On the problem of solving the optimization for continuous space based on information distribution function of ant colony algorithm

NASA Astrophysics Data System (ADS)

Min, Huang; Na, Cai

2017-06-01

These years, ant colony algorithm has been widely used in solving the domain of discrete space optimization, while the research on solving the continuous space optimization was relatively little. Based on the original optimization for continuous space, the article proposes the improved ant colony algorithm which is used to Solve the optimization for continuous space, so as to overcome the ant colony algorithm’s disadvantages of searching for a long time in continuous space. The article improves the solving way for the total amount of information of each interval and the due number of ants. The article also introduces a function of changes with the increase of the number of iterations in order to enhance the convergence rate of the improved ant colony algorithm. The simulation results show that compared with the result in literature[5], the suggested improved ant colony algorithm that based on the information distribution function has a better convergence performance. Thus, the article provides a new feasible and effective method for ant colony algorithm to solve this kind of problem.

KANTS: a stigmergic ant algorithm for cluster analysis and swarm art.

PubMed

Fernandes, Carlos M; Mora, Antonio M; Merelo, Juan J; Rosa, Agostinho C

2014-06-01

KANTS is a swarm intelligence clustering algorithm inspired by the behavior of social insects. It uses stigmergy as a strategy for clustering large datasets and, as a result, displays a typical behavior of complex systems: self-organization and global patterns emerging from the local interaction of simple units. This paper introduces a simplified version of KANTS and describes recent experiments with the algorithm in the context of a contemporary artistic and scientific trend called swarm art, a type of generative art in which swarm intelligence systems are used to create artwork or ornamental objects. KANTS is used here for generating color drawings from the input data that represent real-world phenomena, such as electroencephalogram sleep data. However, the main proposal of this paper is an art project based on well-known abstract paintings, from which the chromatic values are extracted and used as input. Colors and shapes are therefore reorganized by KANTS, which generates its own interpretation of the original artworks. The project won the 2012 Evolutionary Art, Design, and Creativity Competition.

Warehouse stocking optimization based on dynamic ant colony genetic algorithm

NASA Astrophysics Data System (ADS)

Xiao, Xiaoxu

2018-04-01

In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.

Leader-based and self-organized communication: modelling group-mass recruitment in ants.

PubMed

Collignon, Bertrand; Deneubourg, Jean Louis; Detrain, Claire

2012-11-21

For collective decisions to be made, the information acquired by experienced individuals about resources' location has to be shared with naïve individuals through recruitment. Here, we investigate the properties of collective responses arising from a leader-based recruitment and a self-organized communication by chemical trails. We develop a generalized model based on biological data drawn from Tetramorium caespitum ant species of which collective foraging relies on the coupling of group leading and trail recruitment. We show that for leader-based recruitment, small groups of recruits have to be guided in a very efficient way to allow a collective exploitation of food while large group requires less attention from their leader. In the case of self-organized recruitment through a chemical trail, a critical value of trail amount has to be laid per forager in order to launch collective food exploitation. Thereafter, ants can maintain collective foraging by emitting signal intensity below this threshold. Finally, we demonstrate how the coupling of both recruitment mechanisms may benefit to collectively foraging species. These theoretical results are then compared with experimental data from recruitment by T. caespitum ant colonies performing group-mass recruitment towards a single food source. We evidence the key role of leaders as initiators and catalysts of recruitment before this leader-based process is overtaken by self-organised communication through trails. This model brings new insights as well as a theoretical background to empirical studies about cooperative foraging in group-living species. Copyright © 2012 Elsevier Ltd. All rights reserved.

Army ants algorithm for rare event sampling of delocalized nonadiabatic transitions by trajectory surface hopping and the estimation of sampling errors by the bootstrap method.

PubMed

Nangia, Shikha; Jasper, Ahren W; Miller, Thomas F; Truhlar, Donald G

2004-02-22

The most widely used algorithm for Monte Carlo sampling of electronic transitions in trajectory surface hopping (TSH) calculations is the so-called anteater algorithm, which is inefficient for sampling low-probability nonadiabatic events. We present a new sampling scheme (called the army ants algorithm) for carrying out TSH calculations that is applicable to systems with any strength of coupling. The army ants algorithm is a form of rare event sampling whose efficiency is controlled by an input parameter. By choosing a suitable value of the input parameter the army ants algorithm can be reduced to the anteater algorithm (which is efficient for strongly coupled cases), and by optimizing the parameter the army ants algorithm may be efficiently applied to systems with low-probability events. To demonstrate the efficiency of the army ants algorithm, we performed atom-diatom scattering calculations on a model system involving weakly coupled electronic states. Fully converged quantum mechanical calculations were performed, and the probabilities for nonadiabatic reaction and nonreactive deexcitation (quenching) were found to be on the order of 10(-8). For such low-probability events the anteater sampling scheme requires a large number of trajectories ( approximately 10(10)) to obtain good statistics and converged semiclassical results. In contrast by using the new army ants algorithm converged results were obtained by running 10(5) trajectories. Furthermore, the results were found to be in excellent agreement with the quantum mechanical results. Sampling errors were estimated using the bootstrap method, which is validated for use with the army ants algorithm. (c) 2004 American Institute of Physics.

Ant algorithms for discrete optimization.

PubMed

Dorigo, M; Di Caro, G; Gambardella, L M

1999-01-01

This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.

The principles of collective animal behaviour

PubMed Central

Sumpter, D.J.T

2005-01-01

In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society. PMID:16553306

The principles of collective animal behaviour.

PubMed

Sumpter, D J T

2006-01-29

In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.

One-dimensional swarm algorithm packaging

NASA Astrophysics Data System (ADS)

Lebedev, Boris K.; Lebedev, Oleg B.; Lebedeva, Ekaterina O.

2018-05-01

The paper considers an algorithm for solving the problem of onedimensional packaging based on the adaptive behavior model of an ant colony. The key role in the development of the ant algorithm is the choice of representation (interpretation) of the solution. The structure of the solution search graph, the procedure for finding solutions on the graph, the methods of deposition and evaporation of pheromone are described. Unlike the canonical paradigm of an ant algorithm, an ant on the solution search graph generates sets of elements distributed across blocks. Experimental studies were conducted on IBM PC. Compared with the existing algorithms, the results are improved.

Evolving Self-Organized Behavior for Homogeneous and Heterogeneous UAV or UCAV Swarms

DTIC Science & Technology

2006-03-01

of sensed UAVs and a simple target associated pheromone . At its core, the sets of behaviors are built upon behavior rules describing formation...search randomly around the nest, dropping pheromones for communication. When an ant locates food and returns to the hive, it leaves a trail of... pheromones between the hive and the food-source. When other ants are exposed to the pheromone signal released by the first ant, they have a greater

Production scheduling with ant colony optimization

NASA Astrophysics Data System (ADS)

Chernigovskiy, A. S.; Kapulin, D. V.; Noskova, E. E.; Yamskikh, T. N.; Tsarev, R. Yu

2017-10-01

The optimum solution of the production scheduling problem for manufacturing processes at an enterprise is crucial as it allows one to obtain the required amount of production within a specified time frame. Optimum production schedule can be found using a variety of optimization algorithms or scheduling algorithms. Ant colony optimization is one of well-known techniques to solve the global multi-objective optimization problem. In the article, the authors present a solution of the production scheduling problem by means of an ant colony optimization algorithm. A case study of the algorithm efficiency estimated against some others production scheduling algorithms is presented. Advantages of the ant colony optimization algorithm and its beneficial effect on the manufacturing process are provided.

Model Specification Searches Using Ant Colony Optimization Algorithms

ERIC Educational Resources Information Center

Marcoulides, George A.; Drezner, Zvi

2003-01-01

Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

Multirobot Lunar Excavation and ISRU Using Artificial-Neural-Tissue Controllers

NASA Astrophysics Data System (ADS)

Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader; Ho, Alexander; Boucher, Dale; Richard, Jim; D'Eleuterio, Gabriele M. T.

2008-01-01

Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to `breed' controllers for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates `machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader

Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to 'breed' controllersmore » for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates 'machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.« less

Application of ant colony Algorithm and particle swarm optimization in architectural design

NASA Astrophysics Data System (ADS)

Song, Ziyi; Wu, Yunfa; Song, Jianhua

2018-02-01

By studying the development of ant colony algorithm and particle swarm algorithm, this paper expounds the core idea of the algorithm, explores the combination of algorithm and architectural design, sums up the application rules of intelligent algorithm in architectural design, and combines the characteristics of the two algorithms, obtains the research route and realization way of intelligent algorithm in architecture design. To establish algorithm rules to assist architectural design. Taking intelligent algorithm as the beginning of architectural design research, the authors provide the theory foundation of ant colony Algorithm and particle swarm algorithm in architectural design, popularize the application range of intelligent algorithm in architectural design, and provide a new idea for the architects.

Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

ERIC Educational Resources Information Center

Rastegarmoghadam, Mahin; Ziarati, Koorush

2017-01-01

Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making.

PubMed

Hoover, Kevin M; Bubak, Andrew N; Law, Isaac J; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

2016-06-01

Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant's brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2018-03-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2017-12-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making

PubMed Central

Hoover, Kevin M.; Bubak, Andrew N.; Law, Isaac J.; Yaeger, Jazmine D. W.; Renner, Kenneth J.; Swallow, John G.; Greene, Michael J.

2016-01-01

Abstract Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant’s brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions. PMID:29491915

Stability and Responsiveness in a Self-Organized Living Architecture

PubMed Central

Garnier, Simon; Murphy, Tucker; Lutz, Matthew; Hurme, Edward; Leblanc, Simon; Couzin, Iain D.

2013-01-01

Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies. PMID:23555219

Use of radio-tagging to map spatial organization and social interactions in insects.

PubMed

Moreau, Mathieu; Arrufat, Patrick; Latil, Gérard; Jeanson, Raphaël

2011-01-01

Understanding of the organization of animal societies often requires knowledge of the identity of group members and their spatial location. We propose an original experimental design to track automatically the position of individuals using radio frequency identification technology (RFID). Ants equipped with passive transponders were detected by a reader mounted on a mobile arm moving across the nest surface. We developed an algorithm to accurately extract the positions of individuals moving in two dimensions. Our method was validated on synthetic test cases and then used for characterization of the spatial distribution of ants within nests. This approach provides an amenable system for monitoring large populations of individuals over long periods of time.

Ants as biological indicators of Wayana Amerindian land use in French Guiana.

PubMed

Delabie, Jacques H C; Céréghino, Régis; Groc, Sarah; Dejean, Andrea; Gibernau, Marc; Corbara, Bruno; Dejean, Alain

2009-07-01

We examined the ecological impact of traditional land use by Wayana Amerindians in French Guiana using ants as bio-indicators. Ants were sampled through a rapid assessment method and the core results analyzed using Kohonen's self-organizing maps (SOM). Our sample sites included: (1) a Wayana village; (2) a cassava plantation; (3) an abandoned cassava plantation; (4) a forest fragment near the village; (5) a riparian forest; and (6) a primary terra firma forest. The ant diversity decreases according to the degree to which the habitat is disturbed. The SOM allowed us to compare the ecological succession between the six habitats. The protocol used is robust since the same conclusions were drawn using partial data.

RENDEZVOUS: Self-Organizing Services in an Active Network

DTIC Science & Technology

2004-02-01

http://www.cs.washington.edu/research/networking/ants/, and http://www.cs.utah.edu/flux/janos/ants.html, 2001. [2] Krishna P. Gummadi, “King...Proceedings of the Tenth ACM SIGOPS European Workshop, September 2002. [9] Stefan Saroiu, P. Krishna Gummadi, Steven D. Gribble: A Measurement Study...Davis, Eric Lemar, and Brian Bershad. “Migration for Pervasive Applications.” Submitted to OSDI, June 2002. Gummadi, P. Krishna , Stefan Saroiu, and

Improving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results.

PubMed

Otero, Fernando E B; Freitas, Alex A

2016-01-01

Most ant colony optimization (ACO) algorithms for inducing classification rules use a ACO-based procedure to create a rule in a one-at-a-time fashion. An improved search strategy has been proposed in the cAnt-Miner[Formula: see text] algorithm, where an ACO-based procedure is used to create a complete list of rules (ordered rules), i.e., the ACO search is guided by the quality of a list of rules instead of an individual rule. In this paper we propose an extension of the cAnt-Miner[Formula: see text] algorithm to discover a set of rules (unordered rules). The main motivations for this work are to improve the interpretation of individual rules by discovering a set of rules and to evaluate the impact on the predictive accuracy of the algorithm. We also propose a new measure to evaluate the interpretability of the discovered rules to mitigate the fact that the commonly used model size measure ignores how the rules are used to make a class prediction. Comparisons with state-of-the-art rule induction algorithms, support vector machines, and the cAnt-Miner[Formula: see text] producing ordered rules are also presented.

Attractors in Sequence Space: Agent-Based Exploration of MHC I Binding Peptides.

PubMed

Jäger, Natalie; Wisniewska, Joanna M; Hiss, Jan A; Freier, Anja; Losch, Florian O; Walden, Peter; Wrede, Paul; Schneider, Gisbert

2010-01-12

Ant Colony Optimization (ACO) is a meta-heuristic that utilizes a computational analogue of ant trail pheromones to solve combinatorial optimization problems. The size of the ant colony and the representation of the ants' pheromone trails is unique referring to the given optimization problem. In the present study, we employed ACO to generate novel peptides that stabilize MHC I protein on the plasma membrane of a murine lymphoma cell line. A jury of feedforward neural network classifiers served as fitness function for peptide design by ACO. Bioactive murine MHC I H-2K(b) stabilizing as well as nonstabilizing octapeptides were designed, synthesized and tested. These peptides reveal residue motifs that are relevant for MHC I receptor binding. We demonstrate how the performance of the implemented ACO algorithm depends on the colony size and the size of the search space. The actual peptide design process by ACO constitutes a search path in sequence space that can be visualized as trajectories on a self-organizing map (SOM). By projecting the sequence space on a SOM we visualize the convergence of the different solutions that emerge during the optimization process in sequence space. The SOM representation reveals attractors in sequence space for MHC I binding peptides. The combination of ACO and SOM enables systematic peptide optimization. This technique allows for the rational design of various types of bioactive peptides with minimal experimental effort. Here, we demonstrate its successful application to the design of MHC-I binding and nonbinding peptides which exhibit substantial bioactivity in a cell-based assay. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An adaptive grid algorithm for 3-D GIS landform optimization based on improved ant algorithm

NASA Astrophysics Data System (ADS)

Wu, Chenhan; Meng, Lingkui; Deng, Shijun

2005-07-01

The key technique of 3-D GIS is to realize quick and high-quality 3-D visualization, in which 3-D roaming system based on landform plays an important role. However how to increase efficiency of 3-D roaming engine and process a large amount of landform data is a key problem in 3-D landform roaming system and improper process of the problem would result in tremendous consumption of system resources. Therefore it has become the key of 3-D roaming system design that how to realize high-speed process of distributed data for landform DEM (Digital Elevation Model) and high-speed distributed modulation of various 3-D landform data resources. In the paper we improved the basic ant algorithm and designed the modulation strategy of 3-D GIS landform resources based on the improved ant algorithm. By initially hypothetic road weights σi , the change of the information factors in the original algorithm would transform from ˜τj to ∆τj+σi and the weights was decided by 3-D computative capacity of various nodes in network environment. So during the course of initial phase of task assignment, increasing the resource information factors of high task-accomplishing rate and decreasing ones of low accomplishing rate would make load accomplishing rate approach the same value as quickly as possible, then in the later process of task assignment, the load balanced ability of the system was further improved. Experimental results show by improving ant algorithm, our system not only decreases many disadvantage of the traditional ant algorithm, but also like ants looking for food effectively distributes the complicated landform algorithm to many computers to process cooperatively and gains a satisfying search result.

Improved Ant Algorithms for Software Testing Cases Generation

PubMed Central

Yang, Shunkun; Xu, Jiaqi

2014-01-01

Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to porduce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391

Routing and spectrum assignment based on ant colony optimization of minimum consecutiveness loss in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Tian, Qinghua; Zhang, Qi; Rao, Lan; Tian, Feng; Luo, Biao; Liu, Yingjun; Tang, Bao

2016-10-01

Elastic Optical Networks are considered to be a promising technology for future high-speed network. In this paper, we propose a RSA algorithm based on the ant colony optimization of minimum consecutiveness loss (ACO-MCL). Based on the effect of the spectrum consecutiveness loss on the pheromone in the ant colony optimization, the path and spectrum of the minimal impact on the network are selected for the service request. When an ant arrives at the destination node from the source node along a path, we assume that this path is selected for the request. We calculate the consecutiveness loss of candidate-neighbor link pairs along this path after the routing and spectrum assignment. Then, the networks update the pheromone according to the value of the consecutiveness loss. We save the path with the smallest value. After multiple iterations of the ant colony optimization, the final selection of the path is assigned for the request. The algorithms are simulated in different networks. The results show that ACO-MCL algorithm performs better in blocking probability and spectrum efficiency than other algorithms. Moreover, the ACO-MCL algorithm can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness. Compared with other algorithms, the ACO-MCL algorithm can reduce the blocking rate by at least 5.9% in heavy load.

Optimization of Stereo Matching in 3D Reconstruction Based on Binocular Vision

NASA Astrophysics Data System (ADS)

Gai, Qiyang

2018-01-01

Stereo matching is one of the key steps of 3D reconstruction based on binocular vision. In order to improve the convergence speed and accuracy in 3D reconstruction based on binocular vision, this paper adopts the combination method of polar constraint and ant colony algorithm. By using the line constraint to reduce the search range, an ant colony algorithm is used to optimize the stereo matching feature search function in the proposed search range. Through the establishment of the stereo matching optimization process analysis model of ant colony algorithm, the global optimization solution of stereo matching in 3D reconstruction based on binocular vision system is realized. The simulation results show that by the combining the advantage of polar constraint and ant colony algorithm, the stereo matching range of 3D reconstruction based on binocular vision is simplified, and the convergence speed and accuracy of this stereo matching process are improved.

Negative feedback in ants: crowding results in less trail pheromone deposition

PubMed Central

Czaczkes, Tomer J.; Grüter, Christoph; Ratnieks, Francis L. W.

2013-01-01

Crowding in human transport networks reduces efficiency. Efficiency can be increased by appropriate control mechanisms, which are often imposed externally. Ant colonies also have distribution networks to feeding sites outside the nest and can experience crowding. However, ants do not have external controllers or leaders. Here, we report a self-organized negative feedback mechanism, based on local information, which downregulates the production of recruitment signals in crowded parts of a network by Lasius niger ants. We controlled crowding by manipulating trail width and the number of ants on a trail, and observed a 5.6-fold reduction in the number of ants depositing trail pheromone from least to most crowded conditions. We also simulated crowding by placing glass beads covered in nest-mate cuticular hydrocarbons on the trail. After 10 bead encounters over 20 cm, forager ants were 45 per cent less likely to deposit pheromone. The mechanism of negative feedback reported here is unusual in that it acts by downregulating the production of a positive feedback signal, rather than by direct inhibition or the production of an inhibitory signal. PMID:23365196

Textural defect detect using a revised ant colony clustering algorithm

NASA Astrophysics Data System (ADS)

Zou, Chao; Xiao, Li; Wang, Bingwen

2007-11-01

We propose a totally novel method based on a revised ant colony clustering algorithm (ACCA) to explore the topic of textural defect detection. In this algorithm, our efforts are mainly made on the definition of local irregularity measurement and the implementation of the revised ACCA. The local irregular measurement defined evaluates the local textural inconsistency of each pixel against their mini-environment. In our revised ACCA, the behaviors of each ant are divided into two steps: release pheromone and act. The quantity of pheromone released is proportional to the irregularity measurement; the actions of the ants to act next are chosen independently of each other in a stochastic way according to some evaluated heuristic knowledge. The independency of ants implies the inherent parallel computation architecture of this algorithm. We apply the proposed method in some typical textural images with defects. From the series of pheromone distribution map (PDM), it can be clearly seen that the pheromone distribution approaches the textual defects gradually. By some post-processing, the final distribution of pheromone can demonstrate the shape and area of the defects well.

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy

PubMed Central

Guo, Tong; Liu, Qiong; Zhu, Qianwei; Zhao, Xiangmo; Jin, Bo

2017-01-01

In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait. PMID:29168742

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy.

PubMed

Zhu, Yaguang; Guo, Tong; Liu, Qiong; Zhu, Qianwei; Zhao, Xiangmo; Jin, Bo

2017-11-23

Abstract : In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait.

Swarm Intelligence for Urban Dynamics Modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

2009-04-16

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Swarm Intelligence for Urban Dynamics Modelling

NASA Astrophysics Data System (ADS)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

2009-04-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Self-organization leads to supraoptimal performance in public transportation systems.

PubMed

Gershenson, Carlos

2011-01-01

The performance of public transportation systems affects a large part of the population. Current theory assumes that passengers are served optimally when vehicles arrive at stations with regular intervals. In this paper, it is shown that self-organization can improve the performance of public transportation systems beyond the theoretical optimum by responding adaptively to local conditions. This is possible because of a "slower-is-faster" effect, where passengers wait more time at stations but total travel times are reduced. The proposed self-organizing method uses "antipheromones" to regulate headways, which are inspired by the stigmergy (communication via environment) of some ant colonies.

Ant- and Ant-Colony-Inspired ALife Visual Art.

PubMed

Greenfield, Gary; Machado, Penousal

2015-01-01

Ant- and ant-colony-inspired ALife art is characterized by the artistic exploration of the emerging collective behavior of computational agents, developed using ants as a metaphor. We present a chronology that documents the emergence and history of such visual art, contextualize ant- and ant-colony-inspired art within generative art practices, and consider how it relates to other ALife art. We survey many of the algorithms that artists have used in this genre, address some of their aims, and explore the relationships between ant- and ant-colony-inspired art and research on ant and ant colony behavior.

Application of cellular automatons and ant algorithms in avionics

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Selvesiuk, N. I.; Platoshin, G. A.; Semenova, E. V.

2018-03-01

The paper considers two algorithms for searching quasi-optimal solutions of discrete optimization problems with regard to the tasks of avionics placing. The first one solves the problem of optimal placement of devices by installation locations, the second one is for the problem of finding the shortest route between devices. Solutions are constructed using a cellular automaton and the ant colony algorithm.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

A distributed algorithm to maintain and repair the trail networks of arboreal ants.

PubMed

Chandrasekhar, Arjun; Gordon, Deborah M; Navlakha, Saket

2018-06-18

We study how the arboreal turtle ant (Cephalotes goniodontus) solves a fundamental computing problem: maintaining a trail network and finding alternative paths to route around broken links in the network. Turtle ants form a routing backbone of foraging trails linking several nests and temporary food sources. This species travels only in the trees, so their foraging trails are constrained to lie on a natural graph formed by overlapping branches and vines in the tangled canopy. Links between branches, however, can be ephemeral, easily destroyed by wind, rain, or animal movements. Here we report a biologically feasible distributed algorithm, parameterized using field data, that can plausibly describe how turtle ants maintain the routing backbone and find alternative paths to circumvent broken links in the backbone. We validate the ability of this probabilistic algorithm to circumvent simulated breaks in synthetic and real-world networks, and we derive an analytic explanation for why certain features are crucial to improve the algorithm's success. Our proposed algorithm uses fewer computational resources than common distributed graph search algorithms, and thus may be useful in other domains, such as for swarm computing or for coordinating molecular robots.

Optimal management of substrates in anaerobic co-digestion: An ant colony algorithm approach.

PubMed

Verdaguer, Marta; Molinos-Senante, María; Poch, Manel

2016-04-01

Sewage sludge (SWS) is inevitably produced in urban wastewater treatment plants (WWTPs). The treatment of SWS on site at small WWTPs is not economical; therefore, the SWS is typically transported to an alternative SWS treatment center. There is increased interest in the use of anaerobic digestion (AnD) with co-digestion as an SWS treatment alternative. Although the availability of different co-substrates has been ignored in most of the previous studies, it is an essential issue for the optimization of AnD co-digestion. In a pioneering approach, this paper applies an Ant-Colony-Optimization (ACO) algorithm that maximizes the generation of biogas through AnD co-digestion in order to optimize the discharge of organic waste from different waste sources in real-time. An empirical application is developed based on a virtual case study that involves organic waste from urban WWTPs and agrifood activities. The results illustrate the dominate role of toxicity levels in selecting contributions to the AnD input. The methodology and case study proposed in this paper demonstrate the usefulness of the ACO approach in supporting a decision process that contributes to improving the sustainability of organic waste and SWS management. Copyright © 2016 Elsevier Ltd. All rights reserved.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

Ant-cuckoo colony optimization for feature selection in digital mammogram.

PubMed

Jona, J B; Nagaveni, N

2014-01-15

Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques.

SOTXTSTREAM: Density-based self-organizing clustering of text streams.

PubMed

Bryant, Avory C; Cios, Krzysztof J

2017-01-01

A streaming data clustering algorithm is presented building upon the density-based self-organizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets.

Traffic Flow of Interacting Self-Driven Particles: Rails and Trails, Vehicles and Vesicles

NASA Astrophysics Data System (ADS)

Chowdhury, Debashish

One common feature of a vehicle, an ant and a kinesin motor is that they all convert chemical energy, derived from fuel or food, into mechanical energy required for their forward movement; such objects have been modelled in recent years as self-driven particles. Cytoskeletal filaments, e.g., microtubules, form a rail network for intra-cellular transport of vesicular cargo by molecular motors like, for example, kinesins. Similarly, ants move along trails while vehicles move along lanes. Therefore, the traffic of vehicles and organisms as well as that of molecular motors can be modelled as systems of interacting self-driven particles; these are of current interest in non-equilibrium statistical mechanics. In this paper we point out the common features of these model systems and emphasize the crucial differences in their physical properties.

Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm

ERIC Educational Resources Information Center

Leite, Walter L.; Huang, I-Chan; Marcoulides, George A.

2008-01-01

This article presents the use of an ant colony optimization (ACO) algorithm for the development of short forms of scales. An example 22-item short form is developed for the Diabetes-39 scale, a quality-of-life scale for diabetes patients, using a sample of 265 diabetes patients. A simulation study comparing the performance of the ACO algorithm and…

Absence of jamming in ant trails: feedback control of self-propulsion and noise.

PubMed

Chaudhuri, Debasish; Nagar, Apoorva

2015-01-01

We present a model of ant traffic considering individual ants as self-propelled particles undergoing single-file motion on a one-dimensional trail. Recent experiments on unidirectional ant traffic in well-formed natural trails showed that the collective velocity of ants remains approximately unchanged, leading to the absence of jamming even at very high densities [John et al., Phys. Rev. Lett. 102, 108001 (2009)]. Assuming a feedback control mechanism of self-propulsion force generated by each ant using information about the distance from the ant in front, our model captures all the main features observed in the experiment. The distance headway distribution shows a maximum corresponding to separations within clusters. The position of this maximum remains independent of average number density. We find a non-equilibrium first-order transition, with the formation of an infinite cluster at a threshold density where all the ants in the system suddenly become part of a single cluster.

Fermat's principle of least time predicts refraction of ant trails at substrate borders.

PubMed

Oettler, Jan; Schmid, Volker S; Zankl, Niko; Rey, Olivier; Dress, Andreas; Heinze, Jürgen

2013-01-01

Fermat's principle of least time states that light rays passing through different media follow the fastest (and not the most direct) path between two points, leading to refraction at medium borders. Humans intuitively employ this rule, e.g., when a lifeguard has to infer the fastest way to traverse both beach and water to reach a swimmer in need. Here, we tested whether foraging ants also follow Fermat's principle when forced to travel on two surfaces that differentially affected the ants' walking speed. Workers of the little fire ant, Wasmannia auropunctata, established "refracted" pheromone trails to a food source. These trails deviated from the most direct path, but were not different to paths predicted by Fermat's principle. Our results demonstrate a new aspect of decentralized optimization and underline the versatility of the simple yet robust rules governing the self-organization of group-living animals.

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

PubMed Central

Hwang, I-Shyan

2017-01-01

The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized. PMID:29257078

On the nature and shape of tubulin trails: implications on microtubule self-organization.

PubMed

Glade, Nicolas

2012-06-01

Microtubules, major elements of the cell skeleton are, most of the time, well organized in vivo, but they can also show self-organizing behaviors in time and/or space in purified solutions in vitro. Theoretical studies and models based on the concepts of collective dynamics in complex systems, reaction-diffusion processes and emergent phenomena were proposed to explain some of these behaviors. In the particular case of microtubule spatial self-organization, it has been advanced that microtubules could behave like ants, self-organizing by 'talking to each other' by way of hypothetic (because never observed) concentrated chemical trails of tubulin that are expected to be released by their disassembling ends. Deterministic models based on this idea yielded indeed like-looking spatio-temporal self-organizing behaviors. Nevertheless the question remains of whether microscopic tubulin trails produced by individual or bundles of several microtubules are intense enough to allow microtubule self-organization at a macroscopic level. In the present work, by simulating the diffusion of tubulin in microtubule solutions at the microscopic scale, we measure the shape and intensity of tubulin trails and discuss about the assumption of microtubule self-organization due to the production of chemical trails by disassembling microtubules. We show that the tubulin trails produced by individual microtubules or small microtubule arrays are very weak and not elongated even at very high reactive rates. Although the variations of concentration due to such trails are not significant compared to natural fluctuations of the concentration of tubuline in the chemical environment, the study shows that heterogeneities of biochemical composition can form due to microtubule disassembly. They could become significant when produced by numerous microtubule ends located in the same place. Their possible formation could play a role in certain conditions of reaction. In particular, it gives a mesoscopic basis to explain the collective dynamics observed in excitable microtubule solutions showing the propagation of concentration waves of microtubules at the millimeter scale, although we doubt that individual microtubules or bundles can behave like molecular ants.

Spatial-Temporal Reasoning Applications of Computational Intelligence in the Game of Go and Computer Networks

DTIC Science & Technology

2012-01-01

dimensionality, Tesauro used a backpropagation- based , three-layer neural network and implemented the outcome from a self-play game as the reinforcement signal...a school of fish, flock of birds, and colony of ants. Our literature review reveals that no one has used PSO to train the neural network ...trained with a variant of PSO called cellular PSO (CPSO). CSRN is a supervised learning neural network (SLNN). The proposed algorithm for the

Self-Adaptive Stepsize Search Applied to Optimal Structural Design

NASA Astrophysics Data System (ADS)

Nolle, L.; Bland, J. A.

Structural engineering often involves the design of space frames that are required to resist predefined external forces without exhibiting plastic deformation. The weight of the structure and hence the weight of its constituent members has to be as low as possible for economical reasons without violating any of the load constraints. Design spaces are usually vast and the computational costs for analyzing a single design are usually high. Therefore, not every possible design can be evaluated for real-world problems. In this work, a standard structural design problem, the 25-bar problem, has been solved using self-adaptive stepsize search (SASS), a relatively new search heuristic. This algorithm has only one control parameter and therefore overcomes the drawback of modern search heuristics, i.e. the need to first find a set of optimum control parameter settings for the problem at hand. In this work, SASS outperforms simulated-annealing, genetic algorithms, tabu search and ant colony optimization.

Using Ant Colony Optimization for Routing in VLSI Chips

NASA Astrophysics Data System (ADS)

Arora, Tamanna; Moses, Melanie

2009-04-01

Rapid advances in VLSI technology have increased the number of transistors that fit on a single chip to about two billion. A frequent problem in the design of such high performance and high density VLSI layouts is that of routing wires that connect such large numbers of components. Most wire-routing problems are computationally hard. The quality of any routing algorithm is judged by the extent to which it satisfies routing constraints and design objectives. Some of the broader design objectives include minimizing total routed wire length, and minimizing total capacitance induced in the chip, both of which serve to minimize power consumed by the chip. Ant Colony Optimization algorithms (ACO) provide a multi-agent framework for combinatorial optimization by combining memory, stochastic decision and strategies of collective and distributed learning by ant-like agents. This paper applies ACO to the NP-hard problem of finding optimal routes for interconnect routing on VLSI chips. The constraints on interconnect routing are used by ants as heuristics which guide their search process. We found that ACO algorithms were able to successfully incorporate multiple constraints and route interconnects on suite of benchmark chips. On an average, the algorithm routed with total wire length 5.5% less than other established routing algorithms.

Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

PubMed

Li, Yang; Li, Guoqing; Wang, Zhenhao

2015-01-01

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.

PubMed

Mohsen, Abdulqader M

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality.

Application of ant colony optimization in development of models for prediction of anti-HIV-1 activity of HEPT derivatives.

PubMed

Zare-Shahabadi, Vali; Abbasitabar, Fatemeh

2010-09-01

Quantitative structure-activity relationship models were derived for 107 analogs of 1-[(2-hydroxyethoxy) methyl]-6-(phenylthio)thymine, a potent inhibitor of the HIV-1 reverse transcriptase. The activities of these compounds were investigated by means of multiple linear regression (MLR) technique. An ant colony optimization algorithm, called Memorized_ACS, was applied for selecting relevant descriptors and detecting outliers. This algorithm uses an external memory based upon knowledge incorporation from previous iterations. At first, the memory is empty, and then it is filled by running several ACS algorithms. In this respect, after each ACS run, the elite ant is stored in the memory and the process is continued to fill the memory. Here, pheromone updating is performed by all elite ants collected in the memory; this results in improvements in both exploration and exploitation behaviors of the ACS algorithm. The memory is then made empty and is filled again by performing several ACS algorithms using updated pheromone trails. This process is repeated for several iterations. At the end, the memory contains several top solutions for the problem. Number of appearance of each descriptor in the external memory is a good criterion for its importance. Finally, prediction is performed by the elitist ant, and interpretation is carried out by considering the importance of each descriptor. The best MLR model has a training error of 0.47 log (1/EC(50)) units (R(2) = 0.90) and a prediction error of 0.76 log (1/EC(50)) units (R(2) = 0.88). Copyright 2010 Wiley Periodicals, Inc.

The optimal algorithm for Multi-source RS image fusion.

PubMed

Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

2016-01-01

In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

[Application of rational ant colony optimization to improve the reproducibility degree of laser three-dimensional copy].

PubMed

Cui, Xiao-Yan; Huo, Zhong-Gang; Xin, Zhong-Hua; Tian, Xiao; Zhang, Xiao-Dong

2013-07-01

Three-dimensional (3D) copying of artificial ears and pistol printing are pushing laser three-dimensional copying technique to a new page. Laser three-dimensional scanning is a fresh field in laser application, and plays an irreplaceable part in three-dimensional copying. Its accuracy is the highest among all present copying techniques. Reproducibility degree marks the agreement of copied object with the original object on geometry, being the most important index property in laser three-dimensional copying technique. In the present paper, the error of laser three-dimensional copying was analyzed. The conclusion is that the data processing to the point cloud of laser scanning is the key technique to reduce the error and increase the reproducibility degree. The main innovation of this paper is as follows. On the basis of traditional ant colony optimization, rational ant colony optimization algorithm proposed by the author was applied to the laser three-dimensional copying as a new algorithm, and was put into practice. Compared with customary algorithm, rational ant colony optimization algorithm shows distinct advantages in data processing of laser three-dimensional copying, reducing the error and increasing the reproducibility degree of the copy.

A joint swarm intelligence algorithm for multi-user detection in MIMO-OFDM system

NASA Astrophysics Data System (ADS)

Hu, Fengye; Du, Dakun; Zhang, Peng; Wang, Zhijun

2014-11-01

In the multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, traditional multi-user detection (MUD) algorithms that usually used to suppress multiple access interference are difficult to balance system detection performance and the complexity of the algorithm. To solve this problem, this paper proposes a joint swarm intelligence algorithm called Ant Colony and Particle Swarm Optimisation (AC-PSO) by integrating particle swarm optimisation (PSO) and ant colony optimisation (ACO) algorithms. According to simulation results, it has been shown that, with low computational complexity, the MUD for the MIMO-OFDM system based on AC-PSO algorithm gains comparable MUD performance with maximum likelihood algorithm. Thus, the proposed AC-PSO algorithm provides a satisfactory trade-off between computational complexity and detection performance.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

Swarm Intelligence Optimization and Its Applications

NASA Astrophysics Data System (ADS)

Ding, Caichang; Lu, Lu; Liu, Yuanchao; Peng, Wenxiu

Swarm Intelligence is a computational and behavioral metaphor for solving distributed problems inspired from biological examples provided by social insects such as ants, termites, bees, and wasps and by swarm, herd, flock, and shoal phenomena in vertebrates such as fish shoals and bird flocks. An example of successful research direction in Swarm Intelligence is ant colony optimization (ACO), which focuses on combinatorial optimization problems. Ant algorithms can be viewed as multi-agent systems (ant colony), where agents (individual ants) solve required tasks through cooperation in the same way that ants create complex social behavior from the combined efforts of individuals.

A pheromone-rate-based analysis on the convergence time of ACO algorithm.

PubMed

Huang, Han; Wu, Chun-Guo; Hao, Zhi-Feng

2009-08-01

Ant colony optimization (ACO) has widely been applied to solve combinatorial optimization problems in recent years. There are few studies, however, on its convergence time, which reflects how many iteration times ACO algorithms spend in converging to the optimal solution. Based on the absorbing Markov chain model, we analyze the ACO convergence time in this paper. First, we present a general result for the estimation of convergence time to reveal the relationship between convergence time and pheromone rate. This general result is then extended to a two-step analysis of the convergence time, which includes the following: 1) the iteration time that the pheromone rate spends on reaching the objective value and 2) the convergence time that is calculated with the objective pheromone rate in expectation. Furthermore, four brief ACO algorithms are investigated by using the proposed theoretical results as case studies. Finally, the conclusions of the case studies that the pheromone rate and its deviation determine the expected convergence time are numerically verified with the experiment results of four one-ant ACO algorithms and four ten-ant ACO algorithms.

An Adaptive Pheromone Updation of the Ant-System using LMS Technique

NASA Astrophysics Data System (ADS)

Paul, Abhishek; Mukhopadhyay, Sumitra

2010-10-01

We propose a modified model of pheromone updation for Ant-System, entitled as Adaptive Ant System (AAS), using the properties of basic Adaptive Filters. Here, we have exploited the properties of Least Mean Square (LMS) algorithm for the pheromone updation to find out the best minimum tour for the Travelling Salesman Problem (TSP). TSP library has been used for the selection of benchmark problem and the proposed AAS determines the minimum tour length for the problems containing large number of cities. Our algorithm shows effective results and gives least tour length in most of the cases as compared to other existing approaches.

Optic disc detection using ant colony optimization

NASA Astrophysics Data System (ADS)

Dias, Marcy A.; Monteiro, Fernando C.

2012-09-01

The retinal fundus images are used in the treatment and diagnosis of several eye diseases, such as diabetic retinopathy and glaucoma. This paper proposes a new method to detect the optic disc (OD) automatically, due to the fact that the knowledge of the OD location is essential to the automatic analysis of retinal images. Ant Colony Optimization (ACO) is an optimization algorithm inspired by the foraging behaviour of some ant species that has been applied in image processing for edge detection. Recently, the ACO was used in fundus images to detect edges, and therefore, to segment the OD and other anatomical retinal structures. We present an algorithm for the detection of OD in the retina which takes advantage of the Gabor wavelet transform, entropy and ACO algorithm. Forty images of the retina from DRIVE database were used to evaluate the performance of our method.

Annealing Ant Colony Optimization with Mutation Operator for Solving TSP

PubMed Central

2016-01-01

Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality. PMID:27999590

ACOustic: A Nature-Inspired Exploration Indicator for Ant Colony Optimization.

PubMed

Sagban, Rafid; Ku-Mahamud, Ku Ruhana; Abu Bakar, Muhamad Shahbani

2015-01-01

A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens' acoustics of their ant hosts. The parasites' reaction results from their ability to indicate the state of penetration. The proposed indicator solves the problem of robustness that results from the difference of magnitudes in the distance's matrix, especially when combinatorial optimization problems with rugged fitness landscape are applied. The performance of the proposed indicator is evaluated against the existing indicators in six variants of ant colony optimization algorithms. Instances for travelling salesman problem and quadratic assignment problem are used in the experimental evaluation. The analytical results showed that the proposed indicator is more informative and more robust.

Predicting Flood in Perlis Using Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Nadia Sabri, Syaidatul; Saian, Rizauddin

2017-06-01

Flood forecasting is widely being studied in order to reduce the effect of flood such as loss of property, loss of life and contamination of water supply. Usually flood occurs due to continuous heavy rainfall. This study used a variant of Ant Colony Optimization (ACO) algorithm named the Ant-Miner to develop the classification prediction model to predict flood. However, since Ant-Miner only accept discrete data, while rainfall data is a time series data, a pre-processing steps is needed to discretize the rainfall data initially. This study used a technique called the Symbolic Aggregate Approximation (SAX) to convert the rainfall time series data into discrete data. As an addition, Simple K-Means algorithm was used to cluster the data produced by SAX. The findings show that the predictive accuracy of the classification prediction model is more than 80%.

A Stochastic Inversion Method for Potential Field Data: Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Liu, Tianyou

2014-07-01

Simulating natural ants' foraging behavior, the ant colony optimization (ACO) algorithm performs excellently in combinational optimization problems, for example the traveling salesman problem and the quadratic assignment problem. However, the ACO is seldom used to inverted for gravitational and magnetic data. On the basis of the continuous and multi-dimensional objective function for potential field data optimization inversion, we present the node partition strategy ACO (NP-ACO) algorithm for inversion of model variables of fixed shape and recovery of physical property distributions of complicated shape models. We divide the continuous variables into discrete nodes and ants directionally tour the nodes by use of transition probabilities. We update the pheromone trails by use of Gaussian mapping between the objective function value and the quantity of pheromone. It can analyze the search results in real time and promote the rate of convergence and precision of inversion. Traditional mapping, including the ant-cycle system, weaken the differences between ant individuals and lead to premature convergence. We tested our method by use of synthetic data and real data from scenarios involving gravity and magnetic anomalies. The inverted model variables and recovered physical property distributions were in good agreement with the true values. The ACO algorithm for binary representation imaging and full imaging can recover sharper physical property distributions than traditional linear inversion methods. The ACO has good optimization capability and some excellent characteristics, for example robustness, parallel implementation, and portability, compared with other stochastic metaheuristics.

A tunable algorithm for collective decision-making.

PubMed

Pratt, Stephen C; Sumpter, David J T

2006-10-24

Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.

Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

NASA Astrophysics Data System (ADS)

Hou, Huirang; Zheng, Dandan; Nie, Laixiao

2015-04-01

For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until -10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method.

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

NASA Astrophysics Data System (ADS)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

An Information Theoretic Framework and Self-organizing Agent- based Sensor Network Architecture for Power Plant Condition Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loparo, Kenneth; Kolacinski, Richard; Threeanaew, Wanchat

A central goal of the work was to enable both the extraction of all relevant information from sensor data, and the application of information gained from appropriate processing and fusion at the system level to operational control and decision-making at various levels of the control hierarchy through: 1. Exploiting the deep connection between information theory and the thermodynamic formalism, 2. Deployment using distributed intelligent agents with testing and validation in a hardware-in-the loop simulation environment. Enterprise architectures are the organizing logic for key business processes and IT infrastructure and, while the generality of current definitions provides sufficient flexibility, the currentmore » architecture frameworks do not inherently provide the appropriate structure. Of particular concern is that existing architecture frameworks often do not make a distinction between ``data'' and ``information.'' This work defines an enterprise architecture for health and condition monitoring of power plant equipment and further provides the appropriate foundation for addressing shortcomings in current architecture definition frameworks through the discovery of the information connectivity between the elements of a power generation plant. That is, to identify the correlative structure between available observations streams using informational measures. The principle focus here is on the implementation and testing of an emergent, agent-based, algorithm based on the foraging behavior of ants for eliciting this structure and on measures for characterizing differences between communication topologies. The elicitation algorithms are applied to data streams produced by a detailed numerical simulation of Alstom’s 1000 MW ultra-super-critical boiler and steam plant. The elicitation algorithm and topology characterization can be based on different informational metrics for detecting connectivity, e.g. mutual information and linear correlation.« less

Virtual spring damper method for nonholonomic robotic swarm self-organization and leader following

NASA Astrophysics Data System (ADS)

Wiech, Jakub; Eremeyev, Victor A.; Giorgio, Ivan

2018-04-01

In this paper, we demonstrate a method for self-organization and leader following of nonholonomic robotic swarm based on spring damper mesh. By self-organization of swarm robots we mean the emergence of order in a swarm as the result of interactions among the single robots. In other words the self-organization of swarm robots mimics some natural behavior of social animals like ants among others. The dynamics of two-wheel robot is derived, and a relation between virtual forces and robot control inputs is defined in order to establish stable swarm formation. Two cases of swarm control are analyzed. In the first case the swarm cohesion is achieved by virtual spring damper mesh connecting nearest neighboring robots without designated leader. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. The paper ends with numeric simulation for performance evaluation of the proposed control method.

Fermat’s Principle of Least Time Predicts Refraction of Ant Trails at Substrate Borders

PubMed Central

Zankl, Niko; Rey, Olivier; Dress, Andreas; Heinze, Jürgen

2013-01-01

Fermat’s principle of least time states that light rays passing through different media follow the fastest (and not the most direct) path between two points, leading to refraction at medium borders. Humans intuitively employ this rule, e.g., when a lifeguard has to infer the fastest way to traverse both beach and water to reach a swimmer in need. Here, we tested whether foraging ants also follow Fermat’s principle when forced to travel on two surfaces that differentially affected the ants’ walking speed. Workers of the little fire ant, Wasmannia auropunctata, established “refracted” pheromone trails to a food source. These trails deviated from the most direct path, but were not different to paths predicted by Fermat’s principle. Our results demonstrate a new aspect of decentralized optimization and underline the versatility of the simple yet robust rules governing the self-organization of group-living animals. PMID:23527263

Adaptive algorithms of position and energy reconstruction in Anger-camera type detectors: experimental data processing in ANTS

NASA Astrophysics Data System (ADS)

Morozov, A.; Defendi, I.; Engels, R.; Fraga, F. A. F.; Fraga, M. M. F. R.; Gongadze, A.; Guerard, B.; Jurkovic, M.; Kemmerling, G.; Manzin, G.; Margato, L. M. S.; Niko, H.; Pereira, L.; Petrillo, C.; Peyaud, A.; Piscitelli, F.; Raspino, D.; Rhodes, N. J.; Sacchetti, F.; Schooneveld, E. M.; Solovov, V.; Van Esch, P.; Zeitelhack, K.

2013-05-01

The software package ANTS (Anger-camera type Neutron detector: Toolkit for Simulations), developed for simulation of Anger-type gaseous detectors for thermal neutron imaging was extended to include a module for experimental data processing. Data recorded with a sensor array containing up to 100 photomultiplier tubes (PMT) or silicon photomultipliers (SiPM) in a custom configuration can be loaded and the positions and energies of the events can be reconstructed using the Center-of-Gravity, Maximum Likelihood or Least Squares algorithm. A particular strength of the new module is the ability to reconstruct the light response functions and relative gains of the photomultipliers from flood field illumination data using adaptive algorithms. The performance of the module is demonstrated with simulated data generated in ANTS and experimental data recorded with a 19 PMT neutron detector. The package executables are publicly available at http://coimbra.lip.pt/~andrei/

Self-organization and clustering algorithms

NASA Technical Reports Server (NTRS)

Bezdek, James C.

1991-01-01

Kohonen's feature maps approach to clustering is often likened to the k or c-means clustering algorithms. Here, the author identifies some similarities and differences between the hard and fuzzy c-Means (HCM/FCM) or ISODATA algorithms and Kohonen's self-organizing approach. The author concludes that some differences are significant, but at the same time there may be some important unknown relationships between the two methodologies. Several avenues of research are proposed.

Identification of an ant queen pheromone regulating worker sterility.

PubMed

Holman, Luke; Jørgensen, Charlotte G; Nielsen, John; d'Ettorre, Patrizia

2010-12-22

The selective forces that shape and maintain eusocial societies are an enduring puzzle in evolutionary biology. Ordinarily sterile workers can usually reproduce given the right conditions, so the factors regulating reproductive division of labour may provide insight into why eusociality has persisted over evolutionary time. Queen-produced pheromones that affect worker reproduction have been implicated in diverse taxa, including ants, termites, wasps and possibly mole rats, but to date have only been definitively identified in the honeybee. Using the black garden ant Lasius niger, we isolate the first sterility-regulating ant queen pheromone. The pheromone is a cuticular hydrocarbon that comprises the majority of the chemical profile of queens and their eggs, and also affects worker behaviour, by reducing aggression towards objects bearing the pheromone. We further show that the pheromone elicits a strong response in worker antennae and that its production by queens is selectively reduced following an immune challenge. These results suggest that the pheromone has a central role in colony organization and support the hypothesis that worker sterility represents altruistic self-restraint in response to an honest quality signal.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

PubMed Central

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

Fire ants self-assemble into waterproof rafts to survive floods

PubMed Central

Mlot, Nathan J.; Tovey, Craig A.; Hu, David L.

2011-01-01

Why does a single fire ant Solenopsis invicta struggle in water, whereas a group can float effortlessly for days? We use time-lapse photography to investigate how fire ants S. invicta link their bodies together to build waterproof rafts. Although water repellency in nature has been previously viewed as a static material property of plant leaves and insect cuticles, we here demonstrate a self-assembled hydrophobic surface. We find that ants can considerably enhance their water repellency by linking their bodies together, a process analogous to the weaving of a waterproof fabric. We present a model for the rate of raft construction based on observations of ant trajectories atop the raft. Central to the construction process is the trapping of ants at the raft edge by their neighbors, suggesting that some “cooperative” behaviors may rely upon coercion. PMID:21518911

An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

DTIC Science & Technology

2015-01-01

programming formulation of traveling salesman problems , Journal of the ACM, 7(4), 326-329. Montemanni, R., Gambardella, L. M., Rizzoli, A.E., Donati. A.V... salesman problem . BioSystem, 43(1), 73-81. Dror, M., Trudeau, P., 1989. Savings by split delivery routing. Transportation Science, 23, 141- 145. Dror, M...An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to solve the Split Delivery Vehicle Routing Problem Authors: Gautham Rajappa

Effective intervention strategies to improve health outcomes for cardiovascular disease patients with low health literacy skills: a systematic review.

PubMed

Lee, Tae Wha; Lee, Seon Heui; Kim, Hye Hyun; Kang, Soo Jin

2012-12-01

Systematic studies on the relationship between health literacy and health outcomes demonstrate that as health literacy declines, patients engage in fewer preventive health and self-care behaviors and have worse disease-related knowledge. The purpose of this study was to identify effective intervention strategies to improve health outcomes in patients with cardiovascular disease and low literacy skills. This study employs the following criteria recommended by Khan Kunz, Keijnen, and Antes (2003) for systematic review: framing question, identifying relevant literature, assessing quality of the literature, summarizing the evidence, and interpreting the finding. A total of 235 articles were reviewed by the research team, and 9 articles met inclusion criteria. Although nine studies were reviewed for their health outcomes, only six studies, which had a positive quality grade evaluation were used to recommend effective intervention strategies. Interventions were categorized into three groups: tailored counseling, self-monitoring, and periodic reminder. The main strategies used to improve health outcomes of low literacy patients included tailored counseling, improved provider-patient interactions, organizing information by patient preference, self-care algorithms, and self-directed learning. Specific strategies included written materials tailored to appropriate reading levels, materials using plain language, emphasizing key points with large font size, and using visual items such as icons or color codes. With evidence-driven strategies, health care professionals can use tailored interventions to provide better health education and counseling that meets patient needs and improves health outcomes. Copyright © 2012. Published by Elsevier B.V.

A multilevel ant colony optimization algorithm for classical and isothermic DNA sequencing by hybridization with multiplicity information available.

PubMed

Kwarciak, Kamil; Radom, Marcin; Formanowicz, Piotr

2016-04-01

The classical sequencing by hybridization takes into account a binary information about sequence composition. A given element from an oligonucleotide library is or is not a part of the target sequence. However, the DNA chip technology has been developed and it enables to receive a partial information about multiplicity of each oligonucleotide the analyzed sequence consist of. Currently, it is not possible to assess the exact data of such type but even partial information should be very useful. Two realistic multiplicity information models are taken into consideration in this paper. The first one, called "one and many" assumes that it is possible to obtain information if a given oligonucleotide occurs in a reconstructed sequence once or more than once. According to the second model, called "one, two and many", one is able to receive from biochemical experiment information if a given oligonucleotide is present in an analyzed sequence once, twice or at least three times. An ant colony optimization algorithm has been implemented to verify the above models and to compare with existing algorithms for sequencing by hybridization which utilize the additional information. The proposed algorithm solves the problem with any kind of hybridization errors. Computational experiment results confirm that using even the partial information about multiplicity leads to increased quality of reconstructed sequences. Moreover, they also show that the more precise model enables to obtain better solutions and the ant colony optimization algorithm outperforms the existing ones. Test data sets and the proposed ant colony optimization algorithm are available on: http://bioserver.cs.put.poznan.pl/download/ACO4mSBH.zip. Copyright © 2016 Elsevier Ltd. All rights reserved.

TACD: a transportable ant colony discrimination model for corporate bankruptcy prediction

NASA Astrophysics Data System (ADS)

Lalbakhsh, Pooia; Chen, Yi-Ping Phoebe

2017-05-01

This paper presents a transportable ant colony discrimination strategy (TACD) to predict corporate bankruptcy, a topic of vital importance that is attracting increasing interest in the field of economics. The proposed algorithm uses financial ratios to build a binary prediction model for companies with the two statuses of bankrupt and non-bankrupt. The algorithm takes advantage of an improved version of continuous ant colony optimisation (CACO) at the core, which is used to create an accurate, simple and understandable linear model for discrimination. This also enables the algorithm to work with continuous values, leading to more efficient learning and adaption by avoiding data discretisation. We conduct a comprehensive performance evaluation on three real-world data sets under a stratified cross-validation strategy. In three different scenarios, TACD is compared with 11 other bankruptcy prediction strategies. We also discuss the efficiency of the attribute selection methods used in the experiments. In addition to its simplicity and understandability, statistical significance tests prove the efficiency of TACD against the other prediction algorithms in both measures of AUC and accuracy.

Ant colony optimisation-direct cover: a hybrid ant colony direct cover technique for multi-level synthesis of multiple-valued logic functions

NASA Astrophysics Data System (ADS)

Abd-El-Barr, Mostafa

2010-12-01

The use of non-binary (multiple-valued) logic in the synthesis of digital systems can lead to savings in chip area. Advances in very large scale integration (VLSI) technology have enabled the successful implementation of multiple-valued logic (MVL) circuits. A number of heuristic algorithms for the synthesis of (near) minimal sum-of products (two-level) realisation of MVL functions have been reported in the literature. The direct cover (DC) technique is one such algorithm. The ant colony optimisation (ACO) algorithm is a meta-heuristic that uses constructive greediness to explore a large solution space in finding (near) optimal solutions. The ACO algorithm mimics the ant's behaviour in the real world in using the shortest path to reach food sources. We have previously introduced an ACO-based heuristic for the synthesis of two-level MVL functions. In this article, we introduce the ACO-DC hybrid technique for the synthesis of multi-level MVL functions. The basic idea is to use an ant to decompose a given MVL function into a number of levels and then synthesise each sub-function using a DC-based technique. The results obtained using the proposed approach are compared to those obtained using existing techniques reported in the literature. A benchmark set consisting of 50,000 randomly generated 2-variable 4-valued functions is used in the comparison. The results obtained using the proposed ACO-DC technique are shown to produce efficient realisation in terms of the average number of gates (as a measure of chip area) needed for the synthesis of a given MVL function.

Study on bi-directional pedestrian movement using ant algorithms

NASA Astrophysics Data System (ADS)

Sibel, Gokce; Ozhan, Kayacan

2016-01-01

A cellular automata model is proposed to simulate bi-directional pedestrian flow. Pedestrian movement is investigated by using ant algorithms. Ants communicate with each other by dropping a chemical, called a pheromone, on the substrate while crawling forward. Similarly, it is considered that oppositely moving pedestrians drop ‘visual pheromones’ on their way and the visual pheromones might cause attractive or repulsive interactions. This pheromenon is introduced into modelling the pedestrians’ walking preference. In this way, the decision-making process of pedestrians will be based on ‘the instinct of following’. At some densities, the relationships of velocity-density and flux-density are analyzed for different evaporation rates of visual pheromones. Lane formation and phase transition are observed for certain evaporation rates of visual pheromones.

An element search ant colony technique for solving virtual machine placement problem

NASA Astrophysics Data System (ADS)

Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

2017-09-01

The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

Microsporidian and viral pathogens for the biological control of imported fire ants: can we walk the talk?

USDA-ARS?s Scientific Manuscript database

. Invasive ants are among the most serious of arthropod invaders. These ants infest a wide range of habitats and impact biodiversity, agriculture, and human health. Self-sustaining biological control is one of the few hopes for permanent regional suppression of these established invasive ants. Fo...

Ant colony system algorithm for the optimization of beer fermentation control.

PubMed

Xiao, Jie; Zhou, Ze-Kui; Zhang, Guang-Xin

2004-12-01

Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.

Self-organization processes in field-invasion team sports : implications for leadership.

PubMed

Passos, Pedro; Araújo, Duarte; Davids, Keith

2013-01-01

In nature, the interactions between agents in a complex system (fish schools; colonies of ants) are governed by information that is locally created. Each agent self-organizes (adjusts) its behaviour, not through a central command centre, but based on variables that emerge from the interactions with other system agents in the neighbourhood. Self-organization has been proposed as a mechanism to explain the tendencies for individual performers to interact with each other in field-invasion sports teams, displaying functional co-adaptive behaviours, without the need for central control. The relevance of self-organization as a mechanism that explains pattern-forming dynamics within attacker-defender interactions in field-invasion sports has been sustained in the literature. Nonetheless, other levels of interpersonal coordination, such as intra-team interactions, still raise important questions, particularly with reference to the role of leadership or match strategies that have been prescribed in advance by a coach. The existence of key properties of complex systems, such as system degeneracy, nonlinearity or contextual dependency, suggests that self-organization is a functional mechanism to explain the emergence of interpersonal coordination tendencies within intra-team interactions. In this opinion article we propose how leadership may act as a key constraint on the emergent, self-organizational tendencies of performers in field-invasion sports.

Marking individual ants for behavioral sampling in a laboratory colony.

PubMed

Holbrook, C Tate

2009-07-01

Ant societies are tractable and malleable, two features that make them ideal models for probing the organization of complex biological systems. The ability to identify specific individuals while they function as part of a colony permits an integrative analysis of social complexity, including self-organizational processes (i.e., how individual-level properties and social interactions give rise to emergent, colony-level attributes such as division of labor and collective decision making). Effects of genotype, nutrition, and physiology on individual behavior and the organization of work also can be investigated in this manner, through correlative and manipulative approaches. Moreover, aspects of colony demography (e.g., colony size, and age and size distributions of workers) can be altered experimentally to examine colony development and regulatory mechanisms underlying colony homeostasis and resiliency. This protocol describes how to sample the behavior of ants living in a colony under laboratory conditions. Specifically, it outlines how to identify and observe individuals within a colony, an approach that can be used to quantify individual- and colony-level patterns of behavior. When a lower-resolution measure of overall group behavior is desired, individual identities might not be required. Given the diversity of ants and their study, this protocol provides a very general methodology; the details can be modified according to the body size, colony size, and ecology of the focal species, as well as to specific research aims. These basic techniques can also be extended to more advanced experimental designs such as manipulation of colony demography and hormone treatment.

Asteroid Exploration with Autonomic Systems

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Christopher; Hinchey, Mike

2004-01-01

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. The prospective ANTS (Autonomous Nano Technology Swarm) mission comprises autonomous agents including worker agents (small spacecra3) designed to cooperate in asteroid exploration under the overall authoriq of at least one ruler agent (a larger spacecraft) whose goal is to cause science data to be returned to Earth. The ANTS team (ruler plus workers and messenger agents), but not necessarily any individual on the team, will exhibit behaviors that qualify it as an autonomic system, where an autonomic system is defined as a system that self-reconfigures, self-optimizes, self-heals, and self-protects. Autonomic system concepts lead naturally to realistic, scalable architectures rich in capabilities and behaviors. In-depth consideration of a major mission like ANTS in terms of autonomic systems brings new insights into alternative definitions of autonomic behavior. This paper gives an overview of the ANTS mission and discusses the autonomic properties of the mission.

Rationality in collective decision-making by ant colonies.

PubMed

Edwards, Susan C; Pratt, Stephen C

2009-10-22

Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants' decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals.

Ant colony algorithm for clustering in portfolio optimization

NASA Astrophysics Data System (ADS)

Subekti, R.; Sari, E. R.; Kusumawati, R.

2018-03-01

This research aims to describe portfolio optimization using clustering methods with ant colony approach. Two stock portfolios of LQ45 Indonesia is proposed based on the cluster results obtained from ant colony optimization (ACO). The first portfolio consists of assets with ant colony displacement opportunities beyond the defined probability limits of the researcher, where the weight of each asset is determined by mean-variance method. The second portfolio consists of two assets with the assumption that each asset is a cluster formed from ACO. The first portfolio has a better performance compared to the second portfolio seen from the Sharpe index.

Adapting an Ant Colony Metaphor for Multi-Robot Chemical Plume Tracing

PubMed Central

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments. PMID:22666056

Adapting an ant colony metaphor for multi-robot chemical plume tracing.

PubMed

Meng, Qing-Hao; Yang, Wei-Xing; Wang, Yang; Li, Fei; Zeng, Ming

2012-01-01

We consider chemical plume tracing (CPT) in time-varying airflow environments using multiple mobile robots. The purpose of CPT is to approach a gas source with a previously unknown location in a given area. Therefore, the CPT could be considered as a dynamic optimization problem in continuous domains. The traditional ant colony optimization (ACO) algorithm has been successfully used for combinatorial optimization problems in discrete domains. To adapt the ant colony metaphor to the multi-robot CPT problem, the two-dimension continuous search area is discretized into grids and the virtual pheromone is updated according to both the gas concentration and wind information. To prevent the adapted ACO algorithm from being prematurely trapped in a local optimum, the upwind surge behavior is adopted by the robots with relatively higher gas concentration in order to explore more areas. The spiral surge (SS) algorithm is also examined for comparison. Experimental results using multiple real robots in two indoor natural ventilated airflow environments show that the proposed CPT method performs better than the SS algorithm. The simulation results for large-scale advection-diffusion plume environments show that the proposed method could also work in outdoor meandering plume environments.

Joint optimization of maintenance, buffers and machines in manufacturing lines

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Ancient village fire escape path planning based on improved ant colony algorithm

NASA Astrophysics Data System (ADS)

Xia, Wei; Cao, Kang; Hu, QianChuan

2017-06-01

The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.

Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems.

PubMed

Mavrovouniotis, Michalis; Muller, Felipe M; Yang, Shengxiang

2016-06-13

For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems due to their adaptation capabilities. It has been shown that the integration of local search operators can significantly improve the performance of ACO. In this paper, a memetic ACO algorithm, where a local search operator (called unstring and string) is integrated into ACO, is proposed to address DTSPs. The best solution from ACO is passed to the local search operator, which removes and inserts cities in such a way that improves the solution quality. The proposed memetic ACO algorithm is designed to address both symmetric and asymmetric DTSPs. The experimental results show the efficiency of the proposed memetic algorithm for addressing DTSPs in comparison with other state-of-the-art algorithms.

Application of ant colony algorithm in path planning of the data center room robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Ma, Jianming; Wang, Ying

2017-05-01

According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.

A modify ant colony optimization for the grid jobs scheduling problem with QoS requirements

NASA Astrophysics Data System (ADS)

Pu, Xun; Lu, XianLiang

2011-10-01

Job scheduling with customers' quality of service (QoS) requirement is challenging in grid environment. In this paper, we present a modify Ant colony optimization (MACO) for the Job scheduling problem in grid. Instead of using the conventional construction approach to construct feasible schedules, the proposed algorithm employs a decomposition method to satisfy the customer's deadline and cost requirements. Besides, a new mechanism of service instances state updating is embedded to improve the convergence of MACO. Experiments demonstrate the effectiveness of the proposed algorithm.

An incremental anomaly detection model for virtual machines.

PubMed

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform.

An incremental anomaly detection model for virtual machines

PubMed Central

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform. PMID:29117245

Dynamic routing and spectrum assignment based on multilayer virtual topology and ant colony optimization in elastic software-defined optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-07-01

Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.

Agency problems in hospitals participating in self-management project under global budget system in Taiwan.

PubMed

Yan, Yu-Hua; Hsu, Shuofen; Yang, Chen-Wei; Fang, Shih-Chieh

2010-02-01

The main purposes of this study are to clarify the agency problems in the hospitals participating in self-management project within the context of Global Budgeting Payment System regulated by Taiwan government, and also to provide some suggestions for hospital administrator and health policy maker in reducing the waste of healthcare resources resulting from agency problems. For the purposes above, this study examines the relationships between two agency problems (ex ante moral hazard and ex post moral hazard) aroused among the hospitals and Bureau of National Health Insurance in Taiwan's health care sector. This study empirically tested the theoretical model at organization level. The findings suggest that the hospital's ex ante moral hazards before participating the self-management project do have some influence on its ex post moral hazards after participating the self-management project. This study concludes that the goal conflict between the agents and the principal certainly exist. The principal tries hard to control the expenditure escalation and keep the financial balance, but the agents have to subsist within limited healthcare resources. Therefore, the agency cost would definitely occur due to the conflicts between both parties. According to the results of the research, some suggestions and related management concepts were proposed at the end of the paper.

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

An efficient, large-scale, non-lattice-detection algorithm for exhaustive structural auditing of biomedical ontologies.

PubMed

Zhang, Guo-Qiang; Xing, Guangming; Cui, Licong

2018-04-01

One of the basic challenges in developing structural methods for systematic audition on the quality of biomedical ontologies is the computational cost usually involved in exhaustive sub-graph analysis. We introduce ANT-LCA, a new algorithm for computing all non-trivial lowest common ancestors (LCA) of each pair of concepts in the hierarchical order induced by an ontology. The computation of LCA is a fundamental step for non-lattice approach for ontology quality assurance. Distinct from existing approaches, ANT-LCA only computes LCAs for non-trivial pairs, those having at least one common ancestor. To skip all trivial pairs that may be of no practical interest, ANT-LCA employs a simple but innovative algorithmic strategy combining topological order and dynamic programming to keep track of non-trivial pairs. We provide correctness proofs and demonstrate a substantial reduction in computational time for two largest biomedical ontologies: SNOMED CT and Gene Ontology (GO). ANT-LCA achieved an average computation time of 30 and 3 sec per version for SNOMED CT and GO, respectively, about 2 orders of magnitude faster than the best known approaches. Our algorithm overcomes a fundamental computational barrier in sub-graph based structural analysis of large ontological systems. It enables the implementation of a new breed of structural auditing methods that not only identifies potential problematic areas, but also automatically suggests changes to fix the issues. Such structural auditing methods can lead to more effective tools supporting ontology quality assurance work. Copyright © 2018 Elsevier Inc. All rights reserved.

Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem.

PubMed

Zamdborg, Leonid; Holloway, David M; Merelo, Juan J; Levchenko, Vladimir F; Spirov, Alexander V

2015-06-10

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of "genomic parasites", such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts.

Forced evolution in silico by artificial transposons and their genetic operators: The ant navigation problem

PubMed Central

Zamdborg, Leonid; Holloway, David M.; Merelo, Juan J.; Levchenko, Vladimir F.; Spirov, Alexander V.

2015-01-01

Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention. We believe that a vital direction in this field must be algorithms that model the activity of “genomic parasites”, such as transposons, in biological evolution. Many evolutionary biologists posit that it is the co-evolution of populations with their genomic parasites that permits the high efficiency of evolutionary searches found in the living world. This publication is our first step in the direction of developing a minimal assortment of algorithms that simulate the role of genomic parasites. Specifically, we started in the domain of genetic algorithms (GA) and selected the Artificial Ant Problem as a test case. This navigation problem is widely known as a classical benchmark test and possesses a large body of literature. We add new objects to the standard toolkit of GA - artificial transposons and a collection of operators that operate on them. We define these artificial transposons as a fragment of an ant's code with properties that cause it to stand apart from the rest. The minimal set of operators for transposons is a transposon mutation operator, and a transposon reproduction operator that causes a transposon to multiply within the population of hosts. An analysis of the population dynamics of transposons within the course of ant evolution showed that transposons are involved in the processes of propagation and selection of blocks of ant navigation programs. During this time, the speed of evolutionary search increases significantly. We concluded that artificial transposons, analogous to real transposons, are truly capable of acting as intelligent mutators that adapt in response to an evolutionary problem in the course of co-evolution with their hosts. PMID:25767296

Improved understanding of the searching behavior of ant colony optimization algorithms applied to the water distribution design problem

NASA Astrophysics Data System (ADS)

Zecchin, A. C.; Simpson, A. R.; Maier, H. R.; Marchi, A.; Nixon, J. B.

2012-09-01

Evolutionary algorithms (EAs) have been applied successfully to many water resource problems, such as system design, management decision formulation, and model calibration. The performance of an EA with respect to a particular problem type is dependent on how effectively its internal operators balance the exploitation/exploration trade-off to iteratively find solutions of an increasing quality. For a given problem, different algorithms are observed to produce a variety of different final performances, but there have been surprisingly few investigations into characterizing how the different internal mechanisms alter the algorithm's searching behavior, in both the objective and decision space, to arrive at this final performance. This paper presents metrics for analyzing the searching behavior of ant colony optimization algorithms, a particular type of EA, for the optimal water distribution system design problem, which is a classical NP-hard problem in civil engineering. Using the proposed metrics, behavior is characterized in terms of three different attributes: (1) the effectiveness of the search in improving its solution quality and entering into optimal or near-optimal regions of the search space, (2) the extent to which the algorithm explores as it converges to solutions, and (3) the searching behavior with respect to the feasible and infeasible regions. A range of case studies is considered, where a number of ant colony optimization variants are applied to a selection of water distribution system optimization problems. The results demonstrate the utility of the proposed metrics to give greater insight into how the internal operators affect each algorithm's searching behavior.

Growing a hypercubical output space in a self-organizing feature map.

PubMed

Bauer, H U; Villmann, T

1997-01-01

Neural maps project data from an input space onto a neuron position in a (often lower dimensional) output space grid in a neighborhood preserving way, with neighboring neurons in the output space responding to neighboring data points in the input space. A map-learning algorithm can achieve an optimal neighborhood preservation only, if the output space topology roughly matches the effective structure of the data in the input space. We here present a growth algorithm, called the GSOM or growing self-organizing map, which enhances a widespread map self-organization process, Kohonen's self-organizing feature map (SOFM), by an adaptation of the output space grid during learning. The GSOM restricts the output space structure to the shape of a general hypercubical shape, with the overall dimensionality of the grid and its extensions along the different directions being subject of the adaptation. This constraint meets the demands of many larger information processing systems, of which the neural map can be a part. We apply our GSOM-algorithm to three examples, two of which involve real world data. Using recently developed methods for measuring the degree of neighborhood preservation in neural maps, we find the GSOM-algorithm to produce maps which preserve neighborhoods in a nearly optimal fashion.

Solving NP-Hard Problems with Physarum-Based Ant Colony System.

PubMed

Liu, Yuxin; Gao, Chao; Zhang, Zili; Lu, Yuxiao; Chen, Shi; Liang, Mingxin; Tao, Li

2017-01-01

NP-hard problems exist in many real world applications. Ant colony optimization (ACO) algorithms can provide approximate solutions for those NP-hard problems, but the performance of ACO algorithms is significantly reduced due to premature convergence and weak robustness, etc. With these observations in mind, this paper proposes a Physarum-based pheromone matrix optimization strategy in ant colony system (ACS) for solving NP-hard problems such as traveling salesman problem (TSP) and 0/1 knapsack problem (0/1 KP). In the Physarum-inspired mathematical model, one of the unique characteristics is that critical tubes can be reserved in the process of network evolution. The optimized updating strategy employs the unique feature and accelerates the positive feedback process in ACS, which contributes to the quick convergence of the optimal solution. Some experiments were conducted using both benchmark and real datasets. The experimental results show that the optimized ACS outperforms other meta-heuristic algorithms in accuracy and robustness for solving TSPs. Meanwhile, the convergence rate and robustness for solving 0/1 KPs are better than those of classical ACS.

A seismic fault recognition method based on ant colony optimization

NASA Astrophysics Data System (ADS)

Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

2018-05-01

Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

PubMed Central

Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

2014-01-01

A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline. PMID:25025089

Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances.

PubMed

Hajjar, Chantal; Hamdan, Hani

2013-10-01

The self-organizing map is a kind of artificial neural network used to map high dimensional data into a low dimensional space. This paper presents a self-organizing map for interval-valued data based on adaptive Mahalanobis distances in order to do clustering of interval data with topology preservation. Two methods based on the batch training algorithm for the self-organizing maps are proposed. The first method uses a common Mahalanobis distance for all clusters. In the second method, the algorithm starts with a common Mahalanobis distance per cluster and then switches to use a different distance per cluster. This process allows a more adapted clustering for the given data set. The performances of the proposed methods are compared and discussed using artificial and real interval data sets. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ants: the supreme soil manipulators

USDA-ARS?s Scientific Manuscript database

This review focuses on the semiochemical interactions between ants and their soil environment. Ants occupy virtually every ecological niche and have evolved mechanisms to not just cope with, but also manipulate soil organisms. The metapleural gland, specific to ants was thought to be the major sourc...

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

PubMed

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John Bo

2008-10-29

We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors.

An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

NASA Astrophysics Data System (ADS)

Ramadhani, T.; Hertono, G. F.; Handari, B. D.

2017-07-01

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed with four dataset from TSPLIB. The results show that the different chosen cities as depots and the three parameters of MMTSP, in which m is the most important parameter, affect the solution.

Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.

Release and establishment of the little decapitating fly Pseudacteon cultellatus on imported fire ants in Florida

USDA-ARS?s Scientific Manuscript database

The little decapitating fly Pseudacteon cultellatus from Argentina was released as a self-sustaining biological control agent against the red imported fire ant, Solenopsis invicta, in Florida to parasitize small fire ant workers associated with multiple-queen colonies. This fly appears to be establi...

The large decapitating fly Pseudacteon litoralis (Diptera: Phoridae): Successfully established on fire ant populations in Alabama

USDA-ARS?s Scientific Manuscript database

The large fire ant decapitating fly, Pseudacteon litoralis Borgmeier from northeastern Argentina was successfully released as a self-sustaining biocontrol agent of imported fire ants in south central Alabama in 2005. Five years later, this fly is firmly established at this site and has expanded out...

The new and computationally efficient MIL-SOM algorithm: potential benefits for visualization and analysis of a large-scale high-dimensional clinically acquired geographic data.

PubMed

Oyana, Tonny J; Achenie, Luke E K; Heo, Joon

2012-01-01

The objective of this paper is to introduce an efficient algorithm, namely, the mathematically improved learning-self organizing map (MIL-SOM) algorithm, which speeds up the self-organizing map (SOM) training process. In the proposed MIL-SOM algorithm, the weights of Kohonen's SOM are based on the proportional-integral-derivative (PID) controller. Thus, in a typical SOM learning setting, this improvement translates to faster convergence. The basic idea is primarily motivated by the urgent need to develop algorithms with the competence to converge faster and more efficiently than conventional techniques. The MIL-SOM algorithm is tested on four training geographic datasets representing biomedical and disease informatics application domains. Experimental results show that the MIL-SOM algorithm provides a competitive, better updating procedure and performance, good robustness, and it runs faster than Kohonen's SOM.

The New and Computationally Efficient MIL-SOM Algorithm: Potential Benefits for Visualization and Analysis of a Large-Scale High-Dimensional Clinically Acquired Geographic Data

PubMed Central

Oyana, Tonny J.; Achenie, Luke E. K.; Heo, Joon

2012-01-01

The objective of this paper is to introduce an efficient algorithm, namely, the mathematically improved learning-self organizing map (MIL-SOM) algorithm, which speeds up the self-organizing map (SOM) training process. In the proposed MIL-SOM algorithm, the weights of Kohonen's SOM are based on the proportional-integral-derivative (PID) controller. Thus, in a typical SOM learning setting, this improvement translates to faster convergence. The basic idea is primarily motivated by the urgent need to develop algorithms with the competence to converge faster and more efficiently than conventional techniques. The MIL-SOM algorithm is tested on four training geographic datasets representing biomedical and disease informatics application domains. Experimental results show that the MIL-SOM algorithm provides a competitive, better updating procedure and performance, good robustness, and it runs faster than Kohonen's SOM. PMID:22481977

Do Ants Need to Estimate the Geometrical Properties of Trail Bifurcations to Find an Efficient Route? A Swarm Robotics Test Bed

PubMed Central

Garnier, Simon; Combe, Maud; Jost, Christian; Theraulaz, Guy

2013-01-01

Interactions between individuals and the structure of their environment play a crucial role in shaping self-organized collective behaviors. Recent studies have shown that ants crossing asymmetrical bifurcations in a network of galleries tend to follow the branch that deviates the least from their incoming direction. At the collective level, the combination of this tendency and the pheromone-based recruitment results in a greater likelihood of selecting the shortest path between the colony's nest and a food source in a network containing asymmetrical bifurcations. It was not clear however what the origin of this behavioral bias is. Here we propose that it results from a simple interaction between the behavior of the ants and the geometry of the network, and that it does not require the ability to measure the angle of the bifurcation. We tested this hypothesis using groups of ant-like robots whose perceptual and cognitive abilities can be fully specified. We programmed them only to lay down and follow light trails, avoid obstacles and move according to a correlated random walk, but not to use more sophisticated orientation methods. We recorded the behavior of the robots in networks of galleries presenting either only symmetrical bifurcations or a combination of symmetrical and asymmetrical bifurcations. Individual robots displayed the same pattern of branch choice as individual ants when crossing a bifurcation, suggesting that ants do not actually measure the geometry of the bifurcations when travelling along a pheromone trail. Finally at the collective level, the group of robots was more likely to select one of the possible shorter paths between two designated areas when moving in an asymmetrical network, as observed in ants. This study reveals the importance of the shape of trail networks for foraging in ants and emphasizes the underestimated role of the geometrical properties of transportation networks in general. PMID:23555202

The Influence Function of Principal Component Analysis by Self-Organizing Rule.

PubMed

Higuchi; Eguchi

1998-07-28

This article is concerned with a neural network approach to principal component analysis (PCA). An algorithm for PCA by the self-organizing rule has been proposed and its robustness observed through the simulation study by Xu and Yuille (1995). In this article, the robustness of the algorithm against outliers is investigated by using the theory of influence function. The influence function of the principal component vector is given in an explicit form. Through this expression, the method is shown to be robust against any directions orthogonal to the principal component vector. In addition, a statistic generated by the self-organizing rule is proposed to assess the influence of data in PCA.

AINTEGUMENTA-LIKE genes have partly overlapping functions with AINTEGUMENTA but make distinct contributions to Arabidopsis thaliana flower development

PubMed Central

Krizek, Beth A.

2015-01-01

AINTEGUMENTA (ANT) is an important regulator of Arabidopsis flower development that has overlapping functions with the related AINTEGUMENTA-LIKE6 (AIL6) gene in floral organ initiation, identity specification, growth, and patterning. Two other AINTEGUMENTA-LIKE (AIL) genes, AIL5 and AIL7, are expressed in developing flowers in spatial domains that partly overlap with those of ANT. Here, it is shown that AIL5 and AIL7 also act in a partially redundant manner with ANT. The results demonstrate that AIL genes exhibit unequal genetic redundancy with roles for AIL5, AIL6, and AIL7 only revealed in the absence of ANT function. ant ail5 and ant ail7 double mutant flowers show alterations in floral organ positioning and growth, sepal fusion, and reductions in petal number. In ant ail5, petals are often replaced by filaments or dramatically reduced in size. ant ail7 double mutants produce increased numbers of carpels, which have defects in valve fusion and a loss of apical tissues. The distinct phenotypes of ant ail5, ant ail7 and the previously characterized ant ail6 indicate that AIL5, AIL6, and AIL7 make unique contributions to flower development. These distinct roles are also supported by genetic analyses of ant ail triple mutants. While ant ail5 ail6 triple mutants closely resemble ant ail6 double mutants, ant ail5 ail7 triple mutants exhibit more severe deviations from the wild type than either ant ail5 or ant ail7 double mutants. Furthermore, it is shown that AIL5, AIL6, and AIL7 act in a dose dependent manners in ant and other mutant backgrounds. PMID:25956884

Honey Bees Inspired Optimization Method: The Bees Algorithm.

PubMed

Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo

2013-11-06

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

Tallgrass prairie ants: their species composition, ecological roles, and response to management

USDA-ARS?s Scientific Manuscript database

Ants are highly influential organisms in terrestrial ecosystems, including the tallgrass prairie, one of the most endangered ecosystems in North America. Through their tunneling, ants affect soil properties and resource availability for animals and plants. Ants also have important ecological roles a...

A novel global Harmony Search method based on Ant Colony Optimisation algorithm

NASA Astrophysics Data System (ADS)

Fouad, Allouani; Boukhetala, Djamel; Boudjema, Fares; Zenger, Kai; Gao, Xiao-Zhi

2016-03-01

The Global-best Harmony Search (GHS) is a stochastic optimisation algorithm recently developed, which hybridises the Harmony Search (HS) method with the concept of swarm intelligence in the particle swarm optimisation (PSO) to enhance its performance. In this article, a new optimisation algorithm called GHSACO is developed by incorporating the GHS with the Ant Colony Optimisation algorithm (ACO). Our method introduces a novel improvisation process, which is different from that of the GHS in the following aspects. (i) A modified harmony memory (HM) representation and conception. (ii) The use of a global random switching mechanism to monitor the choice between the ACO and GHS. (iii) An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The proposed GHSACO algorithm has been applied to various benchmark functions and constrained optimisation problems. Simulation results demonstrate that it can find significantly better solutions when compared with the original HS and some of its variants.

Complexity Theory

USGS Publications Warehouse

Lee, William H K.

2016-01-01

A complex system consists of many interacting parts, generates new collective behavior through self organization, and adaptively evolves through time. Many theories have been developed to study complex systems, including chaos, fractals, cellular automata, self organization, stochastic processes, turbulence, and genetic algorithms.

Self-Organizing Maps for In Silico Screening and Data Visualization.

PubMed

Digles, Daniela; Ecker, Gerhard F

2011-10-01

Self-organizing maps, which are unsupervised artificial neural networks, have become a very useful tool in a wide area of disciplines, including medicinal chemistry. Here, we will focus on two applications of self-organizing maps: the use of self-organizing maps for in silico screening and for clustering and visualisation of large datasets. Additionally, the importance of parameter selection is discussed and some modifications to the original algorithm are summarised. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Janich, Karl W.

2005-01-01

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

A Global Approach to the Optimal Trajectory Based on an Improved Ant Colony Algorithm for Cold Spray

NASA Astrophysics Data System (ADS)

Cai, Zhenhua; Chen, Tingyang; Zeng, Chunnian; Guo, Xueping; Lian, Huijuan; Zheng, You; Wei, Xiaoxu

2016-12-01

This paper is concerned with finding a global approach to obtain the shortest complete coverage trajectory on complex surfaces for cold spray applications. A slicing algorithm is employed to decompose the free-form complex surface into several small pieces of simple topological type. The problem of finding the optimal arrangement of the pieces is translated into a generalized traveling salesman problem (GTSP). Owing to its high searching capability and convergence performance, an improved ant colony algorithm is then used to solve the GTSP. Through off-line simulation, a robot trajectory is generated based on the optimized result. The approach is applied to coat real components with a complex surface by using the cold spray system with copper as the spraying material.

Establishment, dispersal, and competitive impacts of a third fire ant decapitating fly (Pseudacteon obtusus) in North Central Florida

USDA-ARS?s Scientific Manuscript database

Self-sustaining classical biological control agents offer a hope for permanent wide-area control of imported Solenopsis fire ants in the United States because escape from abundant natural enemies left behind in Argentina is a likely reason for unusually high fire ant densities in the United States. ...

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems

PubMed Central

Idris, Hajara; Junaidu, Sahalu B.; Adewumi, Aderemi O.

2017-01-01

The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user’s Quality of Service (QoS) requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO) algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user’s QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time. PMID:28545075

Effects of predatory ants within and across ecosystems in bromeliad food webs.

PubMed

Gonçalves, Ana Z; Srivastava, Diane S; Oliveira, Paulo S; Romero, Gustavo Q

2017-07-01

Predation is one of the most fundamental ecological processes affecting biotic communities. Terrestrial predators that live at ecosystem boundaries may alter the diversity of terrestrial organisms, but they may also have cross-ecosystem cascading effects when they feed on organisms with complex life cycles (i.e. organisms that shift from aquatic juvenile stages to terrestrial adult stages) or inhibit female oviposition in the aquatic environment. The predatory ant Odontomachus hastatus establishes its colonies among roots of Vriesea procera, an epiphytic bromeliad species with water-filled tanks that shelters many terrestrial and aquatic organisms. Ants may impact terrestrial communities and deter adult insects from ovipositing in the water of bromeliads via consumptive and non-consumptive effects. Ants do not forage within the aquatic environment; thus, they may be more efficient predators on terrestrial organisms. Therefore, we predict that ants will have stronger effects on terrestrial than aquatic food webs. However, such effects may also be site contingent and depend on the local composition of food webs. To test our hypothesis, we surveyed bromeliads with and without O. hastatus colonies from three different coastal field sites in the Atlantic Forest of southeast Brazil, and quantified the effect of this predatory ant on the composition, density and richness of aquatic and terrestrial metazoans found in these bromeliads. We found that ants changed the composition and reduced the overall density of aquatic and terrestrial metazoans in bromeliad ecosystems. However, effects of ants on species diversity were contingent on site. In general terms, the effects of the ant on aquatic and terrestrial metazoan communities were similar in strength and magnitude. Ants reduced the density of virtually all aquatic functional groups, especially detritivore insects as well as metazoans that reach bromeliads through phoresy on the skin of terrestrial animals (i.e. Ostracoda and Helobdella sp.). Our results suggest that the cross-ecosystem effect of this terrestrial predator on the aquatic metazoans was at least as strong as its within-ecosystem effect on the terrestrial ecosystem, and demonstrates that the same predator can simultaneously initiate cascades in multiple ecosystems. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

NASA Technical Reports Server (NTRS)

Alena, Richard I.; Lee, Charles

2004-01-01

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

An interactive control algorithm used for equilateral triangle formation with robotic sensors.

PubMed

Li, Xiang; Chen, Hongcai

2014-04-22

This paper describes an interactive control algorithm, called Triangle Formation Algorithm (TFA), used for three neighboring robotic sensors which are distributed randomly to self-organize into and equilateral triangle (E) formation. The algorithm is proposed based on the triangular geometry and considering the actual sensors used in robotics. In particular, the stability of the TFA, which can be executed by robotic sensors independently and asynchronously for E formation, is analyzed in details based on Lyapunov stability theory. Computer simulations are carried out for verifying the effectiveness of the TFA. The analytical results and simulation studies indicate that three neighboring robots employing conventional sensors can self-organize into E formations successfully regardless of their initial distribution using the same TFAs.

An Interactive Control Algorithm Used for Equilateral Triangle Formation with Robotic Sensors

PubMed Central

Li, Xiang; Chen, Hongcai

2014-01-01

This paper describes an interactive control algorithm, called Triangle Formation Algorithm (TFA), used for three neighboring robotic sensors which are distributed randomly to self-organize into and equilateral triangle (E) formation. The algorithm is proposed based on the triangular geometry and considering the actual sensors used in robotics. In particular, the stability of the TFA, which can be executed by robotic sensors independently and asynchronously for E formation, is analyzed in details based on Lyapunov stability theory. Computer simulations are carried out for verifying the effectiveness of the TFA. The analytical results and simulation studies indicate that three neighboring robots employing conventional sensors can self-organize into E formations successfully regardless of their initial distribution using the same TFAs. PMID:24759118

Efficient distribution of toy products using ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Hidayat, S.; Nurpraja, C. A.

2017-12-01

CV Atham Toys (CVAT) produces wooden toys and furniture, comprises 13 small and medium industries. CVAT always attempt to deliver customer orders on time but delivery costs are high. This is because of inadequate infrastructure such that delivery routes are long, car maintenance costs are high, while fuel subsidy by the government is still temporary. This study seeks to minimize the cost of product distribution based on the shortest route using one of five Ant Colony Optimization (ACO) algorithms to solve the Vehicle Routing Problem (VRP). This study concludes that the best of the five is the Ant Colony System (ACS) algorithm. The best route in 1st week gave a total distance of 124.11 km at a cost of Rp 66,703.75. The 2nd week route gave a total distance of 132.27 km at a cost of Rp 71,095.13. The 3rd week best route gave a total distance of 122.70 km with a cost of Rp 65,951.25. While the 4th week gave a total distance of 132.27 km at a cost of Rp 74,083.63. Prior to this study there was no effort to calculate these figures.

Anthills in School Ecology

ERIC Educational Resources Information Center

Pawson, J. Marke

1975-01-01

Suggests experiments with field ants which can demonstrate the effect an organism has on its surroundings. The ecological aspects explored are plant distribution on the ant hills and the differences between ant hills and the undisturbed soil surrounding. (BR)

SA-SOM algorithm for detecting communities in complex networks

NASA Astrophysics Data System (ADS)

Chen, Luogeng; Wang, Yanran; Huang, Xiaoming; Hu, Mengyu; Hu, Fang

2017-10-01

Currently, community detection is a hot topic. This paper, based on the self-organizing map (SOM) algorithm, introduced the idea of self-adaptation (SA) that the number of communities can be identified automatically, a novel algorithm SA-SOM of detecting communities in complex networks is proposed. Several representative real-world networks and a set of computer-generated networks by LFR-benchmark are utilized to verify the accuracy and the efficiency of this algorithm. The experimental findings demonstrate that this algorithm can identify the communities automatically, accurately and efficiently. Furthermore, this algorithm can also acquire higher values of modularity, NMI and density than the SOM algorithm does.

Ants regulate colony spatial organization using multiple chemical road-signs

PubMed Central

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-01-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical ‘road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony. PMID:28569746

Ants regulate colony spatial organization using multiple chemical road-signs.

PubMed

Heyman, Yael; Shental, Noam; Brandis, Alexander; Hefetz, Abraham; Feinerman, Ofer

2017-06-01

Communication provides the basis for social life. In ant colonies, the prevalence of local, often chemically mediated, interactions introduces strong links between communication networks and the spatial distribution of ants. It is, however, unknown how ants identify and maintain nest chambers with distinct functions. Here, we combine individual tracking, chemical analysis and machine learning to decipher the chemical signatures present on multiple nest surfaces. We present evidence for several distinct chemical 'road-signs' that guide the ants' movements within the dark nest. These chemical signatures can be used to classify nest chambers with different functional roles. Using behavioural manipulations, we demonstrate that at least three of these chemical signatures are functionally meaningful and allow ants from different task groups to identify their specific nest destinations, thus facilitating colony coordination and stabilization. The use of multiple chemicals that assist spatiotemporal guidance, segregation and pattern formation is abundant in multi-cellular organisms. Here, we provide a rare example for the use of these principles in the ant colony.

Modeling the human mental lexicon with self-organizing feature maps

NASA Astrophysics Data System (ADS)

Wittenburg, Peter; Frauenfelder, Uli H.

1992-10-01

Recent efforts to model the remarkable ability of humans to recognize speech and words are described. Different techniques including the use of neural nets for representing phonological similarity between words in the lexicon with self organizing algorithms are discussed. Simulations using the standard Kohonen algorithm are presented to illustrate some problems confronted with this technique in modeling similarity relations of form in the human mental lexicon. Alternative approaches that can potentially deal with some of these limitations are sketched.

An efficient approach to the travelling salesman problem using self-organizing maps.

PubMed

Vieira, Frederico Carvalho; Dória Neto, Adrião Duarte; Costa, José Alfredo Ferreira

2003-04-01

This paper presents an approach to the well-known Travelling Salesman Problem (TSP) using Self-Organizing Maps (SOM). The SOM algorithm has interesting topological information about its neurons configuration on cartesian space, which can be used to solve optimization problems. Aspects of initialization, parameters adaptation, and complexity analysis of the proposed SOM based algorithm are discussed. The results show an average deviation of 3.7% from the optimal tour length for a set of 12 TSP instances.

Inverse estimation of the spheroidal particle size distribution using Ant Colony Optimization algorithms in multispectral extinction technique

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Wang, Yuqing; Ruan, Liming

2014-10-01

Four improved Ant Colony Optimization (ACO) algorithms, i.e. the probability density function based ACO (PDF-ACO) algorithm, the Region ACO (RACO) algorithm, Stochastic ACO (SACO) algorithm and Homogeneous ACO (HACO) algorithm, are employed to estimate the particle size distribution (PSD) of the spheroidal particles. The direct problems are solved by the extended Anomalous Diffraction Approximation (ADA) and the Lambert-Beer law. Three commonly used monomodal distribution functions i.e. the Rosin-Rammer (R-R) distribution function, the normal (N-N) distribution function, and the logarithmic normal (L-N) distribution function are estimated under dependent model. The influence of random measurement errors on the inverse results is also investigated. All the results reveal that the PDF-ACO algorithm is more accurate than the other three ACO algorithms and can be used as an effective technique to investigate the PSD of the spheroidal particles. Furthermore, the Johnson's SB (J-SB) function and the modified beta (M-β) function are employed as the general distribution functions to retrieve the PSD of spheroidal particles using PDF-ACO algorithm. The investigation shows a reasonable agreement between the original distribution function and the general distribution function when only considering the variety of the length of the rotational semi-axis.

Exploring with PAM: Prospecting ANTS Missions for Solar System Surveys

NASA Technical Reports Server (NTRS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.

2003-01-01

ANTS (Autonomous Nano-Technology Swarm), a large (1000 member) swarm of nano to picoclass (10 to 1 kg) totally autonomous spacecraft, are being developed as a NASA advanced mission concept. ANTS, based on a hierarchical insect social order, use an evolvable, self-similar, hierarchical neural system in which individual spacecraft represent the highest level nodes. ANTS uses swarm intelligence attained through collective, cooperative interactions of the nodes at all levels of the system. At the highest levels this can take the form of cooperative, collective behavior among the individual spacecraft in a very large constellation. The ANTS neural architecture is designed for totally autonomous operation of complex systems including spacecraft constellations. The ANTS (Autonomous Nano Technology Swarm) concept has a number of possible applications. A version of ANTS designed for surveying and determining the resource potential of the asteroid belt, called PAM (Prospecting ANTS Mission), is examined here.

Refraction law and Fermat principle: a project using the ant colony optimization algorithm for undergraduate students in physics

NASA Astrophysics Data System (ADS)

Vuong, Q. L.; Rigaut, C.; Gossuin, Y.

2018-07-01

A programming project for undergraduate students in physics is proposed in this work. Its goal is to check the Snell–Descartes law of refraction using the Fermat principle and the ant colony optimization algorithm. The project involves basic mathematics and physics and is adapted to students with basic programming skills. More advanced tools can be used (but are not mandatory) as parallelization or object-oriented programming, which makes the project also suitable for more experienced students. We propose two tests to validate the program. Our algorithm is able to find solutions which are close to the theoretical predictions. Two quantities are defined to study its convergence and the quality of the solutions. It is also shown that the choice of the values of the simulation parameters is important to efficiently obtain precise results.

Self-Organizing Hidden Markov Model Map (SOHMMM).

PubMed

Ferles, Christos; Stafylopatis, Andreas

2013-12-01

A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The Self-Organizing Hidden Markov Model Map (SOHMMM) establishes a cross-section between the theoretic foundations and algorithmic realizations of its constituents. The respective architectures and learning methodologies are fused in an attempt to meet the increasing requirements imposed by the properties of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein chain molecules. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a novel on-line gradient descent unsupervised learning algorithm, which is fully integrated into the SOHMMM. Since the SOHMMM carries out probabilistic sequence analysis with little or no prior knowledge, it can have a variety of applications in clustering, dimensionality reduction and visualization of large-scale sequence spaces, and also, in sequence discrimination, search and classification. Two series of experiments based on artificial sequence data and splice junction gene sequences demonstrate the SOHMMM's characteristics and capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction

PubMed Central

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John BO

2008-01-01

Background We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024–1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581–590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Results Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6°C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, ε of 0.21) and an RMSE of 45.1°C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3°C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5°C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. Conclusion With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors. PMID:18959785

Swarm intelligence. A whole new way to think about business.

PubMed

Bonabeau, E; Meyer, C

2001-05-01

What do ants and bees have to do with business? A great deal, it turns out. Individually, social insects are only minimally intelligent, and their work together is largely self-organized and unsupervised. Yet collectively they're capable of finding highly efficient solutions to difficult problems and can adapt automatically to changing environments. Over the past 20 years, the authors and other researchers have developed rigorous mathematical models to describe this phenomenon, which has been dubbed "swarm intelligence," and they are now applying them to business. Their research has already helped several companies develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy. Emulating the way ants find the shortest path to a new food supply, for example, has led researchers at Hewlett-Packard to develop software programs that can find the most efficient way to route phone traffic over a telecommunications network. South-west Airlines has used a similar model to efficiently route cargo. To allocate labor, honeybees appear to follow one simple but powerful rule--they seem to specialize in a particular activity unless they perceive an important need to perform another function. Using that model, researchers at Northwestern University have devised a system for painting trucks that can automatically adapt to changing conditions. In the future, the authors speculate, a company might structure its entire business using the principles of swarm intelligence. The result, they believe, would be the ultimate self-organizing enterprise--one that could adapt quickly and instinctively to fast-changing markets.

Secure steganographic communication algorithm based on self-organizing patterns.

PubMed

Saunoriene, Loreta; Ragulskis, Minvydas

2011-11-01

A secure steganographic communication algorithm based on patterns evolving in a Beddington-de Angelis-type predator-prey model with self- and cross-diffusion is proposed in this paper. Small perturbations of initial states of the system around the state of equilibrium result in the evolution of self-organizing patterns. Small differences between initial perturbations result in slight differences also in the evolving patterns. It is shown that the generation of interpretable target patterns cannot be considered as a secure mean of communication because contours of the secret image can be retrieved from the cover image using statistical techniques if only it represents small perturbations of the initial states of the system. An alternative approach when the cover image represents the self-organizing pattern that has evolved from initial states perturbed using the dot-skeleton representation of the secret image can be considered as a safe visual communication technique protecting both the secret image and communicating parties.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Optimization research of railway passenger transfer scheme based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Ni, Xiang

2018-05-01

The optimization research of railway passenger transfer scheme can provide strong support for railway passenger transport system, and its essence is path search. This paper realized the calculation of passenger transfer scheme for high speed railway when giving the time and stations of departure and arrival. The specific method that used were generating a passenger transfer service network of high-speed railway, establishing optimization model and searching by Ant Colony Algorithm. Finally, making analysis on the scheme from LanZhouxi to BeiJingXi which were based on high-speed railway network of China in 2017. The results showed that the transfer network and model had relatively high practical value and operation efficiency.

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

NASA Astrophysics Data System (ADS)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

Self-organization, collective decision making and resource exploitation strategies in social insects

NASA Astrophysics Data System (ADS)

Nicolis, S. C.; Dussutour, A.

2008-10-01

Amplifying communications are a ubiquitous characteristic of group-living animals. This work is concerned with their role in the processes of food recruitment and resource exploitation by social insects. The collective choices made by ants faced with different food sources are analyzed using both a mean field description and a stochastic approach. Emphasis is placed on the possibility of optimizing the recruitment and exploitation strategies through an appropriate balance between individual variability, cooperative interactions and environmental constraints.

A Winner Determination Algorithm for Combinatorial Auctions Based on Hybrid Artificial Fish Swarm Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Genrang; Lin, ZhengChun

The problem of winner determination in combinatorial auctions is a hotspot electronic business, and a NP hard problem. A Hybrid Artificial Fish Swarm Algorithm(HAFSA), which is combined with First Suite Heuristic Algorithm (FSHA) and Artificial Fish Swarm Algorithm (AFSA), is proposed to solve the problem after probing it base on the theories of AFSA. Experiment results show that the HAFSA is a rapidly and efficient algorithm for The problem of winner determining. Compared with Ant colony Optimization Algorithm, it has a good performance with broad and prosperous application.

A Unique Blend of 2-Fluorenyl-2-anthracene and 2-Anthryl-2-anthracence Showing White Emission and High Charge Mobility.

PubMed

Chen, Mengyun; Zhao, Yang; Yan, Lijia; Yang, Shuai; Zhu, Yanan; Murtaza, Imran; He, Gufeng; Meng, Hong; Huang, Wei

2017-01-16

White-light-emitting materials with high mobility are necessary for organic white-light-emitting transistors, which can be used for self-driven OLED displays or OLED lighting. In this study, we combined two materials with similar structures-2-fluorenyl-2-anthracene (FlAnt) with blue emission and 2-anthryl-2-anthracence (2A) with greenish-yellow emission-to fabricate OLED devices, which showed unusual solid-state white-light emission with the CIE coordinates (0.33, 0.34) at 10 V. The similar crystal structures ensured that the OTFTs based on mixed FlAnt and 2A showed high mobility of 1.56 cm 2  V -1  s -1 . This simple method provides new insight into the design of high-performance white-emitting transistor materials and structures. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

3D Printer Instrumentation to Create Varied Geometries of Robotic Limbs and Heterogeneous Granular Media

DTIC Science & Technology

2015-05-20

Transfer Robo Ant The 3D printer was used to rapidly prototype a robot ant . The robot ant was used to model the behavior of the fire ant and to model...computer models and 3D printed ant robots are shown below. Snake Bot We used the 3D printed to rapidly design a modular, easily-modified snake...living organism (modern mudskippers, a terrestrial fish) and extinct early tetrapods (e.g. Ichthyostega, Acanthostega) while allowing us to explore

Modeling no-jam traffic in ant trails: a pheromone-controlled approach

NASA Astrophysics Data System (ADS)

Guo, Ning; Hu, Mao-Bin; Jiang, Rui; Ding, Jianxun; Ling, Xiang

2018-05-01

The experiment in John et al (2009 Phys. Rev. Lett. 102 108001) shows that when ants move in a single-file trail, no jam emerges even at very high densities. We propose a self-propelled model of ant traffic to reproduce the fundamental diagram without a jammed branch. In this model, ants can adjust their desired velocities actively by perceiving pheromone concentration near the front of the trail. Moreover, ants will bear the repulsive force when they have physical contact with neighbors. The velocity in the simulation decreases slightly with increasing density, which captures the main feature observed in the experiment. Distributions of velocity and distance headway basically also conform to the experimental ones.

Hybrid real-code ant colony optimisation for constrained mechanical design

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Bureerat, Sujin

2016-01-01

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

NASA Astrophysics Data System (ADS)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

Web Image Retrieval Using Self-Organizing Feature Map.

ERIC Educational Resources Information Center

Wu, Qishi; Iyengar, S. Sitharama; Zhu, Mengxia

2001-01-01

Provides an overview of current image retrieval systems. Describes the architecture of the SOFM (Self Organizing Feature Maps) based image retrieval system, discussing the system architecture and features. Introduces the Kohonen model, and describes the implementation details of SOFM computation and its learning algorithm. Presents a test example…

Image Edge Tracking via Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Li, Ruowei; Wu, Hongkun; Liu, Shilong; Rahman, M. A.; Liu, Sanchi; Kwok, Ngai Ming

2018-04-01

A good edge plot should use continuous thin lines to describe the complete contour of the captured object. However, the detection of weak edges is a challenging task because of the associated low pixel intensities. Ant Colony Optimization (ACO) has been employed by many researchers to address this problem. The algorithm is a meta-heuristic method developed by mimicking the natural behaviour of ants. It uses iterative searches to find the optimal solution that cannot be found via traditional optimization approaches. In this work, ACO is employed to track and repair broken edges obtained via conventional Sobel edge detector to produced a result with more connected edges.

The Other Ex-Ante Moral Hazard in Health*

PubMed Central

Bhattacharya, Jay; Packalen, Mikko

2017-01-01

It is well-known that pooled insurance coverage can induce people to make inefficiently low investments in self-protective activities. We identify another ex-ante moral hazard that runs in the opposite direction. Lower levels of self-protection and the associated chronic conditions and behavioral patterns such as obesity, smoking, and malnutrition increase the incidence of many diseases and consumption of treatments to those diseases. This increases the reward for innovation and thus benefits the innovator. It also increases treatment innovation which benefits all consumers. As individuals do not take these positive externalities into account, their investments in self-protection are inefficiently high. We quantify the lower bound of this externality for obesity. The lower bound is independent of how much additional innovation is generated. The results show that the externality we identify offsets the negative Medicare-induced insurance externality of obesity. The Medicare-induced obesity subsidy is thus not a sufficient rationale for “soda taxes”, “fat taxes” or other penalties on obesity. The quantitative finding also implies that the other ex-ante moral hazard that we identify can be as important as the ex-ante moral hazard that has been a central concept in health economics for decades. PMID:21993331

Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

PubMed

Liu, L L; Liu, M J; Ma, M

2015-09-28

The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

The Role of Symbiont Genetic Distance and Potential Adaptability in Host Preference Towards Pseudonocardia Symbionts in Acromyrmex Leaf-Cutting Ants

PubMed Central

Poulsen, Michael; Maynard, Janielle; Roland, Damien L; Currie, Cameron R

2011-01-01

Fungus-growing ants display symbiont preference in behavioral assays, both towards the fungus they cultivate for food and Actinobacteria they maintain on their cuticle for antibiotic production against parasites. These Actinobacteria, genus Pseudonocardia Henssen (Pseudonocardiacea: Actinomycetales), help defend the ants' fungal mutualist from specialized parasites. In Acromyrmex Mayr (Hymenoptera: Formicidae) leaf-cutting ants, individual colonies maintain either a single or a few strains of Pseudonocardia, and the symbiont is primarily vertically transmitted between generations by colony-founding queens. A recent report found that Acromyrmex workers are able to differentiate between their native Pseudonocardia strain and non-native strains isolated from sympatric or allopatric Acromyrmex species, and show preference for their native strain. Here we explore worker preference when presented with two non-native strains, elucidating the role of genetic distance on preference between strains and Pseudonocardia origin. Our findings suggest that ants tend to prefer bacteria more closely related to their native bacterium and that genetic similarity is probably more important than whether symbionts are ant-associated or free-living. Preliminary findings suggest that when continued exposure to a novel Pseudonocardia strain occurs, ant symbiont preference is potentially adaptable, with colonies apparently being able to alter symbiont preference over time. These findings are discussed in relation to the role of adaptive recognition, potential ecological flexibility in symbiont preference, and more broadly, in relation to self versus non-self recognition. PMID:22225537

75 FR 66404 - Self-Regulatory Organizations; C2 Options Exchange, Incorporated; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-28

... Change The Exchange proposes to modify the wording of Rule 6.12 relating to the C2 matching algorithm... matching algorithm and subsequently overlay certain priorities over the selected base algorithm. There are currently two base algorithms: price-time (often referred to as first in, first out or FIFO) in which...

Developing Software for NASA Missions in the New Millennia

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Christopher; Hinchey, Mike

2004-01-01

NASA is working on new mission concepts for exploration of the solar system. The concepts for these missions include swarms of hundreds of cooperating intelligent spacecraft which will be able to work in teams and gather more data than current single spacecraft missions. These spacecraft will not only have to operate independently for long periods of time on their own and in teams, but will also need to have autonomic properties of self healing, self configuring, self optimizing and self protecting for them to survive in the harsh space environment. Software for these types of missions has never been developed before and represents some of the challenges of software development in the new millennia. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm missions NASA is considering. The ANTS mission will use a swarm of one thousand pico-spacecraft that weigh less than five pounds. Using an insect colony analog, ANTS will explore the asteroid belt and catalog the mass, density, morphology, and chemical composition of the asteroids. Due to the size of the spacecraft, each will only carry a single miniaturized science instrument which will require them to cooperate in searching for asteroids that are of scientific interest. This article also discusses the ANTS mission, the properties the spacecraft will need and how that will effect future software development.

Fault tolerant features and experiments of ANTS distributed real-time system

NASA Astrophysics Data System (ADS)

Dominic-Savio, Patrick; Lo, Jien-Chung; Tufts, Donald W.

1995-01-01

The ANTS project at the University of Rhode Island introduces the concept of Active Nodal Task Seeking (ANTS) as a way to efficiently design and implement dependable, high-performance, distributed computing. This paper presents the fault tolerant design features that have been incorporated in the ANTS experimental system implementation. The results of performance evaluations and fault injection experiments are reported. The fault-tolerant version of ANTS categorizes all computing nodes into three groups. They are: the up-and-running green group, the self-diagnosing yellow group and the failed red group. Each available computing node will be placed in the yellow group periodically for a routine diagnosis. In addition, for long-life missions, ANTS uses a monitoring scheme to identify faulty computing nodes. In this monitoring scheme, the communication pattern of each computing node is monitored by two other nodes.

Temperature: Human Regulating, Ants Conforming

ERIC Educational Resources Information Center

Clopton, Joe R.

2007-01-01

Biological processes speed up as temperature rises. Procedures for demonstrating this with ants traveling on trails, and data gathered by students on the Argentine ant ("Linepithema humile") are presented. The concepts of temperature regulation and conformity are detailed with a focus on the processes rather than on terms that label the organisms.

75 FR 36147 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Order Approving...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-24

..., as Modified by Amendment No. 1 Thereto, Related to the Hybrid Matching Algorithms June 17, 2010. On... Hybrid System. Each rule currently provides allocation algorithms the Exchange can utilize when executing incoming electronic orders, including the Ultimate Matching Algorithm (``UMA''), and price-time and pro...

78 FR 54502 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-04

... transactions. Transactions that originate from unrelated algorithms or separate and distinct trading strategies... transactions were undertaken for manipulative or other fraudulent purposes. Algorithms or trading strategies... activity and the use of algorithms by firms to make trading decisions, FINRA has observed an increase in...

Antimicrobial, antioxidant and sensory features of eugenol, carvacrol and trans-anethole in active packaging for organic ready-to-eat iceberg lettuce.

PubMed

Wieczyńska, Justyna; Cavoski, Ivana

2018-09-01

In this study, bio-based emitting sachets containing eugenol (EUG), carvacrol (CAR) and trans-anethole (ANT) were inserted into cellulose (CE) and polypropylene (PP) pillow packages of organic ready-to-eat (RTE) iceberg lettuce to investigate their functional features. EUG, CAR and ANT sachets in CE; and CAR in PP packages showed antimicrobial activities against coliforms (Δlog CFU g -1 of -1.38, -0.91, -0.93 and -0.93, respectively). EUG and ANT sachets in both packages reduced discoloration (ΔE of 9.5, 1.8, 9.4 and 5.6, respectively). ANT in both, and EUG only in PP packages induced biosynthesis of caffeoyl derivatives (C a T A , D i C a T A , D i C a Q A ), total phenolics and antioxidant activity (FRAP). Also, ANT and EUG in both packages improved overall freshness and odor. Principal component analysis separated ANT and EUG from CAR in both packages. The Pearson correlation confirmed that overall quality improvements were more pronounced by ANT inside the packages in comparison to EUG and CAR. Copyright © 2018 Elsevier Ltd. All rights reserved.

75 FR 5824 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-04

.... Those public customers who continue to receive priority in the execution algorithm are called Priority... standard execution algorithm: \\3\\ Securities Exchange Act Release No. 59287 (January 23, 2009), 74 FR 5694...

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.

PubMed

Quan, Wei; Fang, Jiancheng

2010-01-01

A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.

Solving a combinatorial problem via self-organizing process: an application of the Kohonen algorithm to the traveling salesman problem.

PubMed

Fort, J C

1988-01-01

We present an application of the Kohonen algorithm to the traveling salesman problem: Using only this algorithm, without energy function nor any parameter chosen "ad hoc", we found good suboptimal tours. We give a neural model version of this algorithm, closer to classical neural networks. This is illustrated with various numerical examples.

A Review of the Biological Control of Fire Ants

USDA-ARS?s Scientific Manuscript database

The suppression of well-established invasive ants will likely require biological control by natural enemies. This approach is self-sustaining and can impact undetected or inaccessible populations that are the source of the continual presence and expansion of the invaders. There is an ongoing effor...

The Capabilities of Chaos and Complexity

PubMed Central

Abel, David L.

2009-01-01

To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic) components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone)? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. “System” will be rigorously defined. Can a low-informational rapid succession of Prigogine’s dissipative structures self-order into bona fide organization? PMID:19333445

Social insect genomes exhibit dramatic evolution in gene composition and regulation while preserving regulatory features linked to sociality

PubMed Central

Simola, Daniel F.; Wissler, Lothar; Donahue, Greg; Waterhouse, Robert M.; Helmkampf, Martin; Roux, Julien; Nygaard, Sanne; Glastad, Karl M.; Hagen, Darren E.; Viljakainen, Lumi; Reese, Justin T.; Hunt, Brendan G.; Graur, Dan; Elhaik, Eran; Kriventseva, Evgenia V.; Wen, Jiayu; Parker, Brian J.; Cash, Elizabeth; Privman, Eyal; Childers, Christopher P.; Muñoz-Torres, Monica C.; Boomsma, Jacobus J.; Bornberg-Bauer, Erich; Currie, Cameron R.; Elsik, Christine G.; Suen, Garret; Goodisman, Michael A.D.; Keller, Laurent; Liebig, Jürgen; Rawls, Alan; Reinberg, Danny; Smith, Chris D.; Smith, Chris R.; Tsutsui, Neil; Wurm, Yannick; Zdobnov, Evgeny M.; Berger, Shelley L.; Gadau, Jürgen

2013-01-01

Genomes of eusocial insects code for dramatic examples of phenotypic plasticity and social organization. We compared the genomes of seven ants, the honeybee, and various solitary insects to examine whether eusocial lineages share distinct features of genomic organization. Each ant lineage contains ∼4000 novel genes, but only 64 of these genes are conserved among all seven ants. Many gene families have been expanded in ants, notably those involved in chemical communication (e.g., desaturases and odorant receptors). Alignment of the ant genomes revealed reduced purifying selection compared with Drosophila without significantly reduced synteny. Correspondingly, ant genomes exhibit dramatic divergence of noncoding regulatory elements; however, extant conserved regions are enriched for novel noncoding RNAs and transcription factor–binding sites. Comparison of orthologous gene promoters between eusocial and solitary species revealed significant regulatory evolution in both cis (e.g., Creb) and trans (e.g., fork head) for nearly 2000 genes, many of which exhibit phenotypic plasticity. Our results emphasize that genomic changes can occur remarkably fast in ants, because two recently diverged leaf-cutter ant species exhibit faster accumulation of species-specific genes and greater divergence in regulatory elements compared with other ants or Drosophila. Thus, while the “socio-genomes” of ants and the honeybee are broadly characterized by a pervasive pattern of divergence in gene composition and regulation, they preserve lineage-specific regulatory features linked to eusociality. We propose that changes in gene regulation played a key role in the origins of insect eusociality, whereas changes in gene composition were more relevant for lineage-specific eusocial adaptations. PMID:23636946

Magnetic anisotropy and organization of nanoparticles in heads and antennae of neotropical leaf-cutter ants, Atta colombica

USDA-ARS?s Scientific Manuscript database

Oriented magnetic nanoparticles have been suggested as a good candidate for a magnetic sensor in ants. Behavioral evidence for a magnetic compass in Neotropical leafcutter ants, Atta colombica (Formicidae: Attini), motivated a study of the arrangement of magnetic particles in the ants’ four major bo...

Exploration adjustment by ant colonies

PubMed Central

2016-01-01

How do animals in groups organize their work? Division of labour, i.e. the process by which individuals within a group choose which tasks to perform, has been extensively studied in social insects. Variability among individuals within a colony seems to underpin both the decision over which tasks to perform and the amount of effort to invest in a task. Studies have focused mainly on discrete tasks, i.e. tasks with a recognizable end. Here, we study the distribution of effort in nest seeking, in the absence of new nest sites. Hence, this task is open-ended and individuals have to decide when to stop searching, even though the task has not been completed. We show that collective search effort declines when colonies inhabit better homes, as a consequence of a reduction in the number of bouts (exploratory events). Furthermore, we show an increase in bout exploration time and a decrease in bout instantaneous speed for colonies inhabiting better homes. The effect of treatment on bout effort is very small; however, we suggest that the organization of work performed within nest searching is achieved both by a process of self-selection of the most hard-working ants and individual effort adjustment. PMID:26909180

Branchy alumina nanotubes

NASA Astrophysics Data System (ADS)

Zou, Jianping; Pu, Lin; Bao, Ximao; Feng, Duan

2002-02-01

Branchy alumina nanotubes (bANTs) have been shown to exist in aluminum oxide. Electron-beam evaporated 400 nm Al film on Si substrate is stepwise anodized in dilute sulfuric acid under the constant dc voltage 40 V at 10.0 °C. This electrochemical-anodizing route resulted in the formation of individual bANTs. Transmission electron microscopy showed that the length of the bANTs was around 450 nm, and the inner diameter was around 10-20 nm. We deduced that the bANTs, the completely detached multibranchy cells of anodic porous alumina (APA) film, should be evolved from the stagnant cells of the APA mother film. The bANTs may be used as templates in fabrication of individual branchy nanoscale cables, jacks, and heterojunctions. The proposed formation mechanisms of the bANTs and the stagnant cells should give some insights into the long-standing problem of APA film, i.e., the self-ordering mechanism of the cells arrangement in porous anodization of aluminum.

Collective Response of Leaf-Cutting Ants to the Effects of Wind on Foraging Activity.

PubMed

Alma, Andrea Marina; Farji-Brener, Alejandro G; Elizalde, Luciana

2016-11-01

One advantage of sociality is to mitigate environmental restrictions through collective behavior. Here we document a colony-level response of leaf-cutting ants to wind, an environmental factor that impedes foraging. Given that larger ants adhere more strongly to the substrate, increasing forager size in windy conditions should reduce the negative effect of wind. We tested this idea for Acromyrmex lobicornis in windy regions of Patagonia. We examined (1) whether the fraction of larger ants versus smaller ants increased in windy conditions and (2) whether the effect of wind on the ants' movement was lower for larger ants. The size-frequency distribution of foragers was skewed more toward larger ants in nature under more windy conditions. Under windy conditions in the field, the mobility of smaller ants was more reduced than that of larger ants. The change toward larger foragers in windy conditions reduced the negative effect of wind by 32%, illustrating how a social organism can collectively mitigate the adverse effects of the environment.

Reinforcement interval type-2 fuzzy controller design by online rule generation and q-value-aided ant colony optimization.

PubMed

Juang, Chia-Feng; Hsu, Chia-Hung

2009-12-01

This paper proposes a new reinforcement-learning method using online rule generation and Q-value-aided ant colony optimization (ORGQACO) for fuzzy controller design. The fuzzy controller is based on an interval type-2 fuzzy system (IT2FS). The antecedent part in the designed IT2FS uses interval type-2 fuzzy sets to improve controller robustness to noise. There are initially no fuzzy rules in the IT2FS. The ORGQACO concurrently designs both the structure and parameters of an IT2FS. We propose an online interval type-2 rule generation method for the evolution of system structure and flexible partitioning of the input space. Consequent part parameters in an IT2FS are designed using Q -values and the reinforcement local-global ant colony optimization algorithm. This algorithm selects the consequent part from a set of candidate actions according to ant pheromone trails and Q-values, both of which are updated using reinforcement signals. The ORGQACO design method is applied to the following three control problems: 1) truck-backing control; 2) magnetic-levitation control; and 3) chaotic-system control. The ORGQACO is compared with other reinforcement-learning methods to verify its efficiency and effectiveness. Comparisons with type-1 fuzzy systems verify the noise robustness property of using an IT2FS.

Ante mortem identification of BSE from serum using infrared spectroscopy

NASA Astrophysics Data System (ADS)

Schmitt, Jürgen; Lasch, Peter; Beekes, Michael; Udelhoven, Thomas; Eiden, Michael; Fabian, Heinz; Petrich, Wolfgang H.; Naumann, Dieter

2004-07-01

In our former studies a diagnostic approach for the detection of transmissible spongiform encephalopaties (TSE) based on FT-IR spectroscopy in combination with artificial neural networks was described, based on a controlled animal study with terminally ill Syrian hamsters and control animals. As a consequence of the bovine spongiform encephalopathy (BSE) crisis in Europe, the development of a disgnostic ante mortem test for cattle has become a matter of great scientific importance and public interest. Since 1986 more than 180,000 clinical cases of BSE have been observed in the UK alone. Most of these cases were confirmed by post mortem examination of brain tissue. However, BSE-related risk assessment and risk-management would greatly benefit from ante mortem testing on living animals. For example, a serum-based test could allow for screening of the cattle population, thus, even a BSE eradication program would be conceivable. Here we report on a novel method for ante mortem BSE testing, which combines infrared spectroscopy of serum samples with multivariate pattern recognition analysis. A classification algorithm was trained using infrared spectra of sera from more than 800 animals from a field study (including BSE positive, healthy controls and animals suffering from viral or bacterial infections). In two validation studies sensitivities of 85% and 87% and specificities of 84% and 91% were achieved, respectively. The combination of classification algorithms increased sensitivity and specificity to 96% and 92%, respectively.

Competition as a mechanism structuring mutualisms

Treesearch

Robert J. Warren; Itamar Giladi; Mark A. Bradford

2014-01-01

Summary 1. Hutchinsonian niche theory posits that organisms have fundamental abiotic resource requirements from which they are limited by competition. Organisms also have fundamental biotic requirements, such as mutualists, for which they also might compete. 2. We test this idea with a widespread ant–plant mutualism. Ant-mediated seed dispersal (myrmecochory) in...

A Y-like social chromosome causes alternative colony organization in fire ants

USDA-ARS?s Scientific Manuscript database

Intraspecific variability in social organization is common, yet the underlying causes are rarely known1-3. In the fire ant Solenopsis invicta, the existence of two divergent forms of social organisation is under the control of a single Mendelian genomic element marked by two variants of an odorant b...

A new method for distinguishing colony social forms of the fire ant Solenopsis invicta

USDA-ARS?s Scientific Manuscript database

Two distinct forms of colony social organization occur in the fire ant Solenopsis invicta: Colonies of the monogyne social form are headed by a single egg-laying queen, whereas those of the polygyne social form contain multiple egg-laying queens. This major difference in social organization is ass...

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2012-09-27

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2012-06-25

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2012-08-20

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The other ex ante moral hazard in health.

PubMed

Bhattacharya, Jay; Packalen, Mikko

2012-01-01

It is well-known that pooled insurance coverage can induce people to make inefficiently low investments in self-protective activities. We identify another ex ante moral hazard that runs in the opposite direction. Lower levels of self-protection and the associated chronic conditions and behavioral patterns such as obesity, smoking, and malnutrition increase the incidence of many diseases and consumption of treatments to those diseases. This increases the reward for innovation and thus benefits the innovator. It also increases treatment innovation which benefits all consumers. As individuals do not take these positive externalities into account, their investments in self-protection are inefficiently high. We quantify the lower bound of this externality for obesity. The lower bound is independent of how much additional innovation is generated. The results show that the externality we identify offsets the negative Medicare-induced insurance externality of obesity. The Medicare-induced obesity subsidy is thus not a sufficient rationale for "soda taxes", "fat taxes" or other penalties on obesity. The quantitative finding also implies that the other ex ante moral hazard that we identify can be as important as the ex ante moral hazard that has been a central concept in health economics for decades. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method

NASA Astrophysics Data System (ADS)

Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin

2017-12-01

Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.

Dead ant walking: a myrmecophilous beetle predator uses parasitoid host location cues to selectively prey on parasitized ants

PubMed Central

2016-01-01

Myrmecophiles (i.e. organisms that associate with ants) use a variety of ecological niches and employ different strategies to survive encounters with ants. Because ants are typically excellent defenders, myrmecophiles may choose moments of weakness to take advantage of their ant associates. This hypothesis was studied in the rove beetle, Myrmedonota xipe, which associates with Azteca sericeasur ants in the presence of parasitoid flies. A combination of laboratory and field experiments show that M. xipe beetles selectively locate and prey upon parasitized ants. These parasitized ants are less aggressive towards beetles than healthy ants, allowing beetles to eat the parasitized ants alive without interruption. Moreover, behavioural assays and chemical analysis reveal that M. xipe are attracted to the ant's alarm pheromone, the same secretion used by the phorid fly parasitoids in host location. This strategy allows beetles access to an abundant but otherwise inaccessible resource, as A. sericeasur ants are typically highly aggressive. These results are the first, to our knowledge, to demonstrate a predator sharing cues with a parasitoid to gain access to an otherwise unavailable prey item. Furthermore, this work highlights the importance of studying ant–myrmecophile interactions beyond just their pairwise context. PMID:27512148

Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

NASA Astrophysics Data System (ADS)

Deng, Guang-Feng; Lin, Woo-Tsong

This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.

Toxic industrial deposit remediation by ant activity

NASA Astrophysics Data System (ADS)

Jilkova, Veronika; Frouz, Jan

2016-04-01

Toxic industrial deposits are often contaminated by heavy metals and the substrates have low pH values. In such systems, soil development is thus slowed down by high toxicity and acidic conditions which are unfavourable to soil fauna. Ants (Hymenoptera, Formicidae) are considered tolerant to heavy metal pollution and are known to increase organic matter content and microbial activity in their nests. Here, we focused on soil remediation caused by three ant species (Formica sanguinea, Lasius niger, and Tetramorium sp.) in an ore-washery sedimentation basin near Chvaletice (Czech Republic). Soil samples were taken from the centre of ant nests and from the nest surroundings (>3 m from nests). Samples were then analyzed for microbial activity and biomass and contents of organic matter and nutrients. As a result, ant species that most influenced soil properties was F. sanguinea as there were higher microbial activity and total nitrogen and ammonia contents in ant nests than in the surrounding soil. We expected such a result because F. sanguinea builds conspicuous large nests and is a carnivorous species that brings substantial amounts of nitrogen in insect prey to their nests. Effects of the other two ant species might be lower because of smaller nests and different feeding habits as they rely mainly on honeydew from aphids or on plant seeds that do not contain much nutrients.

Dead ant walking: a myrmecophilous beetle predator uses parasitoid host location cues to selectively prey on parasitized ants.

PubMed

Mathis, Kaitlyn A; Tsutsui, Neil D

2016-08-17

Myrmecophiles (i.e. organisms that associate with ants) use a variety of ecological niches and employ different strategies to survive encounters with ants. Because ants are typically excellent defenders, myrmecophiles may choose moments of weakness to take advantage of their ant associates. This hypothesis was studied in the rove beetle, Myrmedonota xipe, which associates with Azteca sericeasur ants in the presence of parasitoid flies. A combination of laboratory and field experiments show that M. xipe beetles selectively locate and prey upon parasitized ants. These parasitized ants are less aggressive towards beetles than healthy ants, allowing beetles to eat the parasitized ants alive without interruption. Moreover, behavioural assays and chemical analysis reveal that M. xipe are attracted to the ant's alarm pheromone, the same secretion used by the phorid fly parasitoids in host location. This strategy allows beetles access to an abundant but otherwise inaccessible resource, as A. sericeasur ants are typically highly aggressive. These results are the first, to our knowledge, to demonstrate a predator sharing cues with a parasitoid to gain access to an otherwise unavailable prey item. Furthermore, this work highlights the importance of studying ant-myrmecophile interactions beyond just their pairwise context. © 2016 The Author(s).

Rationality in collective decision-making by ant colonies

PubMed Central

Edwards, Susan C.; Pratt, Stephen C.

2009-01-01

Economic models of animal behaviour assume that decision-makers are rational, meaning that they assess options according to intrinsic fitness value and not by comparison with available alternatives. This expectation is frequently violated, but the significance of irrational behaviour remains controversial. One possibility is that irrationality arises from cognitive constraints that necessitate short cuts like comparative evaluation. If so, the study of whether and when irrationality occurs can illuminate cognitive mechanisms. We applied this logic in a novel setting: the collective decisions of insect societies. We tested for irrationality in colonies of Temnothorax ants choosing between two nest sites that varied in multiple attributes, such that neither site was clearly superior. In similar situations, individual animals show irrational changes in preference when a third relatively unattractive option is introduced. In contrast, we found no such effect in colonies. We suggest that immunity to irrationality in this case may result from the ants’ decentralized decision mechanism. A colony's choice does not depend on site comparison by individuals, but instead self-organizes from the interactions of multiple ants, most of which are aware of only a single site. This strategy may filter out comparative effects, preventing systematic errors that would otherwise arise from the cognitive limitations of individuals. PMID:19625319

Rhodoferax antarcticus sp. nov., a moderately psychrophilic purple nonsulfur bacterium isolated from an Antarctic microbial mat

NASA Technical Reports Server (NTRS)

Madigan, M. T.; Jung, D. O.; Woese, C. R.; Achenbach, L. A.

2000-01-01

A new species of purple nonsulfur bacteria isolated from an Antarctic microbial mat is described. The organism, designated strain ANT.BR, was mildly psychrophilic, growing optimally at 15-18 degrees C with a growth temperature range of 0-25 degrees C. Cells of strain ANT.BR were highly motile curved rods and spirals, contained bacteriochlorophyll a, and showed a multicomponent in vivo absorption spectrum. A specific phylogenetic relationship was observed between strain ANT.BR and the purple bacterium Rhodoferax fermentans FR2T, and the two organisms shared several physiological and other phenotypic properties, with the notable exception of growth temperature optimum. Tests of genomic DNA hybridization, however, showed Rfx. fermentans FR2T and strain ANT.BR to be genetically distinct bacteria. Because of its unique set of properties, especially its requirement for low growth temperatures, we propose to recognize strain ANT.BR as a new species of the genus Rhodoferax, Rhodoferax antarcticus, named for its known habitat, the Antarctic.

Trail pheromone disruption of red imported fire ant.

PubMed

Suckling, David M; Stringer, Lloyd D; Bunn, Barry; El-Sayed, Ashraf M; Vander Meer, Robert K

2010-07-01

The fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is considered one of the most aggressive and invasive species in the world. Toxic bait systems are used widely for control, but they also affect non-target ant species and cannot be used in sensitive ecosystems such as organic farms and national parks. The fire ant uses recruitment pheromones to organize the retrieval of large food resources back to the colony, with Z,E-alpha-farnesene responsible for the orientation of workers along trails. We prepared Z,E-alpha-farnesene, (91% purity) from extracted E,E-alpha-farnesene and demonstrated disruption of worker trail orientation after presentation of an oversupply of this compound from filter paper point sources (30 microg). Trails were established between queen-right colony cells and food sources in plastic tubs. Trail-following behavior was recorded by overhead webcam, and ants were digitized before and after presentation of the treatment, using two software approaches. The linear regression statistic, r(2) was calculated. Ants initially showed high linear trail integrity (r(2) = 0.75). Within seconds of presentation of the Z,E-alpha-farnesene treatment, the trailing ants showed little or no further evidence of trail following behavior in the vicinity of the pheromone source. These results show that trailing fire ants become disorientated in the presence of large amounts of Z,E-alpha-farnesene. Disrupting fire ant recruitment to resources may have a negative effect on colony size or other effects yet to be determined. This phenomenon was demonstrated recently for the Argentine ant, where trails were disrupted for two weeks by using their formulated trail pheromone, Z-9-hexadecenal. Further research is needed to establish the long term effects and control potential for trail disruption in S. invicta.

Ants impact the composition of the aquatic macroinvertebrate communities of a myrmecophytic tank bromeliad.

PubMed

Dejean, Alain; Compin, Arthur; Leponce, Maurice; Azémar, Frédéric; Bonhomme, Camille; Talaga, Stanislas; Pelozuelo, Laurent; Hénaut, Yann; Corbara, Bruno

2018-03-01

In an inundated Mexican forest, 89 out of 92 myrmecophytic tank bromeliads (Aechmea bracteata) housed an associated ant colony: 13 sheltered Azteca serica, 43 Dolichoderus bispinosus, and 33 Neoponera villosa. Ant presence has a positive impact on the diversity of the aquatic macroinvertebrate communities (n=30 bromeliads studied). A Principal Component Analysis (PCA) showed that the presence and the species of ant are not correlated to bromeliad size, quantity of water, number of wells, filtered organic matter or incident radiation. The PCA and a generalized linear model showed that the presence of Azteca serica differed from the presence of the other two ant species or no ants in its effects on the aquatic invertebrate community (more predators). Therefore, both ant presence and species of ant affect the composition of the aquatic macroinvertebrate communities in the tanks of A. bracteata, likely due to ant deposition of feces and other waste in these tanks. Copyright © 2018. Published by Elsevier Masson SAS.

orco Mutagenesis Causes Loss of Antennal Lobe Glomeruli and Impaired Social Behavior in Ants.

PubMed

Trible, Waring; Olivos-Cisneros, Leonora; McKenzie, Sean K; Saragosti, Jonathan; Chang, Ni-Chen; Matthews, Benjamin J; Oxley, Peter R; Kronauer, Daniel J C

2017-08-10

Life inside ant colonies is orchestrated with diverse pheromones, but it is not clear how ants perceive these social signals. It has been proposed that pheromone perception in ants evolved via expansions in the numbers of odorant receptors (ORs) and antennal lobe glomeruli. Here, we generate the first mutant lines in the clonal raider ant, Ooceraea biroi, by disrupting orco, a gene required for the function of all ORs. We find that orco mutants exhibit severe deficiencies in social behavior and fitness, suggesting they are unable to perceive pheromones. Surprisingly, unlike in Drosophila melanogaster, orco mutant ants also lack most of the ∼500 antennal lobe glomeruli found in wild-type ants. These results illustrate that ORs are essential for ant social organization and raise the possibility that, similar to mammals, receptor function is required for the development and/or maintenance of the highly complex olfactory processing areas in the ant brain. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

NASA Astrophysics Data System (ADS)

Karaca, Yeliz; Cattani, Carlo

Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

77 FR 76316 - Self-Regulatory Organizations; ICE Clear Europe Limited; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-27

... enhancement to the SPAN for the ICE Margining algorithm employed to calculate Original Margin. All capitalized... Allocation Methodology is an enhancement to the SPAN[supreg] \\6\\ for the ICE Margining algorithm employed to... the SPAN margin calculation algorithm itself has not been changed. As of August 30, 2011, Position...

Macromolecular target prediction by self-organizing feature maps.

PubMed

Schneider, Gisbert; Schneider, Petra

2017-03-01

Rational drug discovery would greatly benefit from a more nuanced appreciation of the activity of pharmacologically active compounds against a diverse panel of macromolecular targets. Already, computational target-prediction models assist medicinal chemists in library screening, de novo molecular design, optimization of active chemical agents, drug re-purposing, in the spotting of potential undesired off-target activities, and in the 'de-orphaning' of phenotypic screening hits. The self-organizing map (SOM) algorithm has been employed successfully for these and other purposes. Areas covered: The authors recapitulate contemporary artificial neural network methods for macromolecular target prediction, and present the basic SOM algorithm at a conceptual level. Specifically, they highlight consensus target-scoring by the employment of multiple SOMs, and discuss the opportunities and limitations of this technique. Expert opinion: Self-organizing feature maps represent a straightforward approach to ligand clustering and classification. Some of the appeal lies in their conceptual simplicity and broad applicability domain. Despite known algorithmic shortcomings, this computational target prediction concept has been proven to work in prospective settings with high success rates. It represents a prototypic technique for future advances in the in silico identification of the modes of action and macromolecular targets of bioactive molecules.

9 CFR 354.122 - Condemnation on ante-mortem inspection.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AGRICULTURE AGENCY ORGANIZATION AND TERMINOLOGY; MANDATORY MEAT AND POULTRY PRODUCTS INSPECTION AND VOLUNTARY..., on ante-mortem inspection, are condemned shall not be dressed, nor shall they be conveyed into any...

Logical NAND and NOR Operations Using Algorithmic Self-assembly of DNA Molecules

NASA Astrophysics Data System (ADS)

Wang, Yanfeng; Cui, Guangzhao; Zhang, Xuncai; Zheng, Yan

DNA self-assembly is the most advanced and versatile system that has been experimentally demonstrated for programmable construction of patterned systems on the molecular scale. It has been demonstrated that the simple binary arithmetic and logical operations can be computed by the process of self assembly of DNA tiles. Here we report a one-dimensional algorithmic self-assembly of DNA triple-crossover molecules that can be used to execute five steps of a logical NAND and NOR operations on a string of binary bits. To achieve this, abstract tiles were translated into DNA tiles based on triple-crossover motifs. Serving as input for the computation, long single stranded DNA molecules were used to nucleate growth of tiles into algorithmic crystals. Our method shows that engineered DNA self-assembly can be treated as a bottom-up design techniques, and can be capable of designing DNA computer organization and architecture.

Five new records of ants (Hymenoptera: Formicidae) for Nebraska

USGS Publications Warehouse

Nemec, Kristine T.; Trager, James C.; Manley, Elizabeth; Allen, Craig R.

2012-01-01

Ants are ubiquitous and influential organisms in terrestrial ecosystems. About 1,000 ant species occur in North America, where they are found in nearly every habitat (Fisher and Cover 2007). Ants are critical to ecological processes and structure. Ants affect soils via tunneling activity (Baxter and Hole 1967), disperse plant seeds (Lengyel et al. 2009), prey upon a variety of insects and other invertebrates (Way and Khoo 1992, Folgarait 1998), are often effective primary consumers through their prodigious consumption of floral and especially extrafloral nectar, and honeydew (Tobin 1994), and serve as prey for invertebrates (Gotelli 1996, Gastreich 1999) and vertebrates (Reiss 2001).

Self-prior strategy for organ reconstruction in fluorescence molecular tomography

PubMed Central

Zhou, Yuan; Chen, Maomao; Su, Han; Luo, Jianwen

2017-01-01

The purpose of this study is to propose a strategy for organ reconstruction in fluorescence molecular tomography (FMT) without prior information from other imaging modalities, and to overcome the high cost and ionizing radiation caused by the traditional structural prior strategy. The proposed strategy is designed as an iterative architecture to solve the inverse problem of FMT. In each iteration, a short time Fourier transform (STFT) based algorithm is used to extract the self-prior information in the space-frequency energy spectrum with the assumption that the regions with higher fluorescence concentration have larger energy intensity, then the cost function of the inverse problem is modified by the self-prior information, and lastly an iterative Laplacian regularization algorithm is conducted to solve the updated inverse problem and obtains the reconstruction results. Simulations and in vivo experiments on liver reconstruction are carried out to test the performance of the self-prior strategy on organ reconstruction. The organ reconstruction results obtained by the proposed self-prior strategy are closer to the ground truth than those obtained by the iterative Tikhonov regularization (ITKR) method (traditional non-prior strategy). Significant improvements are shown in the evaluation indexes of relative locational error (RLE), relative error (RE) and contrast-to-noise ratio (CNR). The self-prior strategy improves the organ reconstruction results compared with the non-prior strategy and also overcomes the shortcomings of the traditional structural prior strategy. Various applications such as metabolic imaging and pharmacokinetic study can be aided by this strategy. PMID:29082094

Self-prior strategy for organ reconstruction in fluorescence molecular tomography.

PubMed

Zhou, Yuan; Chen, Maomao; Su, Han; Luo, Jianwen

2017-10-01

The purpose of this study is to propose a strategy for organ reconstruction in fluorescence molecular tomography (FMT) without prior information from other imaging modalities, and to overcome the high cost and ionizing radiation caused by the traditional structural prior strategy. The proposed strategy is designed as an iterative architecture to solve the inverse problem of FMT. In each iteration, a short time Fourier transform (STFT) based algorithm is used to extract the self-prior information in the space-frequency energy spectrum with the assumption that the regions with higher fluorescence concentration have larger energy intensity, then the cost function of the inverse problem is modified by the self-prior information, and lastly an iterative Laplacian regularization algorithm is conducted to solve the updated inverse problem and obtains the reconstruction results. Simulations and in vivo experiments on liver reconstruction are carried out to test the performance of the self-prior strategy on organ reconstruction. The organ reconstruction results obtained by the proposed self-prior strategy are closer to the ground truth than those obtained by the iterative Tikhonov regularization (ITKR) method (traditional non-prior strategy). Significant improvements are shown in the evaluation indexes of relative locational error (RLE), relative error (RE) and contrast-to-noise ratio (CNR). The self-prior strategy improves the organ reconstruction results compared with the non-prior strategy and also overcomes the shortcomings of the traditional structural prior strategy. Various applications such as metabolic imaging and pharmacokinetic study can be aided by this strategy.

RNA-Seq Links the Transcription Factors AINTEGUMENTA and AINTEGUMENTA-LIKE6 to Cell Wall Remodeling and Plant Defense Pathways1[OPEN

PubMed Central

Bequette, Carlton J.; Fu, Zheng Qing; Loraine, Ann E.

2016-01-01

AINTEGUMENTA (ANT) and AINTEGUMENTA-LIKE6 (AIL6) are two related transcription factors in Arabidopsis (Arabidopsis thaliana) that have partially overlapping roles in several aspects of flower development, including floral organ initiation, identity specification, growth, and patterning. To better understand the biological processes regulated by these two transcription factors, we performed RNA sequencing (RNA-Seq) on ant ail6 double mutants. We identified thousands of genes that are differentially expressed in the double mutant compared with the wild type. Analyses of these genes suggest that ANT and AIL6 regulate floral organ initiation and growth through modifications to the cell wall polysaccharide pectin. We found reduced levels of demethylesterified homogalacturonan and altered patterns of auxin accumulation in early stages of ant ail6 flower development. The RNA-Seq experiment also revealed cross-regulation of AIL gene expression at the transcriptional level. The presence of a number of overrepresented Gene Ontology terms related to plant defense in the set of genes differentially expressed in ant ail6 suggest that ANT and AIL6 also regulate plant defense pathways. Furthermore, we found that ant ail6 plants have elevated levels of two defense hormones: salicylic acid and jasmonic acid, and show increased resistance to the bacterial pathogen Pseudomonas syringae. These results suggest that ANT and AIL6 regulate biological pathways that are critical for both development and defense. PMID:27208279

Stridulations Reveal Cryptic Speciation in Neotropical Sympatric Ants

PubMed Central

Ferreira, Ronara Souza; Poteaux, Chantal; Delabie, Jacques Hubert Charles; Fresneau, Dominique; Rybak, Fanny

2010-01-01

The taxonomic challenge posed by cryptic species underlines the importance of using multiple criteria in species delimitation. In the current paper we tested the use of acoustic analysis as a tool to assess the real diversity in a cryptic species complex of Neotropical ants. In order to understand the potential of acoustics and to improve consistency in the conclusions by comparing different approaches, phylogenetic relationships of all the morphs considered were assessed by the analysis of a fragment of the mitochondrial DNA cytochrome b. We observed that each of the cryptic morph studied presents a morphologically distinct stridulatory organ and that all sympatric morphs produce distinctive stridulations. This is the first evidence of such a degree of specialization in the acoustic organ and signals in ants, which suggests that stridulations may be among the cues used by these ants during inter-specific interactions. Mitochondrial DNA variation corroborated the acoustic differences observed, confirming acoustics as a helpful tool to determine cryptic species in this group of ants, and possibly in stridulating ants in general. Congruent morphological, acoustic and genetic results constitute sufficient evidence to propose each morph studied here as a valid new species, suggesting that P. apicalis is a complex of at least 6 to 9 species, even if they present different levels of divergence. Finally, our results highlight that ant stridulations may be much more informative than hitherto thought, as much for ant communication as for integrative taxonomists. PMID:21203529

Topological mappings of video and audio data.

PubMed

Fyfe, Colin; Barbakh, Wesam; Ooi, Wei Chuan; Ko, Hanseok

2008-12-01

We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM).(1) But whereas the GTM is an extension of a mixture of experts, this model is an extension of a product of experts.(2) We show visualisation and clustering results on a data set composed of video data of lips uttering 5 Korean vowels. Finally we note that we may dispense with the probabilistic underpinnings of the product of experts and derive the same algorithm as a minimisation of mean squared error between the prototypes and the data. This leads us to suggest a new algorithm which incorporates local and global information in the clustering. Both ot the new algorithms achieve better results than the standard Self-Organizing Map.

Methods for data classification

DOEpatents

Garrity, George [Okemos, MI; Lilburn, Timothy G [Front Royal, VA

2011-10-11

The present invention provides methods for classifying data and uncovering and correcting annotation errors. In particular, the present invention provides a self-organizing, self-correcting algorithm for use in classifying data. Additionally, the present invention provides a method for classifying biological taxa.

Ant colony optimisation inversion of surface and borehole magnetic data under lithological constraints

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Liu, Tianyou; Xi, Yufei; Cai, Jianchao; Zhang, Henglei

2015-01-01

The ant colony optimisation algorithm has successfully been used to invert for surface magnetic data. However, the resolution of the distributions of the recovered physical property for deeply buried magnetic sources is not generally very high because of geophysical ambiguities. We use three approaches to deal with this problem. First, the observed surface magnetic data are taken together with the three-component borehole magnetic anomalies to recover the distributions of the physical properties. This cooperative inversion strategy improves the resolution of the inversion results in the vertical direction. Additionally, as the ant colony tours the discrete nodes, we force it to visit the nodes with physical properties that agree with the drilled lithologies. These lithological constraints reduce the non-uniqueness of the inversion problem. Finally, we also implement a K-means cluster analysis for the distributions of the magnetic cells after each iteration, in order to separate the distributions of magnetisation intensity instead of concentrating the distribution in a single area. We tested our method using synthetic data and found that all tests returned favourable results. In the case study of the Mengku iron-ore deposit in northwest China, the recovered distributions of magnetisation are in good agreement with the locations and shapes of the magnetite orebodies as inferred by drillholes. Uncertainty analysis shows that the ant colony algorithm is robust in the presence of noise and that the proposed approaches significantly improve the quality of the inversion results.

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Attracting predators without falling prey: chemical camouflage protects honeydew-producing treehoppers from ant predation.

PubMed

Silveira, Henrique C P; Oliveira, Paulo S; Trigo, José R

2010-02-01

Predaceous ants are dominant organisms on foliage and represent a constant threat to herbivorous insects. The honeydew of sap-feeding hemipterans has been suggested to appease aggressive ants, which then begin tending activities. Here, we manipulated the cuticular chemical profiles of freeze-dried insect prey to show that chemical background matching with the host plant protects Guayaquila xiphias treehoppers against predaceous Camponotus crassus ants, regardless of honeydew supply. Ant predation is increased when treehoppers are transferred to a nonhost plant with which they have low chemical similarity. Palatable moth larvae manipulated to match the chemical background of Guayaquila's host plant attracted lower numbers of predatory ants than unchanged controls. Although aggressive tending ants can protect honeydew-producing hemipterans from natural enemies, they may prey on the trophobionts under shortage of alternative food resources. Thus chemical camouflage in G. xiphias allows the trophobiont to attract predaceous bodyguards at reduced risk of falling prey itself.

Town ants: the beginning of John Moser’s remarkable search for knowledge

Treesearch

J.P. Barnett; D.A. Streett; S.R. Blomquist

2016-01-01

John C. Moser’s career spans over 50 years, and his research has focused on understanding the biology of town ants (Atta texana) and phoretic mites and other associates of ants and pine bark beetles. His approach to developing methods for the control of these pests has been to understand more completely the biology of these organisms. This research...

Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

NASA Astrophysics Data System (ADS)

Oesterle, Jonathan; Lionel, Amodeo

2018-06-01

The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Size does Matter

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

From schools of fish and flocks of birds, to digital networks and self-organizing biopolymers, our understanding of spontaneously emergent phenomena, self-organization, and critical behavior is in large part due to complex systems science. The complex systems approach is indeed a very powerful conceptual framework to shed light on the link between the microscopic dynamical evolution of the basic elements of the system and the emergence of oscopic phenomena; often providing evidence for mathematical principles that go beyond the particulars of the individual system, thus hinting to general modeling principles. By killing the myth of the ant queen and shifting the focus on the dynamical interaction across the elements of the systems, complex systems science has ushered our way into the conceptual understanding of many phenomena at the core of major scientific and social challenges such as the emergence of consensus, social opinion dynamics, conflicts and cooperation, contagion phenomena. For many years though, these complex systems approaches to real-world problems were often suffering from being oversimplified and not grounded on actual data...

Free and constrained expansion of fire ant aggregations

NASA Astrophysics Data System (ADS)

Fernandez-Nieves, Alberto; Anderson, Caleb

We revisit the classical free and constrained expansion of ideal gases with fire ant aggregations. We use rectangular parallel plates to confine fire ants to two-dimensions and watch how these expand when the plates are horizontal or when these are vertical. In the first case, the ants expand in a rather disorganized fashion, while in the second case, when there is work involved, the expansion is rather organized. The behavior is reminiscent of what is expected from the so called reversible process theorems of classical thermodynamics despite the ant aggregation is intrinsically out of equilibrium. This talk will focus on these results and in related observations in the same experimental setting.

Self-Organizing Maps-based ocean currents forecasting system.

PubMed

Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

2016-03-16

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

Self-Organizing Maps-based ocean currents forecasting system

PubMed Central

Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

2016-01-01

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training. PMID:26979129

Accuracy of vaginal symptom self-diagnosis algorithms for deployed military women.

PubMed

Ryan-Wenger, Nancy A; Neal, Jeremy L; Jones, Ashley S; Lowe, Nancy K

2010-01-01

Deployed military women have an increased risk for development of vaginitis due to extreme temperatures, primitive sanitation, hygiene and laundry facilities, and unavailable or unacceptable healthcare resources. The Women in the Military Self-Diagnosis (WMSD) and treatment kit was developed as a field-expedient solution to this problem. The primary study aims were to evaluate the accuracy of women's self-diagnosis of vaginal symptoms and eight diagnostic algorithms and to predict potential self-medication omission and commission error rates. Participants included 546 active duty, deployable Army (43.3%) and Navy (53.6%) women with vaginal symptoms who sought healthcare at troop medical clinics on base.In the clinic lavatory, women conducted a self-diagnosis using a sterile cotton swab to obtain vaginal fluid, a FemExam card to measure positive or negative pH and amines, and the investigator-developed WMSD Decision-Making Guide. Potential self-diagnoses were "bacterial infection" (bacterial vaginosis [BV] and/or trichomonas vaginitis [TV]), "yeast infection" (candida vaginitis [CV]), "no infection/normal," or "unclear." The Affirm VPIII laboratory reference standard was used to detect clinically significant amounts of vaginal fluid DNA for organisms associated with BV, TV, and CV. Women's self-diagnostic accuracy was 56% for BV/TV and 69.2% for CV. False-positives would have led to a self-medication commission error rate of 20.3% for BV/TV and 8% for CV. Potential self-medication omission error rates due to false-negatives were 23.7% for BV/TV and 24.8% for CV. The positive predictive value of diagnostic algorithms ranged from 0% to 78.1% for BV/TV and 41.7% for CV. The algorithms were based on clinical diagnostic standards. The nonspecific nature of vaginal symptoms, mixed infections, and a faulty device intended to measure vaginal pH and amines explain why none of the algorithms reached the goal of 95% accuracy. The next prototype of the WMSD kit will not include nonspecific vaginal signs and symptoms in favor of recently available point-of-care devices that identify antigens or enzymes of the causative BV, TV, and CV organisms.

Symbiotic intelligence: Self-organizing knowledge on distributed networks, driven by human interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, N.; Joslyn, C.; Rocha, L.

1998-07-01

This work addresses how human societies, and other diverse and distributed systems, solve collective challenges that are not approachable from the level of the individual, and how the Internet will change the way societies and organizations view problem solving. The authors apply the ideas developed in self-organizing systems to understand self-organization in informational systems. The simplest explanation as to why animals (for example, ants, wolves, and humans) are organized into societies is that these societies enhance the survival of the individuals which make up the populations. Individuals contribute to, as well as adapt to, these societies because they make lifemore » easier in one way or another, even though they may not always understand the process, either individually or collectively. Despite the lack of understanding of the how of the process, society during its existence as a species has changed significantly, from separate, small hunting tribes to a highly technological, globally integrated society. The authors combine this understanding of societal dynamics with self-organization on the Internet (the Net). The unique capability of the Net is that it combines, in a common medium, the entire human-technological system in both breadth and depth: breadth in the integration of heterogeneous systems of machines, information and people; and depth in the detailed capturing of the entire complexity of human use and creation of information. When the full diversity of societal dynamics is combined with the accuracy of communication on the Net, a phase transition is argued to occur in problem solving capability. Through conceptual examples, an experiment of collective decision making on the Net and a simulation showing the effect of noise and loss on collective decision making, the authors argue that the resulting symbiotic structure of humans and the Net will evolve as an alternative problem solving approach for groups, organizations and society. Self-organizing knowledge formation from this symbiotic intelligence exemplifies a new type of self-organizing system, one without dissipation and not constrained by limited resources.« less

The status of the fungi-grower ants (Hymenoptera: Formicidae) in Puerto Rico and adjacent islands

Treesearch

J.A. Torres

1989-01-01

Ants of the tribe Attini (fungus grower) collect different organic materials that are used to grow a fungus. It was thought that the fungus mycelium was the only source of nutrition for these ants, but Quinlan and Cherrett found that Atta cephalotes (L.) squeezes oils from fresh leaves and uses them as food.  These oils supplement the fungus material eaten by this...

Host Plant Use by Competing Acacia-Ants: Mutualists Monopolize While Parasites Share Hosts

PubMed Central

Kautz, Stefanie; Ballhorn, Daniel J.; Kroiss, Johannes; Pauls, Steffen U.; Moreau, Corrie S.; Eilmus, Sascha; Strohm, Erhard; Heil, Martin

2012-01-01

Protective ant-plant mutualisms that are exploited by non-defending parasitic ants represent prominent model systems for ecology and evolutionary biology. The mutualist Pseudomyrmex ferrugineus is an obligate plant-ant and fully depends on acacias for nesting space and food. The parasite Pseudomyrmex gracilis facultatively nests on acacias and uses host-derived food rewards but also external food sources. Integrative analyses of genetic microsatellite data, cuticular hydrocarbons and behavioral assays showed that an individual acacia might be inhabited by the workers of several P. gracilis queens, whereas one P. ferrugineus colony monopolizes one or more host trees. Despite these differences in social organization, neither of the species exhibited aggressive behavior among conspecific workers sharing a tree regardless of their relatedness. This lack of aggression corresponds to the high similarity of cuticular hydrocarbon profiles among ants living on the same tree. Host sharing by unrelated colonies, or the presence of several queens in a single colony are discussed as strategies by which parasite colonies could achieve the observed social organization. We argue that in ecological terms, the non-aggressive behavior of non-sibling P. gracilis workers — regardless of the route to achieve this social structure — enables this species to efficiently occupy and exploit a host plant. By contrast, single large and long-lived colonies of the mutualist P. ferrugineus monopolize individual host plants and defend them aggressively against invaders from other trees. Our findings highlight the necessity for using several methods in combination to fully understand how differing life history strategies affect social organization in ants. PMID:22662191

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Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-05

... electronic matching algorithm from CBOE Rule 6.45B shall apply to SAL executions (e.g., pro-rata, price-time... entitlement when the pro-rata algorithm is in effect for SAL in selected Hybrid 3.0 classes as part of a pilot... what it would have been under the pre-pilot allocation algorithm. The Exchange will reduce the DPM/LMM...

Emergence of a snake-like structure in mobile distributed agents: an exploratory agent-based modeling approach.

PubMed

Niazi, Muaz A

2014-01-01

The body structure of snakes is composed of numerous natural components thereby making it resilient, flexible, adaptive, and dynamic. In contrast, current computer animations as well as physical implementations of snake-like autonomous structures are typically designed to use either a single or a relatively smaller number of components. As a result, not only these artificial structures are constrained by the dimensions of the constituent components but often also require relatively more computationally intensive algorithms to model and animate. Still, these animations often lack life-like resilience and adaptation. This paper presents a solution to the problem of modeling snake-like structures by proposing an agent-based, self-organizing algorithm resulting in an emergent and surprisingly resilient dynamic structure involving a minimal of interagent communication. Extensive simulation experiments demonstrate the effectiveness as well as resilience of the proposed approach. The ideas originating from the proposed algorithm can not only be used for developing self-organizing animations but can also have practical applications such as in the form of complex, autonomous, evolvable robots with self-organizing, mobile components with minimal individual computational capabilities. The work also demonstrates the utility of exploratory agent-based modeling (EABM) in the engineering of artificial life-like complex adaptive systems.

Emergence of a Snake-Like Structure in Mobile Distributed Agents: An Exploratory Agent-Based Modeling Approach

PubMed Central

Niazi, Muaz A.

2014-01-01

The body structure of snakes is composed of numerous natural components thereby making it resilient, flexible, adaptive, and dynamic. In contrast, current computer animations as well as physical implementations of snake-like autonomous structures are typically designed to use either a single or a relatively smaller number of components. As a result, not only these artificial structures are constrained by the dimensions of the constituent components but often also require relatively more computationally intensive algorithms to model and animate. Still, these animations often lack life-like resilience and adaptation. This paper presents a solution to the problem of modeling snake-like structures by proposing an agent-based, self-organizing algorithm resulting in an emergent and surprisingly resilient dynamic structure involving a minimal of interagent communication. Extensive simulation experiments demonstrate the effectiveness as well as resilience of the proposed approach. The ideas originating from the proposed algorithm can not only be used for developing self-organizing animations but can also have practical applications such as in the form of complex, autonomous, evolvable robots with self-organizing, mobile components with minimal individual computational capabilities. The work also demonstrates the utility of exploratory agent-based modeling (EABM) in the engineering of artificial life-like complex adaptive systems. PMID:24701135

Distribution of the Formosa strain of the fire ant decapitating fly Pseudacteon curvatus (Diptera: Phoridae) three and a half years after releases in North Florida

USDA-ARS?s Scientific Manuscript database

The Formosa biotype of the decapitating fly Pseudacteon curvatus Borgmeier was released and successfully established as a self-sustaining biocontrol agent of the red imported fire ant Solenopsis invicta Buren at several sites around Gainesville, FL in 2003. In order to determine the status of these...

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Ant colony optimization for solving university facility layout problem

NASA Astrophysics Data System (ADS)

Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

2013-04-01

Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

Autonomous sensor manager agents (ASMA)

NASA Astrophysics Data System (ADS)

Osadciw, Lisa A.

2004-04-01

Autonomous sensor manager agents are presented as an algorithm to perform sensor management within a multisensor fusion network. The design of the hybrid ant system/particle swarm agents is described in detail with some insight into their performance. Although the algorithm is designed for the general sensor management problem, a simulation example involving 2 radar systems is presented. Algorithmic parameters are determined by the size of the region covered by the sensor network, the number of sensors, and the number of parameters to be selected. With straight forward modifications, this algorithm can be adapted for most sensor management problems.

An ant colony optimization heuristic for an integrated production and distribution scheduling problem

NASA Astrophysics Data System (ADS)

Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju

2014-04-01

Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.

Rate Adaptive Based Resource Allocation with Proportional Fairness Constraints in OFDMA Systems

PubMed Central

Yin, Zhendong; Zhuang, Shufeng; Wu, Zhilu; Ma, Bo

2015-01-01

Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain different subcarriers according to their subchannel gains. Therefore, how to assign subcarriers and power to different users to achieve a high system sum rate is an important research area in OFDMA systems. In this paper, the focus of study is on the rate adaptive (RA) based resource allocation with proportional fairness constraints. Since the resource allocation is a NP-hard and non-convex optimization problem, a new efficient resource allocation algorithm ACO-SPA is proposed, which combines ant colony optimization (ACO) and suboptimal power allocation (SPA). To reduce the computational complexity, the optimization problem of resource allocation in OFDMA systems is separated into two steps. For the first one, the ant colony optimization algorithm is performed to solve the subcarrier allocation. Then, the suboptimal power allocation algorithm is developed with strict proportional fairness, and the algorithm is based on the principle that the sums of power and the reciprocal of channel-to-noise ratio for each user in different subchannels are equal. To support it, plenty of simulation results are presented. In contrast with root-finding and linear methods, the proposed method provides better performance in solving the proportional resource allocation problem in OFDMA systems. PMID:26426016

Imidacloprid seed treatments affect individual ant behavior and community structure but not egg predation, pest abundance or soybean yield.

PubMed

Penn, Hannah J; Dale, Andrew M

2017-08-01

Neonicotinoid seed treatments are under scrutiny because of their variable efficacy against crop pests and for their potential negative impacts on non-target organisms. Ants provide important biocontrol services in agroecosystems and can be indicators of ecosystem health. This study tested for effects of exposure to imidacloprid plus fungicide or fungicide-treated seeds on individual ant survival, locomotion and foraging capabilities and on field ant community structure, pest abundance, ant predation and yield. Cohorts of ants exposed to either type of treated seed had impaired locomotion and a higher incidence of morbidity and mortality but no loss of foraging capacity. In the field, we saw no difference in ant species richness, regardless of seed treatment. Blocks with imidacloprid did have higher species evenness and diversity, probably owing to variable effects of the insecticide on different ant species, particularly Tetramorium caespitum. Ant predation on sentinel eggs, pest abundance and soybean growth and yield were similar in the two treatments. Both seed treatments had lethal and sublethal effects on ant individuals, and the influence of imidacloprid seed coating in the field was manifested in altered ant community composition. Those effects, however, were not strong enough to affect egg predation, pest abundance or soybean yield in field blocks. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt Derr

Mobile Ad hoc NETworks (MANETs) are distributed self-organizing networks that can change locations and configure themselves on the fly. This paper focuses on an algorithmic approach for the deployment of a MANET within an enclosed area, such as a building in a disaster scenario, which can provide a robust communication infrastructure for search and rescue operations. While a virtual spring mesh (VSM) algorithm provides scalable, self-organizing, and fault-tolerant capabilities required by aMANET, the VSM lacks the MANET's capabilities of deployment mechanisms for blanket coverage of an area and does not provide an obstacle avoidance mechanism. This paper presents a newmore » technique, an extended VSM (EVSM) algorithm that provides the following novelties: (1) new control laws for exploration and expansion to provide blanket coverage, (2) virtual adaptive springs enabling the mesh to expand as necessary, (3) adapts to communications disturbances by varying the density and movement of mobile nodes, and (4) new metrics to assess the performance of the EVSM algorithm. Simulation results show that EVSM provides up to 16% more coverage and is 3.5 times faster than VSM in environments with eight obstacles.« less

Asymmetric neighborhood functions accelerate ordering process of self-organizing maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ota, Kaiichiro; Aoki, Takaaki; Kurata, Koji

2011-02-15

A self-organizing map (SOM) algorithm can generate a topographic map from a high-dimensional stimulus space to a low-dimensional array of units. Because a topographic map preserves neighborhood relationships between the stimuli, the SOM can be applied to certain types of information processing such as data visualization. During the learning process, however, topological defects frequently emerge in the map. The presence of defects tends to drastically slow down the formation of a globally ordered topographic map. To remove such topological defects, it has been reported that an asymmetric neighborhood function is effective, but only in the simple case of mapping one-dimensionalmore » stimuli to a chain of units. In this paper, we demonstrate that even when high-dimensional stimuli are used, the asymmetric neighborhood function is effective for both artificial and real-world data. Our results suggest that applying the asymmetric neighborhood function to the SOM algorithm improves the reliability of the algorithm. In addition, it enables processing of complicated, high-dimensional data by using this algorithm.« less

Dynamic vehicle routing with time windows in theory and practice.

PubMed

Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

2017-01-01

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

Tetramorium tsushimae Ants Use Methyl Branched Hydrocarbons of Aphids for Partner Recognition.

PubMed

Sakata, Itaru; Hayashi, Masayuki; Nakamuta, Kiyoshi

2017-10-01

In mutualisms, partner discrimination is often the most important challenge for interacting organisms. The interaction between ants and aphids is a model system for studying mutualisms; ants are provided with honeydew by aphids and, in turn, the ants offer beneficial services to the aphids. To establish and maintain this system, ants must discriminate mutualistic aphid species correctly. Although recent studies have shown that ants recognize aphids as mutualistic partners based on their cuticular hydrocarbons (CHCs), it was unclear which CHCs are involved in recognition. Here, we tested whether the n-alkane or methylalkane fraction, or both, of aphid CHCs were utilized as partner recognition cues by measuring ant aggressiveness toward these fractions. When workers of Tetramorium tsushimae ants were presented with dummies coated with n-alkanes of their mutualistic aphid Aphis craccivora, ants displayed higher levels of aggression than to dummies treated with total CHCs or methyl alkanes of A. craccivora; responses to dummies treated with n-alkanes of A. craccivora were similar to those to control dummies or dummies treated with the CHCs of the non-mutualistic aphid Acyrthosiphon pisum. By contrast, ants exhibited lower aggression to dummies treated with either total CHCs or the methylalkane fraction of the mutualistic aphid than to control dummies or dummies treated with CHCs of the non-mutualistic aphid. These results suggest that T. tsushimae ants use methylalkanes of the mutualistic aphid's CHCs to recognize partners, and that these ants do not recognize aphids as partners on the basis of n-alkanes.

A Self-Organizing State-Space-Model Approach for Parameter Estimation in Hodgkin-Huxley-Type Models of Single Neurons

PubMed Central

Vavoulis, Dimitrios V.; Straub, Volko A.; Aston, John A. D.; Feng, Jianfeng

2012-01-01

Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm), often in combination with a local search method (such as gradient descent) in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a potentially useful tool in the construction of biophysical neuron models. PMID:22396632

Dual response to nest flooding during monsoon in an Indian ant

PubMed Central

Kolay, Swetashree; Annagiri, Sumana

2015-01-01

Flooding causes destruction of shelter and disruption of activity in animals occupying subterranean nests. To ensure their survival organisms have evolved various responses to combat this problem. In this study we examine the response of an Indian ant, Diacamma indicum, to nest flooding during the monsoon season. Based on characterization of nest location, architecture and the response of these ants to different levels of flooding in their natural habitat as well as in the laboratory, we infer that they exhibit a dual response. On the one hand, the challenges presented by monsoon are dealt with by occupying shallow nests and modifying the entrance with decorations and soil mounds. On the other hand, inundated nests are evacuated and the ants occupy shelters at higher elevations. We conclude that focused studies of the monsoon biology of species that dwell in such climatic conditions may help us appreciate how organisms deal with, and adapt to, extreme seasonal changes. PMID:26349015

The pregnant smoker's experience of ante-natal care--results from a qualitative study.

PubMed

Haugland, S; Haug, K; Wold, B

1996-12-01

1) To obtain insight into pregnant smokers' experience of the information received from doctor and midwife at the ante-natal clinic. 2) To develop an understanding of pregnant women's own ideas of how health personnel can help them stop smoking. Qualitative study with strategic sampling. 33 pregnant smokers took part in an in-depth interview in the third trimester. Home of patients, or surgeries in Hordaland county, Norway. Daily smokers during the last three months before conception, and still smoking in the 16th-18th week of pregnancy. Pregnant women lacking motivation to stop smoking seemed to be most satisfied with ante-natal care. The women interviewed saw doctors and midwives as responsible for raising the subject of smoking, and blamed them for disinterest. The findings suggest that pregnant smokers may be classified into four categories ("it could have been worse", "self-delusion", "self-confident", and "rational"), and that intervention should be tailored to meet each woman's perception of control over smoking behaviour.

Integrating Flexible Sensor and Virtual Self-Organizing DC Grid Model With Cloud Computing for Blood Leakage Detection During Hemodialysis.

PubMed

Huang, Ping-Tzan; Jong, Tai-Lang; Li, Chien-Ming; Chen, Wei-Ling; Lin, Chia-Hung

2017-08-01

Blood leakage and blood loss are serious complications during hemodialysis. From the hemodialysis survey reports, these life-threatening events occur to attract nephrology nurses and patients themselves. When the venous needle and blood line are disconnected, it takes only a few minutes for an adult patient to lose over 40% of his / her blood, which is a sufficient amount of blood loss to cause the patient to die. Therefore, we propose integrating a flexible sensor and self-organizing algorithm to design a cloud computing-based warning device for blood leakage detection. The flexible sensor is fabricated via a screen-printing technique using metallic materials on a soft substrate in an array configuration. The self-organizing algorithm constructs a virtual direct current grid-based alarm unit in an embedded system. This warning device is employed to identify blood leakage levels via a wireless network and cloud computing. It has been validated experimentally, and the experimental results suggest specifications for its commercial designs. The proposed model can also be implemented in an embedded system.

A Proposal of 3-dimensional Self-organizing Memory and Its Application to Knowledge Extraction from Natural Language

NASA Astrophysics Data System (ADS)

Sakakibara, Kai; Hagiwara, Masafumi

In this paper, we propose a 3-dimensional self-organizing memory and describe its application to knowledge extraction from natural language. First, the proposed system extracts a relation between words by JUMAN (morpheme analysis system) and KNP (syntax analysis system), and stores it in short-term memory. In the short-term memory, the relations are attenuated with the passage of processing. However, the relations with high frequency of appearance are stored in the long-term memory without attenuation. The relations in the long-term memory are placed to the proposed 3-dimensional self-organizing memory. We used a new learning algorithm called ``Potential Firing'' in the learning phase. In the recall phase, the proposed system recalls relational knowledge from the learned knowledge based on the input sentence. We used a new recall algorithm called ``Waterfall Recall'' in the recall phase. We added a function to respond to questions in natural language with ``yes/no'' in order to confirm the validity of proposed system by evaluating the quantity of correct answers.

Ant colony optimization algorithm for signal coordination of oversaturated traffic networks.

DOT National Transportation Integrated Search

2010-05-01

Traffic congestion is a daily and growing problem of the modern era in mostly all major cities in the world. : Increasing traffic demand strains the existing transportation system, leading to oversaturated network : conditions, especially at peak hou...

Readiness to tackle chronicity in Spanish health care organisations: a two-year experience with the Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations instrument

PubMed Central

Mira, José Joaquín; Fernández-Cano, Paloma; Contel, Joan Carlos; Guilabert-Mora, Mercedes; Solas-Gaspar, Olga

2015-01-01

Introduction: The Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations instrument was developed to implement the conceptual framework of the Chronic Care Model in the Spanish national health system. It has been used to assess readiness to tackle chronicity in health care organisations. In this study, we use self-assessments at macro-, meso- and micro-management levels to (a) describe the two-year experience with the Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations tool in Spain and (b) assess the validity and reliability of this instrument. Methods: The results from 55 organisational self-assessments were included and described. In addition to that, the internal consistency, reliability and construct validity of Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations were examined using Cronbach's alpha, the Spearman–Brown coefficient and factorial analysis. Results: The obtained scores reflect opportunities for improvement in all dimensions of the instrument. Cronbach's alpha ranged between 0.90 and 0.95 and the Spearman–Brown coefficient ranged between 0.77 and 0.94. All 27 components converged in a second-order factorial solution that explained 53.8% of the total variance, with factorial saturations for the components of between 0.57 and 0.94. Conclusions: Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations is an instrument that allows health care organisations to perform self-assessments regarding their readiness to tackle chronicity and to identify areas for improvement in chronic care. PMID:27118958

Readiness to tackle chronicity in Spanish health care organisations: a two-year experience with the Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations instrument.

PubMed

Mira, José Joaquín; Nuño-Solinís, Roberto; Fernández-Cano, Paloma; Contel, Joan Carlos; Guilabert-Mora, Mercedes; Solas-Gaspar, Olga

2015-01-01

The Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations instrument was developed to implement the conceptual framework of the Chronic Care Model in the Spanish national health system. It has been used to assess readiness to tackle chronicity in health care organisations. In this study, we use self-assessments at macro-, meso- and micro-management levels to (a) describe the two-year experience with the Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations tool in Spain and (b) assess the validity and reliability of this instrument. The results from 55 organisational self-assessments were included and described. In addition to that, the internal consistency, reliability and construct validity of Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations were examined using Cronbach's alpha, the Spearman-Brown coefficient and factorial analysis. The obtained scores reflect opportunities for improvement in all dimensions of the instrument. Cronbach's alpha ranged between 0.90 and 0.95 and the Spearman-Brown coefficient ranged between 0.77 and 0.94. All 27 components converged in a second-order factorial solution that explained 53.8% of the total variance, with factorial saturations for the components of between 0.57 and 0.94. Instrumento de Evaluación de Modelos de Atención ante la Cronicidad/Assessment of Readiness for Chronicity in Health Care Organisations is an instrument that allows health care organisations to perform self-assessments regarding their readiness to tackle chronicity and to identify areas for improvement in chronic care.

Impact of forest seral stage on use of ant communities for rapid assessment of terrestrial ecosystem health.

PubMed

Wike, Lynn D; Martin, F Douglas; Paller, Michael H; Nelson, Eric A

2010-01-01

Bioassessment evaluates ecosystem health by using the responses of a community of organisms that integrate all aspects of the ecosystem. A variety of bioassessment methods have been applied to aquatic ecosystems; however, terrestrial methods are less advanced. The objective of this study was to examine baseline differences in ant communities at different seral stages from clear cut to mature pine plantation as a precursor to developing a broader terrestrial bioassessment protocol. Comparative sampling was conducted at nine sites having four seral stages: clearcut, 5 year recovery, 15 year recovery, and mature stands. Soil and vegetation data were also collected at each site. Ants were identified to genus. Analysis of the ant data indicated that ants respond strongly to habitat changes that accompany ecological succession in managed pine forests, and both individual genera and ant community structure can be used as indicators of successional change. Ants exhibited relatively high diversity in both early and mature seral stages. High ant diversity in mature seral stages was likely related to conditions on the forest floor favoring litter dwelling and cold climate specialists. While ants may be very useful in identifying environmental stress in managed pine forests, adjustments must be made for seral stage when comparing impacted and unimpacted forests.

How to be an ant on figs

NASA Astrophysics Data System (ADS)

Bain, Anthony; Harrison, Rhett D.; Schatz, Bertrand

2014-05-01

Mutualistic interactions are open to exploitation by one or other of the partners and a diversity of other organisms, and hence are best understood as being embedded in a complex network of biotic interactions. Figs participate in an obligate mutualism in that figs are dependent on agaonid fig wasps for pollination and the wasps are dependent on fig ovules for brood sites. Ants are common insect predators and abundant in tropical forests. Ants have been recorded on approximately 11% of fig species, including all six subgenera, and often affect the fig-fig pollinator interaction through their predation of either pollinating and parasitic wasps. On monoecious figs, ants are often associated with hemipterans, whereas in dioecious figs ants predominantly prey on fig wasps. A few fig species are true myrmecophytes, with domatia or food rewards for ants, and in at least one species this is linked to predation of parasitic fig wasps. Ants also play a role in dispersal of fig seeds and may be particularly important for hemi-epiphytic species, which require high quality establishment microsites in the canopy. The intersection between the fig-fig pollinator and ant-plant systems promises to provide fertile ground for understanding mutualistic interactions within the context of complex interaction networks.

Swarms, phase transitions, and collective intelligence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Millonas, M.M.

1992-01-01

A model of the collective behavior of a large number of locally acting organisms is proposed. The model is intended to be realistic, but turns out to fit naturally into the category of connectionist models, Like all connectionist models, its properties can be divided into the categories of structure, dynamics, and learning. The space in which the organisms move is discretized, and is modeled by a lattice of nodes, or cells. Each cell hag a specified volume, and is connected to other cells in the space in a definite way. Organisms move probabilistically between local cells in this space, butmore » with weights dependent on local morphogenic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding constitutes of the organisms constitutes the collective behavior of the group. The generic properties of such systems are analyzed, and a number of results are obtained. The model has various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. It is hoped that the present mode; might serve as a paradigmatic example of a complex cooperative system in nature. In particular this model can be used to explore the relation of phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of second order phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. Monte carlo simulations are used as illustrations.« less

Swarms, phase transitions, and collective intelligence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Millonas, M.M.

1992-12-31

A model of the collective behavior of a large number of locally acting organisms is proposed. The model is intended to be realistic, but turns out to fit naturally into the category of connectionist models, Like all connectionist models, its properties can be divided into the categories of structure, dynamics, and learning. The space in which the organisms move is discretized, and is modeled by a lattice of nodes, or cells. Each cell hag a specified volume, and is connected to other cells in the space in a definite way. Organisms move probabilistically between local cells in this space, butmore » with weights dependent on local morphogenic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding constitutes of the organisms constitutes the collective behavior of the group. The generic properties of such systems are analyzed, and a number of results are obtained. The model has various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. It is hoped that the present mode; might serve as a paradigmatic example of a complex cooperative system in nature. In particular this model can be used to explore the relation of phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of second order phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. Monte carlo simulations are used as illustrations.« less

Adding dynamic rules to self-organizing fuzzy systems

NASA Technical Reports Server (NTRS)

Buhusi, Catalin V.

1992-01-01

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

NASA Astrophysics Data System (ADS)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

A Hybrid Ant Colony Optimization Algorithm for the Extended Capacitated Arc Routing Problem.

PubMed

Li-Ning Xing; Rohlfshagen, P; Ying-Wu Chen; Xin Yao

2011-08-01

The capacitated arc routing problem (CARP) is representative of numerous practical applications, and in order to widen its scope, we consider an extended version of this problem that entails both total service time and fixed investment costs. We subsequently propose a hybrid ant colony optimization (ACO) algorithm (HACOA) to solve instances of the extended CARP. This approach is characterized by the exploitation of heuristic information, adaptive parameters, and local optimization techniques: Two kinds of heuristic information, arc cluster information and arc priority information, are obtained continuously from the solutions sampled to guide the subsequent optimization process. The adaptive parameters ease the burden of choosing initial values and facilitate improved and more robust results. Finally, local optimization, based on the two-opt heuristic, is employed to improve the overall performance of the proposed algorithm. The resulting HACOA is tested on four sets of benchmark problems containing a total of 87 instances with up to 140 nodes and 380 arcs. In order to evaluate the effectiveness of the proposed method, some existing capacitated arc routing heuristics are extended to cope with the extended version of this problem; the experimental results indicate that the proposed ACO method outperforms these heuristics.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

NASA Astrophysics Data System (ADS)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

Termites: a Retinex implementation based on a colony of agents

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Audino, Giuseppe; Farup, Ivar; Rizzi, Alessandro

2012-01-01

This paper describes a novel implementation of the Retinex algorithm with the exploration of the image done by an ant swarm. In this case the purpose of the ant colony is not the optimization of some constraints but is an alternative way to explore the image content as diffused as possible, with the possibility of tuning the exploration parameters to the image content trying to better approach the Human Visual System behavior. For this reason, we used "termites", instead of ants, to underline the idea of the eager exploration of the image. The paper presents the spatial characteristics of locality and discusses differences in path exploration with other Retinex implementations. Furthermore a psychophysical experiment has been carried out on eight images with 20 observers and results indicate that a termite swarm should investigate a particular region of an image to find the local reference white.

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

PubMed Central

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

PubMed

Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

2016-01-01

Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

Self-* properties through gossiping.

PubMed

Babaoglu, Ozalp; Jelasity, Márk

2008-10-28

As computer systems have become more complex, numerous competing approaches have been proposed for these systems to self-configure, self-manage, self-repair, etc. such that human intervention in their operation can be minimized. In ubiquitous systems, this has always been a central issue as well. In this paper, we overview techniques to implement self-* properties in large-scale, decentralized networks through bio-inspired techniques in general, and gossip-based algorithms in particular. We believe that gossip-based algorithms could be an important inspiration for solving problems in ubiquitous computing as well. As an example, we outline a novel approach to arrange large numbers of mobile agents (e.g. vehicles, rescue teams carrying mobile devices) into different formations in a totally decentralized manner. The approach is inspired by the biological mechanism of cell sorting via differential adhesion, as well as by our earlier work in self-organizing peer-to-peer overlay networks.

Improved multi-objective ant colony optimization algorithm and its application in complex reasoning

NASA Astrophysics Data System (ADS)

Wang, Xinqing; Zhao, Yang; Wang, Dong; Zhu, Huijie; Zhang, Qing

2013-09-01

The problem of fault reasoning has aroused great concern in scientific and engineering fields. However, fault investigation and reasoning of complex system is not a simple reasoning decision-making problem. It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints. So far, little research has been carried out in this field. This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes. Three optimization objectives are considered simultaneously: maximum probability of average fault, maximum average importance, and minimum average complexity of test. Under the constraints of both known symptoms and the causal relationship among different components, a multi-objective optimization mathematical model is set up, taking minimizing cost of fault reasoning as the target function. Since the problem is non-deterministic polynomial-hard(NP-hard), a modified multi-objective ant colony algorithm is proposed, in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives. At last, a Pareto optimal set is acquired. Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set, through which the final fault causes can be identified according to decision-making demands, thus realize fault reasoning of the multi-constraint and multi-objective complex system. Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model, which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system.

Arboreal ant colonies as 'hot-points' of cryptic diversity for myrmecophiles: the weaver ant Camponotus sp. aff. textor and its interaction network with its associates.

PubMed

Pérez-Lachaud, Gabriela; Lachaud, Jean-Paul

2014-01-01

Systematic surveys of macrofaunal diversity within ant colonies are lacking, particularly for ants nesting in microhabitats that are difficult to sample. Species associated with ants are generally small and rarely collected organisms, which makes them more likely to be unnoticed. We assumed that this tendency is greater for arthropod communities in microhabitats with low accessibility, such as those found in the nests of arboreal ants that may constitute a source of cryptic biodiversity. We investigated the invertebrate diversity associated with an undescribed, but already threatened, Neotropical Camponotus weaver ant. As most of the common sampling methods used in studies of ant diversity are not suited for evaluating myrmecophile diversity within ant nests, we evaluated the macrofauna within ant nests through exhaustive colony sampling of three nests and examination of more than 80,000 individuals. We identified invertebrates from three classes belonging to 18 taxa, some of which were new to science, and recorded the first instance of the co-occurrence of two brood parasitoid wasp families attacking the same ant host colony. This diversity of ant associates corresponded to a highly complex interaction network. Agonistic interactions prevailed, but the prevalence of myrmecophiles was remarkably low. Our data support the hypothesis of the evolution of low virulence in a variety of symbionts associated with large insect societies. Because most myrmecophiles found in this work are rare, strictly specific, and exhibit highly specialized biology, the risk of extinction for these hitherto unknown invertebrates and their natural enemies is high. The cryptic, far unappreciated diversity within arboreal ant nests in areas at high risk of habitat loss qualifies these nests as 'hot-points' of biodiversity that urgently require special attention as a component of conservation and management programs.

Symbiotic adaptations in the fungal cultivar of leaf-cutting ants.

PubMed

De Fine Licht, Henrik H; Boomsma, Jacobus J; Tunlid, Anders

2014-12-01

Centuries of artificial selection have dramatically improved the yield of human agriculture; however, strong directional selection also occurs in natural symbiotic interactions. Fungus-growing attine ants cultivate basidiomycete fungi for food. One cultivar lineage has evolved inflated hyphal tips (gongylidia) that grow in bundles called staphylae, to specifically feed the ants. Here we show extensive regulation and molecular signals of adaptive evolution in gene trancripts associated with gongylidia biosynthesis, morphogenesis and enzymatic plant cell wall degradation in the leaf-cutting ant cultivar Leucoagaricus gongylophorus. Comparative analysis of staphylae growth morphology and transcriptome-wide expressional and nucleotide divergence indicate that gongylidia provide leaf-cutting ants with essential amino acids and plant-degrading enzymes, and that they may have done so for 20-25 million years without much evolutionary change. These molecular traits and signatures of selection imply that staphylae are highly advanced coevolutionary organs that play pivotal roles in the mutualism between leaf-cutting ants and their fungal cultivars.

Methane and carbon dioxide flux in the profile of wood ant (Formica aquilonia) nests and the surrounding forest floor during a laboratory incubation.

PubMed

Jílková, Veronika; Picek, Tomáš; Šestauberová, Martina; Krištůfek, Václav; Cajthaml, Tomáš; Frouz, Jan

2016-10-01

We compared methane (CH4) and carbon dioxide (CO2) fluxes in samples collected from the aboveground parts of wood ant nests and in the organic and mineral layer of the surrounding forest floor. Gas fluxes were measured during a laboratory incubation, and microbial properties (abundance of fungi, bacteria and methanotrophic bacteria) and nutrient contents (total and available carbon and nitrogen) were also determined. Both CO2 and CH4 were produced from ant nest samples, indicating that the aboveground parts of wood ant nests act as sources of both gases; in comparison, the forest floor produced about four times less CO2 and consumed rather than produced CH4 Fluxes of CH4 and CO2 were positively correlated with contents of available carbon and nitrogen. The methanotrophic community was represented by type II methanotrophic bacteria, but their abundance did not explain CH4 flux. Fungal abundance was greater in ant nest samples than in forest floor samples, but bacterial abundance was similar in both kinds of samples, suggesting that the organic materials in the nests may have been too recalcitrant for bacteria to decompose. The results indicate that the aboveground parts of wood ant nests are hot spots of CO2 and CH4 production in the forest floor. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Clinical consequences of toxic envenomations by Hymenoptera.

PubMed

Schmidt, Justin O

2018-05-19

Many familiar Hymenoptera are brightly colored and can sting painfully-thus, their threat and clinical importance may be exaggerated. Most stinging insects only sting to defend themselves or their colonies from predators. The clinical nature of Hymenoptera envenomations contrasts that of other venomous animals, including other arthropods, primarily because allergic reaction, not direct intoxication, is the usual main concern. This review focuses mainly on the clinical features of direct toxicity to Hymenoptera envenomations, which can induce a high incidence of acute renal failure, liver failure, multiple organ failures, and death. Toxic mass envenomations by honeybees usually entail many hundreds or more stings per victim. In contrast to honeybee toxic envenomations, hornet sting envenomations can be clinically threatening with only 20-200 stings needed to cause kidney and other organ failures. Many lethal envenomations by honeybees occur in rural areas in the New World and Africa and are not recorded or documented. In contrast, deaths by hornets occur mainly to Asia. The most frequent and important envenomating taxa are honeybees, hornets, yellowjacket wasps, paper wasps, fire ants, and jack jumper ants. Occasional envenomating taxa include bumblebees, bullet ants, harvester ants, solitary wasps, solitary bees, and various ants of lesser clinical importance. Envenomations by Hymenoptera usually can be avoided if one considers that bees, wasps and ants "view" us as potential threats or predators, and that with information about the biology of stinging Hymenoptera, humans can minimize adverse incidents. Copyright © 2018 Elsevier Ltd. All rights reserved.

Double Deception: Ant-Mimicking Spiders Elude Both Visually- and Chemically-Oriented Predators

PubMed Central

Uma, Divya; Durkee, Caitlin; Herzner, Gudrun; Weiss, Martha

2013-01-01

Biological mimicry is often multimodal, in that a mimic reinforces its resemblance to another organism via different kinds of signals that can be perceived by a specific target audience. In this paper we describe a novel scenario, in which a mimic deceives at least two distinct audiences, each of which relies primarily on a different sensory modality for decision-making. We have previously shown that Peckhamia picata, a myrmecomorphic spider that morphologically and behaviorally resembles the ant Camponotus nearcticus, experiences reduced predation by visually-oriented jumping spiders. Here we report that Peckhamia also faces reduced aggression from spider-hunting sphecid wasps as well as from its model ant, both of which use chemical cues to identify prey. We also report that Peckhamia does not chemically resemble its model ants, and that its total cuticular hydrocarbons are significantly lower than those of the ants and non-mimic spiders. Although further studies are needed to clarify the basis of Peckhamia's chemically-mediated protection, to our knowledge, such ‘double deception,’ in which a single organism sends misleading visual cues to one set of predators while chemically misleading another set, has not been reported; however, it is likely to be common among what have until now been considered purely visual mimics. PMID:24236152

Temporal Variation in the Abundance and Richness of Foliage-Dwelling Ants Mediated by Extrafloral Nectar.

PubMed

Belchior, Ceres; Sendoya, Sebastián F; Del-Claro, Kleber

2016-01-01

Plants bearing extrafloral nectaries (EFNs) are common in the Brazilian cerrado savanna, where climatic conditions having marked seasonality influence arboreal ant fauna organization. These ant-plant interactions have rarely been studied at community level. Here, we tested whether: 1) EFN-bearing plants are more visited by ants than EFN-lacking plants; 2) ant visitation is higher in the rainy season than in dry season; 3) plants producing young leaves are more visited than those lacking young leaves in the rainy season; 4) during the dry season, plants with old leaves and flowers are more visited than plants with young leaves and bare of leaves or flowers; 5) the composition of visiting ant fauna differs between plants with and without EFNs. Field work was done in a cerrado reserve near Uberlândia, MG State, Brazil, along ten transects (total area 3,000 m2), in the rainy (October-January) and dry seasons (April-July) of 2010-2011. Plants (72 species; 762 individuals) were checked three times per season for ant presence. Results showed that 21 species (29%) and 266 individuals (35%) possessed EFNs. These plants attracted 38 ant species (36 in rainy, 26 in dry season). In the rainy season, plants with EFNs had higher ant abundance/richness than plants without EFNs, but in the dry season, EFN presence did not influence ant visitation. Plant phenology affected ant richness and abundance in different ways: plants with young leaves possessed higher ant richness in the rainy season, but in the dry season ant abundance was higher on plants possessing old leaves or flowers. The species composition of plant-associated ant communities, however, did not differ between plants with and without EFNs in either season. These findings suggest that the effect of EFN presence on a community of plant-visiting ants is context dependent, being conditioned to seasonal variation.

Temporal Variation in the Abundance and Richness of Foliage-Dwelling Ants Mediated by Extrafloral Nectar

PubMed Central

Belchior, Ceres; Sendoya, Sebastián F.

2016-01-01

Plants bearing extrafloral nectaries (EFNs) are common in the Brazilian cerrado savanna, where climatic conditions having marked seasonality influence arboreal ant fauna organization. These ant-plant interactions have rarely been studied at community level. Here, we tested whether: 1) EFN-bearing plants are more visited by ants than EFN-lacking plants; 2) ant visitation is higher in the rainy season than in dry season; 3) plants producing young leaves are more visited than those lacking young leaves in the rainy season; 4) during the dry season, plants with old leaves and flowers are more visited than plants with young leaves and bare of leaves or flowers; 5) the composition of visiting ant fauna differs between plants with and without EFNs. Field work was done in a cerrado reserve near Uberlândia, MG State, Brazil, along ten transects (total area 3,000 m2), in the rainy (October-January) and dry seasons (April-July) of 2010–2011. Plants (72 species; 762 individuals) were checked three times per season for ant presence. Results showed that 21 species (29%) and 266 individuals (35%) possessed EFNs. These plants attracted 38 ant species (36 in rainy, 26 in dry season). In the rainy season, plants with EFNs had higher ant abundance/richness than plants without EFNs, but in the dry season, EFN presence did not influence ant visitation. Plant phenology affected ant richness and abundance in different ways: plants with young leaves possessed higher ant richness in the rainy season, but in the dry season ant abundance was higher on plants possessing old leaves or flowers. The species composition of plant-associated ant communities, however, did not differ between plants with and without EFNs in either season. These findings suggest that the effect of EFN presence on a community of plant-visiting ants is context dependent, being conditioned to seasonal variation. PMID:27438722

Software Piracy Detection Model Using Ant Colony Optimization Algorithm

NASA Astrophysics Data System (ADS)

Astiqah Omar, Nor; Zakuan, Zeti Zuryani Mohd; Saian, Rizauddin

2017-06-01

Internet enables information to be accessible anytime and anywhere. This scenario creates an environment whereby information can be easily copied. Easy access to the internet is one of the factors which contribute towards piracy in Malaysia as well as the rest of the world. According to a survey conducted by Compliance Gap BSA Global Software Survey in 2013 on software piracy, found out that 43 percent of the software installed on PCs around the world was not properly licensed, the commercial value of the unlicensed installations worldwide was reported to be 62.7 billion. Piracy can happen anywhere including universities. Malaysia as well as other countries in the world is faced with issues of piracy committed by the students in universities. Piracy in universities concern about acts of stealing intellectual property. It can be in the form of software piracy, music piracy, movies piracy and piracy of intellectual materials such as books, articles and journals. This scenario affected the owner of intellectual property as their property is in jeopardy. This study has developed a classification model for detecting software piracy. The model was developed using a swarm intelligence algorithm called the Ant Colony Optimization algorithm. The data for training was collected by a study conducted in Universiti Teknologi MARA (Perlis). Experimental results show that the model detection accuracy rate is better as compared to J48 algorithm.

Opposing effects of allogrooming on disease transmission in ant societies

PubMed Central

Theis, Fabian J.; Ugelvig, Line V.; Marr, Carsten; Cremer, Sylvia

2015-01-01

To prevent epidemics, insect societies have evolved collective disease defences that are highly effective at curing exposed individuals and limiting disease transmission to healthy group members. Grooming is an important sanitary behaviour—either performed towards oneself (self-grooming) or towards others (allogrooming)—to remove infectious agents from the body surface of exposed individuals, but at the risk of disease contraction by the groomer. We use garden ants (Lasius neglectus) and the fungal pathogen Metarhizium as a model system to study how pathogen presence affects self-grooming and allogrooming between exposed and healthy individuals. We develop an epidemiological SIS model to explore how experimentally observed grooming patterns affect disease spread within the colony, thereby providing a direct link between the expression and direction of sanitary behaviours, and their effects on colony-level epidemiology. We find that fungus-exposed ants increase self-grooming, while simultaneously decreasing allogrooming. This behavioural modulation seems universally adaptive and is predicted to contain disease spread in a great variety of host–pathogen systems. In contrast, allogrooming directed towards pathogen-exposed individuals might both increase and decrease disease risk. Our model reveals that the effect of allogrooming depends on the balance between pathogen infectiousness and efficiency of social host defences, which are likely to vary across host–pathogen systems. PMID:25870394

On the Correlation Between the Self-Organized Island Pattern and Substrate Elastic Anisotropy

DTIC Science & Technology

2007-04-01

eters would be most useful to experimentalists. The kinetic Monte Carlo KMC has been proposed re- cently to study QD island self-organization by many...time ti. 21,25 Based on a proposed coupled KMC , the authors simu- lated the island ordering and narrow size distribution in two dimensions and further...100, 013527 2006pattern has not been studied so far within the coupled KMC algorithm where the long-range strain energy field is in- cluded

An improved harmony search algorithm for emergency inspection scheduling

NASA Astrophysics Data System (ADS)

Kallioras, Nikos A.; Lagaros, Nikos D.; Karlaftis, Matthew G.

2014-11-01

The ability of nature-inspired search algorithms to efficiently handle combinatorial problems, and their successful implementation in many fields of engineering and applied sciences, have led to the development of new, improved algorithms. In this work, an improved harmony search (IHS) algorithm is presented, while a holistic approach for solving the problem of post-disaster infrastructure management is also proposed. The efficiency of IHS is compared with that of the algorithms of particle swarm optimization, differential evolution, basic harmony search and the pure random search procedure, when solving the districting problem that is the first part of post-disaster infrastructure management. The ant colony optimization algorithm is employed for solving the associated routing problem that constitutes the second part. The comparison is based on the quality of the results obtained, the computational demands and the sensitivity on the algorithmic parameters.

Detection and Length Estimation of Linear Scratch on Solid Surfaces Using an Angle Constrained Ant Colony Technique

NASA Astrophysics Data System (ADS)

Pal, Siddharth; Basak, Aniruddha; Das, Swagatam

In many manufacturing areas the detection of surface defects is one of the most important processes in quality control. Currently in order to detect small scratches on solid surfaces most of the industries working on material manufacturing rely on visual inspection primarily. In this article we propose a hybrid computational intelligence technique to automatically detect a linear scratch from a solid surface and estimate its length (in pixel unit) simultaneously. The approach is based on a swarm intelligence algorithm called Ant Colony Optimization (ACO) and image preprocessing with Wiener and Sobel filters as well as the Canny edge detector. The ACO algorithm is mostly used to compensate for the broken parts of the scratch. Our experimental results confirm that the proposed technique can be used for detecting scratches from noisy and degraded images, even when it is very difficult for conventional image processing to distinguish the scratch area from its background.

Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Hartmann, G. L.; Stein, G.; Pratt, S. G.

1979-01-01

The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.

Evidence of behavioral co-option from context-dependent variation in mandible use in trap-jaw ants ( Odontomachus spp.)

NASA Astrophysics Data System (ADS)

Spagna, Joseph C.; Schelkopf, Adam; Carrillo, Tiana; Suarez, Andrew V.

2009-02-01

Evolutionary co-option of existing structures for new functions is a powerful yet understudied mechanism for generating novelty. Trap-jaw ants of the predatory genus Odontomachus are capable of some of the fastest self-propelled appendage movements ever recorded; their devastating strikes are not only used to disable and capture prey, but produce enough force to launch the ants into the air. We tested four Odontomachus species in a variety of behavioral contexts to examine if their mandibles have been co-opted for an escape mechanism through ballistic propulsion. We found that nest proximity makes no difference in interactions with prey, but that prey size has a strong influence on the suite of behaviors employed by the ants. In trials involving a potential threat (another trap-jaw ant species), vertical jumps were significantly more common in ants acting as intruders than in residents (i.e. a dangerous context), while horizontal jumps occurred at the same rate in both contexts. Additionally, horizontal jump trajectories were heavily influenced by the angle at which the substrate was struck and appear to be under little control by the ant. We conclude that while horizontal jumps may be accidental side-effects of strikes against hard surfaces, vertical escape jumps are likely intentional defensive behaviors that have been co-opted from the original prey-gathering and food-processing functions of Odontomachus jaws.

Invasive Fire Ants Reduce Reproductive Success and Alter the Reproductive Strategies of a Native Vertebrate Insectivore

PubMed Central

Ligon, Russell A.; Siefferman, Lynn; Hill, Geoffrey E.

2011-01-01

Background Introduced organisms can alter ecosystems by disrupting natural ecological relationships. For example, red imported fire ants (Solenopsis invicta) have disrupted native arthropod communities throughout much of their introduced range. By competing for many of the same food resources as insectivorous vertebrates, fire ants also have the potential to disrupt vertebrate communities. Methodology/Principal Findings To explore the effects of fire ants on a native insectivorous vertebrate, we compared the reproductive success and strategies of eastern bluebirds (Sialia sialis) inhabiting territories with different abundances of fire ants. We also created experimental dyads of adjacent territories comprised of one territory with artificially reduced fire ant abundance (treated) and one territory that was unmanipulated (control). We found that more bluebird young fledged from treated territories than from adjacent control territories. Fire ant abundance also explained significant variation in two measures of reproductive success across the study population: number of fledglings and hatching success of second clutches. Furthermore, the likelihood of bluebird parents re-nesting in the same territory was negatively influenced by the abundance of foraging fire ants, and parents nesting in territories with experimentally reduced abundances of fire ants produced male-biased broods relative to pairs in adjacent control territories. Conclusions/Significance Introduced fire ants altered both the reproductive success (number of fledglings, hatching success) and strategies (decision to renest, offspring sex-ratio) of eastern bluebirds. These results illustrate the negative effects that invasive species can have on native biota, including species from taxonomically distant groups. PMID:21799904

Indirect effects of tending ants on holm oak volatiles and acorn quality

PubMed Central

Llusia, Joan; Peñuelas, Josep

2011-01-01

The indirect effect of ants on plants through their mutualism with honeydew-producing insects has been extensively investigated. Honeydew-producing insects that are tended by ants impose a cost on plant fitness and health by reducing seed production and/or plant growth. This cost is associated with sap intake and virus transmissions but may be overcompesated by tending ants if they deter or prey on hebivorous insects. The balance between cost and benefits depends on the tending ant species. In this study we report other indirect effects on plants of the mutualism between aphids and ants. We have found that two Lasius ant species, one native and the other invasive, may change the composition of volatile organic compounds (VOCs) of the holm oak (Quercus ilex) blend when they tend the aphid Lachnus roboris. The aphid regulation of its feeding and honeydew production according to the ant demands was proposed as a plausible mechanism that triggers changes in VOCs. Additionally, we now report here that aphid feeding, which is located most of the time on acorns cap or petiole, significantly increased the relative content of linolenic acid in acorns from holm oak colonized by the invasive ant. This acid is involved in the response of plants to insect herbivory as a precursor or jasmonic acid. No effect was found on acorn production, germination or seedlings quality. These results suggest that tending-ants may trigger the physiological response of holm oaks involved in plant resistance toward aphid herbivory and this response is ant species-dependent. PMID:21494087

Specialization and group size: brain and behavioural correlates of colony size in ants lacking morphological castes

PubMed Central

Amador-Vargas, Sabrina; Gronenberg, Wulfila; Wcislo, William T.; Mueller, Ulrich

2015-01-01

Group size in both multicellular organisms and animal societies can correlate with the degree of division of labour. For ants, the task specialization hypothesis (TSH) proposes that increased behavioural specialization enabled by larger group size corresponds to anatomical specialization of worker brains. Alternatively, the social brain hypothesis proposes that increased levels of social stimuli in larger colonies lead to enlarged brain regions in all workers, regardless of their task specialization. We tested these hypotheses in acacia ants (Pseudomyrmex spinicola), which exhibit behavioural but not morphological task specialization. In wild colonies, we marked, followed and tested ant workers involved in foraging tasks on the leaves (leaf-ants) and in defensive tasks on the host tree trunk (trunk-ants). Task specialization increased with colony size, especially in defensive tasks. The relationship between colony size and brain region volume was task-dependent, supporting the TSH. Specifically, as colony size increased, the relative size of regions within the mushroom bodies of the brain decreased in trunk-ants but increased in leaf-ants; those regions play important roles in learning and memory. Our findings suggest that workers specialized in defence may have reduced learning abilities relative to leaf-ants; these inferences remain to be tested. In societies with monomorphic workers, brain polymorphism enhanced by group size could be a mechanism by which division of labour is achieved. PMID:25567649

Solenopsis invicta virus (sinv-1) infection and insecticide interactions in the red imported fire ant (Hymenoptera: Formicidae)

USDA-ARS?s Scientific Manuscript database

Controlling invasive species is a growing concern; however, pesticides can be detrimental for non-target organisms. The red imported fire ant (Solenopsis invicta Buren; Hymenoptera: Formicidae) has aggressively invaded approximately 138 million ha in the USA and causes over $6 billion in damage and ...

9 CFR 381.72 - Segregation of suspects on ante mortem inspection.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 2 2014-01-01 2014-01-01 false Segregation of suspects on ante mortem inspection. 381.72 Section 381.72 Animals and Animal Products FOOD SAFETY AND INSPECTION SERVICE, DEPARTMENT OF AGRICULTURE AGENCY ORGANIZATION AND TERMINOLOGY; MANDATORY MEAT AND POULTRY PRODUCTS INSPECTION AND VOLUNTARY INSPECTION AND...

ANT: Software for Generating and Evaluating Degenerate Codons for Natural and Expanded Genetic Codes.

PubMed

Engqvist, Martin K M; Nielsen, Jens

2015-08-21

The Ambiguous Nucleotide Tool (ANT) is a desktop application that generates and evaluates degenerate codons. Degenerate codons are used to represent DNA positions that have multiple possible nucleotide alternatives. This is useful for protein engineering and directed evolution, where primers specified with degenerate codons are used as a basis for generating libraries of protein sequences. ANT is intuitive and can be used in a graphical user interface or by interacting with the code through a defined application programming interface. ANT comes with full support for nonstandard, user-defined, or expanded genetic codes (translation tables), which is important because synthetic biology is being applied to an ever widening range of natural and engineered organisms. The Python source code for ANT is freely distributed so that it may be used without restriction, modified, and incorporated in other software or custom data pipelines.

Concepts and applications of "natural computing" techniques in de novo drug and peptide design.

PubMed

Hiss, Jan A; Hartenfeller, Markus; Schneider, Gisbert

2010-05-01

Evolutionary algorithms, particle swarm optimization, and ant colony optimization have emerged as robust optimization methods for molecular modeling and peptide design. Such algorithms mimic combinatorial molecule assembly by using molecular fragments as building-blocks for compound construction, and relying on adaptation and emergence of desired pharmacological properties in a population of virtual molecules. Nature-inspired algorithms might be particularly suited for bioisosteric replacement or scaffold-hopping from complex natural products to synthetically more easily accessible compounds that are amenable to optimization by medicinal chemistry. The theory and applications of selected nature-inspired algorithms for drug design are reviewed, together with practical applications and a discussion of their advantages and limitations.

Life as a cataglyphologist--and beyond.

PubMed

Wehner, Rüdiger

2013-01-01

Rüdiger Wehner's lifelong research activities centered on Cataglyphis have rendered these thermophilic desert ants model organisms in the study of animal navigation. The present account describes how the author encountered Cataglyphis and established a study site at Maharès, Tunisia; how he increasingly focused his research on the neuroethological analysis of the ant's navigational toolkit; and finally, how he extended these studies to thermophilic desert ants in other deserts of the world, to Ocymyrmex in southern Africa and Melophorus in central Australia. By including aspects of functional morphology, physiology, and ecology in his research projects, he has favored-and advocated-an organism-centered approach. Beyond "cataglyphology," he was engaged in substantial teaching both at his home university in Zürich and overseas, writing a textbook, running a department, and working as a Permanent Fellow at the Institute for Advanced Study in Berlin.

Ants and termites increase crop yield in a dry climate.

PubMed

Evans, Theodore A; Dawes, Tracy Z; Ward, Philip R; Lo, Nathan

2011-03-29

Agricultural intensification has increased crop yields, but at high economic and environmental cost. Harnessing ecosystem services of naturally occurring organisms is a cheaper but under-appreciated approach, because the functional roles of organisms are not linked to crop yields, especially outside the northern temperate zone. Ecosystem services in soil come from earthworms in these cooler and wetter latitudes; what may fulfill their functional role in agriculture in warmer and drier habitats, where they are absent, is unproven. Here we show in a field experiment that ants and termites increase wheat yield by 36% from increased soil water infiltration due to their tunnels and improved soil nitrogen. Our results suggest that ants and termites have similar functional roles to earthworms, and that they may provide valuable ecosystem services in dryland agriculture, which may become increasingly important for agricultural sustainability in arid climates.

Supervised self-organization of homogeneous swarms using ergodic projections of Markov chains.

PubMed

Chattopadhyay, Ishanu; Ray, Asok

2009-12-01

This paper formulates a self-organization algorithm to address the problem of global behavior supervision in engineered swarms of arbitrarily large population sizes. The swarms considered in this paper are assumed to be homogeneous collections of independent identical finite-state agents, each of which is modeled by an irreducible finite Markov chain. The proposed algorithm computes the necessary perturbations in the local agents' behavior, which guarantees convergence to the desired observed state of the swarm. The ergodicity property of the swarm, which is induced as a result of the irreducibility of the agent models, implies that while the local behavior of the agents converges to the desired behavior only in the time average, the overall swarm behavior converges to the specification and stays there at all times. A simulation example illustrates the underlying concept.

An ultra-low power wireless sensor network for bicycle torque performance measurements.

PubMed

Gharghan, Sadik K; Nordin, Rosdiadee; Ismail, Mahamod

2015-05-21

In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach.

An Ultra-Low Power Wireless Sensor Network for Bicycle Torque Performance Measurements

PubMed Central

Gharghan, Sadik K.; Nordin, Rosdiadee; Ismail, Mahamod

2015-01-01

In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach. PMID:26007728

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

Selecting Cases for Intensive Analysis: A Diversity of Goals and Methods

ERIC Educational Resources Information Center

Gerring, John; Cojocaru, Lee

2016-01-01

This study revisits the task of case selection in case study research, proposing a new typology of strategies that is explicit, disaggregated, and relatively comprehensive. A secondary goal is to explore the prospects for case selection by "algorithm," aka "ex ante," "automatic," "quantitative,"…

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Visual Navigation during Colony Emigration by the Ant Temnothorax rugatulus

PubMed Central

Bowens, Sean R.; Glatt, Daniel P.; Pratt, Stephen C.

2013-01-01

Many ants rely on both visual cues and self-generated chemical signals for navigation, but their relative importance varies across species and context. We evaluated the roles of both modalities during colony emigration by Temnothorax rugatulus. Colonies were induced to move from an old nest in the center of an arena to a new nest at the arena edge. In the midst of the emigration the arena floor was rotated 60°around the old nest entrance, thus displacing any substrate-bound odor cues while leaving visual cues unchanged. This manipulation had no effect on orientation, suggesting little influence of substrate cues on navigation. When this rotation was accompanied by the blocking of most visual cues, the ants became highly disoriented, suggesting that they did not fall back on substrate cues even when deprived of visual information. Finally, when the substrate was left in place but the visual surround was rotated, the ants' subsequent headings were strongly rotated in the same direction, showing a clear role for visual navigation. Combined with earlier studies, these results suggest that chemical signals deposited by Temnothorax ants serve more for marking of familiar territory than for orientation. The ants instead navigate visually, showing the importance of this modality even for species with small eyes and coarse visual acuity. PMID:23671713

Anti-pathogen protection versus survival costs mediated by an ectosymbiont in an ant host

PubMed Central

Konrad, Matthias; Grasse, Anna V.; Tragust, Simon; Cremer, Sylvia

2015-01-01

The fitness effects of symbionts on their hosts can be context-dependent, with usually benign symbionts causing detrimental effects when their hosts are stressed, or typically parasitic symbionts providing protection towards their hosts (e.g. against pathogen infection). Here, we studied the novel association between the invasive garden ant Lasius neglectus and its fungal ectosymbiont Laboulbenia formicarum for potential costs and benefits. We tested ants with different Laboulbenia levels for their survival and immunity under resource limitation and exposure to the obligate killing entomopathogen Metarhizium brunneum. While survival of L. neglectus workers under starvation was significantly decreased with increasing Laboulbenia levels, host survival under Metarhizium exposure increased with higher levels of the ectosymbiont, suggesting a symbiont-mediated anti-pathogen protection, which seems to be driven mechanistically by both improved sanitary behaviours and an upregulated immune system. Ants with high Laboulbenia levels showed significantly longer self-grooming and elevated expression of immune genes relevant for wound repair and antifungal responses (β-1,3-glucan binding protein, Prophenoloxidase), compared with ants carrying low Laboulbenia levels. This suggests that the ectosymbiont Laboulbenia formicarum weakens its ant host by either direct resource exploitation or the costs of an upregulated behavioural and immunological response, which, however, provides a prophylactic protection upon later exposure to pathogens. PMID:25473011

Composite collective decision-making

PubMed Central

Czaczkes, Tomer J.; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

2015-01-01

Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. PMID:26019155

Utilizing Hierarchical Clustering to improve Efficiency of Self-Organizing Feature Map to Identify Hydrological Homogeneous Regions

NASA Astrophysics Data System (ADS)

Farsadnia, Farhad; Ghahreman, Bijan

2016-04-01

Hydrologic homogeneous group identification is considered both fundamental and applied research in hydrology. Clustering methods are among conventional methods to assess the hydrological homogeneous regions. Recently, Self-Organizing feature Map (SOM) method has been applied in some studies. However, the main problem of this method is the interpretation on the output map of this approach. Therefore, SOM is used as input to other clustering algorithms. The aim of this study is to apply a two-level Self-Organizing feature map and Ward hierarchical clustering method to determine the hydrologic homogenous regions in North and Razavi Khorasan provinces. At first by principal component analysis, we reduced SOM input matrix dimension, then the SOM was used to form a two-dimensional features map. To determine homogeneous regions for flood frequency analysis, SOM output nodes were used as input into the Ward method. Generally, the regions identified by the clustering algorithms are not statistically homogeneous. Consequently, they have to be adjusted to improve their homogeneity. After adjustment of the homogeneity regions by L-moment tests, five hydrologic homogeneous regions were identified. Finally, adjusted regions were created by a two-level SOM and then the best regional distribution function and associated parameters were selected by the L-moment approach. The results showed that the combination of self-organizing maps and Ward hierarchical clustering by principal components as input is more effective than the hierarchical method, by principal components or standardized inputs to achieve hydrologic homogeneous regions.

Pre-Columbian agricultural landscapes, ecosystem engineers, and self-organized patchiness in Amazonia.

PubMed

McKey, Doyle; Rostain, Stéphen; Iriarte, José; Glaser, Bruno; Birk, Jago Jonathan; Holst, Irene; Renard, Delphine

2010-04-27

The scale and nature of pre-Columbian human impacts in Amazonia are currently hotly debated. Whereas pre-Columbian people dramatically changed the distribution and abundance of species and habitats in some parts of Amazonia, their impact in other parts is less clear. Pioneer research asked whether their effects reached even further, changing how ecosystems function, but few in-depth studies have examined mechanisms underpinning the resilience of these modifications. Combining archeology, archeobotany, paleoecology, soil science, ecology, and aerial imagery, we show that pre-Columbian farmers of the Guianas coast constructed large raised-field complexes, growing on them crops including maize, manioc, and squash. Farmers created physical and biogeochemical heterogeneity in flat, marshy environments by constructing raised fields. When these fields were later abandoned, the mosaic of well-drained islands in the flooded matrix set in motion self-organizing processes driven by ecosystem engineers (ants, termites, earthworms, and woody plants) that occur preferentially on abandoned raised fields. Today, feedbacks generated by these ecosystem engineers maintain the human-initiated concentration of resources in these structures. Engineer organisms transport materials to abandoned raised fields and modify the structure and composition of their soils, reducing erodibility. The profound alteration of ecosystem functioning in these landscapes coconstructed by humans and nature has important implications for understanding Amazonian history and biodiversity. Furthermore, these landscapes show how sustainability of food-production systems can be enhanced by engineering into them follows that maintain ecosystem services and biodiversity. Like anthropogenic dark earths in forested Amazonia, these self-organizing ecosystems illustrate the ecological complexity of the legacy of pre-Columbian land use.

Pre-Columbian agricultural landscapes, ecosystem engineers, and self-organized patchiness in Amazonia

PubMed Central

McKey, Doyle; Rostain, Stéphen; Iriarte, José; Glaser, Bruno; Birk, Jago Jonathan; Holst, Irene; Renard, Delphine

2010-01-01

The scale and nature of pre-Columbian human impacts in Amazonia are currently hotly debated. Whereas pre-Columbian people dramatically changed the distribution and abundance of species and habitats in some parts of Amazonia, their impact in other parts is less clear. Pioneer research asked whether their effects reached even further, changing how ecosystems function, but few in-depth studies have examined mechanisms underpinning the resilience of these modifications. Combining archeology, archeobotany, paleoecology, soil science, ecology, and aerial imagery, we show that pre-Columbian farmers of the Guianas coast constructed large raised-field complexes, growing on them crops including maize, manioc, and squash. Farmers created physical and biogeochemical heterogeneity in flat, marshy environments by constructing raised fields. When these fields were later abandoned, the mosaic of well-drained islands in the flooded matrix set in motion self-organizing processes driven by ecosystem engineers (ants, termites, earthworms, and woody plants) that occur preferentially on abandoned raised fields. Today, feedbacks generated by these ecosystem engineers maintain the human-initiated concentration of resources in these structures. Engineer organisms transport materials to abandoned raised fields and modify the structure and composition of their soils, reducing erodibility. The profound alteration of ecosystem functioning in these landscapes coconstructed by humans and nature has important implications for understanding Amazonian history and biodiversity. Furthermore, these landscapes show how sustainability of food-production systems can be enhanced by engineering into them fallows that maintain ecosystem services and biodiversity. Like anthropogenic dark earths in forested Amazonia, these self-organizing ecosystems illustrate the ecological complexity of the legacy of pre-Columbian land use. PMID:20385814

Arboreal Ant Colonies as ‘Hot-Points’ of Cryptic Diversity for Myrmecophiles: The Weaver Ant Camponotus sp. aff. textor and Its Interaction Network with Its Associates

PubMed Central

Pérez-Lachaud, Gabriela; Lachaud, Jean-Paul

2014-01-01

Introduction Systematic surveys of macrofaunal diversity within ant colonies are lacking, particularly for ants nesting in microhabitats that are difficult to sample. Species associated with ants are generally small and rarely collected organisms, which makes them more likely to be unnoticed. We assumed that this tendency is greater for arthropod communities in microhabitats with low accessibility, such as those found in the nests of arboreal ants that may constitute a source of cryptic biodiversity. Materials and Methods We investigated the invertebrate diversity associated with an undescribed, but already threatened, Neotropical Camponotus weaver ant. As most of the common sampling methods used in studies of ant diversity are not suited for evaluating myrmecophile diversity within ant nests, we evaluated the macrofauna within ant nests through exhaustive colony sampling of three nests and examination of more than 80,000 individuals. Results We identified invertebrates from three classes belonging to 18 taxa, some of which were new to science, and recorded the first instance of the co-occurrence of two brood parasitoid wasp families attacking the same ant host colony. This diversity of ant associates corresponded to a highly complex interaction network. Agonistic interactions prevailed, but the prevalence of myrmecophiles was remarkably low. Conclusions Our data support the hypothesis of the evolution of low virulence in a variety of symbionts associated with large insect societies. Because most myrmecophiles found in this work are rare, strictly specific, and exhibit highly specialized biology, the risk of extinction for these hitherto unknown invertebrates and their natural enemies is high. The cryptic, far unappreciated diversity within arboreal ant nests in areas at high risk of habitat loss qualifies these nests as ‘hot-points’ of biodiversity that urgently require special attention as a component of conservation and management programs. PMID:24941047

Odorous House Ants (Tapinoma sessile) as Back-Seat Drivers of Localized Ant Decline in Urban Habitats

PubMed Central

Salyer, Adam; Bennett, Gary W.; Buczkowski, Grzegorz A.

2014-01-01

Invasive species and habitat disturbance threaten biodiversity worldwide by modifying ecosystem performance and displacing native organisms. Similar homogenization impacts manifest locally when urbanization forces native species to relocate or reinvade perpetually altered habitat. This study investigated correlations between ant richness and abundance in response to urbanization and the nearby presence of invasive ant species, odorous house ants (Tapinoma sessile), within its native region. Surveying localized ant composition within natural, semi-natural, and urban habitat supported efforts to determine whether T. sessile appear to be primary (drivers) threats as instigators or secondary (passengers) threats as inheritors of indigenous ant decline. Sampling 180 sites, evenly split between all habitats with and without T. sessile present, yielded 45 total species. Although urbanization and T. sessile presence factors were significantly linked to ant decline, their interaction correlated to the greatest reduction of total ant richness (74%) and abundance (81%). Total richness appeared to decrease from 27 species to 18 when natural habitat is urbanized and from 18 species to 7 with T. sessile present in urban plots. Odorous house ant presence minimally influenced ant communities within natural and semi-natural habitat, highlighting the importance of habitat alteration and T. sessile presence interactions. Results suggest urbanization releases T. sessile from unknown constraints by decreasing ant richness and competition. Within urban environment, T. sessile are pre-adapted to quickly exploit new resources and grow to supercolony strength wherein T. sessile drive adjacent biodiversity loss. Odorous house ants act as passengers and drivers of ecological change throughout different phases of urban ‘invasion’. This progression through surviving habitat alteration, exploiting new resources, thriving, and further reducing interspecific competition supports a “back-seat driver” role and affects pest management strategies. As demonstrated by T. sessile, this article concludes native species can become back-seat drivers of biodiversity loss and potentially thrive as “metro-invasive” species. PMID:25551819

Disentangling a rainforest food web using stable isotopes: dietary diversity in a species-rich ant community.

PubMed

Blüthgen, Nico; Gebauer, Gerhard; Fiedler, Konrad

2003-11-01

For diverse communities of omnivorous insects such as ants, the extent of direct consumption of plant-derived resources vs. predation is largely unknown. However, determination of the extent of "herbivory" among ants may be crucial to understand the hyper-dominance of ants in tropical tree crowns, where prey organisms tend to occur scarcely and unpredictably. We therefore examined N and C stable isotope ratios (delta(15)N and delta(13)C) in 50 ant species and associated insects and plants from a tropical rainforest in North Queensland, Australia. Variation between ant species was pronounced (range of species means: 7.1 per thousand in delta(15)N and 6.8 per thousand in delta(13)C). Isotope signatures of the entire ant community overlapped with those of several herbivorous as well as predacious arthropods. Variability in delta(15)N between ants was not correlated with plant delta(15)N from which they were collected. Ant species spread out in a continuum between largely herbivorous and purely predacious taxa, with a high degree of omnivory. Ant species' delta(15)N were consistent with the trophic level predicted by natural feeding observations, but not their delta(13)C. Low delta(15)N levels were recorded for ant species that commonly forage for nectar on understorey or canopy plants, intermediate levels for species with large colonies that were highly abundant on nectar and honeydew sources and were predacious, and the highest levels for predominantly predatory ground-foraging species. Colonies of the dominant weaver-ants (Oecophylla smaragdina) had significantly lower delta(15)N in mature forests (where preferred honeydew and nectar sources are abundant) than in open secondary vegetation. N concentration of ant dry mass showed only very limited variability across species and no correlation with trophic levels. This study demonstrates that stable isotopes provide a powerful tool for quantitative analyses of trophic niche partitioning and plasticity in complex and diverse tropical omnivore communities.

Non-additive benefit or cost? Disentangling the indirect effects that occur when plants bearing extrafloral nectaries and honeydew-producing insects share exotic ant mutualists.

PubMed

Savage, Amy M; Rudgers, Jennifer A

2013-06-01

In complex communities, organisms often form mutualisms with multiple different partners simultaneously. Non-additive effects may emerge among species linked by these positive interactions. Ants commonly participate in mutualisms with both honeydew-producing insects (HPI) and their extrafloral nectary (EFN)-bearing host plants. Consequently, HPI and EFN-bearing plants may experience non-additive benefits or costs when these groups co-occur. The outcomes of these interactions are likely to be influenced by variation in preferences among ants for honeydew vs. nectar. In this study, a test was made for non-additive effects on HPI and EFN-bearing plants resulting from sharing exotic ant guards. Preferences of the dominant exotic ant species for nectar vs. honeydew resources were also examined. Ant access, HPI and nectar availability were manipulated on the EFN-bearing shrub, Morinda citrifolia, and ant and HPI abundances, herbivory and plant growth were assessed. Ant-tending behaviours toward HPI across an experimental gradient of nectar availability were also tracked in order to investigate mechanisms underlying ant responses. The dominant ant species, Anoplolepis gracilipes, differed from less invasive ants in response to multiple mutualists, with reductions in plot-wide abundances when nectar was reduced, but no response to HPI reduction. Conversely, at sites where A. gracilipes was absent or rare, abundances of less invasive ants increased when nectar was reduced, but declined when HPI were reduced. Non-additive benefits were found at sites dominated by A. gracilipes, but only for M. citrifolia plants. Responses of HPI at these sites supported predictions of the non-additive cost model. Interestingly, the opposite non-additive patterns emerged at sites dominated by other ants. It was demonstrated that strong non-additive benefits and costs can both occur when a plant and herbivore share mutualist partners. These findings suggest that broadening the community context of mutualism studies can reveal important non-additive effects and increase understanding of the dynamics of species interactions.

Desiccation resistance in tropical insects: causes and mechanisms underlying variability in a Panama ant community.

PubMed

Bujan, Jelena; Yanoviak, Stephen P; Kaspari, Michael

2016-09-01

Desiccation resistance, the ability of an organism to reduce water loss, is an essential trait in arid habitats. Drought frequency in tropical regions is predicted to increase with climate change, and small ectotherms are often under a strong desiccation risk. We tested hypotheses regarding the underexplored desiccation potential of tropical insects. We measured desiccation resistance in 82 ant species from a Panama rainforest by recording the time ants can survive desiccation stress. Species' desiccation resistance ranged from 0.7 h to 97.9 h. We tested the desiccation adaptation hypothesis, which predicts higher desiccation resistance in habitats with higher vapor pressure deficit (VPD) - the drying power of the air. In a Panama rainforest, canopy microclimates averaged a VPD of 0.43 kPa, compared to a VPD of 0.05 kPa in the understory. Canopy ants averaged desiccation resistances 2.8 times higher than the understory ants. We tested a number of mechanisms to account for desiccation resistance. Smaller insects should desiccate faster given their higher surface area to volume ratio. Desiccation resistance increased with ant mass, and canopy ants averaged 16% heavier than the understory ants. A second way to increase desiccation resistance is to carry more water. Water content was on average 2.5% higher in canopy ants, but total water content was not a good predictor of ant desiccation resistance or critical thermal maximum (CT max), a measure of an ant's thermal tolerance. In canopy ants, desiccation resistance and CT max were inversely related, suggesting a tradeoff, while the two were positively correlated in understory ants. This is the first community level test of desiccation adaptation hypothesis in tropical insects. Tropical forests do contain desiccation-resistant species, and while we cannot predict those simply based on their body size, high levels of desiccation resistance are always associated with the tropical canopy.

Fossil evidence for the early ant evolution

NASA Astrophysics Data System (ADS)

Perrichot, Vincent; Lacau, Sébastien; Néraudeau, Didier; Nel, André

2008-02-01

Ants are one of the most studied insects in the world; and the literature devoted to their origin and evolution, systematics, ecology, or interactions with plants, fungi and other organisms is prolific. However, no consensus yet exists on the age estimate of the first Formicidae or on the origin of their eusociality. We review the fossil and biogeographical record of all known Cretaceous ants. We discuss the possible origin of the Formicidae with emphasis on the most primitive subfamily Sphecomyrminae according to its distribution and the Early Cretaceous palaeogeography. And we review the evidence of true castes and eusociality of the early ants regarding their morphological features and their manner of preservation in amber. The mid-Cretaceous amber forest from south-western France where some of the oldest known ants lived, corresponded to a moist tropical forest close to the shore with a dominance of gymnosperm trees but where angiosperms (flowering plants) were already diversified. This palaeoenvironmental reconstruction supports an initial radiation of ants in forest ground litter coincident with the rise of angiosperms, as recently proposed as an ecological explanation for their origin and successful evolution.

An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

PubMed Central

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem. PMID:24489491

An improved hierarchical genetic algorithm for sheet cutting scheduling with process constraints.

PubMed

Rao, Yunqing; Qi, Dezhong; Li, Jinling

2013-01-01

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model. The objective of the cutting scheduling problem is minimizing the weighted completed time. A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony--hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem. Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm. The computational result and comparison prove that the presented approach is quite effective for the considered problem.

Organization of rescue behaviour sequences in ants, Cataglyphis cursor, reflects goal-directedness, plasticity and memory.

PubMed

Duhoo, Thierry; Durand, Jean-Luc; Hollis, Karen L; Nowbahari, Elise

2017-06-01

The experimental study of rescue behaviour in ants, behaviour in which individuals help entrapped nestmates in distress, has revealed that rescuers respond to victims with very precisely targeted behaviour. In Cataglyphis cursor, several different components of rescue behaviour have been observed, demonstrating the complexity of this behaviour, including sand digging and sand transport to excavate the victim, followed by pulling on the victim's limbs as well as the object holding the victim in place, behaviour that serves to free the victim. Although previous work suggested that rescue was optimally organized, first to expose and then to extricate the victim under a variety of differing circumstances, experimental analysis of that organization has been lacking. Here, using experimental data, we characterize the pattern of individual rescue behaviour in C. cursor by analysing the probabilities of transitions from one behavioural component to another. The results show that the execution of each behavioural component is determined by the interplay of previous acts. In particular, we show not only that ants move sand away from the victim in an especially efficient sequence of behaviour that greatly minimizes energy expenditure, but also that ants appear to form some kind of memory of what they did in the past, a memory that directs their future behaviour. Copyright © 2017 Elsevier B.V. All rights reserved.

Toxicological and histopathological effects of boric acid on Atta sexdens rubropilosa (Hymenoptera: Formicidae) workers.

PubMed

Sumida, Simone; Silva-Zacarin, Elaine C M; Decio, Pâmela; Malaspina, Osmar; Bueno, Fabiana C; Bueno, Odair C

2010-06-01

The current study compared the toxicity of different concentrations of boric acid in adult workers of Atta sexdens rubropilosa Forel (Hymenoptera: Formicidae), with toxicological bioassays, and examining the dose-dependent and time-dependent histopathological changes, of the midgut, Malpighian tubules, and postpharyngeal glands. Our results revealed the importance of conducting toxicological bioassays combined with morphological analyses of the organs of ants chronically exposed to insecticides used in commercial ant baits. In vitro bioassays showed that boric acid significantly decreases the survivorship of workers regardless of concentration, whereas the morphological data suggested progressive dose-dependent and time-dependent changes in the organs examined, which were evident in the midgut. The midgut is the first organ to be affected, followed by the postpharyngeal gland and Malpighian tubules. This sequence is in agreement with the absorption pathway of this chemical compound in the midgut, its transference to the hemolymph, possibly reaching the postpharyngeal glands, and excretion by the Malpighian tubules. These progressive changes might be due to the cumulative and delayed effect of boric acid. Our findings provide important information for the understanding of the action of boric acid in ant baits in direct and indirect target organs.

The demographic consequences of mutualism: ants increase host-plant fruit production but not population growth.

PubMed

Ford, Kevin R; Ness, Joshua H; Bronstein, Judith L; Morris, William F

2015-10-01

The impact of mutualists on a partner's demography depends on how they affect the partner's multiple vital rates and how those vital rates, in turn, affect population growth. However, mutualism studies rarely measure effects on multiple vital rates or integrate them to assess the ultimate impact on population growth. We used vital rate data, population models and simulations of long-term population dynamics to quantify the demographic impact of a guild of ant species on the plant Ferocactus wislizeni. The ants feed at the plant's extrafloral nectaries and attack herbivores attempting to consume reproductive organs. Ant-guarded plants produced significantly more fruit, but ants had no significant effect on individual growth or survival. After integrating ant effects across these vital rates, we found that projected population growth was not significantly different between unguarded and ant-guarded plants because population growth was only weakly influenced by differences in fruit production (though strongly influenced by differences in individual growth and survival). However, simulations showed that ants could positively affect long-term plant population dynamics through services provided during rare but important events (herbivore outbreaks that reduce survival or years of high seedling recruitment associated with abundant precipitation). Thus, in this seemingly clear example of mutualism, the interaction may actually yield no clear benefit to plant population growth, or if it does, may only do so through the actions of the ants during rare events. These insights demonstrate the value of taking a demographic approach to studying the consequences of mutualism.

Specialization and group size: brain and behavioural correlates of colony size in ants lacking morphological castes.

PubMed

Amador-Vargas, Sabrina; Gronenberg, Wulfila; Wcislo, William T; Mueller, Ulrich

2015-02-22

Group size in both multicellular organisms and animal societies can correlate with the degree of division of labour. For ants, the task specialization hypothesis (TSH) proposes that increased behavioural specialization enabled by larger group size corresponds to anatomical specialization of worker brains. Alternatively, the social brain hypothesis proposes that increased levels of social stimuli in larger colonies lead to enlarged brain regions in all workers, regardless of their task specialization. We tested these hypotheses in acacia ants (Pseudomyrmex spinicola), which exhibit behavioural but not morphological task specialization. In wild colonies, we marked, followed and tested ant workers involved in foraging tasks on the leaves (leaf-ants) and in defensive tasks on the host tree trunk (trunk-ants). Task specialization increased with colony size, especially in defensive tasks. The relationship between colony size and brain region volume was task-dependent, supporting the TSH. Specifically, as colony size increased, the relative size of regions within the mushroom bodies of the brain decreased in trunk-ants but increased in leaf-ants; those regions play important roles in learning and memory. Our findings suggest that workers specialized in defence may have reduced learning abilities relative to leaf-ants; these inferences remain to be tested. In societies with monomorphic workers, brain polymorphism enhanced by group size could be a mechanism by which division of labour is achieved. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

PubMed

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

A ground truth based comparative study on clustering of gene expression data.

PubMed

Zhu, Yitan; Wang, Zuyi; Miller, David J; Clarke, Robert; Xuan, Jianhua; Hoffman, Eric P; Wang, Yue

2008-05-01

Given the variety of available clustering methods for gene expression data analysis, it is important to develop an appropriate and rigorous validation scheme to assess the performance and limitations of the most widely used clustering algorithms. In this paper, we present a ground truth based comparative study on the functionality, accuracy, and stability of five data clustering methods, namely hierarchical clustering, K-means clustering, self-organizing maps, standard finite normal mixture fitting, and a caBIG toolkit (VIsual Statistical Data Analyzer--VISDA), tested on sample clustering of seven published microarray gene expression datasets and one synthetic dataset. We examined the performance of these algorithms in both data-sufficient and data-insufficient cases using quantitative performance measures, including cluster number detection accuracy and mean and standard deviation of partition accuracy. The experimental results showed that VISDA, an interactive coarse-to-fine maximum likelihood fitting algorithm, is a solid performer on most of the datasets, while K-means clustering and self-organizing maps optimized by the mean squared compactness criterion generally produce more stable solutions than the other methods.

Clavulanic acid production estimation based on color and structural features of Streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm.

PubMed

Nurmohamadi, Maryam; Pourghassem, Hossein

2014-05-01

The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorithm based on visual and structural features of SC bacteria instead of statistical methods and experimental evaluation by microbiologist is proposed. In this algorithm, structural features such as the number of newborn branches, thickness of hyphal and bacterial density and also color features such as acceptance color levels are extracted from the SC bacteria. Moreover, PH and biomass of the medium provided by microbiologists are considered as specified features. The level of CA production is estimated by using a new application of Self-Organizing Map (SOM), and a hybrid model of genetic algorithm with back propagation network (GA-BPN). The proposed algorithm is evaluated on four carbonic resources including malt, starch, wheat flour and glycerol that had used as different mediums of bacterial growth. Then, the obtained results are compared and evaluated with observation of specialist. Finally, the Relative Error (RE) for the SOM and GA-BPN are achieved 14.97% and 16.63%, respectively. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Computing chemical organizations in biological networks.

PubMed

Centler, Florian; Kaleta, Christoph; di Fenizio, Pietro Speroni; Dittrich, Peter

2008-07-15

Novel techniques are required to analyze computational models of intracellular processes as they increase steadily in size and complexity. The theory of chemical organizations has recently been introduced as such a technique that links the topology of biochemical reaction network models to their dynamical repertoire. The network is decomposed into algebraically closed and self-maintaining subnetworks called organizations. They form a hierarchy representing all feasible system states including all steady states. We present three algorithms to compute the hierarchy of organizations for network models provided in SBML format. Two of them compute the complete organization hierarchy, while the third one uses heuristics to obtain a subset of all organizations for large models. While the constructive approach computes the hierarchy starting from the smallest organization in a bottom-up fashion, the flux-based approach employs self-maintaining flux distributions to determine organizations. A runtime comparison on 16 different network models of natural systems showed that none of the two exhaustive algorithms is superior in all cases. Studying a 'genome-scale' network model with 762 species and 1193 reactions, we demonstrate how the organization hierarchy helps to uncover the model structure and allows to evaluate the model's quality, for example by detecting components and subsystems of the model whose maintenance is not explained by the model. All data and a Java implementation that plugs into the Systems Biology Workbench is available from http://www.minet.uni-jena.de/csb/prj/ot/tools.

Cuticular Lipids as a Cross-Talk among Ants, Plants and Butterflies

PubMed Central

Barbero, Francesca

2016-01-01

Even though insects and plants are distantly related organisms, they developed an integument which is functionally and structurally similar. Besides functioning as a physical barrier to cope with abiotic and biotic stress, this interface, called cuticle, is also a source of chemical signaling. Crucial compounds with this respect are surface lipids and especially cuticular hydrocarbons (CHCs). This review is focused on the role of CHCs in fostering multilevel relationships among ants, plants and Lepidoptera (primarily butterflies). Indeed, particular traits of ants as eusocial organisms allowed the evolution and the maintenance of a variety of associations with both plants and animals. Basic concepts of myrmecophilous interactions and chemical deception strategies together with chemical composition, biosynthetic pathways and functions of CHCs as molecular cues of multitrophic systems are provided. Finally, the need to adopt a multidisciplinary and comprehensive approach in the survey of complex models is discussed. PMID:27886144

Ants and termites increase crop yield in a dry climate

PubMed Central

Evans, Theodore A.; Dawes, Tracy Z.; Ward, Philip R.; Lo, Nathan

2011-01-01

Agricultural intensification has increased crop yields, but at high economic and environmental cost. Harnessing ecosystem services of naturally occurring organisms is a cheaper but under-appreciated approach, because the functional roles of organisms are not linked to crop yields, especially outside the northern temperate zone. Ecosystem services in soil come from earthworms in these cooler and wetter latitudes; what may fulfill their functional role in agriculture in warmer and drier habitats, where they are absent, is unproven. Here we show in a field experiment that ants and termites increase wheat yield by 36% from increased soil water infiltration due to their tunnels and improved soil nitrogen. Our results suggest that ants and termites have similar functional roles to earthworms, and that they may provide valuable ecosystem services in dryland agriculture, which may become increasingly important for agricultural sustainability in arid climates. PMID:21448161

Cuticular Lipids as a Cross-Talk among Ants, Plants and Butterflies.

PubMed

Barbero, Francesca

2016-11-24

Even though insects and plants are distantly related organisms, they developed an integument which is functionally and structurally similar. Besides functioning as a physical barrier to cope with abiotic and biotic stress, this interface, called cuticle, is also a source of chemical signaling. Crucial compounds with this respect are surface lipids and especially cuticular hydrocarbons (CHCs). This review is focused on the role of CHCs in fostering multilevel relationships among ants, plants and Lepidoptera (primarily butterflies). Indeed, particular traits of ants as eusocial organisms allowed the evolution and the maintenance of a variety of associations with both plants and animals. Basic concepts of myrmecophilous interactions and chemical deception strategies together with chemical composition, biosynthetic pathways and functions of CHCs as molecular cues of multitrophic systems are provided. Finally, the need to adopt a multidisciplinary and comprehensive approach in the survey of complex models is discussed.

Testing the museum versus cradle tropical biological diversity hypothesis: phylogeny, diversification, and ancestral biogeographic range evolution of the ants.

PubMed

Moreau, Corrie S; Bell, Charles D

2013-08-01

Ants are one of the most ecologically and numerically dominant group of terrestrial organisms with most species diversity currently found in tropical climates. Several explanations for the disparity of biological diversity in the tropics compared to temperate regions have been proposed including that the tropics may act as a "museum" where older lineages persist through evolutionary time or as a "cradle" where new species continue to be generated. We infer the molecular phylogenetic relationships of 295 ant specimens including members of all 21 extant subfamilies to explore the evolutionary diversification and biogeography of the ants. By constraining the topology and age of the root node while using 45 fossils as minimum constraints, we converge on an age of 139-158 Mya for the modern ants. Further diversification analyses identified 10 periods with a significant change in the tempo of diversification of the ants, although these shifts did not appear to correspond to ancestral biogeographic range shifts. Likelihood-based historical biogeographic reconstructions suggest that the Neotropics were important in early ant diversification (e.g., Cretaceous). This finding coupled with the extremely high-current species diversity suggests that the Neotropics have acted as both a museum and cradle for ant diversity. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

A performance evaluation of ACO and SA TSP in a supply chain network

NASA Astrophysics Data System (ADS)

Rao, T. Srinivas

2017-07-01

Supply Chain management and E commerce business solutions are one of the prominent areas of active research. In our paper we have modelled a supply chain model which aggregates all the manufacturers requirement and the products are supplied to all the manufacturer through a common vehicle routing algorithm. An appropriate tsp has been constructed for all the manufacturers which determines the shortest route thru which the aggregated material can be supplied in the shortest possible time. In this paper we have solved the shortest route through constructing a Simulated annealing algorithm and Ant colony algorithm and their performance is evaluated.

Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps.

PubMed

Moya, José M; Araujo, Alvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

2009-01-01

The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps

PubMed Central

Moya, José M.; Araujo, Álvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

2009-01-01

The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals. PMID:22291569

Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

NASA Astrophysics Data System (ADS)

Ge, Junwei; Cai, Yu; Fang, Yiqiu

2018-05-01

This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

Skull removal in MR images using a modified artificial bee colony optimization algorithm.

PubMed

Taherdangkoo, Mohammad

2014-01-01

Removal of the skull from brain Magnetic Resonance (MR) images is an important preprocessing step required for other image analysis techniques such as brain tissue segmentation. In this paper, we propose a new algorithm based on the Artificial Bee Colony (ABC) optimization algorithm to remove the skull region from brain MR images. We modify the ABC algorithm using a different strategy for initializing the coordinates of scout bees and their direction of search. Moreover, we impose an additional constraint to the ABC algorithm to avoid the creation of discontinuous regions. We found that our algorithm successfully removed all bony skull from a sample of de-identified MR brain images acquired from different model scanners. The obtained results of the proposed algorithm compared with those of previously introduced well known optimization algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) demonstrate the superior results and computational performance of our algorithm, suggesting its potential for clinical applications.

Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR.

PubMed

Tustison, Nicholas J; Shrinidhi, K L; Wintermark, Max; Durst, Christopher R; Kandel, Benjamin M; Gee, James C; Grossman, Murray C; Avants, Brian B

2015-04-01

Segmenting and quantifying gliomas from MRI is an important task for diagnosis, planning intervention, and for tracking tumor changes over time. However, this task is complicated by the lack of prior knowledge concerning tumor location, spatial extent, shape, possible displacement of normal tissue, and intensity signature. To accommodate such complications, we introduce a framework for supervised segmentation based on multiple modality intensity, geometry, and asymmetry feature sets. These features drive a supervised whole-brain and tumor segmentation approach based on random forest-derived probabilities. The asymmetry-related features (based on optimal symmetric multimodal templates) demonstrate excellent discriminative properties within this framework. We also gain performance by generating probability maps from random forest models and using these maps for a refining Markov random field regularized probabilistic segmentation. This strategy allows us to interface the supervised learning capabilities of the random forest model with regularized probabilistic segmentation using the recently developed ANTsR package--a comprehensive statistical and visualization interface between the popular Advanced Normalization Tools (ANTs) and the R statistical project. The reported algorithmic framework was the top-performing entry in the MICCAI 2013 Multimodal Brain Tumor Segmentation challenge. The challenge data were widely varying consisting of both high-grade and low-grade glioma tumor four-modality MRI from five different institutions. Average Dice overlap measures for the final algorithmic assessment were 0.87, 0.78, and 0.74 for "complete", "core", and "enhanced" tumor components, respectively.

Wound treatment and selective help in a termite-hunting ant.

PubMed

Frank, Erik T; Wehrhahn, Marten; Linsenmair, K Eduard

2018-02-14

Open wounds are a major health risk in animals, with species prone to injuries likely developing means to reduce these risks. We therefore analysed the behavioural response towards open wounds on the social and individual level in the termite group-hunting ant Megaponera analis During termite raids, some ants get injured by termite soldiers (biting off extremities), after the fight injured ants get carried back to the nest by nest-mates. We observed treatment of the injury by nest-mates inside the nest through intense allogrooming at the wound. Lack of treatment increased mortality from 10% to 80% within 24 h, most likely due to infections. Wound clotting occurred extraordinarily fast in untreated injured individuals, within 10 min. Furthermore, heavily injured ants (loss of five extremities) were not rescued or treated; this was regulated not by the helper but by the unresponsiveness of the injured ant. Interestingly, lightly injured ants behaved 'more injured' near nest-mates. We show organized social wound treatment in insects through a multifaceted help system focused on injured individuals. This was not only limited to selective rescuing of lightly injured individuals by carrying them back (thus reducing predation risk), but, moreover, included a differentiated treatment inside the nest. © 2018 The Author(s).

Viruses of invasive Argentine ants from the European Main supercolony: characterization, interactions and evolution.

PubMed

Viljakainen, Lumi; Holmberg, Ida; Abril, Sílvia; Jurvansuu, Jaana

2018-06-25

The Argentine ant (Linepithema humile) is a highly invasive pest, yet very little is known about its viruses. We analysed individual RNA-sequencing data from 48 Argentine ant queens to identify and characterisze their viruses. We discovered eight complete RNA virus genomes - all from different virus families - and one putative partial entomopoxvirus genome. Seven of the nine virus sequences were found from ant samples spanning 7 years, suggesting that these viruses may cause long-term infections within the super-colony. Although all nine viruses successfully infect Argentine ants, they have very different characteristics, such as genome organization, prevalence, loads, activation frequencies and rates of evolution. The eight RNA viruses constituted in total 23 different virus combinations which, based on statistical analysis, were non-random, suggesting that virus compatibility is a factor in infections. We also searched for virus sequences from New Zealand and Californian Argentine ant RNA-sequencing data and discovered that many of the viruses are found on different continents, yet some viruses are prevalent only in certain colonies. The viral loads described here most probably present a normal asymptomatic level of infection; nevertheless, detailed knowledge of Argentine ant viruses may enable the design of viral biocontrol methods against this pest.

Fidelity and Promiscuity in an Ant-Plant Mutualism: A Case Study of Triplaris and Pseudomyrmex

PubMed Central

Sanchez, Adriana

2015-01-01

The association between the myrmecophyte Triplaris and ants of the genus Pseudomyrmex is an often-reported example of mutualism but no molecular studies have examined this association to date. In this study, the interspecific relationships of Triplaris were reconstructed using five molecular markers (two chloroplast and three nuclear), and the relationships of the associated Pseudomyrmex using two molecular regions (one mitochondrial and one nuclear). A data set including all known collections of plant hosts and resident ants was also compiled. The pattern of distribution of both organisms reveals that there are varying degrees of host specificity; most ants show broader host usage (promiscuous) but one species (P. dendroicus) is faithful to a single species of Triplaris. In most ant-plant interactions, host usage is not specific at the species level and preferences may result from geographical or ecological sorting. The specificity of P. dendroicus could be based on chemical recognition of the host they were raised on. PMID:26630384

An Engineered orco Mutation Produces Aberrant Social Behavior and Defective Neural Development in Ants.

PubMed

Yan, Hua; Opachaloemphan, Comzit; Mancini, Giacomo; Yang, Huan; Gallitto, Matthew; Mlejnek, Jakub; Leibholz, Alexandra; Haight, Kevin; Ghaninia, Majid; Huo, Lucy; Perry, Michael; Slone, Jesse; Zhou, Xiaofan; Traficante, Maria; Penick, Clint A; Dolezal, Kelly; Gokhale, Kaustubh; Stevens, Kelsey; Fetter-Pruneda, Ingrid; Bonasio, Roberto; Zwiebel, Laurence J; Berger, Shelley L; Liebig, Jürgen; Reinberg, Danny; Desplan, Claude

2017-08-10

Ants exhibit cooperative behaviors and advanced forms of sociality that depend on pheromone-mediated communication. Odorant receptor neurons (ORNs) express specific odorant receptors (ORs) encoded by a dramatically expanded gene family in ants. In most eusocial insects, only the queen can transmit genetic information, restricting genetic studies. In contrast, workers in Harpegnathos saltator ants can be converted into gamergates (pseudoqueens) that can found entire colonies. This feature facilitated CRISPR-Cas9 generation of germline mutations in orco, the gene that encodes the obligate co-receptor of all ORs. orco mutations should significantly impact olfaction. We demonstrate striking functions of Orco in odorant perception, reproductive physiology, and social behavior plasticity. Surprisingly, unlike in other insects, loss of OR functionality also dramatically impairs development of the antennal lobe to which ORNs project. Therefore, the development of genetics in Harpegnathos establishes this ant species as a model organism to study the complexity of eusociality. Copyright © 2017 Elsevier Inc. All rights reserved.

A locally-blazed ant trail achieves efficient collective navigation despite limited information

PubMed Central

Fonio, Ehud; Heyman, Yael; Boczkowski, Lucas; Gelblum, Aviram; Kosowski, Adrian; Korman, Amos; Feinerman, Ofer

2016-01-01

Any organism faces sensory and cognitive limitations which may result in maladaptive decisions. Such limitations are prominent in the context of groups where the relevant information at the individual level may not coincide with collective requirements. Here, we study the navigational decisions exhibited by Paratrechina longicornis ants as they cooperatively transport a large food item. These decisions hinge on the perception of individuals which often restricts them from providing the group with reliable directional information. We find that, to achieve efficient navigation despite partial and even misleading information, these ants employ a locally-blazed trail. This trail significantly deviates from the classical notion of an ant trail: First, instead of systematically marking the full path, ants mark short segments originating at the load. Second, the carrying team constantly loses the guiding trail. We experimentally and theoretically show that the locally-blazed trail optimally and robustly exploits useful knowledge while avoiding the pitfalls of misleading information. DOI: http://dx.doi.org/10.7554/eLife.20185.001 PMID:27815944

Congestion control and routing over satellite networks

NASA Astrophysics Data System (ADS)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE) method and then develop a novel on-demand routing system named Cross Entropy Accelerated Ant Routing System (CEAARS) for regular constellation LEO satellite networks. By implementing simulations on an Iridium-like satellite network, we compare the proposed CEAARS algorithm with the two approaches to adaptive routing protocols on the Internet: distance-vector (DV) and link-state (LS), as well as with the original Cross Entropy Ant Routing System (CEARS). DV algorithms are based on distributed Bellman Ford algorithm, and LS algorithms are implementation of Dijkstras single source shortest path. The results show that CEAARS not only remarkably improves the convergence speed of achieving optimal or suboptimal paths, but also reduces the number of overhead ants (management packets).

Monitoring the Diversity of Hunting Ants (Hymenoptera: Formicidae) on a Fragmented and Restored Andean Landscape.

PubMed

Herrera-Rangel, J; Jiménez-Carmona, E; Armbrecht, I

2015-10-01

Hunting ants are predators of organisms belonging to different trophic levels. Their presence, abundance, and diversity may reflect the diversity of other ants and contribute to evaluate habitat conditions. Between 2003 and 2005 the restoration of seven corridors in an Andean rural landscape of Colombia was performed. The restoration took place in lands that were formerly either forestry plantations or pasturelands. To evaluate restoration progress, hunting ants were intensely sampled for 7 yr, using sifted leaf litter and mini-Winkler, and pitfall traps in 21 plots classified into five vegetation types: forests, riparian forests, two types of restored corridors, and pasturelands. The ant communities were faithful to their habitat over time, and the main differences in ant composition, abundance, and richness were due to differences among land use types. The forests and riparian forests support 45% of the species in the landscape while the restored corridors contain between 8.3-25%. The change from forest to pasturelands represents a loss of 80% of the species. Ant composition in restored corridors was significantly different than in forests but restored corridors of soil of forestry plantations retained 16.7% more species than restored corridors from pasturelands. Ubiquitous hunting ants, Hypoponera opacior (Forel) and Gnamptogenys ca andina were usually associated with pastures and dominate restored corridors. Other cryptic, small, and specialized hunting ants are not present in the restored corridors. Results suggest that the history of land use is important for the biodiversity of hunting ants but also that corridors have not yet effectively contributed toward conservation goals. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Anti-pathogen protection versus survival costs mediated by an ectosymbiont in an ant host.

PubMed

Konrad, Matthias; Grasse, Anna V; Tragust, Simon; Cremer, Sylvia

2015-01-22

The fitness effects of symbionts on their hosts can be context-dependent, with usually benign symbionts causing detrimental effects when their hosts are stressed, or typically parasitic symbionts providing protection towards their hosts (e.g. against pathogen infection). Here, we studied the novel association between the invasive garden ant Lasius neglectus and its fungal ectosymbiont Laboulbenia formicarum for potential costs and benefits. We tested ants with different Laboulbenia levels for their survival and immunity under resource limitation and exposure to the obligate killing entomopathogen Metarhizium brunneum. While survival of L. neglectus workers under starvation was significantly decreased with increasing Laboulbenia levels, host survival under Metarhizium exposure increased with higher levels of the ectosymbiont, suggesting a symbiont-mediated anti-pathogen protection, which seems to be driven mechanistically by both improved sanitary behaviours and an upregulated immune system. Ants with high Laboulbenia levels showed significantly longer self-grooming and elevated expression of immune genes relevant for wound repair and antifungal responses (β-1,3-glucan binding protein, Prophenoloxidase), compared with ants carrying low Laboulbenia levels. This suggests that the ectosymbiont Laboulbenia formicarum weakens its ant host by either direct resource exploitation or the costs of an upregulated behavioural and immunological response, which, however, provides a prophylactic protection upon later exposure to pathogens. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Heterogeneous activity causes a nonlinear increase in the group energy use of ant workers isolated from queen and brood.

PubMed

Ferral, Nolan; Holloway, Kyara; Li, Mingzhong; Yin, Zhaozheng; Hou, Chen

2018-06-01

Increasing evidence has shown that the energy use of ant colonies increases sublinearly with colony size so that large colonies consume less per capita energy than small colonies. It has been postulated that social environment (e.g., in the presence of queen and brood) is critical for the sublinear group energetics, and a few studies of ant workers isolated from queens and brood observed linear relationships between group energetics and size. In this paper, we hypothesize that the sublinear energetics arise from the heterogeneity of activity in ant groups, that is, large groups have relatively more inactive members than small groups. We further hypothesize that the energy use of ant worker groups that are allowed to move freely increases more slowly than the group size even if they are isolated from queen and brood. Previous studies only provided indirect evidence for these hypotheses due to technical difficulties. In this study, we applied the automated behavioral monitoring and respirometry simultaneously on isolated worker groups for long time periods, and analyzed the image with the state-of-the-art algorithms. Our results show that when activity was not confined, large groups had lower per capita energy use, a lower percentage of active members, and lower average walking speed than small groups; while locomotion was confined, however, the per capita energy use was a constant regardless of the group size. The quantitative analysis shows a direct link between variation in group energy use and the activity level of ant workers when isolated from queen and brood. © 2016 Institute of Zoology, Chinese Academy of Sciences.

DIRBoost-an algorithm for boosting deformable image registration: application to lung CT intra-subject registration.

PubMed

Muenzing, Sascha E A; van Ginneken, Bram; Viergever, Max A; Pluim, Josien P W

2014-04-01

We introduce a boosting algorithm to improve on existing methods for deformable image registration (DIR). The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well known in the field of machine learning. DIRBoost utilizes a method for automatic registration error detection to obtain estimates of local registration quality. All areas detected as erroneously registered are subjected to boosting, i.e. undergo iterative registrations by employing boosting masks on both the fixed and moving image. We validated the DIRBoost algorithm on three different DIR methods (ANTS gSyn, NiftyReg, and DROP) on three independent reference datasets of pulmonary image scan pairs. DIRBoost reduced registration errors significantly and consistently on all reference datasets for each DIR algorithm, yielding an improvement of the registration accuracy by 5-34% depending on the dataset and the registration algorithm employed. Copyright © 2014 Elsevier B.V. All rights reserved.

Utility Rate Equations of Group Population Dynamics in Biological and Social Systems

PubMed Central

Yukalov, Vyacheslav I.; Yukalova, Elizaveta P.; Sornette, Didier

2013-01-01

We present a novel system of equations to describe the evolution of self-organized structured societies (biological or human) composed of several trait groups. The suggested approach is based on the combination of ideas employed in the theory of biological populations, system theory, and utility theory. The evolution equations are defined as utility rate equations, whose parameters are characterized by the utility of each group with respect to the society as a whole and by the mutual utilities of groups with respect to each other. We analyze in detail the cases of two groups (cooperators and defectors) and of three groups (cooperators, defectors, and regulators) and find that, in a self-organized society, neither defectors nor regulators can overpass the maximal fractions of about each. This is in agreement with the data for bee and ant colonies. The classification of societies by their distance from equilibrium is proposed. We apply the formalism to rank the countries according to the introduced metric quantifying their relative stability, which depends on the cost of defectors and regulators as well as their respective population fractions. We find a remarkable concordance with more standard economic ranking based, for instance, on GDP per capita. PMID:24386163

Utility rate equations of group population dynamics in biological and social systems.

PubMed

Yukalov, Vyacheslav I; Yukalova, Elizaveta P; Sornette, Didier

2013-01-01

We present a novel system of equations to describe the evolution of self-organized structured societies (biological or human) composed of several trait groups. The suggested approach is based on the combination of ideas employed in the theory of biological populations, system theory, and utility theory. The evolution equations are defined as utility rate equations, whose parameters are characterized by the utility of each group with respect to the society as a whole and by the mutual utilities of groups with respect to each other. We analyze in detail the cases of two groups (cooperators and defectors) and of three groups (cooperators, defectors, and regulators) and find that, in a self-organized society, neither defectors nor regulators can overpass the maximal fractions of about [Formula: see text] each. This is in agreement with the data for bee and ant colonies. The classification of societies by their distance from equilibrium is proposed. We apply the formalism to rank the countries according to the introduced metric quantifying their relative stability, which depends on the cost of defectors and regulators as well as their respective population fractions. We find a remarkable concordance with more standard economic ranking based, for instance, on GDP per capita.

Self-organized discrimination of resources.

PubMed

Campo, Alexandre; Garnier, Simon; Dédriche, Olivier; Zekkri, Mouhcine; Dorigo, Marco

2011-01-01

When selecting a resource to exploit, an insect colony must take into account at least two constraints: the resource must be abundant enough to sustain the whole group, but not too large to limit exploitation costs, and risks of conflicts with other colonies. Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected. As a result, the individuals gather at the smallest resource that can host the whole group, hence reducing competition and exploitation costs while fulfilling the overall group's needs. Our analysis reveals that the group becomes better at discriminating between similar resources as it grows in size. Also, the discrimination mechanism is flexible and the group readily switches to a better suited resource as it appears in the environment. The collective decision emerges through the self-organization of individuals, that is, in absence of any centralized control. It also requires a minimal individual cognitive investment, making the proposed mechanism likely to occur in other social species and suitable for the development of distributed decision making tools.

Self-Organized Discrimination of Resources

PubMed Central

Campo, Alexandre; Garnier, Simon; Dédriche, Olivier; Zekkri, Mouhcine; Dorigo, Marco

2011-01-01

When selecting a resource to exploit, an insect colony must take into account at least two constraints: the resource must be abundant enough to sustain the whole group, but not too large to limit exploitation costs, and risks of conflicts with other colonies. Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected. As a result, the individuals gather at the smallest resource that can host the whole group, hence reducing competition and exploitation costs while fulfilling the overall group's needs. Our analysis reveals that the group becomes better at discriminating between similar resources as it grows in size. Also, the discrimination mechanism is flexible and the group readily switches to a better suited resource as it appears in the environment. The collective decision emerges through the self-organization of individuals, that is, in absence of any centralized control. It also requires a minimal individual cognitive investment, making the proposed mechanism likely to occur in other social species and suitable for the development of distributed decision making tools. PMID:21625643

String tightening as a self-organizing phenomenon.

PubMed

Banerjee, Bonny

2007-09-01

The phenomenon of self-organization has been of special interest to the neural network community throughout the last couple of decades. In this paper, we study a variant of the self-organizing map (SOM) that models the phenomenon of self-organization of the particles forming a string when the string is tightened from one or both of its ends. The proposed variant, called the string tightening self-organizing neural network (STON), can be used to solve certain practical problems, such as computation of shortest homotopic paths, smoothing paths to avoid sharp turns, computation of convex hull, etc. These problems are of considerable interest in computational geometry, robotics path-planning, artificial intelligence (AI) (diagrammatic reasoning), very large scale integration (VLSI) routing, and geographical information systems. Given a set of obstacles and a string with two fixed terminal points in a 2-D space, the STON model continuously tightens the given string until the unique shortest configuration in terms of the Euclidean metric is reached. The STON minimizes the total length of a string on convergence by dynamically creating and selecting feature vectors in a competitive manner. Proof of correctness of this anytime algorithm and experimental results obtained by its deployment have been presented in the paper.

How self-organization can guide evolution.

PubMed

Glancy, Jonathan; Stone, James V; Wilson, Stuart P

2016-11-01

Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection , and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection.

Swarmathon 2017

NASA Image and Video Library

2017-04-19

A cube identified with an AprilTag, similar to a barcode, is delivered to a "home" square in the middle of a competition arena during the Swarmathon competition. At the Kennedy Space Center Visitor Complex, student teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food.

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

PubMed

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

An ant colony optimization based feature selection for web page classification.

PubMed

Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

NASA Astrophysics Data System (ADS)

Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing

2016-10-01

Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.

Advanced Targeting Cost Function Design for Evolutionary Optimization of Control of Logistic Equation

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana

2010-06-01

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outline the effectiveness and robustness of used method and targeting CF.

Efficient self-organizing multilayer neural network for nonlinear system modeling.

PubMed

Han, Hong-Gui; Wang, Li-Dan; Qiao, Jun-Fei

2013-07-01

It has been shown extensively that the dynamic behaviors of a neural system are strongly influenced by the network architecture and learning process. To establish an artificial neural network (ANN) with self-organizing architecture and suitable learning algorithm for nonlinear system modeling, an automatic axon-neural network (AANN) is investigated in the following respects. First, the network architecture is constructed automatically to change both the number of hidden neurons and topologies of the neural network during the training process. The approach introduced in adaptive connecting-and-pruning algorithm (ACP) is a type of mixed mode operation, which is equivalent to pruning or adding the connecting of the neurons, as well as inserting some required neurons directly. Secondly, the weights are adjusted, using a feedforward computation (FC) to obtain the information for the gradient during learning computation. Unlike most of the previous studies, AANN is able to self-organize the architecture and weights, and to improve the network performances. Also, the proposed AANN has been tested on a number of benchmark problems, ranging from nonlinear function approximating to nonlinear systems modeling. The experimental results show that AANN can have better performances than that of some existing neural networks. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Is phenotypic plasticity a key mechanism for responding to thermal stress in ants?

NASA Astrophysics Data System (ADS)

Oms, Cristela Sánchez; Cerdá, Xim; Boulay, Raphaël

2017-06-01

Unlike natural selection, phenotypic plasticity allows organisms to respond quickly to changing environmental conditions. However, plasticity may not always be adaptive. In insects, body size and other morphological measurements have been shown to decrease as temperature increases. This relationship may lead to a physiological conflict in ants, where larger body size and longer legs often confer better thermal resistance. Here, we tested the effect of developmental temperature (20, 24, 28 or 32 °C) on adult thermal resistance in the thermophilic ant species Aphaenogaster senilis. We found that no larval development occurred at 20 °C. However, at higher temperatures, developmental speed increased as expected and smaller adults were produced. In thermal resistance tests, we found that ants reared at 28 and 32 °C had half-lethal temperatures that were 2 °C higher than those of ants reared at 24 °C. Thus, although ants reared at higher temperatures were smaller in size, they were nonetheless more thermoresistant. These results show that A. senilis can exploit phenotypic plasticity to quickly adjust its thermal resistance to local conditions and that this process is independent of morphological adaptations. This mechanism may be particularly relevant given current rapid climate warming.

A Pilot Study Exploring the Use of Breath Analysis to Differentiate Healthy Cattle from Cattle Experimentally Infected with Mycobacterium bovis

PubMed Central

Ellis, Christine K.; Stahl, Randal S.; Nol, Pauline; Waters, W. Ray; Palmer, Mitchell V.; Rhyan, Jack C.; VerCauteren, Kurt C.; McCollum, Matthew; Salman, M. D.

2014-01-01

Bovine tuberculosis, caused by Mycobacterium bovis, is a zoonotic disease of international public health importance. Ante-mortem surveillance is essential for control; however, current surveillance tests are hampered by limitations affecting ease of use or quality of results. There is an emerging interest in human and veterinary medicine in diagnosing disease via identification of volatile organic compounds produced by pathogens and host-pathogen interactions. The objective of this pilot study was to explore application of existing human breath collection and analysis methodologies to cattle as a means to identify M. bovis infection through detection of unique volatile organic compounds or changes in the volatile organic compound profiles present in breath. Breath samples from 23 male Holstein calves (7 non-infected and 16 M. bovis-infected) were collected onto commercially available sorbent cartridges using a mask system at 90 days post-inoculation with M. bovis. Samples were analyzed using gas chromatography-mass spectrometry, and chromatographic data were analyzed using standard analytical chemical and metabolomic analyses, principle components analysis, and a linear discriminant algorithm. The findings provide proof of concept that breath-derived volatile organic compound analysis can be used to differentiate between healthy and M. bovis-infected cattle. PMID:24586655

Optimization of Straight Cylindrical Turning Using Artificial Bee Colony (ABC) Algorithm

NASA Astrophysics Data System (ADS)

Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

2017-04-01

Artificial bee colony (ABC) algorithm, that mimics the intelligent foraging behavior of honey bees, is increasingly gaining acceptance in the field of process optimization, as it is capable of handling nonlinearity, complexity and uncertainty. Straight cylindrical turning is a complex and nonlinear machining process which involves the selection of appropriate cutting parameters that affect the quality of the workpiece. This paper presents the estimation of optimal cutting parameters of the straight cylindrical turning process using the ABC algorithm. The ABC algorithm is first tested on four benchmark problems of numerical optimization and its performance is compared with genetic algorithm (GA) and ant colony optimization (ACO) algorithm. Results indicate that, the rate of convergence of ABC algorithm is better than GA and ACO. Then, the ABC algorithm is used to predict optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool nose radius to achieve good surface finish. Results indicate that, the ABC algorithm estimated a comparable surface finish when compared with real coded genetic algorithm and differential evolution algorithm.

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

Composite collective decision-making.

PubMed

Czaczkes, Tomer J; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen

2015-06-22

Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Optimization on Paddy Crops in Central Java (with Solver, SVD on Least Square and ACO (Ant Colony Algorithm))

NASA Astrophysics Data System (ADS)

Parhusip, H. A.; Trihandaru, S.; Susanto, B.; Prasetyo, S. Y. J.; Agus, Y. H.; Simanjuntak, B. H.

2017-03-01

Several algorithms and objective functions on paddy crops have been studied to get optimal paddy crops in Central Java based on the data given from Surakarta and Boyolali. The algorithms are linear solver, least square and Ant Colony Algorithms (ACO) to develop optimization procedures on paddy crops modelled with Modified GSTAR (Generalized Space-Time Autoregressive) and nonlinear models where the nonlinear models are quadratic and power functions. The studied data contain paddy crops from Surakarta and Boyolali determining the best period of planting in the year 1992-2012 for Surakarta where 3 periods for planting are known and the optimal amount of paddy crops in Boyolali in the year 2008-2013. Having these analyses may guide the local agriculture government to give a decision on rice sustainability in its region. The best period for planting in Surakarta is observed, i.e. the best period is in September-December based on the data 1992-2012 by considering the planting area, the cropping area, and the paddy crops are the most important factors to be taken into account. As a result, we can refer the paddy crops in this best period (about 60.4 thousand tons per year) as the optimal results in 1992-2012 where the used objective function is quadratic. According to the research, the optimal paddy crops in Boyolali about 280 thousand tons per year where the studied factors are the amount of rainfalls, the harvested area and the paddy crops in 2008-2013. In this case, linear and power functions are studied to be the objective functions. Compared to all studied algorithms, the linear solver is still recommended to be an optimization tool for a local agriculture government to predict paddy crops in future.

Ant-Man and the quantum realm

NASA Astrophysics Data System (ADS)

Michalakis, Spiros

2015-11-01

I was in Los Angeles airport, stuffing French fries into my mouth and waiting for a flight to Charlotte, North Carolina, when my phone buzzed. The e-mail was from the Science and Entertainment Exchange, a non-profit organization working to elevate the level of science in the movies, and it told me to report to Atlanta to consult on a new superhero movie: Ant-Man.

Leucoagaricus gongylophorus Produces Diverse Enzymes for the Degradation of Recalcitrant Plant Polymers in Leaf-Cutter Ant Fungus Gardens

PubMed Central

Aylward, Frank O.; Burnum-Johnson, Kristin E.; Tringe, Susannah G.; Teiling, Clotilde; Tremmel, Daniel M.; Moeller, Joseph A.; Scott, Jarrod J.; Barry, Kerrie W.; Piehowski, Paul D.; Nicora, Carrie D.; Malfatti, Stephanie A.; Monroe, Matthew E.; Purvine, Samuel O.; Goodwin, Lynne A.; Smith, Richard D.; Weinstock, George M.; Gerardo, Nicole M.; Suen, Garret; Lipton, Mary S.

2013-01-01

Plants represent a large reservoir of organic carbon comprised primarily of recalcitrant polymers that most metazoans are unable to deconstruct. Many herbivores gain access to nutrients in this material indirectly by associating with microbial symbionts, and leaf-cutter ants are a paradigmatic example. These ants use fresh foliar biomass as manure to cultivate gardens composed primarily of Leucoagaricus gongylophorus, a basidiomycetous fungus that produces specialized hyphal swellings that serve as a food source for the host ant colony. Although leaf-cutter ants are conspicuous herbivores that contribute substantially to carbon turnover in Neotropical ecosystems, the process through which plant biomass is degraded in their fungus gardens is not well understood. Here we present the first draft genome of L. gongylophorus, and, using genomic and metaproteomic tools, we investigate its role in lignocellulose degradation in the gardens of both Atta cephalotes and Acromyrmex echinatior leaf-cutter ants. We show that L. gongylophorus produces a diversity of lignocellulases in ant gardens and is likely the primary driver of plant biomass degradation in these ecosystems. We also show that this fungus produces distinct sets of lignocellulases throughout the different stages of biomass degradation, including numerous cellulases and laccases that likely play an important role in lignocellulose degradation. Our study provides a detailed analysis of plant biomass degradation in leaf-cutter ant fungus gardens and insight into the enzymes underlying the symbiosis between these dominant herbivores and their obligate fungal cultivar. PMID:23584789

Ant workers exhibit specialization and memory during raft formation.

PubMed

Avril, Amaury; Purcell, Jessica; Chapuisat, Michel

2016-06-01

By working together, social insects achieve tasks that are beyond the reach of single individuals. A striking example of collective behaviour is self-assembly, a process in which individuals link their bodies together to form structures such as chains, ladders, walls or rafts. To get insight into how individual behavioural variation affects the formation of self-assemblages, we investigated the presence of task specialization and the role of past experience in the construction of ant rafts. We subjected groups of Formica selysi workers to two consecutive floods and monitored the position of individuals in rafts. Workers showed specialization in their positions when rafting, with the same individuals consistently occupying the top, middle, base or side position in the raft. The presence of brood modified workers' position and raft shape. Surprisingly, workers' experience in the first rafting trial with brood influenced their behaviour and raft shape in the subsequent trial without brood. Overall, this study sheds light on the importance of workers' specialization and memory in the formation of self-assemblages.

Ant workers exhibit specialization and memory during raft formation

NASA Astrophysics Data System (ADS)

Avril, Amaury; Purcell, Jessica; Chapuisat, Michel

2016-06-01

By working together, social insects achieve tasks that are beyond the reach of single individuals. A striking example of collective behaviour is self-assembly, a process in which individuals link their bodies together to form structures such as chains, ladders, walls or rafts. To get insight into how individual behavioural variation affects the formation of self-assemblages, we investigated the presence of task specialization and the role of past experience in the construction of ant rafts. We subjected groups of Formica selysi workers to two consecutive floods and monitored the position of individuals in rafts. Workers showed specialization in their positions when rafting, with the same individuals consistently occupying the top, middle, base or side position in the raft. The presence of brood modified workers' position and raft shape. Surprisingly, workers' experience in the first rafting trial with brood influenced their behaviour and raft shape in the subsequent trial without brood. Overall, this study sheds light on the importance of workers' specialization and memory in the formation of self-assemblages.

Non-additive benefit or cost? Disentangling the indirect effects that occur when plants bearing extrafloral nectaries and honeydew-producing insects share exotic ant mutualists

PubMed Central

Savage, Amy M.; Rudgers, Jennifer A.

2013-01-01

Background and Aims In complex communities, organisms often form mutualisms with multiple different partners simultaneously. Non-additive effects may emerge among species linked by these positive interactions. Ants commonly participate in mutualisms with both honeydew-producing insects (HPI) and their extrafloral nectary (EFN)-bearing host plants. Consequently, HPI and EFN-bearing plants may experience non-additive benefits or costs when these groups co-occur. The outcomes of these interactions are likely to be influenced by variation in preferences among ants for honeydew vs. nectar. In this study, a test was made for non-additive effects on HPI and EFN-bearing plants resulting from sharing exotic ant guards. Preferences of the dominant exotic ant species for nectar vs. honeydew resources were also examined. Methods Ant access, HPI and nectar availability were manipulated on the EFN-bearing shrub, Morinda citrifolia, and ant and HPI abundances, herbivory and plant growth were assessed. Ant-tending behaviours toward HPI across an experimental gradient of nectar availability were also tracked in order to investigate mechanisms underlying ant responses. Key Results The dominant ant species, Anoplolepis gracilipes, differed from less invasive ants in response to multiple mutualists, with reductions in plot-wide abundances when nectar was reduced, but no response to HPI reduction. Conversely, at sites where A. gracilipes was absent or rare, abundances of less invasive ants increased when nectar was reduced, but declined when HPI were reduced. Non-additive benefits were found at sites dominated by A. gracilipes, but only for M. citrifolia plants. Responses of HPI at these sites supported predictions of the non-additive cost model. Interestingly, the opposite non-additive patterns emerged at sites dominated by other ants. Conclusions It was demonstrated that strong non-additive benefits and costs can both occur when a plant and herbivore share mutualist partners. These findings suggest that broadening the community context of mutualism studies can reveal important non-additive effects and increase understanding of the dynamics of species interactions. PMID:23609021

MGA trajectory planning with an ACO-inspired algorithm

NASA Astrophysics Data System (ADS)

Ceriotti, Matteo; Vasile, Massimiliano

2010-11-01

Given a set of celestial bodies, the problem of finding an optimal sequence of swing-bys, deep space manoeuvres (DSM) and transfer arcs connecting the elements of the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial-continuous problem. Its automated solution would greatly improve the design of future space missions, allowing the assessment of a large number of alternative mission options in a short time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the optimal planetary sequence and a good estimation of the set of associated optimal trajectories. The trajectory model consists of a sequence of celestial bodies connected by two-dimensional transfer arcs containing one DSM. For each transfer arc, the position of the planet and the spacecraft, at the time of arrival, are matched by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. For each departure date, this model generates a full tree of possible transfers from the departure to the destination planet. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by ant colony optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select a feasible direction. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter. Solutions are compared to those found through more traditional genetic-algorithm techniques.

Olfactory pathway of the hornet Vespa velutina: New insights into the evolution of the hymenopteran antennal lobe.

PubMed

Couto, Antoine; Lapeyre, Benoit; Thiéry, Denis; Sandoz, Jean-Christophe

2016-08-01

In the course of evolution, eusociality has appeared several times independently in Hymenoptera, within different families such as Apidae (bees), Formicidae (ants), and Vespidae (wasps and hornets), among others. The complex social organization of eusocial Hymenoptera relies on sophisticated olfactory communication systems. Whereas the olfactory systems of several bee and ant species have been well characterized, very little information is as yet available in Vespidae, although this family represents a highly successful insect group, displaying a wide range of life styles from solitary to eusocial. Using fluorescent labeling, confocal microscopy, and 3D reconstructions, we investigated the organization of the olfactory pathway in queens, workers, and males of the eusocial hornet Vespa velutina. First, we found that caste and sex dimorphism is weakly pronounced in hornets, with regard to both whole-brain morphology and antennal lobe organization, although several male-specific macroglomeruli are present. The V. velutina antennal lobe contains approximately 265 glomeruli (in females), grouped in nine conspicuous clusters formed by afferent tract subdivisions. As in bees and ants, hornets display a dual olfactory pathway, with two major efferent tracts, the medial and the lateral antennal lobe tracts (m- and l-ALT), separately arborizing two antennal lobe hemilobes and projecting to partially different regions of higher order olfactory centers. Finally, we found remarkable anatomical similarities in the glomerular cluster organizations among hornets, ants, and bees, suggesting the possible existence of homologies in the olfactory pathways of these eusocial Hymenoptera. We propose a common framework for describing AL compartmentalization across Hymenoptera and discuss possible evolutionary scenarios. J. Comp. Neurol. 524:2335-2359, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Solving graph data issues using a layered architecture approach with applications to web spam detection.

PubMed

Scarselli, Franco; Tsoi, Ah Chung; Hagenbuchner, Markus; Noi, Lucia Di

2013-12-01

This paper proposes the combination of two state-of-the-art algorithms for processing graph input data, viz., the probabilistic mapping graph self organizing map, an unsupervised learning approach, and the graph neural network, a supervised learning approach. We organize these two algorithms in a cascade architecture containing a probabilistic mapping graph self organizing map, and a graph neural network. We show that this combined approach helps us to limit the long-term dependency problem that exists when training the graph neural network resulting in an overall improvement in performance. This is demonstrated in an application to a benchmark problem requiring the detection of spam in a relatively large set of web sites. It is found that the proposed method produces results which reach the state of the art when compared with some of the best results obtained by others using quite different approaches. A particular strength of our method is its applicability towards any input domain which can be represented as a graph. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evolution of synchronization and desynchronization in digital organisms.

PubMed

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 Carnivorous Plant Fed by Its Ant Symbiont: A Unique Multi-Faceted Nutritional Mutualism

PubMed Central

Bazile, Vincent; Moran, Jonathan A.; Le Moguédec, Gilles; Marshall, David J.; Gaume, Laurence

2012-01-01

Scarcity of essential nutrients has led plants to evolve alternative nutritional strategies, such as myrmecotrophy (ant-waste-derived nutrition) and carnivory (invertebrate predation). The carnivorous plant Nepenthes bicalcarata grows in the Bornean peatswamp forests and is believed to have a mutualistic relationship with its symbiotic ant Camponotus schmitzi. However, the benefits provided by the ant have not been quantified. We tested the hypothesis of a nutritional mutualism, using foliar isotopic and reflectance analyses and by comparing fitness-related traits between ant-inhabited and uninhabited plants. Plants inhabited by C. schmitzi produced more leaves of greater area and nitrogen content than unoccupied plants. The ants were estimated to provide a 200% increase in foliar nitrogen to adult plants. Inhabited plants also produced more and larger pitchers containing higher prey biomass. C. schmitzi-occupied pitchers differed qualitatively in containing C. schmitzi wastes and captured large ants and flying insects. Pitcher abortion rates were lower in inhabited plants partly because of herbivore deterrence as herbivory-aborted buds decreased with ant occupation rate. Lower abortion was also attributed to ant nutritional service. The ants had higher δ15N values than any tested prey, and foliar δ15N increased with ant occupation rate, confirming their predatory behaviour and demonstrating their direct contribution to the plant-recycled N. We estimated that N. bicalcarata derives on average 42% of its foliar N from C. schmitzi wastes, (76% in highly-occupied plants). According to the Structure Independent Pigment Index, plants without C. schmitzi were nutrient stressed compared to both occupied plants, and pitcher-lacking plants. This attests to the physiological cost of pitcher production and poor nutrient assimilation in the absence of the symbiont. Hence C. schmitzi contributes crucially to the nutrition of N. bicalcarata, via protection of assimilatory organs, enhancement of prey capture, and myrmecotrophy. This combination of carnivory and myrmecotrophy represents an outstanding strategy of nutrient sequestration. PMID:22590524

Compilation of Pilot Personality Norms

DTIC Science & Technology

2011-07-01

Relationships (BOR-N) Identifies individuals who report a history of involvement in unstable relationships. .63 Self - Harm (BOR-S) Identifies individuals who...Negative Relationships (BOR-N) 44.89 7.81 47.73 7.91 45.06 7.84 Self - Harm (BOR-S) 44.89 7.17 43.61 6.84 44.82 7.16 Antisocial Features (ANT) 51.89

Agents, assemblers, and ANTS: scheduling assembly with market and biological software mechanisms

NASA Astrophysics Data System (ADS)

Toth-Fejel, Tihamer T.

2000-06-01

Nanoscale assemblers will need robust, scalable, flexible, and well-understood mechanisms such as software agents to control them. This paper discusses assemblers and agents, and proposes a taxonomy of their possible interaction. Molecular assembly is seen as a special case of general assembly, subject to many of the same issues, such as the advantages of convergent assembly, and the problem of scheduling. This paper discusses the contract net architecture of ANTS, an agent-based scheduling application under development. It also describes an algorithm for least commitment scheduling, which uses probabilistic committed capacity profiles of resources over time, along with realistic costs, to provide an abstract search space over which the agents can wander to quickly find optimal solutions.

Self-organization is a dynamic and lineage-intrinsic property of mammary epithelial cells

PubMed Central

Chanson, Lea; Brownfield, Douglas; Garbe, James C.; Kuhn, Irene; Stampfer, Martha R.; Bissell, Mina J.; LaBarge, Mark A.

2011-01-01

Loss of organization is a principle feature of cancers; therefore it is important to understand how normal adult multilineage tissues, such as bilayered secretory epithelia, establish and maintain their architectures. The self-organization process that drives heterogeneous mixtures of cells to form organized tissues is well studied in embryology and with mammalian cell lines that were abnormal or engineered. Here we used a micropatterning approach that confined cells to a cylindrical geometry combined with an algorithm to quantify changes of cellular distribution over time to measure the ability of different cell types to self-organize relative to each other. Using normal human mammary epithelial cells enriched into pools of the two principal lineages, luminal and myoepithelial cells, we demonstrated that bilayered organization in mammary epithelium was driven mainly by lineage-specific differential E-cadherin expression, but that P-cadherin contributed specifically to organization of the myoepithelial layer. Disruption of the actomyosin network or of adherens junction proteins resulted in either prevention of bilayer formation or loss of preformed bilayers, consistent with continual sampling of the local microenvironment by cadherins. Together these data show that self-organization is an innate and reversible property of communities of normal adult human mammary epithelial cells. PMID:21300877

Self-organization is a dynamic and lineage-intrinsic property of mammary epithelial cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chanson, L.; Brownfield, D.; Garbe, J. C.

Loss of organization is a principle feature of cancers; therefore it is important to understand how normal adult multilineage tissues, such as bilayered secretory epithelia, establish and maintain their architectures. The self-organization process that drives heterogeneous mixtures of cells to form organized tissues is well studied in embryology and with mammalian cell lines that were abnormal or engineered. Here we used a micropatterning approach that confined cells to a cylindrical geometry combined with an algorithm to quantify changes of cellular distribution over time to measure the ability of different cell types to self-organize relative to each other. Using normal humanmore » mammary epithelial cells enriched into pools of the two principal lineages, luminal and myoepithelial cells, we demonstrated that bilayered organization in mammary epithelium was driven mainly by lineage-specific differential E-cadherin expression, but that P-cadherin contributed specifically to organization of the myoepithelial layer. Disruption of the actomyosin network or of adherens junction proteins resulted in either prevention of bilayer formation or loss of preformed bilayers, consistent with continual sampling of the local microenvironment by cadherins. Together these data show that self-organization is an innate and reversible property of communities of normal adult human mammary epithelial cells.« less

The Antsy Social Network: Determinants of Nest Structure and Arrangement in Asian Weaver Ants.

PubMed

Devarajan, Kadambari

2016-01-01

Asian weaver ants (Oecophylla smaragdina) are arboreal ants that are known to form mutualistic complexes with their host trees. They are eusocial ants that build elaborate nests in the canopy in tropical areas. A colony comprises of multiple nests, usually on multiple trees, and the boundaries of the colony may be difficult to identify. However, they provide the ideal model for studying group living in invertebrates since there are a definite number of nests for a given substrate, the tree. Here, we briefly examine the structure of the nests and the processes involved in the construction and maintenance of these nests. We have described the spatial arrangement of weaver ant nests on trees in two distinct tropical clusters, a few hundred kilometres apart in India. Measurements were made for 13 trees with a total of 71 nests in the two field sites. We have considered a host of biotic and abiotic factors that may be crucial in determining the location of the nesting site by Asian weaver ants. Our results indicate that tree characteristics and architecture followed by leaf features help determine nest location in Asian weaver ants. While environmental factors may not be as influential to nest arrangement, they seem to be important determinants of nest structure. The parameters that may be considered in establishing the nests could be crucial in picking the evolutionary drivers for colonial living in social organisms.

Semi-automatic mapping of linear-trending bedforms using 'Self-Organizing Maps' algorithm

NASA Astrophysics Data System (ADS)

Foroutan, M.; Zimbelman, J. R.

2017-09-01

Increased application of high resolution spatial data such as high resolution satellite or Unmanned Aerial Vehicle (UAV) images from Earth, as well as High Resolution Imaging Science Experiment (HiRISE) images from Mars, makes it necessary to increase automation techniques capable of extracting detailed geomorphologic elements from such large data sets. Model validation by repeated images in environmental management studies such as climate-related changes as well as increasing access to high-resolution satellite images underline the demand for detailed automatic image-processing techniques in remote sensing. This study presents a methodology based on an unsupervised Artificial Neural Network (ANN) algorithm, known as Self Organizing Maps (SOM), to achieve the semi-automatic extraction of linear features with small footprints on satellite images. SOM is based on competitive learning and is efficient for handling huge data sets. We applied the SOM algorithm to high resolution satellite images of Earth and Mars (Quickbird, Worldview and HiRISE) in order to facilitate and speed up image analysis along with the improvement of the accuracy of results. About 98% overall accuracy and 0.001 quantization error in the recognition of small linear-trending bedforms demonstrate a promising framework.

How large is large enough for insects? Forest fragmentation effects at three spatial scales

NASA Astrophysics Data System (ADS)

Ribas, C. R.; Sobrinho, T. G.; Schoereder, J. H.; Sperber, C. F.; Lopes-Andrade, C.; Soares, S. M.

2005-02-01

Several mechanisms may lead to species loss in fragmented habitats, such as edge and shape effects, loss of habitat and heterogeneity. Ants and crickets were sampled in 18 forest remnants in south-eastern Brazil, to test whether a group of small remnants maintains the same insect species richness as similar sized large remnants, at three spatial scales. We tested hypotheses about alpha and gamma diversity to explain the results. Groups of remnants conserve as many species of ants as a single one. Crickets, however, showed a scale-dependent pattern: at small scales there was no significant or important difference between groups of remnants and a single one, while at the larger scale the group of remnants maintained more species. Alpha diversity (local species richness) was similar in a group of remnants and in a single one, at the three spatial scales, both for ants and crickets. Gamma diversity, however, varied both with taxa (ants and crickets) and spatial scale, which may be linked to insect mobility, remnant isolation, and habitat heterogeneity. Biological characteristics of the organisms involved have to be considered when studying fragmentation effects, as well as spatial scale at which it operates. Mobility of the organisms influences fragmentation effects, and consequently conservation strategies.

Ants can be used as bio-indicators to reveal biological effects of electromagnetic waves from some wireless apparatus.

PubMed

Cammaerts, Marie-Claire; Johansson, Olle

2014-12-01

Society is confronted with an increasing number of applications making use of wireless communication. We also notice an increasing awareness about potentially harmful effects of the related electromagnetic fields on living organisms. At present, it is not realistic to expect that wireless communication will decrease or disappear within the near future. That is why we currently are investigating the mechanisms behind these effects and the effectiveness of possible solutions. In order to be efficient and effective, we designed and validated a fast and easy test on ants - these insects being used as a biological model - for revealing the effect of wireless equipments like mobile phones, smartphones, digital enhanced cordless telephone (DECT) phones, WiFi routers and so on. This test includes quantification of ants' locomotion under natural conditions, then in the vicinity of such wireless equipments. Observations, numerical results and statistical results allow detecting any effect of a radiating source on these living organisms.

Swarmathon 2017

NASA Image and Video Library

2017-04-20

In the Swarmathon competition at the Kennedy Space Center Visitor Complex, students were asked to develop computer code for the small robots, programming them to look for "resources" in the form of cubes with AprilTags, similar to barcodes. Teams developed search algorithms for the Swarmies to operate autonomously, communicating and interacting as a collective swarm similar to ants foraging for food.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

Linear antenna array optimization using flower pollination algorithm.

PubMed

Saxena, Prerna; Kothari, Ashwin

2016-01-01

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

Sun Basking in Red Wood Ants Formica polyctena (Hymenoptera, Formicidae): Individual Behaviour and Temperature-Dependent Respiration Rates

PubMed Central

Kadochová, Štěpánka; Frouz, Jan; Roces, Flavio

2017-01-01

In early spring, red wood ants Formica polyctena are often observed clustering on the nest surface in large numbers basking in the sun. It has been hypothesized that sun-basking behaviour may contribute to nest heating because of both heat carriage into the nest by sun-basking workers, and catabolic heat production from the mobilization of the workers’ lipid reserves. We investigated sun-basking behaviour in laboratory colonies of F. polyctena exposed to an artificial heat source. Observations on identified individuals revealed that not all ants bask in the sun. Sun-basking and non-sun-basking workers did not differ in body size nor in respiration rates. The number of sun-basking ants and the number of their visits to the hot spot depended on the temperature of both the air and the hot spot. To investigate whether sun basking leads to a physiological activation linked with increased lipolysis, we measured respiration rates of individual workers as a function of temperature, and compared respiration rates of sun-basking workers before and two days after they were allowed to expose themselves to a heat source over 10 days, at self-determined intervals. As expected for ectothermic animals, respiration rates increased with increasing temperatures in the range 5 to 35°C. However, the respiration rates of sun-basking workers measured two days after a long-term exposure to the heat source were similar to those before sun basking, providing no evidence for a sustained increase of the basal metabolic rates after prolonged sun basking. Based on our measurements, we argue that self-heating of the nest mound in early spring has therefore to rely on alternative heat sources, and speculate that physical transport of heat in the ant bodies may have a significant effect. PMID:28114396

Fire Ant Decapitating Fly Cooperative Release Programs (1994–2008): Two Pseudacteon Species, P. tricuspis and P. curvatus, Rapidly Expand Across Imported Fire Ant Populations in the Southeastern United States

PubMed Central

Callcott, Anne-Marie A.; Porter, Sanford D.; Weeks, Ronald D.; “Fudd” Graham, L. C.; Johnson, Seth J.; Gilbert, Lawrence E.

2011-01-01

Natural enemies of the imported fire ants, Solenopsis invicta Buren S. richteri Forel (Hymenoptera: Formicidae), and their hybrid, include a suite of more than 20 fire ant decapitating phorid flies from South America in the genus Pseudacteon. Over the past 12 years, many researchers and associates have cooperated in introducing several species as classical or self-sustaining biological control agents in the United States. As a result, two species of flies, Pseudacteon tricuspis Borgmeier and P. curvatus Borgmeier (Diptera: Phoridae), are well established across large areas of the southeastern United States. Whereas many researchers have published local and state information about the establishment and spread of these flies, here distribution data from both published and unpublished sources has been compiled for the entire United States with the goal of presenting confirmed and probable distributions as of the fall of 2008. Documented rates of expansion were also used to predict the distribution of these flies three years later in the fall of 2011. In the fall of 2008, eleven years after the first successful release, we estimate that P. tricuspis covered about 50% of the fire ant quarantined area and that it will occur in almost 65% of the quarantine area by 2011. Complete coverage of the fire ant quarantined area will be delayed or limited by this species' slow rate of spread and frequent failure to establish in more northerly portions of the fire ant range and also, perhaps, by its preference for red imported fire ants (S. invicta). Eight years after the first successful release of P. curvatus, two biotypes of this species (one biotype occurring predominantly in the black and hybrid imported fire ants and the other occurring in red imported fire ants) covered almost 60% of the fire ant quarantined area. We estimate these two biotypes will cover almost 90% of the quarantine area by 2011 and 100% by 2012 or 2013. Strategic selection of several distributional gaps for future releases will accelerate complete coverage of quarantine areas. However, some gaps may be best used for the release of additional species of decapitating flies because establishment rates may be higher in areas without competing species. PMID:21526930

USING ANT COMMUNITIES FOR RAPID ASSESSMENT OF TERRESTRIAL ECOSYSTEM HEALTH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wike, L; Doug Martin, D; Michael Paller, M

2007-01-12

Ecosystem health with its near infinite number of variables is difficult to measure, and there are many opinions as to which variables are most important, most easily measured, and most robust, Bioassessment avoids the controversy of choosing which physical and chemical parameters to measure because it uses responses of a community of organisms that integrate all aspects of the system in question. A variety of bioassessment methods have been successfully applied to aquatic ecosystems using fish and macroinvertebrate communities. Terrestrial biotic index methods are less developed than those for aquatic systems and we are seeking to address this problem here.more » This study had as its objective to examine the baseline differences in ant communities at different seral stages from clear cut back to mature pine plantation as a precursor to developing a bioassessment protocol. Comparative sampling was conducted at four seral stages; clearcut, 5 year, 15 year and mature pine plantation stands. Soil and vegetation data were collected at each site. All ants collected were preserved in 70% ethyl alcohol and identified to genus. Analysis of the ant data indicates that ants respond strongly to the habitat changes that accompany ecological succession in managed pine forests and that individual genera as well as ant community structure can be used as an indicator of successional change. Ants exhibited relatively high diversity in both early and mature seral stages. High ant diversity in the mature seral stages was likely related to conditions on the forest floor which favored litter dwelling and cool climate specialists.« less

Integrating Paleodistribution Models and Phylogeography in the Grass-Cutting Ant Acromyrmex striatus (Hymenoptera: Formicidae) in Southern Lowlands of South America

PubMed Central

Cristiano, Maykon Passos; Clemes Cardoso, Danon; Fernandes-Salomão, Tânia Maria; Heinze, Jürgen

2016-01-01

Past climate changes often have influenced the present distribution and intraspecific genetic diversity of organisms. The objective of this study was to investigate the phylogeography and historical demography of populations of Acromyrmex striatus (Roger, 1863), a leaf-cutting ant species restricted to the open plains of South America. Additionally, we modeled the distribution of this species to predict its contemporary and historic habitat. From the partial sequences of the mitochondrial gene cytochrome oxidase I of 128 A. striatus workers from 38 locations we estimated genetic diversity and inferred historical demography, divergence time, and population structure. The potential distribution areas of A. striatus for current and quaternary weather conditions were modeled using the maximum entropy algorithm. We identified a total of 58 haplotypes, divided into five main haplogroups. The analysis of molecular variance (AMOVA) revealed that the largest proportion of genetic variation is found among the groups of populations. Paleodistribution models suggest that the potential habitat of A. striatus may have decreased during the Last Interglacial Period (LIG) and expanded during the Last Maximum Glacial (LGM). Overall, the past potential distribution recovered by the model comprises the current potential distribution of the species. The general structuring pattern observed was consistent with isolation by distance, suggesting a balance between gene flow and drift. Analysis of historical demography showed that populations of A. striatus had remained constant throughout its evolutionary history. Although fluctuations in the area of their potential historic habitat occurred during quaternary climate changes, populations of A. striatus are strongly structured geographically. However, explicit barriers to gene flow have not been identified. These findings closely match those in Mycetophylax simplex, another ant species that in some areas occurs in sympatry with A. striatus. Ecophysiological traits of this species and isolation by distance may together have shaped the phylogeographic pattern. PMID:26734939

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

NASA Astrophysics Data System (ADS)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

Is phenotypic plasticity a key mechanism for responding to thermal stress in ants?

PubMed

Oms, Cristela Sánchez; Cerdá, Xim; Boulay, Raphaël

2017-06-01

Unlike natural selection, phenotypic plasticity allows organisms to respond quickly to changing environmental conditions. However, plasticity may not always be adaptive. In insects, body size and other morphological measurements have been shown to decrease as temperature increases. This relationship may lead to a physiological conflict in ants, where larger body size and longer legs often confer better thermal resistance. Here, we tested the effect of developmental temperature (20, 24, 28 or 32 °C) on adult thermal resistance in the thermophilic ant species Aphaenogaster senilis. We found that no larval development occurred at 20 °C. However, at higher temperatures, developmental speed increased as expected and smaller adults were produced. In thermal resistance tests, we found that ants reared at 28 and 32 °C had half-lethal temperatures that were 2 °C higher than those of ants reared at 24 °C. Thus, although ants reared at higher temperatures were smaller in size, they were nonetheless more thermoresistant. These results show that A. senilis can exploit phenotypic plasticity to quickly adjust its thermal resistance to local conditions and that this process is independent of morphological adaptations. This mechanism may be particularly relevant given current rapid climate warming.

Alate susceptibility in ants

PubMed Central

Ho, Eddie K H; Frederickson, Megan E

2014-01-01

Pathogens are predicted to pose a particular threat to eusocial insects because infections can spread rapidly in colonies with high densities of closely related individuals. In ants, there are two major castes: workers and reproductives. Sterile workers receive no direct benefit from investing in immunity, but can gain indirect fitness benefits if their immunity aids the survival of their fertile siblings. Virgin reproductives (alates), on the other hand, may be able to increase their investment in reproduction, rather than in immunity, because of the protection they receive from workers. Thus, we expect colonies to have highly immune workers, but relatively more susceptible alates. We examined the survival of workers, gynes, and males of nine ant species collected in Peru and Canada when exposed to the entomopathogenic fungus Beauveria bassiana. For the seven species in which treatment with B. bassiana increased ant mortality relative to controls, we found workers were significantly less susceptible compared with both alate sexes. Female and male alates did not differ significantly in their immunocompetence. Our results suggest that, as with other nonreproductive tasks in ant colonies like foraging and nest maintenance, workers have primary responsibility for colony immunity, allowing alates to specialize on reproduction. We highlight the importance of colony-level selection on individual immunity in ants and other eusocial organisms. PMID:25540683

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2012-01-01

In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.

Action of Ants on Vertebrate Carcasses and Blow Flies (Calliphoridae).

PubMed

Paula, Michele C; Morishita, Gustavo M; Cavarson, Carolina H; Gonçalves, Cristiano R; Tavares, Paulo R A; Mendonça, Angélica; Súarez, Yzel R; Antonialli-Junior, William F

2016-11-01

Forensic entomology is a science that uses insect fauna as a tool to assist in criminal investigations and civil proceedings. Although the most researched insects are the Diptera and Coleoptera, ants may be present in all stages of decomposition. The aim of this study was to evaluate the role of ants and their action on blow flies during the decomposition process. Experiments were performed in which four pig carcasses were exposed in the cold and dry season (November/2012 and March/2013) and four in the hot and wet season (May/2013 and August/2013). Flies were the first insects to detect and interact with the carcasses, and six species of the Calliphoridae family were identified. Ants (Hymenoptera: Formicidae) were the second group, with six subfamilies identified. Myrmycinae represented 42% of the species, followed by Formicinae (28%), Ectatominae and Ponerinae (both 10%), and Ecitoninae and Dolichoderinae (both 5%). The ants acted on the carcasses as predators of visiting species, omnivores, and necrophagous, in all cases significantly affecting the decomposition time, slowing it down when the ants preyed on adult and immature insects consuming the carcass, or accelerating it by consuming the carcass and creating holes that could serve as gateways for the action of other organisms. The ants also generated artifacts that could lead to forensic misinterpretation. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Postfire Succession of Ants (Hymenoptera: Formicidae) Nesting in Dead Wood of Northern Boreal Forest.

PubMed

Boucher, Philippe; Hébert, Christian; Francoeur, André; Sirois, Luc

2015-10-01

Dead wood decomposition begins immediately after tree death and involves a large array of invertebrates. Ecological successions are still poorly known for saproxylic organisms, particularly in boreal forests. We investigated the use of dead wood as nesting sites for ants along a 60-yr postfire chronosequence in northeastern coniferous forests. We sampled a total of 1,625 pieces of dead wood, in which 263 ant nests were found. Overall, ant abundance increased during the first 30 yr after wildfire, and then declined. Leptothorax cf. canadensis Provancher, the most abundant species in our study, was absent during the first 2 yr postfire, but increased steadily until 30 yr after fire, whereas Myrmica alaskensis Wheeler, second in abundance, was found at all stages of succession in the chronosequence. Six other species were less frequently found, among which Camponotus herculeanus (Linné), Formica neorufibarbis Emery, and Formica aserva Forel were locally abundant, but more scarcely distributed. Dead wood lying on the ground and showing numerous woodborer holes had a higher probability of being colonized by ants. The C:N ratio was lower for dead wood colonized by ants than for noncolonized dead wood, showing that the continuous occupation of dead wood by ants influences the carbon and nitrogen dynamics of dead wood after wildfire in northern boreal forests. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Detection and dispersal of explosives by ants

NASA Astrophysics Data System (ADS)

McFee, John E.; Achal, Steve; Faust, Anthony A.; Puckrin, Eldon; House, Andrew; Reynolds, Damon; McDougall, William; Asquini, Adam

2009-05-01

The ability of animals to detect explosives is well documented. Mammalian systems, insects and even single celled organisms have all been studied and in a few cases employed to detect explosives. This paper will describe the potential ability of ants to detect, disperse and possibly neutralize bulk explosives. In spring 2008 a team of DRDC and Itres scientists conducted experiments on detecting surface-laid and buried landmines, improvised explosive devices (IEDs) and their components. Measurements were made using state-of-the-art short wave and thermal infrared hyperspectral imagers mounted on a personnel lift. During one of the early morning measurement sessions, a wispy, long linear trail was seen to emanate several meters from piles of explosives that were situated on the ground. Upon close visual inspection, it was observed that ants had found the piles of explosives and were carrying it to their ant hill, a distance of almost 20 meters from the piles. Initial analysis of the hyperspectral images clearly revealed the trail to the ant hill of explosives, despite being present in quantities not visible to the unaided eye. This paper details these observations and discusses them in the context of landmine and IED detection and neutralization. Possible reasons for such behaviour are presented. A number of questions regarding the behaviour, many pertinent to the use of ants in a counter-landmine/IED role, are presented and possible methods of answering them are discussed. Anecdotal evidence from deminers of detection and destruction of explosives by ants are presented.

Ant Abundance along a Productivity Gradient: Addressing Two Conflicting Hypotheses

PubMed Central

Segev, Udi; Kigel, Jaime; Lubin, Yael; Tielbörger, Katja

2015-01-01

The number of individuals within a population or community and their body size can be associated with changes in resource supply. While these relationships may provide a key to better understand the role of abiotic vs. biotic constraints in animal communities, little is known about the way size and abundance of organisms change along resource gradients. Here, we studied this interplay in ants, addressing two hypotheses with opposite predictions regarding variation in population densities along resource gradients- the ‘productivity hypothesis’ and the ‘productivity-based thinning hypothesis’. The hypotheses were tested in two functional groups of ground-dwelling ants that are directly primary consumers feeding on seeds: specialized seed-eaters and generalist species. We examined variations in colony density and foraging activity (a size measurement of the forager caste) in six ant assemblages along a steep productivity gradient in a semi-arid region, where precipitation and plant biomass vary 6-fold over a distance of 250km. An increase in the density or foraging activity of ant colonies along productivity gradients is also likely to affect competitive interactions among colonies, and consequently clinal changes in competition intensity were also examined. Ant foraging activity increased with productivity for both functional groups. However, colony density revealed opposing patterns: it increased with productivity for the specialized seed-eaters, but decreased for the generalist species. Competition intensity, evaluated by spatial partitioning of species at food baits and distribution of colonies, was uncorrelated with productivity in the specialized seed-eaters, but decreased with increasing productivity in the generalists. Our results provide support for two contrasting hypotheses regarding the effect of resource availability on the abundance of colonial organisms- the ‘productivity hypothesis’ for specialized seed-eaters and the ‘productivity-based thinning hypothesis’ for generalist species. These results also stress the importance of considering the role of functional groups in studies of community structure. PMID:26176853

Implications of Genital Mutilation at Autopsy.

PubMed

Byard, Roger W

2017-07-01

Given the potential significance of mutilation of the external genitalia in medicolegal fatalities, a review of the literature was undertaken to identify subcategories. Such mutilations may have been sustained sometime before death, around the time of death, or after death. The most common type of ante mortem genital mutilations involves cultural practices such as male circumcision. Less common male mutilations such as subincisions are tribally based. Female genital mutilation is found particularly in African, Middle Eastern, or Asian populations. Self-inflicted genital injuries are most common in males and may be related to attempts at suicide, or to self-harming practices. The latter have a strong association with psychiatric illnesses. Postmortem injuries may arise from animal predation or deliberate mutilation of a corpse. The latter may be associated with ante mortem genital injuries in sadistic homicides. The range of possible causes of genital mutilations in forensic cases necessitates extremely careful evaluation. © 2017 American Academy of Forensic Sciences.

Self-deployable mobile sensor networks for on-demand surveillance

NASA Astrophysics Data System (ADS)

Miao, Lidan; Qi, Hairong; Wang, Feiyi

2005-05-01

This paper studies two interconnected problems in mobile sensor network deployment, the optimal placement of heterogeneous mobile sensor platforms for cost-efficient and reliable coverage purposes, and the self-organizable deployment. We first develop an optimal placement algorithm based on a "mosaicked technology" such that different types of mobile sensors form a mosaicked pattern uniquely determined by the popularity of different types of sensor nodes. The initial state is assumed to be random. In order to converge to the optimal state, we investigate the swarm intelligence (SI)-based sensor movement strategy, through which the randomly deployed sensors can self-organize themselves to reach the optimal placement state. The proposed algorithm is compared with the random movement and the centralized method using performance metrics such as network coverage, convergence time, and energy consumption. Simulation results are presented to demonstrate the effectiveness of the mosaic placement and the SI-based movement.

The Effects of Mindfulness-Based Intervention on Children's Attention Regulation.

PubMed

Felver, Joshua C; Tipsord, Jessica M; Morris, Maxwell J; Racer, Kristina Hiatt; Dishion, Thomas J

2017-08-01

This article describes results from a randomized clinical trial of a mindfulness-based intervention for parents and children, Mindful Family Stress Reduction, on a behavioral measure of attention in youths, the Attention Network Task (ANT). Forty-one parent-child dyads were randomly assigned to either the mindfulness-based intervention condition or a wait-list control. School-age youths completed the ANT before and after the intervention. Results demonstrate significant, medium-size ( f 2 = -.16) intervention effects to the conflict monitoring subsystem of the ANT such that those in the intervention condition decreased in conflict monitoring more than those in the wait-list control. Youths in the intervention condition also showed improvements in their orienting subsystem scores, compared with controls. Mindfulness-based interventions for youths have potential utility to improve attentional self-regulation, and future research should consider incorporating measures of attention into interventions that use mindfulness training.

Young fire ant workers feign death and survive aggressive neighbors

NASA Astrophysics Data System (ADS)

Cassill, Deby L.; Vo, Kim; Becker, Brandie

2008-07-01

Feigning death is a method of self-defense employed among a wide range of prey species when threatened by predator species. This paper reports on death-feigning behavior by the fire ant, Solenopsis invicta, during intraspecific aggression among neighboring fire ant workers. Days-old workers responded to aggression by death feigning, weeks-old workers responded by fleeing and months-old workers responded by fighting back. By feigning death, days-old workers were four times more likely to survive aggression than older workers. From a proximate perspective, retaliation by young workers against aggressive older workers is certain to fail. With their relatively soft exoskeleton, young workers would be prone to injury and death and unable to execute an effective attack of biting or stinging older workers with harder exoskeletons. From an ultimate perspective, death feigning allows young workers to survive and contribute to brood care and colony growth, both of which are essential to queen survival and fitness.

Musical Training and Late-Life Cognition

PubMed Central

Gooding, Lori F; Abner, Erin L; Jicha, Gregory A; Kryscio, Richard J; Schmitt, Fredrick A

2014-01-01

This study investigated effects of early- to mid-life musical training on cognition in older adults. A Musical Training Survey examined self-reported musical experience and objective knowledge in 237 cognitively intact participants. Responses were classified into Low, Medium, and High knowledge groups. Linear mixed models compared the groups’ longitudinal performance on the Animal Naming Test (ANT; semantic verbal fluency) and Logical Memory Story A Immediate Recall (LMI; episodic memory) controlling for baseline age, time since baseline, education, sex, and full-scale IQ. Results indicate that High knowledge participants had significantly higher LMI scores at baseline and over time compared to Low knowledge participants. ANT scores did not differ among the groups. Ability to read music was associated with higher mean scores for both ANT and LMI over time. Early-to mid-life musical training may be associated with improved late-life episodic and semantic memory as well as a useful marker of cognitive reserve. PMID:24375575

A self-organizing neural network for the traveling salesman problem that is competitive with simulated annealing.

PubMed

Budinich, M

1996-02-15

Unsupervised learning applied to an unstructured neural network can give approximate solutions to the traveling salesman problem. For 50 cities in the plane this algorithm performs like the elastic net of Durbin and Willshaw (1987) and it improves when increasing the number of cities to get better than simulated annealing for problems with more than 500 cities. In all the tests this algorithm requires a fraction of the time taken by simulated annealing.

Colony-Level Differences in the Scaling Rules Governing Wood Ant Compound Eye Structure.

PubMed

Perl, Craig D; Niven, Jeremy E

2016-04-12

Differential organ growth during development is essential for adults to maintain the correct proportions and achieve their characteristic shape. Organs scale with body size, a process known as allometry that has been studied extensively in a range of organisms. Such scaling rules, typically studied from a limited sample, are assumed to apply to all members of a population and/or species. Here we study scaling in the compound eyes of workers of the wood ant, Formica rufa, from different colonies within a single population. Workers' eye area increased with body size in all the colonies showing a negative allometry. However, both the slope and intercept of some allometric scaling relationships differed significantly among colonies. Moreover, though mean facet diameter and facet number increased with body size, some colonies primarily increased facet number whereas others increased facet diameter, showing that the cellular level processes underlying organ scaling differed among colonies. Thus, the rules that govern scaling at the organ and cellular levels can differ even within a single population.

An Ant Colony Optimization Based Feature Selection for Web Page Classification

PubMed Central

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods. PMID:25136678

Power plant maintenance scheduling using ant colony optimization: an improved formulation

NASA Astrophysics Data System (ADS)

Foong, Wai Kuan; Maier, Holger; Simpson, Angus

2008-04-01

It is common practice in the hydropower industry to either shorten the maintenance duration or to postpone maintenance tasks in a hydropower system when there is expected unserved energy based on current water storage levels and forecast storage inflows. It is therefore essential that a maintenance scheduling optimizer can incorporate the options of shortening the maintenance duration and/or deferring maintenance tasks in the search for practical maintenance schedules. In this article, an improved ant colony optimization-power plant maintenance scheduling optimization (ACO-PPMSO) formulation that considers such options in the optimization process is introduced. As a result, both the optimum commencement time and the optimum outage duration are determined for each of the maintenance tasks that need to be scheduled. In addition, a local search strategy is presented in this article to boost the robustness of the algorithm. When tested on a five-station hydropower system problem, the improved formulation is shown to be capable of allowing shortening of maintenance duration in the event of expected demand shortfalls. In addition, the new local search strategy is also shown to have significantly improved the optimization ability of the ACO-PPMSO algorithm.

Optimal angle of polycrystalline silicon solar panels placed in a building using the ant colony optimization algorithm

NASA Astrophysics Data System (ADS)

Saouane, I.; Chaker, A.; Zaidi, B.; Shekhar, C.

2017-03-01

This paper describes the mathematical model used to determine the amount of solar radiation received on an inclined solar photovoltaic panel. The optimum slope angles for each month, season, and year have also been calculated for a solar photovoltaic panel. The optimization of the procedure to maximize the solar energy collected by the solar panel by varying the tilt angle is also presented. As a first step, the global solar radiation on the horizontal surface of a thermal photovoltaic panel during clear sky is estimated. Thereafter, the Muneer model, which provides the most accurate estimation of the total solar radiation at a given geographical point has been used to determine the optimum collector slope. Also, the Ant Colony Optimization (ACO) algorithm was applied to obtain the optimum tilt angle settings for PV collector to improve the PV collector efficiency. The results show good agreement between calculated and predicted results. Additionally, this paper presents studies carried out on the polycrystalline silicon solar panels for electrical energy generation in the city of Ghardaia. The electrical energy generation has been studied as a function of amount of irradiation received and the angle of optimum orientation of the solar panels.

The MAGIC-5 CAD for nodule detection in low dose and thin slice lung CTs

NASA Astrophysics Data System (ADS)

Cerello, Piergiorgio; MAGIC-5 Collaboration

2010-11-01

Lung cancer is the leading cause of cancer-related mortality in developed countries. Only 10-15% of all men and women diagnosed with lung cancer live 5 years after the diagnosis. However, the 5-year survival rate for patients diagnosed in the early asymptomatic stage of the disease can reach 70%. Early-stage lung cancers can be diagnosed by detecting non-calcified small pulmonary nodules with computed tomography (CT). Computer-aided detection (CAD) could support radiologists in the analysis of the large amount of noisy images generated in screening programs, where low-dose and thin-slice settings are used. The MAGIC-5 project, funded by the Istituto Nazionale di Fisica Nucleare (INFN, Italy) and Ministero dell'Università e della Ricerca (MUR, Italy), developed a multi-method approach based on three CAD algorithms to be used in parallel with a merging of their results: the Channeler Ant Model (CAM), based on Virtual Ant Colonies, the Dot-Enhancement/Pleura Surface Normals/VBNA (DE-PSN-VBNA), and the Region Growing Volume Plateau (RGVP). Preliminary results show quite good performances, to be improved with the refining of the single algorithm and the added value of the results merging.

Factors affecting occupational therapists' decision to join their regional professional association: Facteurs influençant la décision des ergothérapeutes de joindre les rangs de leur association professionnelle régionale.

PubMed

Reyes, Angelica N; Brown, Cary A

2018-01-01

Voluntary occupational therapy organizations fill an important role. However, recruitment and retention can be problematic. Little is known about factors influencing occupational therapists to join/maintain membership in professional associations. This study investigated factors influencing occupational therapists' decision to join/remain members of their association. An electronic survey was carried out and data were analyzed using SPSS software and manual categorization of open-ended comments. Two hundred and fifty-four therapists responded. Generation of new ideas, opportunities for professional development, self-improvement, maintenance of standards, improvement of the profession, and discounts on equipment/educational opportunities were significant factors in deciding to join the organization. The factors perceived as priorities varied in relation to participants' year of graduation. More-customized strategies, reflecting priorities that vary during a therapist's career path, may need to be employed to best address recruitment and retention across the range of therapists' needs and goals.

Innovation and application of ANN in Europe demonstrated by Kohonen maps

NASA Technical Reports Server (NTRS)

Goser, Karl

1994-01-01

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

Search Techniques for Self-Organizing Systems

DTIC Science & Technology

1975-07-01

according to their associated function values. The classes need not have equal function value ranges (i.e., the . ................... "The Mucciardi- Gose ... Gose , "An Automatic Clustering Algorithm and Its !’ropertizs in High-Dimensional Spaces,’[ IFEE Trans. S s~tems, Man and Cybernetics, Vol. SMC-2

Biomechanical simulations of costo-vertebral and anterior vertebral body tethers for the fusionless treatment of pediatric scoliosis.

PubMed

Aubin, Carl-Éric; Clin, Julien; Rawlinson, Jeremy

2018-01-01

Compression-based fusionless tethers are an alternative to conventional surgical treatments of pediatric scoliosis. Anterior approaches place an anterior (ANT) tether on the anterolateral convexity of the deformed spine to modify growth. Posterior, or costo-vertebral (CV), approaches have not been assessed for biomechanical and corrective effectiveness. The objective was to biomechanically assess CV and ANT tethers using six patient-specific, finite element models of adolescent scoliotic patients (11.9 ± 0.7 years, Cobb 34° ± 10°). A validated algorithm simulated the growth and Hueter-Volkmann growth modulation over a period of 2 years with the CV and ANT tethers at two initial tensions (100, 200 N). The models without tethering also simulated deformity progression with Cobb angle increasing from 34° to 56°, axial rotation 11° to 13°, and kyphosis 28° to 32° (mean values). With the CV tether, the Cobb angle was reduced to 27° and 20° for tensions of 100 and 200 N, respectively, kyphosis to 21° and 19°, and no change in axial rotation. With the ANT tether, Cobb was reduced to 32° and 9° for 100 and 200 N, respectively, kyphosis unchanged, and axial rotation to 3° and 0°. While the CV tether mildly corrected the coronal curve over a 2-year growth period, it had sagittal lordosing effect, particularly with increasing initial axial rotation (>15°). The ANT tether achieved coronal correction, maintained kyphosis, and reduced the axial rotation, but over-correction was simulated at higher initial tensions. This biomechanical study captured the differences between a CV and ANT tether and indicated the variability arising from the patient-specific characteristics. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:254-264, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Effects of isolation on ant assemblages depend on microhabitat

USGS Publications Warehouse

Chen, Xuan; Adams, Benjamin; Layne, Michael; Swarzenski, Christopher M.; Norris, David O.; Hooper-Bui, Linda

2017-01-01

How isolation affects biological communities is a fundamental question in ecology and conservation biology. Local diversity (α) and regional diversity (γ) are consistently lower in insular areas. The pattern of species turnover (β diversity) and the influence of isolation on competitive interactions are less predictable. Differences in communities across microhabitats within an isolated patch could contribute to the variability in patterns related to isolation. Trees form characteristically dense and sparse patches (low vs. high isolation) in floating marshes in coastal Louisiana, and canopy and root areas around these trees could support distinct ant communities. Consequently, trees in floating marshes provide an ideal environment to study the effects of isolation on community assemblages in different microhabitats. We sampled ant communities in 120 trees during the summer of 2016. We found ant α diversity was not different between the canopy and roots, and the magnitude and directional effects of isolation on ants were inconsistent between the canopy and root areas. In the roots of sparse sites, ant diversity (α, β, and γ) was lower, species composition was changed, and the signature of interspecific competition was more prominent compared to dense sites. In the canopy, however, significant differences between dense and sparse sites were only detected in α and γ diversity, and ant species co‐occurrence was not significantly different from a random distribution. The inconsistent responses of ants in canopy and root areas to isolation may be due to the differences of species pool size, environmental harshness, and species interactions between strata. In addition, these findings indicate that communities in distinct microenvironments can respond differentially to habitat isolation. We suggest incorporating organisms from different microhabitats into future research to better understand the influence of isolation on the assembly of biological communities.

Communications and control for electric power systems: Power flow classification for static security assessment

NASA Technical Reports Server (NTRS)

Niebur, D.; Germond, A.

1993-01-01

This report investigates the classification of power system states using an artificial neural network model, Kohonen's self-organizing feature map. The ultimate goal of this classification is to assess power system static security in real-time. Kohonen's self-organizing feature map is an unsupervised neural network which maps N-dimensional input vectors to an array of M neurons. After learning, the synaptic weight vectors exhibit a topological organization which represents the relationship between the vectors of the training set. This learning is unsupervised, which means that the number and size of the classes are not specified beforehand. In the application developed in this report, the input vectors used as the training set are generated by off-line load-flow simulations. The learning algorithm and the results of the organization are discussed.

Social Life in Arid Environments: The Case Study of Cataglyphis Ants.

PubMed

Boulay, Raphaël; Aron, Serge; Cerdá, Xim; Doums, Claudie; Graham, Paul; Hefetz, Abraham; Monnin, Thibaud

2017-01-31

Unlike most desert-dwelling animals, Cataglyphis ants do not attempt to escape the heat; rather, they apply their impressive heat tolerance to avoid competitors and predators. This thermally defined niche has promoted a range of adaptations both at the individual and colony levels. We have also recently discovered that within the genus Cataglyphis there are incredibly diverse social systems, modes of reproduction, and dispersal, prompting the tantalizing question of whether social diversity may also be a consequence of the harsh environment within which we find these charismatic ants. Here we review recent advances regarding the physiological, behavioral, life-history, colony, and ecological characteristics of Cataglyphis and consider perspectives on future research that will build our understanding of organic adaptive responses to desertification.

Case study: Optimizing fault model input parameters using bio-inspired algorithms

NASA Astrophysics Data System (ADS)

Plucar, Jan; Grunt, Onřej; Zelinka, Ivan

2017-07-01

We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.

The Postpharyngeal Gland: Specialized Organ for Lipid Nutrition in Leaf-Cutting Ants

PubMed Central

Decio, Pâmela; Vieira, Alexsandro Santana; Dias, Nathalia Baptista; Palma, Mario Sergio; Bueno, Odair Correa

2016-01-01

There are several hypotheses about the possible functions of the postpharyngeal gland (PPG) in ants. The proposed functions include roles as cephalic or gastric caeca and diverticulum of the digestive tract, mixing of hydrocarbons, nestmate recognition, feeding larvae, and the accumulation of lipids inside this gland, whose origin is contradictory. The current study aimed to investigate the functions of these glands by examining the protein expression profile of the PPGs of Atta sexdens rubropilosa (Hymenoptera, Formicidae). Mated females received lipid supplementation and their glands were extracted and analyzed using a proteomic approach. The protocol used combined two-dimensional electrophoresis and shotgun strategies, followed by mass spectrometry. We also detected lipid β-oxidation by immunofluorescent marking of acyl-CoA dehydrogenase. Supplying ants with lipids elicited responses in the glandular cells of the PPG; these included increased expression of proteins related to defense mechanisms and signal transduction and reorganization of the cytoskeleton due to cell expansion. In addition, some proteins in PPG were overexpressed, especially those involved in lipid and energy metabolism. Part of the lipids may be reduced, used for the synthesis of fatty alcohol, transported to the hemolymph, or may be used as substrate for the synthesis of acetyl-CoA, which is oxidized to form molecules that drive oxidative phosphorylation and produce energy for cellular metabolic processes. These findings suggest that this organ is specialized for lipid nutrition of adult leaf-cutting ants and characterized like a of diverticulum foregut, with the ability to absorb, store, metabolize, and mobilize lipids to the hemolymph. However, we do not rule out that the PPG may have other functions in other species of ants. PMID:27149618

The Postpharyngeal Gland: Specialized Organ for Lipid Nutrition in Leaf-Cutting Ants.

PubMed

Decio, Pâmela; Vieira, Alexsandro Santana; Dias, Nathalia Baptista; Palma, Mario Sergio; Bueno, Odair Correa

2016-01-01

There are several hypotheses about the possible functions of the postpharyngeal gland (PPG) in ants. The proposed functions include roles as cephalic or gastric caeca and diverticulum of the digestive tract, mixing of hydrocarbons, nestmate recognition, feeding larvae, and the accumulation of lipids inside this gland, whose origin is contradictory. The current study aimed to investigate the functions of these glands by examining the protein expression profile of the PPGs of Atta sexdens rubropilosa (Hymenoptera, Formicidae). Mated females received lipid supplementation and their glands were extracted and analyzed using a proteomic approach. The protocol used combined two-dimensional electrophoresis and shotgun strategies, followed by mass spectrometry. We also detected lipid β-oxidation by immunofluorescent marking of acyl-CoA dehydrogenase. Supplying ants with lipids elicited responses in the glandular cells of the PPG; these included increased expression of proteins related to defense mechanisms and signal transduction and reorganization of the cytoskeleton due to cell expansion. In addition, some proteins in PPG were overexpressed, especially those involved in lipid and energy metabolism. Part of the lipids may be reduced, used for the synthesis of fatty alcohol, transported to the hemolymph, or may be used as substrate for the synthesis of acetyl-CoA, which is oxidized to form molecules that drive oxidative phosphorylation and produce energy for cellular metabolic processes. These findings suggest that this organ is specialized for lipid nutrition of adult leaf-cutting ants and characterized like a of diverticulum foregut, with the ability to absorb, store, metabolize, and mobilize lipids to the hemolymph. However, we do not rule out that the PPG may have other functions in other species of ants.

Life-history traits and parasitism rates of four phorid species (Diptera: Phoridae), parasitoids of Atta vollenweideri (Hymenoptera: Formicidae) in Argentina.

PubMed

Guillade, Andrea C; Folgarait, Patricia J

2011-02-01

Leaf-cutting ants in the genus Atta F. (Formicidae, Attini) are among the most important pest arthropods in Central and South America, consuming more vegetation than any other animal group. Among the organisms attacking ants in nature, flies of the family Phoridae have been proposed as the most promising biocontrol agents for pest ants. Four phorid species, Apocephalus setitarsus Brown, Myrmosicarius brandaoi Disney, Myrmosicarius gonzalezae Disney, and Eibesfeldtphora trilobata Disney, were reared from ants collected at Atta vollenweideri Forel nests and off foraging trails in Santa Fe province in Argentina. E. trilobata attacked larger ants and had bigger adults than the other species, also exhibiting the longest developmental time. Correlations between size of hosts and size of adults, as well as between size of adults and developmental times, could be established only in some cases. No differences were found between the sizes of the hosts from which males and females emerged. The natural percentage of parasitism varied throughout the seasons and seemed to be influenced by the extreme drought affecting the study site. We discuss why all four species would be suitable candidates for integrating an assemblage of biocontrol agents against A. vollenweideri.

Ant larvae as players in social conflict: relatedness and individual identity mediate cannibalism intensity.

PubMed

Schultner, Eva; Gardner, Andy; Karhunen, Markku; Helanterä, Heikki

2014-12-01

Conflict arises among social organisms when individuals differ in their inclusive-fitness interests. Ant societies are excellent models for understanding how genetic relatedness mediates conflict intensity. However, although conflicts within colonies typically arise over offspring production, the role of larvae as actors in social conflict has received little attention. We develop and empirically test kin-selection theory of larval egg cannibalism in ant societies. Specifically, we investigate how selection for cannibalism is mediated by nestmate relatedness and larval sex in a mathematical model and then test the model's predictions by measuring cannibalism levels in eight ant species with varying nestmate relatedness. In line with our theoretical predictions, cannibalism levels in larvae were significantly influenced by relatedness and sex. Increased relatedness was associated with reduced levels of cannibalism, indicating that larval behavior is mediated by inclusive-fitness considerations. Levels of cannibalism were significantly higher in male larvae, and our model suggests that this is due to sex differences in the benefits of cannibalism. By examining the selfish interests of larvae and the constraints they face in a social environment, our study presents a novel perspective on conflict in ants and on the evolution of selfish elements in social systems in general.

An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem.

PubMed

Jin, Hui-Dong; Leung, Kwong-Sak; Wong, Man-Leung; Xu, Z B

2003-01-01

As a typical combinatorial optimization problem, the traveling salesman problem (TSP) has attracted extensive research interest. In this paper, we develop a self-organizing map (SOM) with a novel learning rule. It is called the integrated SOM (ISOM) since its learning rule integrates the three learning mechanisms in the SOM literature. Within a single learning step, the excited neuron is first dragged toward the input city, then pushed to the convex hull of the TSP, and finally drawn toward the middle point of its two neighboring neurons. A genetic algorithm is successfully specified to determine the elaborate coordination among the three learning mechanisms as well as the suitable parameter setting. The evolved ISOM (eISOM) is examined on three sets of TSP to demonstrate its power and efficiency. The computation complexity of the eISOM is quadratic, which is comparable to other SOM-like neural networks. Moreover, the eISOM can generate more accurate solutions than several typical approaches for TSP including the SOM developed by Budinich, the expanding SOM, the convex elastic net, and the FLEXMAP algorithm. Though its solution accuracy is not yet comparable to some sophisticated heuristics, the eISOM is one of the most accurate neural networks for the TSP.

Evaluating effects of habitat loss and land-use continuity on ant species richness in seminatural grassland remnants.

PubMed

Dauber, Jens; Bengtsson, Jan; Lenoir, Lisette

2006-08-01

Seminatural grasslands in Europe are susceptible to habitat destruction and fragmentation that result in negative effects on biodiversity because of increased isolation and area effects on extinction rate. However even small habitatpatches of seminatural grasslands might be of value for conservation and restoration of species richness in a landscape with a long history of management, which has been argued to lead to high species richness. We tested whether ant communities have been negatively affected by habitat loss and increased isolation of seminatural grasslands during the twentieth century. We examined species richness and community composition in seminatural grasslands of different size in a mosaic landscape in Central Sweden. Grasslands managed continuously over centuries harbored species-rich and ecologically diverse ant communities. Grassland remnant size had no effect on ant species richness. Small grassland remnants did not harbor a nested subset of the ant species of larger habitats. Community composition of ants was mainly affected by habitat conditions. Our results suggest that the abandonment of traditional land use and the encroachment of trees, rather than the effects of fragmentation, are important for species composition in seminatural grasslands. Our results highlight the importance of considering land-use continuity and dispersal ability of thefocal organisms when examining the effects of habitat loss and fragmentation on biodiversity. Landscape history should be considered in conservation programs focusing on effects of land-use change.

Walking like an ant: a quantitative and experimental approach to understanding locomotor mimicry in the jumping spider Myrmarachne formicaria

PubMed Central

Hoy, Ron R.; Cohen, Itai; Beatus, Tsevi

2017-01-01

Protective mimicry, in which a palatable species avoids predation by being mistaken for an unpalatable model, is a remarkable example of adaptive evolution. These complex interactions between mimics, models and predators can explain similarities between organisms beyond the often-mechanistic constraints typically invoked in studies of convergent evolution. However, quantitative studies of protective mimicry typically focus on static traits (e.g. colour and shape) rather than on dynamic traits like locomotion. Here, we use high-speed cameras and behavioural experiments to investigate the role of locomotor behaviour in mimicry by the ant-mimicking jumping spider Myrmarachne formicaria, comparing its movement to that of ants and non-mimicking spiders. Contrary to previous suggestions, we find mimics walk using all eight legs, raising their forelegs like ant antennae only when stationary. Mimics exhibited winding trajectories (typical wavelength = 5–10 body lengths), which resemble the winding patterns of ants specifically engaged in pheromone-trail following, although mimics walked on chemically inert surfaces. Mimics also make characteristically short (approx. 100 ms) pauses. Our analysis suggests that this makes mimics appear ant-like to observers with slow visual systems. Finally, behavioural experiments with predatory spiders yield results consistent with the protective mimicry hypothesis. These findings highlight the importance of dynamic behaviours and observer perception in mimicry. PMID:28701553

HelpfulMed: Intelligent Searching for Medical Information over the Internet.

ERIC Educational Resources Information Center

Chen, Hsinchun; Lally, Ann M.; Zhu, Bin; Chau, Michael

2003-01-01

Discussion of the information needs of medical professionals and researchers focuses on the architecture of a Web portal designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, and self-organizing map technologies to provide searchers with fine-grained results. Reports results of evaluation of spider algorithms…

Escalated convergent artificial bee colony

NASA Astrophysics Data System (ADS)

Jadon, Shimpi Singh; Bansal, Jagdish Chand; Tiwari, Ritu

2016-03-01

Artificial bee colony (ABC) optimisation algorithm is a recent, fast and easy-to-implement population-based meta heuristic for optimisation. ABC has been proved a rival algorithm with some popular swarm intelligence-based algorithms such as particle swarm optimisation, firefly algorithm and ant colony optimisation. The solution search equation of ABC is influenced by a random quantity which helps its search process in exploration at the cost of exploitation. In order to find a fast convergent behaviour of ABC while exploitation capability is maintained, in this paper basic ABC is modified in two ways. First, to improve exploitation capability, two local search strategies, namely classical unidimensional local search and levy flight random walk-based local search are incorporated with ABC. Furthermore, a new solution search strategy, namely stochastic diffusion scout search is proposed and incorporated into the scout bee phase to provide more chance to abandon solution to improve itself. Efficiency of the proposed algorithm is tested on 20 benchmark test functions of different complexities and characteristics. Results are very promising and they prove it to be a competitive algorithm in the field of swarm intelligence-based algorithms.

Next Generation System and Software Architectures: Challenges from Future NASA Exploration Missions

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Rouff, Christopher A.; Hinchey, Michael G.; Rash, James L.; Truszkowski, Walt

2006-01-01

The four key objective properties of a system that are required of it in order for it to qualify as "autonomic" are now well-accepted-self-configuring, self-healing, self-protecting, and self-optimizing- together with the attribute properties-viz. self-aware, environment-aware, self-monitoring and self- adjusting. This paper describes the need for next generation system software architectures, where components are agents, rather than objects masquerading as agents, and where support is provided for self-* properties (both existing self-chop and emerging self-* properties). These are discussed as exhibited in NASA missions, and in particular with reference to a NASA concept mission, ANTS, which is illustrative of future NASA exploration missions based on the technology of intelligent swarms.

From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers.

PubMed

Nakrani, Sunil; Tovey, Craig

2007-12-01

An Internet hosting center hosts services on its server ensemble. The center must allocate servers dynamically amongst services to maximize revenue earned from hosting fees. The finite server ensemble, unpredictable request arrival behavior and server reallocation cost make server allocation optimization difficult. Server allocation closely resembles honeybee forager allocation amongst flower patches to optimize nectar influx. The resemblance inspires a honeybee biomimetic algorithm. This paper describes details of the honeybee self-organizing model in terms of information flow and feedback, analyzes the homology between the two problems and derives the resulting biomimetic algorithm for hosting centers. The algorithm is assessed for effectiveness and adaptiveness by comparative testing against benchmark and conventional algorithms. Computational results indicate that the new algorithm is highly adaptive to widely varying external environments and quite competitive against benchmark assessment algorithms. Other swarm intelligence applications are briefly surveyed, and some general speculations are offered regarding their various degrees of success.

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

Time optimized path-choice in the termite hunting ant Megaponera analis.

PubMed

Frank, Erik T; Hönle, Philipp O; Linsenmair, K Eduard

2018-05-10

Trail network systems among ants have received a lot of scientific attention due to their various applications in problem solving of networks. Recent studies have shown that ants select the fastest available path when facing different velocities on different substrates, rather than the shortest distance. The progress of decision-making by these ants is determined by pheromone-based maintenance of paths, which is a collective decision. However, path optimization through individual decision-making remains mostly unexplored. Here we present the first study of time-optimized path selection via individual decision-making by scout ants. Megaponera analis scouts search for termite foraging sites and lead highly organized raid columns to them. The path of the scout determines the path of the column. Through installation of artificial roads around M. analis nests we were able to influence the pathway choice of the raids. After road installation 59% of all recorded raids took place completely or partly on the road, instead of the direct, i.e. distance-optimized, path through grass from the nest to the termites. The raid velocity on the road was more than double the grass velocity, the detour thus saved 34.77±23.01% of the travel time compared to a hypothetical direct path. The pathway choice of the ants was similar to a mathematical model of least time allowing us to hypothesize the underlying mechanisms regulating the behavior. Our results highlight the importance of individual decision-making in the foraging behavior of ants and show a new procedure of pathway optimization. © 2018. Published by The Company of Biologists Ltd.

A Unique Human Chorionic Gonadotropin Antagonist Suppresses Ovarian Hyperstimulation Syndrome in Rats

PubMed Central

Vardhana, Pratibhasri A.; Julius, Martin A.; Pollak, Susan V.; Lustbader, Evan G.; Trousdale, Rhonda K.; Lustbader, Joyce W.

2009-01-01

Ovarian hyperstimulation syndrome (OHSS) is a complication of in vitro fertilization associated with physiological changes after hCG administration to induce final oocyte maturation. It presents as widespread increases in vascular permeability and, in rare cases, results in cycle cancellation, multi-organ dysfunction, and pregnancy termination. These physiological changes are due primarily to activation of the vascular endothelial growth factor (VEGF) system in response to exogenous human chorionic gonadotropin (hCG). An hCG antagonist (hCG-Ant) could attenuate these effects by competitively binding to the LH/CG receptor, thereby blocking LH activity in vivo. We expressed a form of hCG that lacks three of its four N-linked glycosylation sites and tested its efficacy as an antagonist. The hCG-Ant binds the LH receptor with an affinity similar to native hCG and inhibits cAMP response in vitro. In a rat model for ovarian stimulation, hCG-Ant dramatically reduces ovulation and steroid hormone production. In a well-established rat OHSS model, vascular permeability and vascular endothelial growth factor (VEGF) expression are dramatically reduced after hCG-Ant treatment. Finally, hCG-Ant does not appear to alter blastocyst development when given after hCG in mice. These studies demonstrate that removing specific glycosylation sites on native hCG can produce an hCG-Ant that is capable of binding without activating the LH receptor and blocking the actions of hCG. Thus hCG-Ant will be investigated as a potential therapy for OHSS. PMID:19443574

Leucoagaricus gongylophorus Produces Diverse Enzymes for the Degradation of Recalcitrant Plant Polymers in Leaf-Cutter Ant Fungus Gardens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aylward, Frank O.; Burnum-Johnson, Kristin E.; Tringe, Susannah G.

Plants represent a large reservoir of organic carbon comprised largely of recalcitrant polymers that most metazoans are unable to deconstruct. Many herbivores gain access to nutrients in this material indirectly by associating with microbial symbionts, and leaf-cutter ants are a paradigmatic example. These ants use fresh foliar biomass as manure to cultivate fungus gardens composed primarily of Leucoagaricus gongylophorus, a basidiomycetous symbiont that produces specialized hyphal swellings that serve as a food source for the host ant colony. Although leaf-cutter ants are conspicuous herbivores that contribute substantially to carbon turnover in Neotropical ecosystems, the process through which plant biomass ismore » degraded in their fungus gardens is not well understood. Here we present the first draft genome of L. gongylophorus, and using genomic, metaproteomic, and phylogenetic tools we investigate its role in lignocellulose degradation in the fungus gardens of both Atta cephalotes and Acromyrmex echinatior leaf-cutter ants. We show that L. gongylophorus produces a diversity of lignocellulases in fungus gardens, and is likely the primary driver of plant biomass degradation in these ecosystems. We also show that this fungus produces distinct sets of lignocellulases throughout the different stages of biomass degradation, including numerous cellulases and laccases that may be playing an important but previously uncharacterized role in lignocellulose degradation. Our study provides a comprehensive analysis of plant biomass degradation in leaf-cutter ant fungus gardens and provides insight into the molecular dynamics underlying the symbiosis between these dominant herbivores and their obligate fungal cultivar.« less

Differential evolution-simulated annealing for multiple sequence alignment

NASA Astrophysics Data System (ADS)

Addawe, R. C.; Addawe, J. M.; Sueño, M. R. K.; Magadia, J. C.

2017-10-01

Multiple sequence alignments (MSA) are used in the analysis of molecular evolution and sequence structure relationships. In this paper, a hybrid algorithm, Differential Evolution - Simulated Annealing (DESA) is applied in optimizing multiple sequence alignments (MSAs) based on structural information, non-gaps percentage and totally conserved columns. DESA is a robust algorithm characterized by self-organization, mutation, crossover, and SA-like selection scheme of the strategy parameters. Here, the MSA problem is treated as a multi-objective optimization problem of the hybrid evolutionary algorithm, DESA. Thus, we name the algorithm as DESA-MSA. Simulated sequences and alignments were generated to evaluate the accuracy and efficiency of DESA-MSA using different indel sizes, sequence lengths, deletion rates and insertion rates. The proposed hybrid algorithm obtained acceptable solutions particularly for the MSA problem evaluated based on the three objectives.

Self-organization of intertidal snails facilitates evolution of aggregation behavior.

PubMed

Stafford, Richard; Davies, Mark S; Williams, Gray A

2008-01-01

Many intertidal snails form aggregations during emersion to minimize desiccation stress. Here we investigate possible mechanisms for the evolution of such behavior. Two behavioral traits (following of mucus trails, and crevice occupation), which both provide selective advantages to individuals that possess the traits over individuals that do not, result in self-organization of aggregations in crevices in the rock surface. We suggest that the existence of self-organizing aggregations provides a mechanism by which aggregation behavior can evolve. The inclusion of an explicitly coded third behavior, aggregation, in a simulated population produces patterns statistically similar to those found on real rocky shores. Allowing these three behaviors to evolve using an evolutionary algorithm, however, results in aggregation behavior being selected against on shores with high crevice density. The inclusion of broadcast spawning dispersal mechanisms in the simulation, however, results in aggregation behavior evolving as predicted on shores with both high crevice density and low crevice density (evolving in crevices first, and then both in crevices and on flat rock), indicating the importance of environmental interactions in understanding evolutionary processes. We propose that self-organization can be an important factor in the evolution of group behaviors.

Using ant colony optimization on the quadratic assignment problem to achieve low energy cost in geo-distributed data centers

NASA Astrophysics Data System (ADS)

Osei, Richard

There are many problems associated with operating a data center. Some of these problems include data security, system performance, increasing infrastructure complexity, increasing storage utilization, keeping up with data growth, and increasing energy costs. Energy cost differs by location, and at most locations fluctuates over time. The rising cost of energy makes it harder for data centers to function properly and provide a good quality of service. With reduced energy cost, data centers will have longer lasting servers/equipment, higher availability of resources, better quality of service, a greener environment, and reduced service and software costs for consumers. Some of the ways that data centers have tried to using to reduce energy costs include dynamically switching on and off servers based on the number of users and some predefined conditions, the use of environmental monitoring sensors, and the use of dynamic voltage and frequency scaling (DVFS), which enables processors to run at different combinations of frequencies with voltages to reduce energy cost. This thesis presents another method by which energy cost at data centers could be reduced. This method involves the use of Ant Colony Optimization (ACO) on a Quadratic Assignment Problem (QAP) in assigning user request to servers in geo-distributed data centers. In this paper, an effort to reduce data center energy cost involves the use of front portals, which handle users' requests, were used as ants to find cost effective ways to assign users requests to a server in heterogeneous geo-distributed data centers. The simulation results indicate that the ACO for Optimal Server Activation and Task Placement algorithm reduces energy cost on a small and large number of users' requests in a geo-distributed data center and its performance increases as the input data grows. In a simulation with 3 geo-distributed data centers, and user's resource request ranging from 25,000 to 25,000,000, the ACO algorithm was able to reduce energy cost on an average of $.70 per second. The ACO for Optimal Server Activation and Task Placement algorithm has proven to work as an alternative or improvement in reducing energy cost in geo-distributed data centers.

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

PubMed

Rubenstein, Michael; Sai, Ying; Chuong, Cheng-Ming; Shen, Wei-Min

2009-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

Broadband external cavity quantum cascade laser based sensor for gasoline detection

NASA Astrophysics Data System (ADS)

Ding, Junya; He, Tianbo; Zhou, Sheng; Li, Jinsong

2018-02-01

A new type of tunable diode spectroscopy sensor based on an external cavity quantum cascade laser (ECQCL) and a quartz crystal tuning fork (QCTF) were used for quantitative analysis of volatile organic compounds. In this work, the sensor system had been tested on different gasoline sample analysis. For signal processing, the self-established interpolation algorithm and multiple linear regression algorithm model were used for quantitative analysis of major volatile organic compounds in gasoline samples. The results were very consistent with that of the standard spectra taken from the Pacific Northwest National Laboratory (PNNL) database. In future, The ECQCL sensor will be used for trace explosive, chemical warfare agent, and toxic industrial chemical detection and spectroscopic analysis, etc.

Prevalence and Associated Risk Factors of Asymptomatic Bacteriuria in Ante-Natal Clients in a Large Teaching Hospital in Ghana.

PubMed

Labi, A-K; Yawson, A E; Ganyaglo, G Y; Newman, M J

2015-09-01

Asymptomatic bacteriuria, the presence of bacteria in urine without symptoms of acute urinary tract infection, predisposes pregnant women to the development of urinary tract infections and pyelonephritis, with an attendant pregnancy related complications. To measure the prevalence of asymptomatic bacteriuria among ante-natal clients at the Korle-Bu Teaching Hospital in Ghana and its' associated risk factors. A cross-sectional study involving 274 antenatal clients was conducted over a period of 4 weeks. A face to face questionnaire was completed and midstream urine collected for culture and antimicrobial susceptibility testing. The prevalence of asymptomatic bacteriuria was 5.5%. It was associated with sexual activity during pregnancy (Fisher's Exact 5.871, p-value 0.0135), but not with sexual frequency. There were no significant associations with educational status, parity, gestational age, marital status and the number of foetuses carried. The commonest organism isolated was Enterococcus spp (26.7%) although the enterobacteriaceae formed the majority of isolated organisms (46.7%). Nitrofurantoin was the antibiotic with the highest sensitivity to all the isolated organisms. The prevalence of asymptomatic bacteriuria among ante-natal clients at this large teaching hospital in Ghana is 5.5%, which is lower than what has been found in other African settings. Enterococcus spp was the commonest causative organism. However, due to the complications associated with asymptomatic bacteriuria, a policy to screen and treat- all pregnant women attending the hospital, is worth considering.

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

Convergence in Multispecies Interactions.

PubMed

Bittleston, Leonora S; Pierce, Naomi E; Ellison, Aaron M; Pringle, Anne

2016-04-01

The concepts of convergent evolution and community convergence highlight how selective pressures can shape unrelated organisms or communities in similar ways. We propose a related concept, convergent interactions, to describe the independent evolution of multispecies interactions with similar physiological or ecological functions. A focus on convergent interactions clarifies how natural selection repeatedly favors particular kinds of associations among species. Characterizing convergent interactions in a comparative context is likely to facilitate prediction of the ecological roles of organisms (including microbes) in multispecies interactions and selective pressures acting in poorly understood or newly discovered multispecies systems. We illustrate the concept of convergent interactions with examples: vertebrates and their gut bacteria; ectomycorrhizae; insect-fungal-bacterial interactions; pitcher-plant food webs; and ants and ant-plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID

PubMed Central

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-01-01

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm–neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS. PMID:29671822

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

PubMed

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-04-19

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

Multiple-hopping trajectories near a rotating asteroid

NASA Astrophysics Data System (ADS)

Shen, Hong-Xin; Zhang, Tian-Jiao; Li, Zhao; Li, Heng-Nian

2017-03-01

We present a study of the transfer orbits connecting landing points of irregular-shaped asteroids. The landing points do not touch the surface of the asteroids and are chosen several meters above the surface. The ant colony optimization technique is used to calculate the multiple-hopping trajectories near an arbitrary irregular asteroid. This new method has three steps which are as follows: (1) the search of the maximal clique of candidate target landing points; (2) leg optimization connecting all landing point pairs; and (3) the hopping sequence optimization. In particular this method is applied to asteroids 433 Eros and 216 Kleopatra. We impose a critical constraint on the target landing points to allow for extensive exploration of the asteroid: the relative distance between all the arrived target positions should be larger than a minimum allowed value. Ant colony optimization is applied to find the set and sequence of targets, and the differential evolution algorithm is used to solve for the hopping orbits. The minimum-velocity increment tours of hopping trajectories connecting all the landing positions are obtained by ant colony optimization. The results from different size asteroids indicate that the cost of the minimum velocity-increment tour depends on the size of the asteroids.

Ant Navigation: Fractional Use of the Home Vector

PubMed Central

Cheung, Allen; Hiby, Lex; Narendra, Ajay

2012-01-01

Home is a special location for many animals, offering shelter from the elements, protection from predation, and a common place for gathering of the same species. Not surprisingly, many species have evolved efficient, robust homing strategies, which are used as part of each and every foraging journey. A basic strategy used by most animals is to take the shortest possible route home by accruing the net distances and directions travelled during foraging, a strategy well known as path integration. This strategy is part of the navigation toolbox of ants occupying different landscapes. However, when there is a visual discrepancy between test and training conditions, the distance travelled by animals relying on the path integrator varies dramatically between species: from 90% of the home vector to an absolute distance of only 50 cm. We here ask what the theoretically optimal balance between PI-driven and landmark-driven navigation should be. In combination with well-established results from optimal search theory, we show analytically that this fractional use of the home vector is an optimal homing strategy under a variety of circumstances. Assuming there is a familiar route that an ant recognizes, theoretically optimal search should always begin at some fraction of the home vector, depending on the region of familiarity. These results are shown to be largely independent of the search algorithm used. Ant species from different habitats appear to have optimized their navigation strategy based on the availability and nature of navigational information content in their environment. PMID:23209744

The "olfactory mirror" and other recent attempts to demonstrate self-recognition in non-primate species.

PubMed

Gallup, Gordon G; Anderson, James R

2018-03-01

The recent attempt by Horowitz (2017) to develop an "olfactory mirror" test of self-recognition in domestic dogs raises some important questions about the kinds of data that are required to provide definitive evidence for self-recognition in dogs and other species. We conclude that the "olfactory mirror" constitutes a compelling analog to the mark test for mirror self-recognition in primates, but despite claims to the contrary neither dogs, elephants, dolphins, magpies, horses, manta rays, squid, nor ants have shown compelling, reproducible evidence for self-recognition in any modality. Copyright © 2017 Elsevier B.V. All rights reserved.

From Present Surveying to Future Prospecting of the Asteroid Belt

NASA Technical Reports Server (NTRS)

Clark, P. E.; Curtis, S. A.; Rilee, M.; Cheung, C.

2004-01-01

We have applied a future mission architecture, the Autonomous Nano-Technology Swarm (ANTS), to a proposed mission for in situ survey, or prospecting, of the asteroid belt, the Prospecting Asteroid Mission (PAM) as part of a NASA 2003 Revolutionary Aerospace Concept (RASC) study. ANTS architecture builds on and advances recent trends in robotics, artificial intelligence, and materials processing to minimize costs and maximize effectiveness of space operations. PAM and other applications have been proposed for the survey of inaccessible, high surface area populations of great interest from the standpoint of resources and/or solar system origin. The ANTS architecture is inspired by the success of social insect colonies, a success based on the division of labor within the colonies in two key ways: 1) within their specialties, individual specialists generally outperform generalists, and 2) with sufficiently efficient social interaction and coordination, the group of specialists generally outperforms the group of generalists. Thus systems designed as ANTS are built from potentially very large numbers of highly autonomous, yet socially interactive, elements. The architecture is self-similar in that elements and sub-elements of the system may also be recursively structured as ANTS on scales ranging from microscopic to interplanetary distances. Here, we analyze requirements for the mission application at the low gravity target end of the spectrum, the Prospecting Asteroid Mission (PAM), and for specialized autonomous operations which would support this mission. ANTS as applied to PAM involves the activities of hundreds of individual specialist 'sciencecraft'. Most of them, called Workers, carry and operate eight to nine different scientific instruments, as listed in the table, including spectrometers, ranging and radio science devices, and imagers. The remaining specialists, Messenger/Rulers, provide communication and coordination functions among specialists operating autonomously as individuals, team members, and subswarms.

Self-organized topology of recurrence-based complex networks

NASA Astrophysics Data System (ADS)

Yang, Hui; Liu, Gang

2013-12-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

Self-organized topology of recurrence-based complex networks.

PubMed

Yang, Hui; Liu, Gang

2013-12-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

Self-organized topology of recurrence-based complex networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Hui, E-mail: huiyang@usf.edu; Liu, Gang

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article ismore » to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.« less

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology

PubMed Central

RUBENSTEIN, MICHAEL; SAI, YING; CHUONG, CHENG-MING; SHEN, WEI-MIN

2010-01-01

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. “Self” here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering. PMID:19557691

Mitigating clogging and arrest in confined self-propelled systems

NASA Astrophysics Data System (ADS)

Savoie, William; Aguilar, Jeffrey; Monaenkova, Daria; Linevich, Vadim; Goldman, Daniel

Ensembles of self-propelling elements, like colloidal surfers, bacterial biofilms, and robot swarms can spontaneously form density heterogeneities. To understand how to prevent potentially catastrophic clogs in task-oriented active matter systems (like soil excavating robots), we present a robophysical study of excavation of granular media in a confined environment. We probe the efficacy of two social strategies observed in our studies of fire ants (S. invicta). The first behavior (denoted as unequal workload) prescribes to each excavator a different probability to enter the digging area. The second behavior (denoted as reversal\\x9D), is characterized by a probability to forfeit excavation when progress is sufficiently obstructed. For equal workload distribution and no reversal behavior, clogs at the digging site prevent excavation for sufficient numbers of robots. Measurements of aggregation relaxation times reveal how the strategies mitigate clogs. The unequal workload behavior reduces the tunnel density, decreasing the probability of clog formation. Reversal behavior, while allowing clogs to form, reduces aggregation relaxation time. We posit that application of social behaviors can be useful for swarm robot systems where global control and organization may not be possible.

Dysphonia Detected by Pattern Recognition of Spectral Composition.

ERIC Educational Resources Information Center

Leinonen, Lea; And Others

1992-01-01

This study analyzed production of a long vowel sound within Finnish words by normal or dysphonic voices, using the Self-Organizing Map, the artificial neural network algorithm of T. Kohonen which produces two-dimensional representations of speech. The method was found to be both sensitive and specific in the detection of dysphonia. (Author/JDD)

Paternal engagement during childbirth depending on the manner of their preparation.

PubMed

Sioma-Markowska, Urszula; Poręba, Ryszard; Machura, Mariola; Skrzypulec-Plinta, Violetta

2016-01-01

The analysis of the forms of paternal activity depending on the manner of their preparation, including stages of labor. A prospective survey-based study involved 250 fathers who participated in their child's birth. The fathers included in the study were present during all stages of family-assisted natural labor. The study was conducted one day after childbirth with the use of a survey prepared by the authors. Statistical calculations were conducted using the Statistica PL software. The frequency of individual qualitative features (non-measurable) was assessed by means of a non-parametric χ² (chi-squared) test. The statistical significance level was p < 0.05. A half of the fathers included in the study (52.4%) participated in childbirth with no prior preparation. The dominant form of preparation involved self-education from books, magazines and the Internet (24%). 23.6% of fathers participated in ante-natal classes. The study demonstrated that fathers prepared for childbirth in ante-natal classes more often engaged in the supportive role, provided nursing care and carried out instrumental monitoring during each stage of childbirth. The fathers prepared for childbirth in ante-natal classes more often engage in the supportive role, provide nursing care and carry out instrumental control during each stage of childbirth. Ante-natal classes should be promoted as an optimal form of preparation for active participation in childbirth. Moreover, other forms of paternal ante-natal education as well as continued education in a delivery room should be developed.

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Self-organized modularization in evolutionary algorithms.

PubMed

Dauscher, Peter; Uthmann, Thomas

2005-01-01

The principle of modularization has proven to be extremely successful in the field of technical applications and particularly for Software Engineering purposes. The question to be answered within the present article is whether mechanisms can also be identified within the framework of Evolutionary Computation that cause a modularization of solutions. We will concentrate on processes, where modularization results only from the typical evolutionary operators, i.e. selection and variation by recombination and mutation (and not, e.g., from special modularization operators). This is what we call Self-Organized Modularization. Based on a combination of two formalizations by Radcliffe and Altenberg, some quantitative measures of modularity are introduced. Particularly, we distinguish Built-in Modularity as an inherent property of a genotype and Effective Modularity, which depends on the rest of the population. These measures can easily be applied to a wide range of present Evolutionary Computation models. It will be shown, both theoretically and by simulation, that under certain conditions, Effective Modularity (as defined within this paper) can be a selection factor. This causes Self-Organized Modularization to take place. The experimental observations emphasize the importance of Effective Modularity in comparison with Built-in Modularity. Although the experimental results have been obtained using a minimalist toy model, they can lead to a number of consequences for existing models as well as for future approaches. Furthermore, the results suggest a complex self-amplification of highly modular equivalence classes in the case of respected relations. Since the well-known Holland schemata are just the equivalence classes of respected relations in most Simple Genetic Algorithms, this observation emphasizes the role of schemata as Building Blocks (in comparison with arbitrary subsets of the search space).

The draft genome of a termite illuminates alternative social organization

USDA-ARS?s Scientific Manuscript database

Termites have substantial economic and ecological impact worldwide. They are also the oldest organisms living in complex societies, having evolved a caste system independent of that of eusocial Hymenoptera (ants, bees and wasps). Here we provide the first genome sequence for a termite, Zootermopsis ...

An imperialist competitive algorithm for virtual machine placement in cloud computing

NASA Astrophysics Data System (ADS)

Jamali, Shahram; Malektaji, Sepideh; Analoui, Morteza

2017-05-01

Cloud computing, the recently emerged revolution in IT industry, is empowered by virtualisation technology. In this paradigm, the user's applications run over some virtual machines (VMs). The process of selecting proper physical machines to host these virtual machines is called virtual machine placement. It plays an important role on resource utilisation and power efficiency of cloud computing environment. In this paper, we propose an imperialist competitive-based algorithm for the virtual machine placement problem called ICA-VMPLC. The base optimisation algorithm is chosen to be ICA because of its ease in neighbourhood movement, good convergence rate and suitable terminology. The proposed algorithm investigates search space in a unique manner to efficiently obtain optimal placement solution that simultaneously minimises power consumption and total resource wastage. Its final solution performance is compared with several existing methods such as grouping genetic and ant colony-based algorithms as well as bin packing heuristic. The simulation results show that the proposed method is superior to other tested algorithms in terms of power consumption, resource wastage, CPU usage efficiency and memory usage efficiency.

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

PubMed

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

Parsing the life-shortening effects of dietary protein: effects of individual amino acids

PubMed Central

Bouchebti, Sofia; Bazazi, Sepideh; Le Hesran, Sophie; Puga, Camille; Latil, Gérard; Simpson, Stephen J.

2017-01-01

High-protein diets shorten lifespan in many organisms. Is it because protein digestion is energetically costly or because the final products (the amino acids) are harmful? To answer this question while circumventing the life-history trade-off between reproduction and longevity, we fed sterile ant workers on diets based on whole proteins or free amino acids. We found that (i) free amino acids shortened lifespan even more than proteins; (ii) the higher the amino acid-to-carbohydrate ratio, the shorter ants lived and the lower their lipid reserves; (iii) for the same amino acid-to-carbohydrate ratio, ants eating free amino acids had more lipid reserves than those eating whole proteins; and (iv) on whole protein diets, ants seem to regulate food intake by prioritizing sugar, while on free amino acid diets, they seem to prioritize amino acids. To test the effect of the amino acid profile, we tested diets containing proportions of each amino acid that matched the ant's exome; surprisingly, longevity was unaffected by this change. We further tested diets with all amino acids under-represented except one, finding that methionine, serine, threonine and phenylalanine are especially harmful. All together, our results show certain amino acids are key elements behind the high-protein diet reduction in lifespan. PMID:28053059

Parsing the life-shortening effects of dietary protein: effects of individual amino acids.

PubMed

Arganda, Sara; Bouchebti, Sofia; Bazazi, Sepideh; Le Hesran, Sophie; Puga, Camille; Latil, Gérard; Simpson, Stephen J; Dussutour, Audrey

2017-01-11

High-protein diets shorten lifespan in many organisms. Is it because protein digestion is energetically costly or because the final products (the amino acids) are harmful? To answer this question while circumventing the life-history trade-off between reproduction and longevity, we fed sterile ant workers on diets based on whole proteins or free amino acids. We found that (i) free amino acids shortened lifespan even more than proteins; (ii) the higher the amino acid-to-carbohydrate ratio, the shorter ants lived and the lower their lipid reserves; (iii) for the same amino acid-to-carbohydrate ratio, ants eating free amino acids had more lipid reserves than those eating whole proteins; and (iv) on whole protein diets, ants seem to regulate food intake by prioritizing sugar, while on free amino acid diets, they seem to prioritize amino acids. To test the effect of the amino acid profile, we tested diets containing proportions of each amino acid that matched the ant's exome; surprisingly, longevity was unaffected by this change. We further tested diets with all amino acids under-represented except one, finding that methionine, serine, threonine and phenylalanine are especially harmful. All together, our results show certain amino acids are key elements behind the high-protein diet reduction in lifespan. © 2017 The Author(s).

Intronic sequences are required for AINTEGUMENTA-LIKE6 expression in Arabidopsis flowers.

PubMed

Krizek, Beth A

2015-10-12

The AINTEGUMENTA-LIKE6/PLETHORA3 (AIL6/PLT3) gene of Arabidopsis thaliana is a key regulator of growth and patterning in both shoots and roots. AIL6 encodes an AINTEGUMENTA-LIKE/PLETHORA (AIL/PLT) transcription factor that is expressed in the root stem cell niche, the peripheral region of the shoot apical meristem and young lateral organ primordia. In flowers, AIL6 acts redundantly with AINTEGUMENTA (ANT) to regulate floral organ positioning, growth, identity and patterning. Experiments were undertaken to define the genomic regions required for AIL6 function and expression in flowers. Transgenic plants expressing a copy of the coding region of AIL6 in the context of 7.7 kb of 5' sequence and 919 bp of 3' sequence (AIL6:cAIL6-3') fail to fully complement AIL6 function when assayed in the ant-4 ail6-2 double mutant background. In contrast, a genomic copy of AIL6 with the same amount of 5' and 3' sequence (AIL6:gAIL6-3') can fully complement ant-4 ail6-2. In addition, a genomic copy of AIL6 with 590 bp of 5' sequence and 919 bp of 3' sequence (AIL6m:gAIL6-3') complements ant-4 ail6-2 and contains all regulatory elements needed to confer normal AIL6 expression in inflorescences. Efforts to map cis-regulatory elements reveal that the third intron of AIL6 contains enhancer elements that confer expression in young flowers but in a broader pattern than that of AIL6 mRNA in wild-type flowers. Some AIL6:gAIL6-3' and AIL6m:gAIL6-3' lines confer an over-rescue phenotype in the ant-4 ail6-2 background that is correlated with higher levels of AIL6 mRNA accumulation. The results presented here indicate that AIL6 intronic sequences serve as transcriptional enhancer elements. In addition, the results show that increased expression of AIL6 can partially compensate for loss of ANT function in flowers.

Effects of phenyllactic acid on growth performance, intestinal microbiota, relative organ weight, blood characteristics, and meat quality of broiler chicks.

PubMed

Wang, J P; Lee, J H; Yoo, J S; Cho, J H; Kim, H J; Kim, I H

2010-07-01

This study was conducted to determine the effects of dietary supplementation with phenyllactic acid (PLA) on growth performance, intestinal microbiota, relative organ weight, blood characteristics, and meat quality in broilers. A total of 500 male broilers (BW = 46.3 g) were randomly allotted into 1 of the following 5 dietary treatments: 1) basal diet (CON), 2) basal diet + 44 mg/kg of avilamycin (ANT), 3) basal diet + 0.2% PLA (PLA0.2), 4) basal diet + 0.4% PLA (PLA0.4), 5) basal diet + 0.2% PLA + 44 mg/kg of avilamycin (PA). Chicks fed PLA had lower feed intake (FI) from d 0 to 7 (P < 0.05) than those fed CON and ANT. From d 21 to 35, BW gain was greater in ANT, PLA0.4, and PA diets than CON and PLA0.2 diets (P < 0.05), whereas the FI was lowest in the PLA0.4 diet. Feed efficiency was depressed (P < 0.05) by the antibiotics and PLA supplementation during d 0 to 7, whereas it was improved (P < 0.05) in the PLA and ANT diets during d 21 to 35, with the best value in PLA0.4.The population of Escherichia coli in the large intestine was lower in the ANT, PLA0.4, and PA groups than the CON and PLA0.2 groups (P < 0.05). The relative weights of gizzard, liver, spleen, bursa of Fabricius, breast, and abdominal fat were unaffected by any of the dietary supplementations. Treatment of PLA led to an increase (P < 0.05) in the concentrations of white blood cells and lymphocyte percentage. The yellowness of breast muscle decreased by ANT, PLA0.4, and PA treatment. In conclusion, PLA can improve growth performance when it is supplemented in finisher diet (d 21 to 35), whereas it can depress BW gain and FI in earlier days (d 0 to 7). In addition, PLA can also decrease the number of E. coli in the large intestine and improve the number of immune-related blood cells.

Overcoming PCR Inhibition During DNA-Based Gut Content Analysis of Ants.

PubMed

Penn, Hannah J; Chapman, Eric G; Harwood, James D

2016-10-01

Generalist predators play an important role in many terrestrial systems, especially within agricultural settings, and ants (Hymenoptera: Formicidae) often constitute important linkages of these food webs, as they are abundant and influential in these ecosystems. Molecular gut content analysis provides a means of delineating food web linkages of ants based on the presence of prey DNA within their guts. Although this method can provide insight, its use on ants has been limited, potentially due to inhibition when amplifying gut content DNA. We designed a series of experiments to determine those ant organs responsible for inhibition and identified variation in inhibition among three species (Tetramorium caespitum (L.), Solenopsis invicta Buren, and Camponotus floridanus (Buckley)). No body segment, other than the gaster, caused significant inhibition. Following dissection, we determined that within the gaster, the digestive tract and crop cause significant levels of inhibition. We found significant differences in the frequency of inhibition between the three species tested, with inhibition most evident in T. caespitum The most effective method to prevent inhibition before DNA extraction was to exude crop contents and crop structures onto UV-sterilized tissue. However, if extracted samples exhibit inhibition, addition of bovine serum albumin to PCR reagents will overcome this problem. These methods will circumvent gut content inhibition within selected species of ants, thereby allowing more detailed and reliable studies of ant food webs. As little is known about the prevalence of this inhibition in other species, it is recommended that the protocols in this study are used until otherwise shown to be unnecessary. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Association Between Sluggish Cognitive Tempo Symptoms and Attentional Network and Working Memory in Primary Schoolchildren.

PubMed

Camprodon-Rosanas, E; Ribas-Fitó, N; Batlle, S; Persavento, C; Alvarez-Pedrerol, M; Sunyer, J; Forns, J

2017-04-01

Few consistent data are available in relation to the cognitive and neuropsychological processes involved in sluggish cognitive tempo (SCT) symptoms. The objective of this study was to determine the association of working memory and attentional networks with SCT symptoms in primary schoolchildren. The participants were schoolchildren aged 7 to 10 years ( n = 183) from primary schools in Catalonia (Spain). All the participants completed a working memory task (n-back) and an attentional network task (ANT). Their parents completed an SCT-Child Behavior Checklist self-report and a questionnaire concerning sociodemographic variables. Teachers of the participants provided information on ADHD symptoms and learning determinants. SCT symptoms were correlated with lower scores in both the n-back and ANT. In multivariate regression analysis, SCT symptoms were associated with slower hit reaction times from the ANT. Our results suggest that SCT symptoms are associated with a neuropsychological profile that is different from the classical ADHD profile and characterized by slower reaction times.

New adaptive color quantization method based on self-organizing maps.

PubMed

Chang, Chip-Hong; Xu, Pengfei; Xiao, Rui; Srikanthan, Thambipillai

2005-01-01

Color quantization (CQ) is an image processing task popularly used to convert true color images to palletized images for limited color display devices. To minimize the contouring artifacts introduced by the reduction of colors, a new competitive learning (CL) based scheme called the frequency sensitive self-organizing maps (FS-SOMs) is proposed to optimize the color palette design for CQ. FS-SOM harmonically blends the neighborhood adaptation of the well-known self-organizing maps (SOMs) with the neuron dependent frequency sensitive learning model, the global butterfly permutation sequence for input randomization, and the reinitialization of dead neurons to harness effective utilization of neurons. The net effect is an improvement in adaptation, a well-ordered color palette, and the alleviation of underutilization problem, which is the main cause of visually perceivable artifacts of CQ. Extensive simulations have been performed to analyze and compare the learning behavior and performance of FS-SOM against other vector quantization (VQ) algorithms. The results show that the proposed FS-SOM outperforms classical CL, Linde, Buzo, and Gray (LBG), and SOM algorithms. More importantly, FS-SOM achieves its superiority in reconstruction quality and topological ordering with a much greater robustness against variations in network parameters than the current art SOM algorithm for CQ. A most significant bit (MSB) biased encoding scheme is also introduced to reduce the number of parallel processing units. By mapping the pixel values as sign-magnitude numbers and biasing the magnitudes according to their sign bits, eight lattice points in the color space are condensed into one common point density function. Consequently, the same processing element can be used to map several color clusters and the entire FS-SOM network can be substantially scaled down without severely scarifying the quality of the displayed image. The drawback of this encoding scheme is the additional storage overhead, which can be cut down by leveraging on existing encoder in an overall lossy compression scheme.

Worker Personality and Its Association with Spatially Structured Division of Labor

PubMed Central

Pamminger, Tobias; Foitzik, Susanne; Kaufmann, Katharina C.; Schützler, Natalie; Menzel, Florian

2014-01-01

Division of labor is a defining characteristic of social insects and fundamental to their ecological success. Many of the numerous tasks essential for the survival of the colony must be performed at a specific location. Consequently, spatial organization is an integral aspect of division of labor. The mechanisms organizing the spatial distribution of workers, separating inside and outside workers without central control, is an essential, but so far neglected aspect of division of labor. In this study, we investigate the behavioral mechanisms governing the spatial distribution of individual workers and its physiological underpinning in the ant Myrmica rubra. By investigating worker personalities we uncover position-associated behavioral syndromes. This context-independent and temporally stable set of correlated behaviors (positive association between movements and attraction towards light) could promote the basic separation between inside (brood tenders) and outside workers (foragers). These position-associated behavior syndromes are coupled with a high probability to perform tasks, located at the defined position, and a characteristic cuticular hydrocarbon profile. We discuss the potentially physiological causes for the observed behavioral syndromes and highlight how the study of animal personalities can provide new insights for the study of division of labor and self-organized processes in general. PMID:24497911

Transfer of radionuclides and dose assessment to ants and anthills in a Swedish forest ecosystem.

PubMed

Rosén, K; Lenoir, L; Stark, K; Vinichuk, M; Sundell-Bergman, S

2018-05-15

In forest ecosystems soil organisms are important for immobilization, translocation and recycling of radionuclides. Still, there is a lack of studies on the role of insects such as ants in the turnover of radionuclides and how radioactivity affects an ant community. In this study seven anthills were sampled in an area that was heavily contaminated after the fallout from the Chernobyl accident. Samples of ant and anthill materials were taken from different depths of the anthills as well as from the surrounding soil and the activity concentrations of 137 Cs were determined. In addition, a radiation dose assessment was performed for ants and anthills using the ERICA tool. The deposition of 137 Cs in 1986 in the study area was calculated back to be on average 110,500 Bq m -2 . The averaged data for all the seven locations investigated indicate that the level of 137 Cs activity concentrations in the anthill's material increased with depth of the anthill being highest at the depth 50-65 cm. The concentration in the upper layers (0-2 cm) and of the ants showed significant correlations with the deposition upon multivariate analysis. The concentration ratio (CR) defined as the ratio between the mass activity for 137 Cs density in ants (Bq kg -1 d.w.) and mass activity density in soil (Bq kg -1 d.w.) was determined to be in the range of 0.04-0.14. Also, the transfer factor (TF) defined as the ratio between the mass activity for 137 Cs density in ant (Bq kg -1 d.w.) and to the unit area activity density (in Bq m -2 d.w.) was determined for 137 Cs to be 0.0015 m 2 kg -1 d.w. The assessed radiation doses were found to be a 4.9 μGy h -1 which is below international reference levels for non-human biota. Copyright © 2018. Published by Elsevier Ltd.

The effect of anatomical modeling on space radiation dose estimates: a comparison of doses for NASA phantoms and the 5th, 50th, and 95th percentile male and female astronauts.

PubMed

Bahadori, Amir A; Van Baalen, Mary; Shavers, Mark R; Dodge, Charles; Semones, Edward J; Bolch, Wesley E

2011-03-21

The National Aeronautics and Space Administration (NASA) performs organ dosimetry and risk assessment for astronauts using model-normalized measurements of the radiation fields encountered in space. To determine the radiation fields in an organ or tissue of interest, particle transport calculations are performed using self-shielding distributions generated with the computer program CAMERA to represent the human body. CAMERA mathematically traces linear rays (or path lengths) through the computerized anatomical man (CAM) phantom, a computational stylized model developed in the early 1970s with organ and body profiles modeled using solid shapes and scaled to represent the body morphometry of the 1950 50th percentile (PCTL) Air Force male. With the increasing use of voxel phantoms in medical and health physics, a conversion from a mathematical-based to a voxel-based ray-tracing algorithm is warranted. In this study, the voxel-based ray tracer (VoBRaT) is introduced to ray trace voxel phantoms using a modified version of the algorithm first proposed by Siddon (1985 Med. Phys. 12 252-5). After validation, VoBRAT is used to evaluate variations in body self-shielding distributions for NASA phantoms and six University of Florida (UF) hybrid phantoms, scaled to represent the 5th, 50th, and 95th PCTL male and female astronaut body morphometries, which have changed considerably since the inception of CAM. These body self-shielding distributions are used to generate organ dose equivalents and effective doses for five commonly evaluated space radiation environments. It is found that dosimetric differences among the phantoms are greatest for soft radiation spectra and light vehicular shielding.

Ant brood function as life preservers during floods.

PubMed

Purcell, Jessica; Avril, Amaury; Jaffuel, Geoffrey; Bates, Sarah; Chapuisat, Michel

2014-01-01

Social organisms can surmount many ecological challenges by working collectively. An impressive example of such collective behavior occurs when ants physically link together into floating 'rafts' to escape from flooded habitat. However, raft formation may represent a social dilemma, with some positions posing greater individual risks than others. Here, we investigate the position and function of different colony members, and the costs and benefits of this functional geometry in rafts of the floodplain-dwelling ant Formica selysi. By causing groups of ants to raft in the laboratory, we observe that workers are distributed throughout the raft, queens are always in the center, and 100% of brood items are placed on the base. Through a series of experiments, we show that workers and brood are extremely resistant to submersion. Both workers and brood exhibit high survival rates after they have rafted, suggesting that occupying the base of the raft is not as costly as expected. The placement of all brood on the base of one cohesive raft confers several benefits: it preserves colony integrity, takes advantage of brood buoyancy, and increases the proportion of workers that immediately recover after rafting.

Autonomous NanoTechnology Swarm (ANTS) Prospecting Asteroid Mission (PAM), Asteroid Proximity Operations

NASA Technical Reports Server (NTRS)

Marr, Greg; Cooley, Steve; Roithmayr, Carlos; Kay-Bunnell, Linda; Williams, Trevor

2004-01-01

The Autonomous NanoTechnology Swarm (ANTS) is a generic mission architecture based on spatially distributed spacecraft, autonomous and redundant components, and hierarchical organization. The ANTS Prospecting Asteroid Mission (PAM) is an ANTS application which will nominally use a swarm of 1000 spacecraft. There would be 10 types of "specialists" with common spacecraft buses. There would be 10 subswarms of approximately 100 spacecraft each or approximately 10 of each specialist in each swarm. The ANTS PAM primary objective is the exploration of the asteroid belt in search of resources and material with astrobiologically relevant origins and signatures. The ANTS PAM spacecraft will nominally be released from a station in an Earth-Moon L1 libration point orbit, and they will use Solar sails for propulsion. The sail structure would be highly flexible, capable of changing morphology to change cross-section for capture of sunlight or to form effective "tip vanes" for attitude control. ANTS PAM sails would be capable of full to partial deployment, to change effective sail area and center of pressure, and thus allow attitude control. Results of analysis of a transfer trajectory from Earth to a sample target asteroid will be presented. ANTS PAM will require continuous coverage of different asteroid locations as close as one to two asteroid "diameters" from the surface of the asteroid for periods of science data collection during asteroid proximity operations. Hovering spacecraft could meet the science data collection objectives. The results of hovering analysis will be presented. There are locations for which hovering is not possible, for example on the illuminated side of the asteroid. For cases where hovering is not possible, the results of utilizing asteroid formations to orbit the asteroid and achieve the desired asteroid viewing will be presented for sample asteroids. The ability of ANTS PAM to reduce the area of the solar sail during asteroid proximity operations is critical to the maintenance of orbiting formations for a period of time. Results of analysis of potential "traffic" problems during asteroid proximity operations will be presented.

A new type of exocrine gland and its function in mass recruitment in the ant Cylindromyrmex whymperi (Formicidae, Cerapachyinae)

NASA Astrophysics Data System (ADS)

Gobin, Bruno; Rüppell, Olav; Hartmann, Annegret; Jungnickel, Harald; Morgan, David; Billen, Johan

2001-08-01

Workers of the ant Cylindromyrmex whymperi display mass trail recruitment. Bioassays show that the trail pheromone originates from a unique gland between abdominal sternites 6 and 7. The gland has a hitherto unknown structural organization. Upon leaving the secretory cell, the duct cell widens to form a sclerotized pear-shaped reservoir chamber, lined with multiple duct cells. Each duct thus forms a miniature reservoir for the secretions of each single secretory cell, a novel structural arrangement in exocrine glands of social Hymenoptera.

Solving the vehicle routing problem by a hybrid meta-heuristic algorithm

NASA Astrophysics Data System (ADS)

Yousefikhoshbakht, Majid; Khorram, Esmaile

2012-08-01

The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.

Field-testing ecological and economic benefits of coffee certification programs.

PubMed

Philpott, Stacy M; Bichier, Peter; Rice, Robert; Greenberg, Russell

2007-08-01

Coffee agroecosystems are critical to the success of conservation efforts in Latin America because of their ecological and economic importance. Coffee certification programs may offer one way to protect biodiversity and maintain farmer livelihoods. Established coffee certification programs fall into three distinct, but not mutually exclusive categories: organic, fair trade, and shade. The results of previous studies demonstrate that shade certification can benefit biodiversity, but it remains unclear whether a farmer's participation in any certification program can provide both ecological and economic benefits. To assess the value of coffee certification for conservation efforts in the region, we examined economic and ecological aspects of coffee production for eight coffee cooperatives in Chiapas, Mexico, that were certified organic, certified organic and fair trade, or uncertified. We compared vegetation and ant and bird diversity in coffee farms and forests, and interviewed farmers to determine coffee yield, gross revenue from coffee production, and area in coffee production. Although there are no shade-certified farms in the study region, we used vegetation data to determine whether cooperatives would qualify for shade certification. We found no differences in vegetation characteristics, ant or bird species richness, or fraction of forest fauna in farms based on certification. Farmers with organic and organic and fair-trade certification had more land under cultivation and in some cases higher revenue than uncertified farmers. Coffee production area did not vary among farm types. No cooperative passed shade-coffee certification standards because the plantations lacked vertical stratification, yet vegetation variables for shade certification significantly correlated with ant and bird diversity. Although farmers in the Chiapas highlands with organic and/or fair-trade certification may reap some economic benefits from their certification status, their farms may not protect as much biodiversity as shade-certified farms. Working toward triple certification (organic, fair trade, and shade) at the farm level may enhance biodiversity protection, increase benefits to farmers, and lead to more successful conservation strategies in coffee-growing regions.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.