behaviors.
Baldassarre, Gianluca; Nolfi, Stefano; Parisi, Domenico
2003-01-01
We present a set of experiments in which simulated robots are evolved for the ability to aggregate and move together toward a light target. By developing and using quantitative indexes that capture the structural properties of the emerged formations, we show that evolved individuals display interesting behavioral patterns in which groups of robots act as a single unit. Moreover, evolved groups of robots with identical controllers display primitive forms of situated specialization and play different behavioral functions within the group according to the circumstances. Overall, the results presented in the article demonstrate that evolutionary techniques, by exploiting the self-organizing behavioral properties that emerge from the interactions between the robots and between the robots and the environment, are a powerful method for synthesizing collective behavior.
Evolution of bacterial life-history traits is sensitive to community structure.
Ketola, Tarmo; Mikonranta, Lauri; Mappes, Johanna
2016-06-01
Very few studies have experimentally assessed the evolutionary effects of species interactions within the same trophic level. Here we show that when Serratia marcescens evolve in multispecies communities, their growth rate exceeds the growth rate of the bacteria that evolved alone, whereas the biomass yield gets lower. In addition to the community effects per se, we found that few species in the communities caused strong effects on S. marcescens evolution. The results indicate that evolutionary responses (of a focal species) are different in communities, compared to species evolving alone. Moreover, selection can lead to very different outcomes depending on the community structure. Such context dependencies cast doubt on our ability to predict the course of evolution in the wild, where species often inhabit very different kinds of communities. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.
Evolving neural networks through augmenting topologies.
Stanley, Kenneth O; Miikkulainen, Risto
2002-01-01
An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning task. We claim that the increased efficiency is due to (1) employing a principled method of crossover of different topologies, (2) protecting structural innovation using speciation, and (3) incrementally growing from minimal structure. We test this claim through a series of ablation studies that demonstrate that each component is necessary to the system as a whole and to each other. What results is significantly faster learning. NEAT is also an important contribution to GAs because it shows how it is possible for evolution to both optimize and complexify solutions simultaneously, offering the possibility of evolving increasingly complex solutions over generations, and strengthening the analogy with biological evolution.
Bound states in the continuum on periodic structures: perturbation theory and robustness.
Yuan, Lijun; Lu, Ya Yan
2017-11-01
On periodic structures, a bound state in the continuum (BIC) is a standing or propagating Bloch wave with a frequency in the radiation continuum. Some BICs (e.g., antisymmetric standing waves) are symmetry protected, since they have incompatible symmetry with outgoing waves in the radiation channels. The propagating BICs do not have this symmetry mismatch, but they still crucially depend on the symmetry of the structure. In this Letter, a perturbation theory is developed for propagating BICs on two-dimensional periodic structures. The Letter shows that these BICs are robust against structural perturbations that preserve the symmetry, indicating that these BICs, in fact, are implicitly protected by symmetry.
Halim, Dunant; Cheng, Li; Su, Zhongqing
2011-03-01
The work was aimed to develop a robust virtual sensing design methodology for sensing and active control applications of vibro-acoustic systems. The proposed virtual sensor was designed to estimate a broadband acoustic interior sound pressure using structural sensors, with robustness against certain dynamic uncertainties occurring in an acoustic-structural coupled enclosure. A convex combination of Kalman sub-filters was used during the design, accommodating different sets of perturbed dynamic model of the vibro-acoustic enclosure. A minimax optimization problem was set up to determine an optimal convex combination of Kalman sub-filters, ensuring an optimal worst-case virtual sensing performance. The virtual sensing and active noise control performance was numerically investigated on a rectangular panel-cavity system. It was demonstrated that the proposed virtual sensor could accurately estimate the interior sound pressure, particularly the one dominated by cavity-controlled modes, by using a structural sensor. With such a virtual sensing technique, effective active noise control performance was also obtained even for the worst-case dynamics. © 2011 Acoustical Society of America
NASA Astrophysics Data System (ADS)
Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.
2017-09-01
Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.
NASA Astrophysics Data System (ADS)
Herman, Jonathan D.; Zeff, Harrison B.; Reed, Patrick M.; Characklis, Gregory W.
2014-10-01
While optimality is a foundational mathematical concept in water resources planning and management, "optimal" solutions may be vulnerable to failure if deeply uncertain future conditions deviate from those assumed during optimization. These vulnerabilities may produce severely asymmetric impacts across a region, making it vital to evaluate the robustness of management strategies as well as their impacts for regional stakeholders. In this study, we contribute a multistakeholder many-objective robust decision making (MORDM) framework that blends many-objective search and uncertainty analysis tools to discover key tradeoffs between water supply alternatives and their robustness to deep uncertainties (e.g., population pressures, climate change, and financial risks). The proposed framework is demonstrated for four interconnected water utilities representing major stakeholders in the "Research Triangle" region of North Carolina, U.S. The utilities supply well over one million customers and have the ability to collectively manage drought via transfer agreements and shared infrastructure. We show that water portfolios for this region that compose optimal tradeoffs (i.e., Pareto-approximate solutions) under expected future conditions may suffer significantly degraded performance with only modest changes in deeply uncertain hydrologic and economic factors. We then use the Patient Rule Induction Method (PRIM) to identify which uncertain factors drive the individual and collective vulnerabilities for the four cooperating utilities. Our framework identifies key stakeholder dependencies and robustness tradeoffs associated with cooperative regional planning, which are critical to understanding the tensions between individual versus regional water supply goals. Cooperative demand management was found to be the key factor controlling the robustness of regional water supply planning, dominating other hydroclimatic and economic uncertainties through the 2025 planning horizon. Results suggest that a modest reduction in the projected rate of demand growth (from approximately 3% per year to 2.4%) will substantially improve the utilities' robustness to future uncertainty and reduce the potential for regional tensions. The proposed multistakeholder MORDM framework offers critical insights into the risks and challenges posed by rising water demands and hydrological uncertainties, providing a planning template for regions now forced to confront rapidly evolving water scarcity risks.
Evolution of Bow-Tie Architectures in Biology
Friedlander, Tamar; Mayo, Avraham E.; Tlusty, Tsvi; Alon, Uri
2015-01-01
Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. PMID:25798588
Control design for robust stability in linear regulators: Application to aerospace flight control
NASA Technical Reports Server (NTRS)
Yedavalli, R. K.
1986-01-01
Time domain stability robustness analysis and design for linear multivariable uncertain systems with bounded uncertainties is the central theme of the research. After reviewing the recently developed upper bounds on the linear elemental (structured), time varying perturbation of an asymptotically stable linear time invariant regulator, it is shown that it is possible to further improve these bounds by employing state transformations. Then introducing a quantitative measure called the stability robustness index, a state feedback conrol design algorithm is presented for a general linear regulator problem and then specialized to the case of modal systems as well as matched systems. The extension of the algorithm to stochastic systems with Kalman filter as the state estimator is presented. Finally an algorithm for robust dynamic compensator design is presented using Parameter Optimization (PO) procedure. Applications in a aircraft control and flexible structure control are presented along with a comparison with other existing methods.
Liu, Mengying; Sun, Peihua
2014-01-01
A typical model of hypersonic vehicle has the complicated dynamics such as the unstable states, the nonminimum phases, and the strong coupling input-output relations. As a result, designing a robust stabilization controller is essential to implement the anticipated tasks. This paper presents a robust stabilization controller based on the guardian maps theory for hypersonic vehicle. First, the guardian maps theories are provided to explain the constraint relations between the open subsets of complex plane and the eigenvalues of the state matrix of closed-loop control system. Then, a general control structure in relation to the guardian maps theories is proposed to achieve the respected design demands. Furthermore, the robust stabilization control law depending on the given general control structure is designed for the longitudinal model of hypersonic vehicle. Finally, a simulation example is provided to verify the effectiveness of the proposed methods. PMID:24795535
Liu, Yanbin; Liu, Mengying; Sun, Peihua
2014-01-01
A typical model of hypersonic vehicle has the complicated dynamics such as the unstable states, the nonminimum phases, and the strong coupling input-output relations. As a result, designing a robust stabilization controller is essential to implement the anticipated tasks. This paper presents a robust stabilization controller based on the guardian maps theory for hypersonic vehicle. First, the guardian maps theories are provided to explain the constraint relations between the open subsets of complex plane and the eigenvalues of the state matrix of closed-loop control system. Then, a general control structure in relation to the guardian maps theories is proposed to achieve the respected design demands. Furthermore, the robust stabilization control law depending on the given general control structure is designed for the longitudinal model of hypersonic vehicle. Finally, a simulation example is provided to verify the effectiveness of the proposed methods.
Robust Fixed-Structure Controller Synthesis
NASA Technical Reports Server (NTRS)
Corrado, Joseph R.; Haddad, Wassim M.; Gupta, Kajal (Technical Monitor)
2000-01-01
The ability to develop an integrated control system design methodology for robust high performance controllers satisfying multiple design criteria and real world hardware constraints constitutes a challenging task. The increasingly stringent performance specifications required for controlling such systems necessitates a trade-off between controller complexity and robustness. The principle challenge of the minimal complexity robust control design is to arrive at a tractable control design formulation in spite of the extreme complexity of such systems. Hence, design of minimal complexitY robust controllers for systems in the face of modeling errors has been a major preoccupation of system and control theorists and practitioners for the past several decades.
ACOSS Six (Active Control of Space Structures)
1981-10-01
modes, specially useful simpler conditions for ensuring closed-loop asymptotic stability are also derived. In addition, conditions for robustness of...in this initial study of FOCL stability and robustness . Such a condition is strong but not unreasonable nor unrealistic. Many useful simple in- sights...smallest possible feedback gains) and many interesting numerical results on closed-loop stability and robustness of the modal-dashpot designs. The
Wall-pressure fluctuations beneath a spatially evolving turbulent boundary layer
NASA Astrophysics Data System (ADS)
Mahesh, Krishnan; Kumar, Praveen
2016-11-01
Wall-pressure fluctuations beneath a turbulent boundary layer are important in applications dealing with structural deformation and acoustics. Simulations are performed for flat plate and axisymmetric, spatially evolving zero-pressure-gradient turbulent boundary layers at inflow Reynolds number of 1400 and 2200 based on momentum thickness. The simulations generate their own inflow using the recycle-rescale method. The results for mean velocity and second-order statistics show excellent agreement with the data available in literature. The spectral characteristics of wall-pressure fluctuations and their relation to flow structure will be discussed. This work is supported by ONR.
Robust estimation approach for blind denoising.
Rabie, Tamer
2005-11-01
This work develops a new robust statistical framework for blind image denoising. Robust statistics addresses the problem of estimation when the idealized assumptions about a system are occasionally violated. The contaminating noise in an image is considered as a violation of the assumption of spatial coherence of the image intensities and is treated as an outlier random variable. A denoised image is estimated by fitting a spatially coherent stationary image model to the available noisy data using a robust estimator-based regression method within an optimal-size adaptive window. The robust formulation aims at eliminating the noise outliers while preserving the edge structures in the restored image. Several examples demonstrating the effectiveness of this robust denoising technique are reported and a comparison with other standard denoising filters is presented.
Collapse of cooperation in evolving games
Stewart, Alexander J.; Plotkin, Joshua B.
2014-01-01
Game theory provides a quantitative framework for analyzing the behavior of rational agents. The Iterated Prisoner’s Dilemma in particular has become a standard model for studying cooperation and cheating, with cooperation often emerging as a robust outcome in evolving populations. Here we extend evolutionary game theory by allowing players’ payoffs as well as their strategies to evolve in response to selection on heritable mutations. In nature, many organisms engage in mutually beneficial interactions and individuals may seek to change the ratio of risk to reward for cooperation by altering the resources they commit to cooperative interactions. To study this, we construct a general framework for the coevolution of strategies and payoffs in arbitrary iterated games. We show that, when there is a tradeoff between the benefits and costs of cooperation, coevolution often leads to a dramatic loss of cooperation in the Iterated Prisoner’s Dilemma. The collapse of cooperation is so extreme that the average payoff in a population can decline even as the potential reward for mutual cooperation increases. Depending upon the form of tradeoffs, evolution may even move away from the Iterated Prisoner’s Dilemma game altogether. Our work offers a new perspective on the Prisoner’s Dilemma and its predictions for cooperation in natural populations; and it provides a general framework to understand the coevolution of strategies and payoffs in iterated interactions. PMID:25422421
Clear: Composition of Likelihoods for Evolve and Resequence Experiments.
Iranmehr, Arya; Akbari, Ali; Schlötterer, Christian; Bafna, Vineet
2017-06-01
The advent of next generation sequencing technologies has made whole-genome and whole-population sampling possible, even for eukaryotes with large genomes. With this development, experimental evolution studies can be designed to observe molecular evolution "in action" via evolve-and-resequence (E&R) experiments. Among other applications, E&R studies can be used to locate the genes and variants responsible for genetic adaptation. Most existing literature on time-series data analysis often assumes large population size, accurate allele frequency estimates, or wide time spans. These assumptions do not hold in many E&R studies. In this article, we propose a method-composition of likelihoods for evolve-and-resequence experiments (Clear)-to identify signatures of selection in small population E&R experiments. Clear takes whole-genome sequences of pools of individuals as input, and properly addresses heterogeneous ascertainment bias resulting from uneven coverage. Clear also provides unbiased estimates of model parameters, including population size, selection strength, and dominance, while being computationally efficient. Extensive simulations show that Clear achieves higher power in detecting and localizing selection over a wide range of parameters, and is robust to variation of coverage. We applied the Clear statistic to multiple E&R experiments, including data from a study of adaptation of Drosophila melanogaster to alternating temperatures and a study of outcrossing yeast populations, and identified multiple regions under selection with genome-wide significance. Copyright © 2017 by the Genetics Society of America.
Sauterey, Boris; Ward, Ben A.; Follows, Michael J.; Bowler, Chris; Claessen, David
2015-01-01
The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that “Everything is everywhere, but the environment selects”, we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean. PMID:25852217
Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David
2015-01-01
The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.
Evolution of the Division of Labor between Genes and Enzymes in the RNA World
Boza, Gergely; Szilágyi, András; Kun, Ádám; Santos, Mauro; Szathmáry, Eörs
2014-01-01
The RNA world is a very likely interim stage of the evolution after the first replicators and before the advent of the genetic code and translated proteins. Ribozymes are known to be able to catalyze many reaction types, including cofactor-aided metabolic transformations. In a metabolically complex RNA world, early division of labor between genes and enzymes could have evolved, where the ribozymes would have been transcribed from the genes more often than the other way round, benefiting the encapsulating cells through this dosage effect. Here we show, by computer simulations of protocells harboring unlinked RNA replicators, that the origin of replicational asymmetry producing more ribozymes from a gene template than gene strands from a ribozyme template is feasible and robust. Enzymatic activities of the two modeled ribozymes are in trade-off with their replication rates, and the relative replication rates compared to those of complementary strands are evolvable traits of the ribozymes. The degree of trade-off is shown to have the strongest effect in favor of the division of labor. Although some asymmetry between gene and enzymatic strands could have evolved even in earlier, surface-bound systems, the shown mechanism in protocells seems inevitable and under strong positive selection. This could have preadapted the genetic system for transcription after the subsequent origin of chromosomes and DNA. PMID:25474573
Evolution of the division of labor between genes and enzymes in the RNA world.
Boza, Gergely; Szilágyi, András; Kun, Ádám; Santos, Mauro; Szathmáry, Eörs
2014-12-01
The RNA world is a very likely interim stage of the evolution after the first replicators and before the advent of the genetic code and translated proteins. Ribozymes are known to be able to catalyze many reaction types, including cofactor-aided metabolic transformations. In a metabolically complex RNA world, early division of labor between genes and enzymes could have evolved, where the ribozymes would have been transcribed from the genes more often than the other way round, benefiting the encapsulating cells through this dosage effect. Here we show, by computer simulations of protocells harboring unlinked RNA replicators, that the origin of replicational asymmetry producing more ribozymes from a gene template than gene strands from a ribozyme template is feasible and robust. Enzymatic activities of the two modeled ribozymes are in trade-off with their replication rates, and the relative replication rates compared to those of complementary strands are evolvable traits of the ribozymes. The degree of trade-off is shown to have the strongest effect in favor of the division of labor. Although some asymmetry between gene and enzymatic strands could have evolved even in earlier, surface-bound systems, the shown mechanism in protocells seems inevitable and under strong positive selection. This could have preadapted the genetic system for transcription after the subsequent origin of chromosomes and DNA.
Winkler, James D; Garcia, Carlos; Olson, Michelle; Callaway, Emily; Kao, Katy C
2014-06-01
Biocatalyst robustness toward stresses imposed during fermentation is important for efficient bio-based production. Osmotic stress, imposed by high osmolyte concentrations or dense populations, can significantly impact growth and productivity. In order to better understand the osmotic stress tolerance phenotype, we evolved sexual (capable of in situ DNA exchange) and asexual Escherichia coli strains under sodium chloride (NaCl) stress. All isolates had significantly improved growth under selection and could grow in up to 0.80 M (47 g/liter) NaCl, a concentration that completely inhibits the growth of the unevolved parental strains. Whole genome resequencing revealed frequent mutations in genes controlling N-acetylglucosamine catabolism (nagC, nagA), cell shape (mrdA, mreB), osmoprotectant uptake (proV), and motility (fimA). Possible epistatic interactions between nagC, nagA, fimA, and proV deletions were also detected when reconstructed as defined mutations. Biofilm formation under osmotic stress was found to be decreased in most mutant isolates, coupled with perturbations in indole secretion. Transcriptional analysis also revealed significant changes in ompACGL porin expression and increased transcription of sulfonate uptake systems in the evolved mutants. These findings expand our current knowledge of the osmotic stress phenotype and will be useful for the rational engineering of osmotic tolerance into industrial strains in the future. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
The role of the hospital in a changing environment.
McKee, M.; Healy, J.
2000-01-01
Hospitals pose many challenges to those undertaking reform of health care systems. This paper examines the evolving role of the hospital within the health care system in industrialized countries and explores the evidence on which policy-makers might base their decisions. It begins by tracing the evolving concept of the hospital, concluding that hospitals must continue to evolve in response to factors such as changing health care needs and emerging technologies. The size and distribution of hospitals are matters for ongoing debate. This paper concludes that evidence in favour of concentrating hospital facilities, whether as a means of enhancing effectiveness or efficiency, is less robust than is often assumed. Noting that care provided in hospitals is often less than satisfactory, this paper summarizes the evidence underlying three reform strategies: (i) behavioural interventions such as quality assurance programmes; (ii) changing organizational culture; and (iii) the use of financial incentives. Isolated behavioural interventions have a limited impact, but are more effective when combined. Financial incentives are blunt instruments that must be monitored. Organizational culture, which has previously received relatively little attention, appears to be an important determinant of quality of care and is threatened by ill-considered policies intended to 're-engineer' hospital services. Overall, evidence on the effectiveness of policies relating to hospitals is limited and this paper indicates where such evidence can be found. PMID:10916917
Organizational Structure at the Crossroads.
ERIC Educational Resources Information Center
Person, Ruth
1994-01-01
Because colleges and universities have adopted new information technology idiosyncratically, formal structures to manage and govern its use have not evolved at the same pace. In creating such structures, issues to be considered include centralization vs. decentralization, attitudes toward change, institutional diversity, entrepreneurial spirit,…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Yonggang; Wen, Ting; Park, Changyong
2016-01-14
The structure stability under high pressure and thermal expansion behavior of Na 3OBr and Na 4OI 2, two prototypes of alkali-metal-rich antiperovskites, were investigated by in situ synchrotron X-ray diffraction techniques under high pressure and low temp. Both are soft materials with bulk modulus of 58.6 GPa and 52.0 GPa for Na 3OBr and Na 4OI 2, resp. The cubic Na 3OBr structure and tetragonal Na 4OI 2 with intergrowth K 2NiF 4 structure are stable under high pressure up to 23 GPa. Although being a characteristic layered structure, Na 4OI 2 exhibits nearly isotropic compressibility. Neg. thermal expansion wasmore » obsd. at low temp. range (20-80 K) in both transition-metal-free antiperovskites for the first time. The robust high pressure structure stability was examined. and confirmed by first-principles calculations. among various possible polymorphisms qualitatively. The results provide in-depth understanding of the neg. thermal expansion and robust crystal structure stability of these antiperovskite systems and their potential applications.« less
On actuator placement for robust time-optimal control of uncertain flexible spacecraft
NASA Technical Reports Server (NTRS)
Wie, Bong; Sinha, Ravi; Liu, Qiang
1992-01-01
The problem of computing open-loop, on-off jet firing logic for flexible spacecraft in the face of plant modeling uncertainty is investigated. The primary control objective is to achieve a fast maneuvering time with a minimum of structural vibrations during and/or after a maneuver. This paper is also concerned with the problem of selecting a proper pair of jets for practical trade-offs among the maneuvering time, fuel consumption, structural mode excitation, and performance robustness. A time-optimal control problem subject to parameter robustness constraints is formulated. A three-mass-spring model of flexible spacecraft with a rigid-body mode and two flexible modes is used to illustrate the concept.
The application of a shift theorem analysis technique to multipoint measurements
NASA Astrophysics Data System (ADS)
Dieckmann, M. E.; Chapman, S. C.
1999-03-01
A Fourier domain technique has been proposed previously which, in principle, quantifies the extent to which multipoint in-situ measurements can identify whether or not an observed structure is time stationary in its rest frame. Once a structure, sampled for example by four spacecraft, is shown to be quasi-stationary in its rest frame, the structure's velocity vector can be determined with respect to the sampling spacecraft. We investigate the properties of this technique, which we will refer to as a stationarity test, by applying it to two point measurements of a simulated boundary layer. The boundary layer was evolved using a PIC (particle in cell) electromagnetic code. Initial and boundary conditions were chosen such, that two cases could be considered, i.e. a spacecraft pair moving through (1) a time stationary boundary structure and (2) a boundary structure which is evolving (expanding) in time. The code also introduces noise in the simulated data time series which is uncorrelated between the two spacecraft. We demonstrate that, provided that the time series is Hanning windowed, the test is effective in determining the relative velocity between the boundary layer and spacecraft and in determining the range of frequencies over which the data can be treated as time stationary or time evolving. This work presents a first step towards understanding the effectiveness of this technique, as required in order for it to be applied to multispacecraft data.
NASA Astrophysics Data System (ADS)
Geng, Lin; Bi, Chuan-Xing; Xie, Feng; Zhang, Xiao-Zheng
2018-07-01
Interpolated time-domain equivalent source method is extended to reconstruct the instantaneous surface normal velocity of a vibrating structure by using the time-evolving particle velocity as the input, which provides a non-contact way to overall understand the instantaneous vibration behavior of the structure. In this method, the time-evolving particle velocity in the near field is first modeled by a set of equivalent sources positioned inside the vibrating structure, and then the integrals of equivalent source strengths are solved by an iterative solving process and are further used to calculate the instantaneous surface normal velocity. An experiment of a semi-cylindrical steel plate impacted by a steel ball is investigated to examine the ability of the extended method, where the time-evolving normal particle velocity and pressure on the hologram surface measured by a Microflown pressure-velocity probe are used as the inputs of the extended method and the method based on pressure measurements, respectively, and the instantaneous surface normal velocity of the plate measured by a laser Doppler vibrometry is used as the reference for comparison. The experimental results demonstrate that the extended method is a powerful tool to visualize the instantaneous surface normal velocity of a vibrating structure in both time and space domains and can obtain more accurate results than that of the method based on pressure measurements.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Hannigan, Geoffrey D.; Duhaime, Melissa B.; Koutra, Danai
2018-01-01
Viruses and bacteria are critical components of the human microbiome and play important roles in health and disease. Most previous work has relied on studying bacteria and viruses independently, thereby reducing them to two separate communities. Such approaches are unable to capture how these microbial communities interact, such as through processes that maintain community robustness or allow phage-host populations to co-evolve. We implemented a network-based analytical approach to describe phage-bacteria network diversity throughout the human body. We built these community networks using a machine learning algorithm to predict which phages could infect which bacteria in a given microbiome. Our algorithm was applied to paired viral and bacterial metagenomic sequence sets from three previously published human cohorts. We organized the predicted interactions into networks that allowed us to evaluate phage-bacteria connectedness across the human body. We observed evidence that gut and skin network structures were person-specific and not conserved among cohabitating family members. High-fat diets appeared to be associated with less connected networks. Network structure differed between skin sites, with those exposed to the external environment being less connected and likely more susceptible to network degradation by microbial extinction events. This study quantified and contrasted the diversity of virome-microbiome networks across the human body and illustrated how environmental factors may influence phage-bacteria interactive dynamics. This work provides a baseline for future studies to better understand system perturbations, such as disease states, through ecological networks. PMID:29668682
[Urban Health (StadtGesundheit): The Wider Perspective Exemplified by the City State of Hamburg].
Fehr, R; Fertmann, R; Stender, K-P; Lettau, N; Trojan, A
2016-09-01
Public health and city planning have common roots, and in many places they are now reuniting under the heading of urban health. To organize this field adequately requires a broad, integrative view of medical care, health promotion, and health in all urban policies. Given current crises and developments including climate change and globalization, such a wider perspective should also be useful for Germany. Using the City State of Hamburg as an example and combining historic and systematic approaches, we explore the preconditions for in-depth analyses. Our results show that health is a significant topic of Hamburg urban policy, featuring a broad range of structures, processes and actors, both within the health sector and far beyond. Health promotion over the last 30 years evolved notably from a niche topic into an established field with remarkable cooperative structures. The tradition of comprehensive reporting on urban health in Hamburg that was initiated more than 200 years ago is no longer alive today. However, local health reporting keeps integrating a wide range of diverse topics. Communication among the Hamburg health actors - beyond straightforward medical quality assurance - does not seem to focus on critical evaluations, e. g. concerning social and ecologic sustainability. A prerequisite for in-depth analyses including external comparisons is to secure permanent access to relevant sources. Robust approaches to this end, however, seem to be lacking. © Georg Thieme Verlag KG Stuttgart · New York.
Patchy particles made by colloidal fusion
NASA Astrophysics Data System (ADS)
Gong, Zhe; Hueckel, Theodore; Yi, Gi-Ra; Sacanna, Stefano
2017-10-01
Patches on the surfaces of colloidal particles provide directional information that enables the self-assembly of the particles into higher-order structures. Although computational tools can make quantitative predictions and can generate design rules that link the patch motif of a particle to its internal microstructure and to the emergent properties of the self-assembled materials, the experimental realization of model systems of particles with surface patches (or `patchy' particles) remains a challenge. Synthetic patchy colloidal particles are often poor geometric approximations of the digital building blocks used in simulations and can only rarely be manufactured in sufficiently high yields to be routinely used as experimental model systems. Here we introduce a method, which we refer to as colloidal fusion, for fabricating functional patchy particles in a tunable and scalable manner. Using coordination dynamics and wetting forces, we engineer hybrid liquid-solid clusters that evolve into particles with a range of patchy surface morphologies on addition of a plasticizer. We are able to predict and control the evolutionary pathway by considering surface-energy minimization, leading to two main branches of product: first, spherical particles with liquid surface patches, capable of forming curable bonds with neighbouring particles to assemble robust supracolloidal structures; and second, particles with a faceted liquid compartment, which can be cured and purified to yield colloidal polyhedra. These findings outline a scalable strategy for the synthesis of patchy particles, first by designing their surface patterns by computer simulation, and then by recreating them in the laboratory with high fidelity.
Hannigan, Geoffrey D; Duhaime, Melissa B; Koutra, Danai; Schloss, Patrick D
2018-04-01
Viruses and bacteria are critical components of the human microbiome and play important roles in health and disease. Most previous work has relied on studying bacteria and viruses independently, thereby reducing them to two separate communities. Such approaches are unable to capture how these microbial communities interact, such as through processes that maintain community robustness or allow phage-host populations to co-evolve. We implemented a network-based analytical approach to describe phage-bacteria network diversity throughout the human body. We built these community networks using a machine learning algorithm to predict which phages could infect which bacteria in a given microbiome. Our algorithm was applied to paired viral and bacterial metagenomic sequence sets from three previously published human cohorts. We organized the predicted interactions into networks that allowed us to evaluate phage-bacteria connectedness across the human body. We observed evidence that gut and skin network structures were person-specific and not conserved among cohabitating family members. High-fat diets appeared to be associated with less connected networks. Network structure differed between skin sites, with those exposed to the external environment being less connected and likely more susceptible to network degradation by microbial extinction events. This study quantified and contrasted the diversity of virome-microbiome networks across the human body and illustrated how environmental factors may influence phage-bacteria interactive dynamics. This work provides a baseline for future studies to better understand system perturbations, such as disease states, through ecological networks.
Mallik, Saurav; Basu, Sudipto; Hait, Suman; Kundu, Sudip
2018-04-21
Do coding and regulatory segments of a gene co-evolve with each-other? Seeking answers to this question, here we analyze the case of Escherichia coli ribosomal protein S15, that represses its own translation by specifically binding its messenger RNA (rpsO mRNA) and stabilizing a pseudoknot structure at the upstream untranslated region, thus trapping the ribosome into an incomplete translation initiation complex. In the absence of S15, ribosomal protein S1 recognizes rpsO and promotes translation by melting this very pseudoknot. We employ a robust statistical method to detect signatures of positive epistasis between residue site pairs and find that biophysical constraints of translational regulation (S15-rpsO and S1-rpsO recognition, S15-mediated rpsO structural rearrangement, and S1-mediated melting) are strong predictors of positive epistasis. Transforming the epistatic pairs into a network, we find that signatures of two different, but interconnected regulatory cascades are imprinted in the sequence-space and can be captured in terms of two dense network modules that are sparsely connected to each other. This network topology further reflects a general principle of how functionally coupled components of biological networks are interconnected. These results depict a model case, where translational regulation drives characteristic residue-level epistasis-not only between a protein and its own mRNA but also between a protein and the mRNA of an entirely different protein. © 2018 Wiley Periodicals, Inc.
ERIC Educational Resources Information Center
Soderberg, Patti; Price, Frank
2003-01-01
Examines a lesson in which students are engaged in inquiry in evolutionary biology to develop better understanding of concepts and reasoning skills necessary to support knowledge claims about changes in the genetic structure of populations known as microevolution. Explains how a software simulation, EVOLVE, can be used to foster discussions about…
Catalytic Oxygen Evolution by a Bioinorganic Model of the Photosystem II Oxygen-Evolving Complex
ERIC Educational Resources Information Center
Howard, Derrick L.; Tinoco, Arthur D.; Brudvig, Gary W.; Vrettos, John S.; Allen, Bertha Connie
2005-01-01
Bioinorganic models of the manganese Mn4 cluster are important not only as aids in understanding the structure and function of the oxygen-evolving complex (OEC), but also in developing artificial water-oxidation catalysts. The mechanism of water oxidation by photosystem II (PSII) is thought to involve the formation of a high-valent terminal Mn-oxo…
A Design Tool for Robust Composite Structures
2010-06-01
a a UNIVERSITY OF ^?CAiVI BRIDGE FINAL REPORT A Design Tool for Robust Composite Structures Frank Zok Materials Department University of ...organic fibers, especially Dyneema®. The principal objectives of the present study were to ascertain the fundamental mechanical properties of Dyneema...composites increases by a factor of 2 and the ductility by almost a factor of 3 over the strain rate range 10-3 s-1 to 104 s- 1. One consequence is
Keshavan, J; Gremillion, G; Escobar-Alvarez, H; Humbert, J S
2014-06-01
Safe, autonomous navigation by aerial microsystems in less-structured environments is a difficult challenge to overcome with current technology. This paper presents a novel visual-navigation approach that combines bioinspired wide-field processing of optic flow information with control-theoretic tools for synthesis of closed loop systems, resulting in robustness and performance guarantees. Structured singular value analysis is used to synthesize a dynamic controller that provides good tracking performance in uncertain environments without resorting to explicit pose estimation or extraction of a detailed environmental depth map. Experimental results with a quadrotor demonstrate the vehicle's robust obstacle-avoidance behaviour in a straight line corridor, an S-shaped corridor and a corridor with obstacles distributed in the vehicle's path. The computational efficiency and simplicity of the current approach offers a promising alternative to satisfying the payload, power and bandwidth constraints imposed by aerial microsystems.
Molecular engineering of chiral colloidal liquid crystals using DNA origami
NASA Astrophysics Data System (ADS)
Siavashpouri, Mahsa; Wachauf, Christian H.; Zakhary, Mark J.; Praetorius, Florian; Dietz, Hendrik; Dogic, Zvonimir
2017-08-01
Establishing precise control over the shape and the interactions of the microscopic building blocks is essential for design of macroscopic soft materials with novel structural, optical and mechanical properties. Here, we demonstrate robust assembly of DNA origami filaments into cholesteric liquid crystals, one-dimensional supramolecular twisted ribbons and two-dimensional colloidal membranes. The exquisite control afforded by the DNA origami technology establishes a quantitative relationship between the microscopic filament structure and the macroscopic cholesteric pitch. Furthermore, it also enables robust assembly of one-dimensional twisted ribbons, which behave as effective supramolecular polymers whose structure and elastic properties can be precisely tuned by controlling the geometry of the elemental building blocks. Our results demonstrate the potential synergy between DNA origami technology and colloidal science, in which the former allows for rapid and robust synthesis of complex particles, and the latter can be used to assemble such particles into bulk materials.
Molecular engineering of chiral colloidal liquid crystals using DNA origami.
Siavashpouri, Mahsa; Wachauf, Christian H; Zakhary, Mark J; Praetorius, Florian; Dietz, Hendrik; Dogic, Zvonimir
2017-08-01
Establishing precise control over the shape and the interactions of the microscopic building blocks is essential for design of macroscopic soft materials with novel structural, optical and mechanical properties. Here, we demonstrate robust assembly of DNA origami filaments into cholesteric liquid crystals, one-dimensional supramolecular twisted ribbons and two-dimensional colloidal membranes. The exquisite control afforded by the DNA origami technology establishes a quantitative relationship between the microscopic filament structure and the macroscopic cholesteric pitch. Furthermore, it also enables robust assembly of one-dimensional twisted ribbons, which behave as effective supramolecular polymers whose structure and elastic properties can be precisely tuned by controlling the geometry of the elemental building blocks. Our results demonstrate the potential synergy between DNA origami technology and colloidal science, in which the former allows for rapid and robust synthesis of complex particles, and the latter can be used to assemble such particles into bulk materials.
Robust fixed order dynamic compensation for large space structure control
NASA Technical Reports Server (NTRS)
Calise, Anthony J.; Byrns, Edward V., Jr.
1989-01-01
A simple formulation for designing fixed order dynamic compensators which are robust to both uncertainty at the plant input and structured uncertainty in the plant dynamics is presented. The emphasis is on designing low order compensators for systems of high order. The formulation is done in an output feedback setting which exploits an observer canonical form to represent the compensator dynamics. The formulation also precludes the use of direct feedback of the plant output. The main contribution lies in defining a method for penalizing the states of the plant and of the compensator, and for choosing the distribution on initial conditions so that the loop transfer matrix approximates that of a full state design. To improve robustness to parameter uncertainty, the formulation avoids the introduction of sensitivity states, which has led to complex formulations in earlier studies where only structured uncertainty has been considered.
Martínez, Leandro
2015-01-01
The analysis of structural mobility in molecular dynamics plays a key role in data interpretation, particularly in the simulation of biomolecules. The most common mobility measures computed from simulations are the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuations (RMSF) of the structures. These are computed after the alignment of atomic coordinates in each trajectory step to a reference structure. This rigid-body alignment is not robust, in the sense that if a small portion of the structure is highly mobile, the RMSD and RMSF increase for all atoms, resulting possibly in poor quantification of the structural fluctuations and, often, to overlooking important fluctuations associated to biological function. The motivation of this work is to provide a robust measure of structural mobility that is practical, and easy to interpret. We propose a Low-Order-Value-Optimization (LOVO) strategy for the robust alignment of the least mobile substructures in a simulation. These substructures are automatically identified by the method. The algorithm consists of the iterative superposition of the fraction of structure displaying the smallest displacements. Therefore, the least mobile substructures are identified, providing a clearer picture of the overall structural fluctuations. Examples are given to illustrate the interpretative advantages of this strategy. The software for performing the alignments was named MDLovoFit and it is available as free-software at: http://leandro.iqm.unicamp.br/mdlovofit.
Martínez, Leandro
2015-01-01
The analysis of structural mobility in molecular dynamics plays a key role in data interpretation, particularly in the simulation of biomolecules. The most common mobility measures computed from simulations are the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuations (RMSF) of the structures. These are computed after the alignment of atomic coordinates in each trajectory step to a reference structure. This rigid-body alignment is not robust, in the sense that if a small portion of the structure is highly mobile, the RMSD and RMSF increase for all atoms, resulting possibly in poor quantification of the structural fluctuations and, often, to overlooking important fluctuations associated to biological function. The motivation of this work is to provide a robust measure of structural mobility that is practical, and easy to interpret. We propose a Low-Order-Value-Optimization (LOVO) strategy for the robust alignment of the least mobile substructures in a simulation. These substructures are automatically identified by the method. The algorithm consists of the iterative superposition of the fraction of structure displaying the smallest displacements. Therefore, the least mobile substructures are identified, providing a clearer picture of the overall structural fluctuations. Examples are given to illustrate the interpretative advantages of this strategy. The software for performing the alignments was named MDLovoFit and it is available as free-software at: http://leandro.iqm.unicamp.br/mdlovofit PMID:25816325
Glowacka, Halszka; McFarlin, Shannon C; Vogel, Erin R; Stoinski, Tara S; Ndagijimana, Felix; Tuyisingize, Deo; Mudakikwa, Antoine; Schwartz, Gary T
2017-08-01
The robust masticatory system of mountain gorillas is thought to have evolved for the comminution of tough vegetation, yet, compared to other primates, the toughness of the mountain gorilla diet is unremarkable. This may be a result of low plant toughness in the mountain gorilla environment or of mountain gorillas feeding selectively on low-toughness foods. The goal of this paper is to determine how the toughness of the mountain gorilla diet varies across their habitat, which spans a large altitudinal range, and whether there is a relationship between toughness and food selection by mountain gorillas. We collected data on the following variables to determine whether, and if so how, they change with altitude: leaf toughness of two plant species consumed by mountain gorillas, at every 100 m increase in altitude (2,600-3,700 m); toughness of consumed foods comprising over 85% of the gorilla diet across five vegetation zones; and toughness of unconsumed/infrequently consumed plant parts of those foods. Although leaf toughness increased with altitude, the toughness of the gorilla diet remained similar. There was a negative relationship between toughness and consumption frequency, and toughness was a better predictor of consumption frequency than plant frequency, biomass, and density. Consumed plant parts were less tough than unconsumed/infrequently consumed parts and toughness of the latter increased with altitude. Although it is unclear whether gorillas select food based on toughness or use toughness as a sensory cue to impart other plant properties (e.g., macronutrients, chemicals), our results that gorillas maintain a consistent low-toughness dietary profile across altitude, despite toughness increasing with altitude, suggest that the robust gorilla masticatory apparatus evolved for repetitive mastication of foods that are not high in toughness. © 2017 Wiley Periodicals, Inc.
Saiag, Esther
2005-01-01
In many developed countries, a coordinated effort is underway to build national and regional Health Information Infrastructures (HII) for the linking of disparate sites of care, so that an access to a comprehensive Health Record will be feasible when critical medical decisions are made [1]. However, widespread adoption of such national projects is hindered by a series of barriers- regulatory, technical, financial and cultural. Above all, a robust national HII requires a firm foundation of trust: patients must be assured that their confidential health information will not be misused and that there are adequate legal remedies in the event of inappropriate behavior on the part of either authorized or unauthorized parties[2].The Israeli evolving National HII is an innovative state of the art implementation of a wide-range clinical inter-organizational data exchange, based on a unique concept of virtually temporary sharing of information. A logically connection of multiple caregivers and medical organizations creates a patient-centric virtual repository, without centralization. All information remains in its original format, location, system and ownership. On demand, relevant information is instantly integrated and delivered to the point of care. This system, successfully covering more than half of Israel's population, is currently evolving from a voluntary private-public partnership (dbMOTION and CLALIT HMO) to a formal national reality. The governmental leadership, now taking over the process, is essential to achieve a full potential of the health information technology. All partners of the Israeli health system are coordinated in concert with each other, driven with a shared vision - realizing that a secured, private, confidential health information exchange is assured.
Urich, Christian; Rauch, Wolfgang
2014-12-01
Long-term projections for key drivers needed in urban water infrastructure planning such as climate change, population growth, and socio-economic changes are deeply uncertain. Traditional planning approaches heavily rely on these projections, which, if a projection stays unfulfilled, can lead to problematic infrastructure decisions causing high operational costs and/or lock-in effects. New approaches based on exploratory modelling take a fundamentally different view. Aim of these is, to identify an adaptation strategy that performs well under many future scenarios, instead of optimising a strategy for a handful. However, a modelling tool to support strategic planning to test the implication of adaptation strategies under deeply uncertain conditions for urban water management does not exist yet. This paper presents a first step towards a new generation of such strategic planning tools, by combing innovative modelling tools, which coevolve the urban environment and urban water infrastructure under many different future scenarios, with robust decision making. The developed approach is applied to the city of Innsbruck, Austria, which is spatially explicitly evolved 20 years into the future under 1000 scenarios to test the robustness of different adaptation strategies. Key findings of this paper show that: (1) Such an approach can be used to successfully identify parameter ranges of key drivers in which a desired performance criterion is not fulfilled, which is an important indicator for the robustness of an adaptation strategy; and (2) Analysis of the rich dataset gives new insights into the adaptive responses of agents to key drivers in the urban system by modifying a strategy. Copyright © 2014 Elsevier Ltd. All rights reserved.
Decentralized robust nonlinear model predictive controller for unmanned aerial systems
NASA Astrophysics Data System (ADS)
Garcia Garreton, Gonzalo A.
The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1. A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2. A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3. An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4. A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible.
Designing Flood Management Systems for Joint Economic and Ecological Robustness
NASA Astrophysics Data System (ADS)
Spence, C. M.; Grantham, T.; Brown, C. M.; Poff, N. L.
2015-12-01
Freshwater ecosystems across the United States are threatened by hydrologic change caused by water management operations and non-stationary climate trends. Nonstationary hydrology also threatens flood management systems' performance. Ecosystem managers and flood risk managers need tools to design systems that achieve flood risk reduction objectives while sustaining ecosystem functions and services in an uncertain hydrologic future. Robust optimization is used in water resources engineering to guide system design under climate change uncertainty. Using principles introduced by Eco-Engineering Decision Scaling (EEDS), we extend robust optimization techniques to design flood management systems that meet both economic and ecological goals simultaneously across a broad range of future climate conditions. We use three alternative robustness indices to identify flood risk management solutions that preserve critical ecosystem functions in a case study from the Iowa River, where recent severe flooding has tested the limits of the existing flood management system. We seek design modifications to the system that both reduce expected cost of flood damage while increasing ecologically beneficial inundation of riparian floodplains across a wide range of plausible climate futures. The first robustness index measures robustness as the fraction of potential climate scenarios in which both engineering and ecological performance goals are met, implicitly weighting each climate scenario equally. The second index builds on the first by using climate projections to weight each climate scenario, prioritizing acceptable performance in climate scenarios most consistent with climate projections. The last index measures robustness as mean performance across all climate scenarios, but penalizes scenarios with worse performance than average, rewarding consistency. Results stemming from alternate robustness indices reflect implicit assumptions about attitudes toward risk and reveal the tradeoffs between using structural and non-structural flood management strategies to ensure economic and ecological robustness.
The Evolution of Genome Structure by Natural and Sexual Selection.
Kirkpatrick, Mark
2017-01-01
Progress on understanding how genome structure evolves is accelerating with the arrival of new genomic, comparative, and theoretical approaches. This article reviews progress in understanding how chromosome inversions and sex chromosomes evolve, and how their evolution affects species' ecology. Analyses of clines in inversion frequencies in flies and mosquitoes imply strong local adaptation, and roles for both over- and under dominant selection. Those results are consistent with the hypothesis that inversions become established when they capture locally adapted alleles. Inversions can carry alleles that are beneficial to closely related species, causing them to introgress following hybridization. Models show that this "adaptive cassette" scenario can trigger large range expansions, as recently happened in malaria mosquitoes. Sex chromosomes are the most rapidly evolving genome regions of some taxa. Sexually antagonistic selection may be the key force driving transitions of sex determination between different pairs of chromosomes and between XY and ZW systems. Fusions between sex-chromosomes and autosomes most often involve the Y chromosome, a pattern that can be explained if fusions are mildly deleterious and fix by drift. Sexually antagonistic selection is one of several hypotheses to explain the recent discovery that the sex determination system has strong effects on the adult sex ratios of tetrapods. The emerging view of how genome structure evolves invokes a much richer constellation of forces than was envisioned during the Golden Age of research on Drosophila karyotypes. © The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Ruan, Jujun; Zhang, Chao; Li, Ya; Li, Peiyi; Yang, Zaizhi; Chen, Xiaohong; Huang, Mingzhi; Zhang, Tao
2017-02-01
This work proposes an on-line hybrid intelligent control system based on a genetic algorithm (GA) evolving fuzzy wavelet neural network software sensor to control dissolved oxygen (DO) in an anaerobic/anoxic/oxic process for treating papermaking wastewater. With the self-learning and memory abilities of neural network, handling the uncertainty capacity of fuzzy logic, analyzing local detail superiority of wavelet transform and global search of GA, this proposed control system can extract the dynamic behavior and complex interrelationships between various operation variables. The results indicate that the reasonable forecasting and control performances were achieved with optimal DO, and the effluent quality was stable at and below the desired values in real time. Our proposed hybrid approach proved to be a robust and effective DO control tool, attaining not only adequate effluent quality but also minimizing the demand for energy, and is easily integrated into a global monitoring system for purposes of cost management. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Lagrangian discontinuous Galerkin hydrodynamic method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Xiaodong; Morgan, Nathaniel Ray; Burton, Donald E.
Here, we present a new Lagrangian discontinuous Galerkin (DG) hydrodynamic method for solving the two-dimensional gas dynamic equations on unstructured hybrid meshes. The physical conservation laws for the momentum and total energy are discretized using a DG method based on linear Taylor expansions. Three different approaches are investigated for calculating the density variation over the element. The first approach evolves a Taylor expansion of the specific volume field. The second approach follows certain finite element methods and uses the strong mass conservation to calculate the density field at a location inside the element or on the element surface. The thirdmore » approach evolves a Taylor expansion of the density field. The nodal velocity, and the corresponding forces, are explicitly calculated by solving a multidirectional approximate Riemann problem. An effective limiting strategy is presented that ensures monotonicity of the primitive variables. This new Lagrangian DG hydrodynamic method conserves mass, momentum, and total energy. Results from a suite of test problems are presented to demonstrate the robustness and expected second-order accuracy of this new method.« less
NASA Astrophysics Data System (ADS)
Werkheiser, W. H.
2016-12-01
10 Years of Scientific Integrity Policy at the U.S. Geological Survey The U.S. Geological Survey implemented its first scientific integrity policy in January 2007. Following the 2009 and 2010 executive memoranda aimed at creating scientific integrity policies throughout the federal government, USGS' policy served as a template to inform the U.S. Department of Interior's policy set forth in January 2011. Scientific integrity policy at the USGS and DOI continues to evolve as best practices come to the fore and the broader Federal scientific integrity community evolves in its understanding of a vital and expanding endeavor. We find that scientific integrity is best served by: formal and informal mechanisms through which to resolve scientific integrity issues; a well-communicated and enforceable code of scientific conduct that is accessible to multiple audiences; an unfailing commitment to the code on the part of all parties; awareness through mandatory training; robust protection to encourage whistleblowers to come forward; and outreach with the scientific integrity community to foster consistency and share experiences.
Antibiotic Resistance in Plant-Pathogenic Bacteria.
Sundin, George W; Wang, Nian
2018-06-01
Antibiotics have been used for the management of relatively few bacterial plant diseases and are largely restricted to high-value fruit crops because of the expense involved. Antibiotic resistance in plant-pathogenic bacteria has become a problem in pathosystems where these antibiotics have been used for many years. Where the genetic basis for resistance has been examined, antibiotic resistance in plant pathogens has most often evolved through the acquisition of a resistance determinant via horizontal gene transfer. For example, the strAB streptomycin-resistance genes occur in Erwinia amylovora, Pseudomonas syringae, and Xanthomonas campestris, and these genes have presumably been acquired from nonpathogenic epiphytic bacteria colocated on plant hosts under antibiotic selection. We currently lack knowledge of the effect of the microbiome of commensal organisms on the potential of plant pathogens to evolve antibiotic resistance. Such knowledge is critical to the development of robust resistance management strategies to ensure the safe and effective continued use of antibiotics in the management of critically important diseases. Expected final online publication date for the Annual Review of Phytopathology Volume 56 is August 25, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
A Lagrangian discontinuous Galerkin hydrodynamic method
Liu, Xiaodong; Morgan, Nathaniel Ray; Burton, Donald E.
2017-12-11
Here, we present a new Lagrangian discontinuous Galerkin (DG) hydrodynamic method for solving the two-dimensional gas dynamic equations on unstructured hybrid meshes. The physical conservation laws for the momentum and total energy are discretized using a DG method based on linear Taylor expansions. Three different approaches are investigated for calculating the density variation over the element. The first approach evolves a Taylor expansion of the specific volume field. The second approach follows certain finite element methods and uses the strong mass conservation to calculate the density field at a location inside the element or on the element surface. The thirdmore » approach evolves a Taylor expansion of the density field. The nodal velocity, and the corresponding forces, are explicitly calculated by solving a multidirectional approximate Riemann problem. An effective limiting strategy is presented that ensures monotonicity of the primitive variables. This new Lagrangian DG hydrodynamic method conserves mass, momentum, and total energy. Results from a suite of test problems are presented to demonstrate the robustness and expected second-order accuracy of this new method.« less
NASA Astrophysics Data System (ADS)
Werkheiser, W. H.
2017-12-01
10 Years of Scientific Integrity Policy at the U.S. Geological Survey The U.S. Geological Survey implemented its first scientific integrity policy in January 2007. Following the 2009 and 2010 executive memoranda aimed at creating scientific integrity policies throughout the federal government, USGS' policy served as a template to inform the U.S. Department of Interior's policy set forth in January 2011. Scientific integrity policy at the USGS and DOI continues to evolve as best practices come to the fore and the broader Federal scientific integrity community evolves in its understanding of a vital and expanding endeavor. We find that scientific integrity is best served by: formal and informal mechanisms through which to resolve scientific integrity issues; a well-communicated and enforceable code of scientific conduct that is accessible to multiple audiences; an unfailing commitment to the code on the part of all parties; awareness through mandatory training; robust protection to encourage whistleblowers to come forward; and outreach with the scientific integrity community to foster consistency and share experiences.
NASA Astrophysics Data System (ADS)
Tanimoto, Jun; Sagara, Hirokji
2015-11-01
We built a new indirect reciprocity model based on binary image scores, where an agent's strategy and norm co-evolve. The norm, meaning what behavior is evaluated as "good" or "bad," stipulates how image scores of two agents playing a game is altered, which has been presumed to be a fixed value in most previous studies. Also, unlike former studies, our model allows an agent to play with an agent who has a different norm. This point of relaxing the freedom of the model pulls down cooperation level vis-à-vis the case where an agent always plays with another one having same norm. However, it is observed that a rather larger dilemma shows robust cooperation establishing compared with a smaller dilemma, since a norm that punishes a so-called second-order free-rider is prompted. To encourage the evolution of norms to be able to punish second-order free-riders, a society needs a small number of defectors. This is elucidated by the fact that cases with action error are more cooperative than those without action error.
Vehicle active steering control research based on two-DOF robust internal model control
NASA Astrophysics Data System (ADS)
Wu, Jian; Liu, Yahui; Wang, Fengbo; Bao, Chunjiang; Sun, Qun; Zhao, Youqun
2016-07-01
Because of vehicle's external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.
Teleconnections in the Presence of Climate Change: A Case Study of the Annular Modes
NASA Astrophysics Data System (ADS)
Gerber, Edwin; Baldwin, Mark
2010-05-01
Long model integrations of future and past climates present a problem for defining teleconnection patterns through Empirical Orthogonal Function (EOF) or correlation analysis when trends in the underlying climate begin to dominate the covariance structure. Similar issues may soon appear in observations as the record becomes longer, especially if climate trends accelerate. The Northern and Southern Annular Modes provide a prime example, because the poleward shift of the jet streams strongly projects onto these patterns, particularly in the Southern Hemisphere. Climate forecasts of the 21st century by chemistry climate models provide a case study. Computation of the annular modes in these long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The new procedure involves two key changes. First, the global mean geopotential height is removed at each time step before computing anomalies. This is particularly important high in the atmosphere, where seasonal variations in geopotential height become significant, and filters out trends due to changes in the temperature structure of the atmosphere. Pattern definition can be very sensitive near the tropopause, as regions of the atmosphere that used to be more of stratospheric character begin to take on tropospheric characteristics as the tropopause rises. The second change is to define anomalies relative to a slowly evolving seasonal climatology, so that the covariance structure reflects internal variability. Once these changes are accounted for, it is found that the zonal mean variability of the atmosphere stays remarkably constant, despite significant changes in the baseline climate forecast for the rest of the century. This stability of the internal variability makes it possible to relate trends in climate to teleconnections.
Validation of a coupled core-transport, pedestal-structure, current-profile and equilibrium model
NASA Astrophysics Data System (ADS)
Meneghini, O.
2015-11-01
The first workflow capable of predicting the self-consistent solution to the coupled core-transport, pedestal structure, and equilibrium problems from first-principles and its experimental tests are presented. Validation with DIII-D discharges in high confinement regimes shows that the workflow is capable of robustly predicting the kinetic profiles from on axis to the separatrix and matching the experimental measurements to within their uncertainty, with no prior knowledge of the pedestal height nor of any measurement of the temperature or pressure. Self-consistent coupling has proven to be essential to match the experimental results, and capture the non-linear physics that governs the core and pedestal solutions. In particular, clear stabilization of the pedestal peeling ballooning instabilities by the global Shafranov shift and destabilization by additional edge bootstrap current, and subsequent effect on the core plasma profiles, have been clearly observed and documented. In our model, self-consistency is achieved by iterating between the TGYRO core transport solver (with NEO and TGLF for neoclassical and turbulent flux), and the pedestal structure predicted by the EPED model. A self-consistent equilibrium is calculated by EFIT, while the ONETWO transport package evolves the current profile and calculates the particle and energy sources. The capabilities of such workflow are shown to be critical for the design of future experiments such as ITER and FNSF, which operate in a regime where the equilibrium, the pedestal, and the core transport problems are strongly coupled, and for which none of these quantities can be assumed to be known. Self-consistent core-pedestal predictions for ITER, as well as initial optimizations, will be presented. Supported by the US Department of Energy under DE-FC02-04ER54698, DE-SC0012652.
NASA Astrophysics Data System (ADS)
Coelho, Luís Francisco Mello; Ribeiro, Milton Cezar; Pereira, Rodrigo Augusto Santinelo
2014-05-01
The success of fig trees in tropical ecosystems is evidenced by the great diversity (+750 species) and wide geographic distribution of the genus. We assessed the contribution of environmental variables on the species richness and density of fig trees in fragments of seasonal semideciduous forest (SSF) in Brazil. We assessed 20 forest fragments in three regions in Sao Paulo State, Brazil. Fig tree richness and density was estimated in rectangular plots, comprising 31.4 ha sampled. Both richness and fig tree density were linearly modeled as function of variables representing (1) fragment metrics, (2) forest structure, and (3) landscape metrics expressing water drainage in the fragments. Model selection was performed by comparing the AIC values (Akaike Information Criterion) and the relative weight of each model (wAIC). Both species richness and fig tree density were better explained by the water availability in the fragment (meter of streams/ha): wAICrichness = 0.45, wAICdensity = 0.96. The remaining variables related to anthropic perturbation and forest structure were of little weight in the models. The rainfall seasonality in SSF seems to select for both establishment strategies and morphological adaptations in the hemiepiphytic fig tree species. In the studied SSF, hemiepiphytes established at lower heights in their host trees than reported for fig trees in evergreen rainforests. Some hemiepiphytic fig species evolved superficial roots extending up to 100 m from their trunks, resulting in hectare-scale root zones that allow them to efficiently forage water and soil nutrients. The community of fig trees was robust to variation in forest structure and conservation level of SSF fragments, making this group of plants an important element for the functioning of seasonal tropical forests.
The Unusual Genetics and Biochemistry of Bovine Immunoglobulins.
Stanfield, Robyn L; Haakenson, Jeremy; Deiss, Thaddeus C; Criscitiello, Michael F; Wilson, Ian A; Smider, Vaughn V
2018-01-01
Antibodies are the key circulating molecules that have evolved to fight infection by the adaptive immune system of vertebrates. Typical antibodies of most species contain six complementarity-determining regions (CDRs), where the third CDR of the heavy chain (CDR H3) has the greatest diversity and often makes the most significant contact with antigen. Generally, the process of V(D)J recombination produces a vast repertoire of antibodies; multiple V, D, and J gene segments recombine with additional junctional diversity at the V-D and D-J joints, and additional combinatorial possibilities occur through heavy- and light-chain pairing. Despite these processes, the overall structure of the resulting antibody is largely conserved, and binding to antigen occurs predominantly through the CDR loops of the immunoglobulin V domains. Bovines have deviated from this general paradigm by having few VH regions and thus little germline combinatorial diversity, but their antibodies contain long CDR H3 regions, with substantial diversity generated through somatic hypermutation. A subset of the repertoire comprises antibodies with ultralong CDR H3s, which can reach over 70 amino acids in length. Structurally, these unusual antibodies form a β-ribbon "stalk" and disulfide-bonded "knob" that protrude far from the antibody surface. These long CDR H3s allow cows to mount a particularly robust immune response when immunized with viral antigens, particularly to broadly neutralizing epitopes on a stabilized HIV gp140 trimer, which has been a challenge for other species. The unusual genetics and structural biology of cows provide for a unique paradigm for creation of immune diversity and could enable generation of antibodies against especially challenging targets and epitopes. © 2018 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Perdigão, Rui A. P.; Hall, Julia; Pires, Carlos A. L.; Blöschl, Günter
2017-04-01
Classical and stochastic dynamical system theories assume structural coherence and dynamic recurrence with invariants of motion that are not necessarily so. These are grounded on the unproven assumption of universality in the dynamic laws derived from statistical kinematic evaluation of non-representative empirical records. As a consequence, the associated formulations revolve around a restrictive set of configurations and intermittencies e.g. in an ergodic setting, beyond which any predictability is essentially elusive. Moreover, dynamical systems are fundamentally framed around dynamic codependence among intervening processes, i.e. entail essentially redundant interactions such as couplings and feedbacks. That precludes synergistic cooperation among processes that, whilst independent from each other, jointly produce emerging dynamic behaviour not present in any of the intervening parties. In order to overcome these fundamental limitations, we introduce a broad class of non-recursive dynamical systems that formulate dynamic emergence of unprecedented states in a fundamental synergistic manner, with fundamental principles in mind. The overall theory enables innovations to be predicted from the internal system dynamics before any a priori information is provided about the associated dynamical properties. The theory is then illustrated to anticipate, from non-emergent records, the spatiotemporal emergence of multiscale hyper chaotic regimes, critical transitions and structural coevolutionary changes in synthetic and real-world complex systems. Example applications are provided within the hydro-climatic context, formulating and dynamically forecasting evolving hydro-climatic distributions, including the emergence of extreme precipitation and flooding in a structurally changing hydro-climate system. Validation is then conducted with a posteriori verification of the simulated dynamics against observational records. Agreement between simulations and observations is confirmed with robust nonlinear information diagnostics.