Direction Of Evolution Research Articles

BAYESIAN BETA REGRESSION: APPLICATIONS TO HOUSEHOLD EXPENDITURE DATA AND GENETIC DISTANCE BETWEEN FOOT‐AND‐MOUTH DISEASE VIRUSES

SummaryThere is considerable interest in understanding how factors such as time and geographic distance between isolates might influence the evolutionary direction of foot‐and‐mouth disease. Genetic differences between viruses can be measured as the proportion of nucleotides that differ for a given sequence or gene. We present a Bayesian hierarchical regression model for the statistical analysis of continuous data with sample space restricted to the interval (0, 1). The data are modelled using beta distributions with means that depend on covariates through a link function. We discuss methodology for: (i) the incorporation of informative prior information into an analysis; (ii) fitting the model using Markov chain Monte Carlo sampling; (iii) model selection using Bayes factors; and (iv) semiparametric beta regression using penalized splines. The model was applied to two different datasets.

Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

Natives adapting to invasive species: ecology, genes, and the sustainability of conservation

AbstractContemporary anthropogenic evolution is common. Biological invasions are an especially dynamic form of novel selection. This paper considers how native species evolve in response to biological invasions and the potential consequences of such evolution. Among numerous recent cases, the most widely reported instances are of phytophagous insects shifting onto introduced host plants. For example, our studies show that in North America and Australia, soapberry bugs evolved substantially after colonizing introduced hosts. Such cases permit close estimation of evolution's direction and rate, and we have used cross‐rearing studies of derived and ancestral‐type populations to measure changes in reaction norms and performance tradeoffs. Different fitness traits have followed very different paths in evolving to their current phenotypic values. Our hybridization studies show that the genetic architecture of these adaptations involves a surprising degree of non‐additive variation (epistasis, dominance). The importance of non‐additive genetic variation in rapid evolution will be clarified as more studies take advantage of similar situations. As appreciation grows for the deep contemporary interplay of evolution and ecology, debate about qualitative terms describing evolution's rate will become less relevant. From a conservation standpoint, contemporary evolution in native species presents challenges for ecologically appropriate and sustainable management. Evolving natives and invaders may reconfigure contemporary and future communities. Adaptive evolution may also enhance native communities’ capacity to control invasive populations.

Mammary glands and feathers: Comparing two skin appendages which help define novel classes during vertebrate evolution

It may appear counter-intuitive to compare feathers and mammary glands. However, through this Evo-Devo analysis, we appreciate how species interact with the environment, requiring different ectodermal organs. Novel ectodermal organs help define evolutionary directions, leading to new organism classes as exemplified by feathers for Aves and mammary glands for Mammals. Here, we review their structure, function, morphogenesis and regenerative cycling. Interestingly, both organs undergo extensive branching for different reasons; feather branching is driven by mechanical advantage while mammary glands nourish young. Besides natural selection, both are regulated by sex hormones and acquired a secondary function for attracting mates, contributing to sexual selection.

Optimal economic emission dispatch of hydrothermal power systems

This study develops an improved genetic algorithm-based multi-objective approach for the optimal economic emission dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The improved genetic algorithm (IGA) equipped with an improved evolutionary direction operator and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the ε-constraint technique is employed to manage the multi-objective problem. To show the advantages of the proposed algorithm, which is applied to test EED problems of the HPS with one example considering the best cost, one example considering the best emission, and one example addressing the best compromise. The proposed approach integrates the IGA, the MU and the ε-constraint technique, revealing that the proposed approach has the following merits – ease of implementation; applicability to non-smooth fuel cost and emission level functions; better effectiveness than the previous method; better efficiency than genetic algorithm with the MU (GA-MU), and the requirement for only a small population in applying the optimal EED problem of the HPS.

Genetic-based algorithm for power economic load dispatch

An improved genetic algorithm with multiplier updating (IGAMU) to solve practical power economic load dispatch (PELD) problems of different sizes and complexities with non-convex cost curves, where conventional mathematical methods are inapplicable, is developed. The improved genetic algorithm (IGA) provides an improved evolutionary direction operator and a migrating operator, enabling it to efficiently search and actively explore solutions. Multiplier updating (MU) is introduced to avoid deforming the augmented Lagrange function, which is adopted to manage the system constraints of PELD problems. The proposed IGAMU integrates the IGA with the MU. Two practical examples are employed to demonstrate that the proposed algorithm has the benefits of straightforwardness, ease of implementation, better effectiveness than previous methods, better effectiveness and efficiency than the genetic algorithm (GA) with MU (GA–MU), automatic adjustment of the randomly assigned penalty to an appropriate value and the requirement for only a small population when applied to real-life PELD operations.

Multiple-compartment bacterial clearance kinetics during murine bacteremia

Hypervirulence and carbapenem resistance have emerged as two distinct evolutionary directions for Klebsiella pneumoniae, which pose a great threat in clinical settings. Multiple virulence factors contribute to hypervirulence, and the mechanisms of carbapenem resistance are complicated. However, more and more K. pneumoniae strains have been identified in recent years integrating both phenotypes, resulting in devastating clinical outcomes. Hypervirulent and carbapenem-resistant K. pneumoniae (CR-hvKP) emerged in the early 2010s and thereafter have become increasingly prevalent. CR-hvKP are primarily prevalent in Asia, especially China, but are reported all over the world. Mechanisms for the emergence of CR-hvKP can be summarised by three patterns: (i) carbapenem-resistant K. pneumoniae (CRKP) acquiring a hypervirulent phenotype; (ii) hypervirulent K. pneumoniae (hvKP) acquiring a carbapenem-resistant phenotype; and (iii) K. pneumoniae acquiring both a carbapenem resistance and hypervirulence hybrid plasmid. With their global dissemination, continued surveillance of the emergence of CR-hvKP should be more highly prioritised.

Evolving Compact and Interpretable Takagi–Sugeno Fuzzy Models With a New Encoding Scheme

Developing Takagi-Sugeno fuzzy models by evolutionary algorithms mainly requires three factors: an encoding scheme, an evaluation method, and appropriate evolutionary operations. At the same time, these three factors should be designed so that they can consider three important aspects of fuzzy modeling: modeling accuracy, compactness, and interpretability. This paper proposes a new evolutionary algorithm that fulfills such requirements and solves fuzzy modeling problems. Two major ideas proposed in this paper lie in a new encoding scheme and a new fitness function, respectively. The proposed encoding scheme consists of three chromosomes, one of which uses unique chained possibilistic representation of rule structure. The proposed encoding scheme can achieve simultaneous optimization of parameters of antecedent membership functions and rule structures with the new fitness function developed in this paper. The proposed fitness function consists of five functions that consider three evaluation criteria in fuzzy modeling problems. The proposed fitness function guides evolutionary search direction so that the proposed algorithm can find more accurate compact fuzzy models with interpretable antecedent membership functions. Several evolutionary operators that are appropriate for the proposed encoding scheme are carefully designed. Simulation results on three modeling problems show that the proposed encoding scheme and the proposed fitness functions are effective in finding accurate, compact, and interpretable Takagi-Sugeno fuzzy models. From the simulation results, it is shown that the proposed algorithm can successfully find fuzzy models that approximate the given unknown function accurately with a compact number of fuzzy rules and membership functions. At the same time, the fuzzy models use interpretable antecedent membership functions, which are helpful in understanding the underlying behavior of the obtained fuzzy models.

Karyotype differentiation in Chromaphyosemion killifishes (Cyprinodontiformes, Nothobranchiidae). II: Cytogenetic and mitochondrial DNA analyses demonstrate karyotype differentiation and its evolutionary direction in C. riggenbachi

African killifishes of the genus Chromaphyosemion show a high degree of phenotypic and karyotypic diversity. The latter is especially pronounced in C. riggenbachi, a morphologically defined species restricted to a small distribution area in Cameroon. This study presents a detailed reconstruction of karyotype differentiation within C. riggenbachi using conventional Giemsa staining and sequential chromosome banding as well as a phylogenetic analysis based on part of the mitochondrial (mt) cytochrome b gene from eleven populations. The cytogenetic analysis revealed differences in chromosome morphology, banding patterns and/or diploid chromosome number (2n) among all populations examined. Diploid number ranged from 2n = 20 to 2n = 36 and varied mainly among populations, while C-banding patterns and NOR phenotypes showed fixed differences among populations as well as some variability within populations. The mtDNA analysis disclosed five clearly differentiated haplotype groups. Mapping the karyotype data onto the mtDNA dendrogram revealed a decrease in 2n from the most basal to the most derived groups, thus demonstrating a reduction of 2n during their evolutionary history. Our results indicate that karyotype differentiation involved Robertsonian fusions as well as non-Robertsonian processes. Causes of the high karyotypic variability may include an elevated chromosomal mutation rate as well as certain features of the ecology and mating system that could facilitate the fixation of chromosomal rearrangements. The pattern of karyotype and haplotype differentiation and the results of previous crossing experiments suggest incipient speciation in C. riggenbachi.

Masses and angular momenta of contact binary stars

Abstract Results are presented on component masses and system angular momenta for over 100 low-temperature contact binaries. It is found that the secondary components in close binary systems are very similar in mass. Our observational evidence strongly supports the argument that the evolutionary process goes from near-contact binaries to A-type contact binaries, without any need of mass loss from the system. Furthermore, the evolutionary direction of A-type into W-type systems with a simultaneous mass and angular momentum loss is also discussed. The opposite direction of evolution seems to be unlikely, since it requires an increase of the total mass and the angular momentum of the system.

A cytological study on Kelloggia (Rubiaceae), an intercontinental disjunct genus between eastern Asia and western North America

A cytological study was carried out for the first time on four populations of the only two species of Kelloggia (Rubiaceae), which occur disjunctly in eastern Asia (K. chinensis Franch.) and western North America (K. galioides Torr.). The consistent mitotic prophase chromosome condensation pattern and interphase nuclei type were determined for both species. The chromosome base number of the genus is suggested to be x = 11. The karyotype of 2n = 22 = 2x = 16m + 6sm was examined for both species. The karyotypical asymmetry of 1A and 2A was found in K. chinensis and K. galioides, respectively. According to the predominant evolutionary direction of karyotype asymmetry in angiosperms, K. galioides (2A) seems slightly more evolved than K. chinensis (1A). Our finding is consistent with the hypothesis of the Old World origin of Kelloggia based on molecular study.

Garden Alive: an Emotionally Intelligent Interactive Garden

In this paper, we introduce the "Garden Alive" system that allows users to interact with an emotionally intelligent virtual garden by manipulating tangible user interfaces. The Garden Alive aims to provide both entertainment and education. The proposed system is composed of three components. In the first module, tangible user interfaces bridge to the garden in a virtual world. In the second module, an artificial intelligent module consists of two sub-modules: an evolution module and an emotion module. The third module is the virtual garden, which displays growth and the reactions of virtual plants. As for the user interfaces, user's hand gestures are recognized by cameras, the amount of light measured by light detection sensors, and the position of water detected by water detection sensors. Based on this sensed information, the artificial intelligent module determines the evolutionary direction of the plants and changes their emotional state. Our Virtual Garden has adapted the L-system [12] so the virtual plants grow in a similar manner to real plants. In this proposed "Garden Alive" system, there are several kinds of plants and each has different genes that is to individually unique. So we can observe plants evolving for generations by evaluating a proposed fitness function. Finally, we implemented intelligent plants which show emotional reactions according to interaction with the user, instead of simply reacting to stimulus. Therefore, the proposed system is applicable for use to both entertainment and education.

Improved Genetic Algorithm for Power Economic Dispatch of Units With Valve-Point Effects and Multiple Fuels

This paper presents an improved genetic algorithm with multiplier updating (IGA/spl I.bar/MU) to solve power economic dispatch (PED) problems of units with valve-point effects and multiple fuels. The proposed IGA/spl I.bar/MU integrates the improved genetic algorithm (IGA) and the multiplier updating (MU). The IGA equipped with an improved evolutionary direction operator and a migration operation can efficiently search and actively explore solutions, and the MU is employed to handle the equality and inequality constraints of the PED problem. Few PED problem-related studies have seldom addressed both valve-point loadings and change fuels. To show the advantages of the proposed algorithm, which was applied to test PED problems with one example considering valve-point effects, one example considering multiple fuels, and one example addressing both valve-point effects and multiple fuels. Additionally, the proposed algorithm was compared with previous methods and the conventional genetic algorithm (CGA) with the MU (CGA/spl I.bar/MU), revealing that the proposed IGA/spl I.bar/MU is more effective than previous approaches, and applies the realistic PED problem more efficiently than does the CGA/spl I.bar/MU. Especially, the proposed algorithm is highly promising for the large-scale system of the actual PED operation.

Biological Transmission of Arboviruses: Reexamination of and New Insights into Components, Mechanisms, and Unique Traits as Well as Their Evolutionary Trends

Among animal viruses, arboviruses are unique in that they depend on arthropod vectors for transmission. Field research and laboratory investigations related to the three components of this unique mode of transmission, virus, vector, and vertebrate host, have produced an enormous amount of valuable information that may be found in numerous publications. However, despite many reviews on specific viruses, diseases, or interests, a systematic approach to organizing the available information on all facets of biological transmission and then to interpret it in the context of the evolutionary process has not been attempted before. Such an attempt in this review clearly demonstrates tremendous progress made worldwide to characterize the viruses, to comprehend disease transmission and pathogenesis, and to understand the biology of vectors and their role in transmission. The rapid progress in molecular biologic techniques also helped resolve many virologic puzzles and yielded highly valuable data hitherto unavailable, such as characterization of virus receptors, the genetic basis of vertebrate resistance to viral infection, and phylogenetic evidence of the history of host range shifts in arboviruses. However, glaring gaps in knowledge of many critical subjects, such as the mechanism of viral persistence and the existence of vertebrate reservoirs, are still evident. Furthermore, with the accumulated data, new questions were raised, such as evolutionary directions of virus virulence and of host range. Although many fundamental questions on the evolution of this unique mode of transmission remained unresolved in the absence of a fossil record, available observations for arboviruses and the information derived from studies in other fields of the biological sciences suggested convergent evolution as a plausible process. Overall, discussion of the diverse range of theories proposed and observations made by many investigators was found to be highly valuable for sorting out the possible mechanism(s) of the emergence of arboviral diseases.

ADAPTIVE-IMPROVED GENETIC ALGORITHM FOR THE ECONOMIC DISPATCH OF UNITS WITH MULTIPLE FUEL OPTIONS

ABSTRACT This article presents the improved genetic algorithm with the Adaptive Multiplier Updating Method (IGA_AMUM) for power economic dispatch of units having multiple fuel options. The Improved Genetic Algorithm (IGA) equipped with an improved, evolutionary direction operator and a migration can search efficiently and actively explore solutions. The Adaptive Multiplier Updating Method (AMUM) is introduced to avoid deforming the augmented Lagrange function and resulting in a difficult solution search. The proposed method integrates the IGA and the AMUM that has merits of automatically adjusting the randomly given penalty to a proper value and requiring only a small-size population for the Economic Dispatch Problem (EDP) with multiple fuel options. Numerical results indicate that the proposed algorithm is more suitable than previous approaches in the practical application. Moreover, the proposed algorithm provides an efficacious approach for the large-scale system of the EDP with multiple fuel options.

Remaking Italian Capitalism? The Politics of Corporate Governance Reform

This article addresses the issue of how to explain institutional change in national political economies. Within an actor-centred institutionalist theoretical framework, it explores the utility of a coalitional explanation for changes in the financial and corporate governance systems of Italy. Finance and corporate governance are useful foci for understanding change and the evolutionary direction of national political economies as a whole because, first, national and European reformers have focused a great deal of their energy on transforming financial market structures and corporate governance and, second, the regulation of finance and corporate governance is increasingly important as a means for states to exert influence over their economies. The paper finds considerable change in Italian capitalism as a result of successful elite reformers, party system changes, and the emergence of a reform coalition. However, change is limited and Italy retains a distinctive model of capitalism.

Using origin analysis to detect merging and splitting of source code entities

Merging and splitting source code entities is a common activity during the lifespan of a software system; as developers rethink the essential structure of a system or plan for a new evolutionary direction, so must they be able to reorganize the design artifacts at various abstraction levels as seems appropriate. However, while the raw effects of such changes may be plainly evident in the new artifacts, the original context of the design changes is often lost. That is, it may be obvious which characters of which files have changed, but it may not be obvious where or why moving, renaming, merging, and/or splitting of design elements has occurred. In this paper, we discuss how we have extended origin analysis (Q. Tu et al., 2002), (M.W. Godfrey et al., 2002) to aid in the detection of merging and splitting of files and functions in procedural code; in particular, we show how reasoning about how call relationships have changed can aid a developer in locating where merges and splits have occurred, thereby helping to recover some information about the context of the design change. We also describe a case study of these techniques (as implemented in the Beagle tool) using the PostgreSQL database system as the subject.

An attempt at improving a global spectral model by incorporating the second law of thermodynamics

A fluid such as the atmosphere is a many‐body system that has a vast amount of degrees of freedom in terms of statistical physics and thus obeys the second law of thermodynamics controlling the irreversible evolutionary direction of a many‐body system. This study shows that incorporating the thermodynamic irreversibility law into a hydrodynamic system leads to a noticeable improvement of a numerical weather prediction model. This is demonstrated by improved simulations from a set of numerical experiments using a global spectral model which incorporates the second law.

An Analysis of Core Deformations in Protein Superfamilies

An analysis is presented on how structural cores modify their shape across homologous proteins, and whether or not a relationship exists between these structural changes and the vibrational normal modes that proteins experience as a result of the topological constraints imposed by the fold. A set of 35 representative, well-populated protein families is studied. The evolutionary directions of deformation are obtained by using multiple structural alignments to superimpose the structures and extract a conserved core, together with principal components analysis to extract the main deformation modes from the three-dimensional superimposition. In parallel, a low-resolution normal mode analysis technique is employed to study the properties of the mechanical core plasticity of these same families. We show that the evolutionary deformations span a low dimensional space of 4–5 dimensions on average. A statistically significant correspondence exists between these principal deformations and the ∼20 slowest vibrational modes accessible to a particular topology. We conclude that, to a significant extent, the structural response of a protein topology to sequence changes takes place by means of collective deformations along combinations of a small number of low-frequency modes. The findings have implications in structure prediction by homology modeling.

Core deformations in protein families: a physical perspective

An analysis is presented on how structural cores change shape within protein families, and whether or not there is a relationship between these structural changes and the vibrational modes that proteins experiment due to topological constraints. A set of 13 representative and well-populated protein families are studied. The evolutionary directions of deformation are obtained by applying a new multiple structural alignment technique to superimpose the structures and extract a conserved core, together with Principal Components Analysis (PCA) to extract the main deformation modes. A low-resolution Normal Mode Analysis (NMA) technique is used in parallel to study the properties of the mechanical core plasticity of the same proteins. We find that the evolutionary deformations span a low dimensional space. A statistically significant correspondence exists between these principal deformations and the vibrational modes accessible to a particular topology. We conclude that, to a significant extent, the structures of evolving proteins seem to respond to sequence changes by collective deformations along combinations of low-frequency modes. The findings have implications in structure prediction by homology modeling.