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Sample records for bee colony optimization

  1. Artificial Bee Colony Optimization for Short-Term Hydrothermal Scheduling

    NASA Astrophysics Data System (ADS)

    Basu, M.

    2014-12-01

    Artificial bee colony optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal system. Artificial bee colony optimization is a swarm-based algorithm inspired by the food foraging behavior of honey bees. The algorithm is tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and thermal units with valve point loading. The ramp-rate limits of thermal generators are taken into consideration. The transmission losses are also accounted for through the use of loss coefficients. The algorithm is tested on two hydrothermal multi-reservoir cascaded hydroelectric test systems. The results of the proposed approach are compared with those of differential evolution, evolutionary programming and particle swarm optimization. From numerical results, it is found that the proposed artificial bee colony optimization based approach is able to provide better solution.

  2. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

    NASA Astrophysics Data System (ADS)

    Chen, Wei

    2015-07-01

    In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

  3. Artificial Bee Colony Algorithm for Solving Optimal Power Flow Problem

    PubMed Central

    Le Dinh, Luong; Vo Ngoc, Dieu

    2013-01-01

    This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem. PMID:24470790

  4. Artificial bee colony algorithm for solving optimal power flow problem.

    PubMed

    Le Dinh, Luong; Vo Ngoc, Dieu; Vasant, Pandian

    2013-01-01

    This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem. PMID:24470790

  5. A hybrid artificial bee colony algorithm for numerical function optimization

    NASA Astrophysics Data System (ADS)

    Alqattan, Zakaria N.; Abdullah, Rosni

    2015-02-01

    Artificial Bee Colony (ABC) algorithm is one of the swarm intelligence algorithms; it has been introduced by Karaboga in 2005. It is a meta-heuristic optimization search algorithm inspired from the intelligent foraging behavior of the honey bees in nature. Its unique search process made it as one of the most competitive algorithm with some other search algorithms in the area of optimization, such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, the ABC performance of the local search process and the bee movement or the solution improvement equation still has some weaknesses. The ABC is good in avoiding trapping at the local optimum but it spends its time searching around unpromising random selected solutions. Inspired by the PSO, we propose a Hybrid Particle-movement ABC algorithm called HPABC, which adapts the particle movement process to improve the exploration of the original ABC algorithm. Numerical benchmark functions were used in order to experimentally test the HPABC algorithm. The results illustrate that the HPABC algorithm can outperform the ABC algorithm in most of the experiments (75% better in accuracy and over 3 times faster).

  6. Modified artificial bee colony algorithm for reactive power optimization

    NASA Astrophysics Data System (ADS)

    Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

    2015-05-01

    Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

  7. ABCluster: the artificial bee colony algorithm for cluster global optimization.

    PubMed

    Zhang, Jun; Dolg, Michael

    2015-10-01

    Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters. PMID:26327507

  8. Modified artificial bee colony optimization with block perturbation strategy

    NASA Astrophysics Data System (ADS)

    Jia, Dongli; Duan, Xintao; Khurram Khan, Muhammad

    2015-05-01

    As a newly emerged swarm intelligence-based optimizer, the artificial bee colony (ABC) algorithm has attracted the interest of researchers in recent years owing to its ease of use and efficiency. In this article, a modified ABC algorithm with block perturbation strategy (BABC) is proposed. Unlike basic ABC, in the BABC algorithm, not one element but a block of elements from the parent solutions is changed while producing a new solution. The performance of the BABC algorithm is investigated and compared with that of the basic ABC, modified ABC, Brest's differential evolution, self-adaptive differential evolution and restart covariance matrix adaptation evolution strategy (IPOP-CMA-ES) over a set of widely used benchmark functions. The obtained results show that the performance of BABC is better than, or at least comparable to, that of the basic ABC, improved differential evolution variants and IPOP-CMA-ES in terms of convergence speed and final solution accuracy.

  9. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    PubMed

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200

  10. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    PubMed Central

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness. PMID:24592200

  11. A multistrategy optimization improved artificial bee colony algorithm.

    PubMed

    Liu, Wen

    2014-01-01

    Being prone to the shortcomings of premature and slow convergence rate of artificial bee colony algorithm, an improved algorithm was proposed. Chaotic reverse learning strategies were used to initialize swarm in order to improve the global search ability of the algorithm and keep the diversity of the algorithm; the similarity degree of individuals of the population was used to characterize the diversity of population; population diversity measure was set as an indicator to dynamically and adaptively adjust the nectar position; the premature and local convergence were avoided effectively; dual population search mechanism was introduced to the search stage of algorithm; the parallel search of dual population considerably improved the convergence rate. Through simulation experiments of 10 standard testing functions and compared with other algorithms, the results showed that the improved algorithm had faster convergence rate and the capacity of jumping out of local optimum faster. PMID:24982924

  12. A hybrid artificial bee colony optimization and quantum evolutionary algorithm for continuous optimization problems.

    PubMed

    Duan, Hai-Bin; Xu, Chun-Fang; Xing, Zhi-Hui

    2010-02-01

    In this paper, a novel hybrid Artificial Bee Colony (ABC) and Quantum Evolutionary Algorithm (QEA) is proposed for solving continuous optimization problems. ABC is adopted to increase the local search capacity as well as the randomness of the populations. In this way, the improved QEA can jump out of the premature convergence and find the optimal value. To show the performance of our proposed hybrid QEA with ABC, a number of experiments are carried out on a set of well-known Benchmark continuous optimization problems and the related results are compared with two other QEAs: the QEA with classical crossover operation, and the QEA with 2-crossover strategy. The experimental comparison results demonstrate that the proposed hybrid ABC and QEA approach is feasible and effective in solving complex continuous optimization problems. PMID:20180252

  13. 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. PMID:25059256

  14. A new improved artificial bee colony algorithm for ship hull form optimization

    NASA Astrophysics Data System (ADS)

    Huang, Fuxin; Wang, Lijue; Yang, Chi

    2016-04-01

    The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.

  15. New Enhanced Artificial Bee Colony (JA-ABC5) Algorithm with Application for Reactive Power Optimization

    PubMed Central

    2015-01-01

    The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement. PMID:25879054

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

    NASA Astrophysics Data System (ADS)

    Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

    2016-06-01

    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.

  17. Optimization of solar air collector using genetic algorithm and artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Şencan Şahin, Arzu

    2012-11-01

    Thermal performance of solar air collector depends on many parameters as inlet air temperature, air velocity, collector slope and properties related to collector. In this study, the effect of the different parameters which affect the performance of the solar air collector are investigated. In order to maximize the thermal performance of a solar air collector genetic algorithm (GA) and artificial bee colony algorithm (ABC) have been used. The results obtained indicate that GA and ABC algorithms can be applied successfully for the optimization of the thermal performance of solar air collector.

  18. Efficient implementation and application of the artificial bee colony algorithm to low-dimensional optimization problems

    NASA Astrophysics Data System (ADS)

    von Rudorff, Guido Falk; Wehmeyer, Christoph; Sebastiani, Daniel

    2014-06-01

    We adapt a swarm-intelligence-based optimization method (the artificial bee colony algorithm, ABC) to enhance its parallel scaling properties and to improve the escaping behavior from deep local minima. Specifically, we apply the approach to the geometry optimization of Lennard-Jones clusters. We illustrate the performance and the scaling properties of the parallelization scheme for several system sizes (5-20 particles). Our main findings are specific recommendations for ranges of the parameters of the ABC algorithm which yield maximal performance for Lennard-Jones clusters and Morse clusters. The suggested parameter ranges for these different interaction potentials turn out to be very similar; thus, we believe that our reported values are fairly general for the ABC algorithm applied to chemical optimization problems.

  19. Artificial Bee Colony Optimization of Capping Potentials for Hybrid Quantum Mechanical/Molecular Mechanical Calculations.

    PubMed

    Schiffmann, Christoph; Sebastiani, Daniel

    2011-05-10

    We present an algorithmic extension of a numerical optimization scheme for analytic capping potentials for use in mixed quantum-classical (quantum mechanical/molecular mechanical, QM/MM) ab initio calculations. Our goal is to minimize bond-cleavage-induced perturbations in the electronic structure, measured by means of a suitable penalty functional. The optimization algorithm-a variant of the artificial bee colony (ABC) algorithm, which relies on swarm intelligence-couples deterministic (downhill gradient) and stochastic elements to avoid local minimum trapping. The ABC algorithm outperforms the conventional downhill gradient approach, if the penalty hypersurface exhibits wiggles that prevent a straight minimization pathway. We characterize the optimized capping potentials by computing NMR chemical shifts. This approach will increase the accuracy of QM/MM calculations of complex biomolecules. PMID:26610125

  20. Coupling Optimization Design of Aspirated Compressor Airfoil and Aspirated Scheme Based on Artificial Bee Colony Algorithm and CST Method

    NASA Astrophysics Data System (ADS)

    Li, Jun; Liu, Bo; Zhao, Yan; Yang, Xiaodong; Lu, Xiaofeng; Wang, Lei

    2015-04-01

    This paper focuses on creating a new design method optimizing both aspirated compressor airfoil and the aspiration scheme simultaneously. The optimization design method is based on the artificial bee colony algorithm and the CST method, while the flow field is computed by one 2D computational program. The optimization process of the rotor tip and stator tip airfoil from an aspirated fan stage is demonstrated to verify the effectiveness of the new coupling method. The results show that the total pressure losses of the optimized stator tip and rotor tip airfoil are reduced relatively by 54% and 20%, respectively. Artificial bee colony algorithm and CST method indicate a satisfying applicability in aspirated airfoil optimization design. Finally, the features of aspirated airfoil designing process are concluded.

  1. A self adaptive hybrid enhanced artificial bee colony algorithm for continuous optimization problems.

    PubMed

    Shan, Hai; Yasuda, Toshiyuki; Ohkura, Kazuhiro

    2015-06-01

    The artificial bee colony (ABC) algorithm is one of popular swarm intelligence algorithms that inspired by the foraging behavior of honeybee colonies. To improve the convergence ability, search speed of finding the best solution and control the balance between exploration and exploitation using this approach, we propose a self adaptive hybrid enhanced ABC algorithm in this paper. To evaluate the performance of standard ABC, best-so-far ABC (BsfABC), incremental ABC (IABC), and the proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation (CEC) 2014 test suite. Our experimental results show the comparative performance of standard ABC, BsfABC, IABC, and the proposed ABC algorithms. According to the results, we conclude that the proposed ABC algorithm is competitive to those state-of-the-art modified ABC algorithms such as BsfABC and IABC algorithms based on the benchmark problems defined by CEC 2014 test suite with dimension sizes of 10, 30, and 50, respectively. PMID:25982071

  2. Optimization of Spherical Roller Bearing Design Using Artificial Bee Colony Algorithm and Grid Search Method

    NASA Astrophysics Data System (ADS)

    Tiwari, Rajiv; Waghole, Vikas

    2015-07-01

    Bearing standards impose restrictions on the internal geometry of spherical roller bearings. Geometrical and strength constraints conditions have been formulated for the optimization of bearing design. The long fatigue life is one of the most important criteria in the optimum design of bearing. The life is directly proportional to the dynamic capacity; hence, the objective function has been chosen as the maximization of dynamic capacity. The effect of speed and static loads acting on the bearing are also taken into account. Design variables for the bearing include five geometrical parameters: the roller diameter, the roller length, the bearing pitch diameter, the number of rollers, and the contact angle. There are a few design constraint parameters which are also included in the optimization, the bounds of which are obtained by initial runs of the optimization. The optimization program is made to run for different values of these design constraint parameters and a range of the parameters is obtained for which the objective function has a higher value. The artificial bee colony algorithm (ABCA) has been used to solve the constrained optimized problem and the optimum design is compared with the one obtained from the grid search method (GSM), both operating independently. Both the ABCA and the GSM have been finally combined together to reach the global optimum point. A constraint violation study has also been carried out to give priority to the constraint having greater possibility of violations. Optimized bearing designs show a better performance parameter with those specified in bearing catalogs. The sensitivity analysis of bearing parameters has also been carried out to see the effect of manufacturing tolerance on the objective function.

  3. Enhancing artificial bee colony algorithm with self-adaptive searching strategy and artificial immune network operators for global optimization.

    PubMed

    Chen, Tinggui; Xiao, Renbin

    2014-01-01

    Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments. PMID:24772023

  4. Enhancing Artificial Bee Colony Algorithm with Self-Adaptive Searching Strategy and Artificial Immune Network Operators for Global Optimization

    PubMed Central

    Chen, Tinggui; Xiao, Renbin

    2014-01-01

    Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments. PMID:24772023

  5. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

    PubMed

    Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

    2014-05-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt. PMID:25685507

  6. Protein Tertiary Structure Prediction Based on Main Chain Angle Using a Hybrid Bees Colony Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Mahmood, Zakaria N.; Mahmuddin, Massudi; Mahmood, Mohammed Nooraldeen

    Encoding proteins of amino acid sequence to predict classified into their respective families and subfamilies is important research area. However for a given protein, knowing the exact action whether hormonal, enzymatic, transmembranal or nuclear receptors does not depend solely on amino acid sequence but on the way the amino acid thread folds as well. This study provides a prototype system that able to predict a protein tertiary structure. Several methods are used to develop and evaluate the system to produce better accuracy in protein 3D structure prediction. The Bees Optimization algorithm which inspired from the honey bees food foraging method, is used in the searching phase. In this study, the experiment is conducted on short sequence proteins that have been used by the previous researches using well-known tools. The proposed approach shows a promising result.

  7. Comparative Study on Synthesizing Reconfigurable Time- Modulated Linear Arrays using Differential Evolution, Artificial Bee Colony and Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Mandal, S. K.; Singh, Harshavardhan; Mahanti, G. K.; Ghatak, Rowdra

    2014-10-01

    This paper presents a new technique based on optimization tools to design phase only, digitally controlled, reconfigurable antenna arrays through time modulation. In the proposed approach, the on-time durations of the time-modulated elements and the static amplitudes of the array elements are perturbed in such a way that the same on-time sequence and discrete values of static amplitudes for four bit digital attenuators produces either a pencil or a flat-top beam pattern, depending on the suitable discrete phase distributions of five bit digital phase shifters. In order to illustrate the technique, three optimization tools: differential evolution (DE), artificial bee colony (ABC), and particle swarm optimization (PSO) are employed and their performances are compared. The numerical results for a 20-element linear array are presented.

  8. An Experimental Approach for Optimizing Coating Parameters of Electroless Ni-P-Cu Coating Using Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee colony algorithm. Experiments are carried out by utilizing the combination of three coating process parameters, namely, nickel sulphate, sodium hypophosphite, and copper sulphate, and the fourth parameter is postdeposition heat treatment temperature. The design of experiment is based on the Taguchi L27 experimental design. After coating, measurement of wear and coefficient of friction of each heat-treated sample is done using a multitribotester apparatus with block-on-roller arrangement. Both friction and wear are found to increase with increase of source of nickel concentration and decrease with increase of source of copper concentration. Artificial bee colony algorithm is successfully employed to optimize the multiresponse objective function for both wear depth and coefficient of friction. It is found that, within the operating range, a lower value of nickel concentration, medium value of hypophosphite concentration, higher value of copper concentration, and higher value of heat treatment temperature are suitable for having minimum wear and coefficient of friction. The surface morphology, phase transformation behavior, and composition of coatings are also studied with the help of scanning electron microscopy, X-ray diffraction analysis, and energy dispersed X-ray analysis, respectively. PMID:27382630

  9. An Experimental Approach for Optimizing Coating Parameters of Electroless Ni-P-Cu Coating Using Artificial Bee Colony Algorithm.

    PubMed

    Roy, Supriyo; Sahoo, Prasanta

    2014-01-01

    This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee colony algorithm. Experiments are carried out by utilizing the combination of three coating process parameters, namely, nickel sulphate, sodium hypophosphite, and copper sulphate, and the fourth parameter is postdeposition heat treatment temperature. The design of experiment is based on the Taguchi L27 experimental design. After coating, measurement of wear and coefficient of friction of each heat-treated sample is done using a multitribotester apparatus with block-on-roller arrangement. Both friction and wear are found to increase with increase of source of nickel concentration and decrease with increase of source of copper concentration. Artificial bee colony algorithm is successfully employed to optimize the multiresponse objective function for both wear depth and coefficient of friction. It is found that, within the operating range, a lower value of nickel concentration, medium value of hypophosphite concentration, higher value of copper concentration, and higher value of heat treatment temperature are suitable for having minimum wear and coefficient of friction. The surface morphology, phase transformation behavior, and composition of coatings are also studied with the help of scanning electron microscopy, X-ray diffraction analysis, and energy dispersed X-ray analysis, respectively. PMID:27382630

  10. Solving Integer Programming Problems by Using Artificial Bee Colony Algorithm

    NASA Astrophysics Data System (ADS)

    Akay, Bahriye; Karaboga, Dervis

    This paper presents a study that applies the Artificial Bee Colony algorithm to integer programming problems and compares its performance with those of Particle Swarm Optimization algorithm variants and Branch and Bound technique presented to the literature. In order to cope with integer programming problems, in neighbour solution production unit, solutions are truncated to the nearest integer values. The experimental results show that Artificial Bee Colony algorithm can handle integer programming problems efficiently and Artificial Bee Colony algorithm can be considered to be very robust by the statistics calculated such as mean, median, standard deviation.

  11. The Artificial Bee Colony algorithm in layer optimization for the maximum fundamental frequency of symmetrical laminated composite plates

    NASA Astrophysics Data System (ADS)

    Kemal Apalak, M.; Karaboga, Dervis; Akay, Bahriye

    2014-03-01

    In this study the layer optimization was carried out for maximizing the lowest (first) fundamental frequency of symmetrical laminated composite plates subjected to any combination of the three classical boundary conditions, and the applicability of the Artificial Bee Colony (ABC) algorithm to the layer optimization was investigated. The finite element method was used for calculating the first natural frequencies of the laminated composite plates with various stacking sequences. The ABC algorithm maximizes the first natural frequency of the laminated composite plate defined as an objective function. The optimal stacking sequences were determined for two layer numbers, twenty boundary conditions and two plate length/width ratios. The outer layers of the composite plate had a stiffness increasing effect, and as the number of clamped plate edges was increased both he stiffness and natural frequency of the plate increased. The optimal stacking sequences were in good agreement with those determined by the Ritz-based layerwise optimization method (Narita 2003: J. Sound Vibration 263 (5), 1005-1016) as well as by the genetic algorithm method combined with the finite element method.

  12. Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm.

    PubMed

    Li, Bai; Lin, Mu; Liu, Qiao; Li, Ya; Zhou, Changjun

    2015-10-01

    Protein folding is a fundamental topic in molecular biology. Conventional experimental techniques for protein structure identification or protein folding recognition require strict laboratory requirements and heavy operating burdens, which have largely limited their applications. Alternatively, computer-aided techniques have been developed to optimize protein structures or to predict the protein folding process. In this paper, we utilize a 3D off-lattice model to describe the original protein folding scheme as a simplified energy-optimal numerical problem, where all types of amino acid residues are binarized into hydrophobic and hydrophilic ones. We apply a balance-evolution artificial bee colony (BE-ABC) algorithm as the minimization solver, which is featured by the adaptive adjustment of search intensity to cater for the varying needs during the entire optimization process. In this work, we establish a benchmark case set with 13 real protein sequences from the Protein Data Bank database and evaluate the convergence performance of BE-ABC algorithm through strict comparisons with several state-of-the-art ABC variants in short-term numerical experiments. Besides that, our obtained best-so-far protein structures are compared to the ones in comprehensive previous literature. This study also provides preliminary insights into how artificial intelligence techniques can be applied to reveal the dynamics of protein folding. Graphical Abstract Protein folding optimization using 3D off-lattice model and advanced optimization techniques. PMID:26381910

  13. Pathogen webs in collapsing honey bee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent losses in honey bee colonies are unusual in their severity, geographical distribution, and, in some cases, failure to present recognized symptoms of known disease. Domesticated honey bees face numerous pests and pathogens, tempting hypotheses that colony collapses arise from exposure to new o...

  14. Chronic sublethal stress causes bee colony failure

    PubMed Central

    Bryden, John; Gill, Richard J; Mitton, Robert A A; Raine, Nigel E; Jansen, Vincent A A; Hodgson, David

    2013-01-01

    Current bee population declines and colony failures are well documented yet poorly understood and no single factor has been identified as a leading cause. The evidence is equivocal and puzzling: for instance, many pathogens and parasites can be found in both failing and surviving colonies and field pesticide exposure is typically sublethal. Here, we investigate how these results can be due to sublethal stress impairing colony function. We mathematically modelled stress on individual bees which impairs colony function and found how positive density dependence can cause multiple dynamic outcomes: some colonies fail while others thrive. We then exposed bumblebee colonies to sublethal levels of a neonicotinoid pesticide. The dynamics of colony failure, which we observed, were most accurately described by our model. We argue that our model can explain the enigmatic aspects of bee colony failures, highlighting an important role for sublethal stress in colony declines. PMID:24112478

  15. Metatranscriptomic analyses of honey bee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bees face numerous biotic threats from viruses to bacteria, fungi, protists, and mites. Here we describe a thorough analysis of microbes harbored by worker honey bees collected from field colonies in geographically distinct regions of Turkey. Turkey is one of the World’s most important centers...

  16. Predictive Markers of Honey Bee Colony Collapse

    PubMed Central

    Dainat, Benjamin; Evans, Jay D.; Chen, Yan Ping; Gauthier, Laurent; Neumann, Peter

    2012-01-01

    Across the Northern hemisphere, managed honey bee colonies, Apis mellifera, are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Parasites and pathogens are considered as principal actors, in particular the ectoparasitic mite Varroa destructor, associated viruses and the microsporidian Nosema ceranae. Here we used long term monitoring of colonies and screening for eleven disease agents and genes involved in bee immunity and physiology to identify predictive markers of honeybee colony losses during winter. The data show that DWV, Nosema ceranae, Varroa destructor and Vitellogenin can be predictive markers for winter colony losses, but their predictive power strongly depends on the season. In particular, the data support that V. destructor is a key player for losses, arguably in line with its specific impact on the health of individual bees and colonies. PMID:22384162

  17. Predictive markers of honey bee colony collapse

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Managed honey bee colonies are currently affected by abrupt depopulation during winter and many factors are suspected to be involved, either alone or in combination. Pathogens are considered as principal actors, contributing to weaken colony health and leaving room for secondary infections. In parti...

  18. Pathogen Webs in Collapsing Honey Bee Colonies

    PubMed Central

    Cornman, R. Scott; Tarpy, David R.; Chen, Yanping; Jeffreys, Lacey; Lopez, Dawn; Pettis, Jeffery S.; vanEngelsdorp, Dennis; Evans, Jay D.

    2012-01-01

    Recent losses in honey bee colonies are unusual in their severity, geographical distribution, and, in some cases, failure to present recognized characteristics of known disease. Domesticated honey bees face numerous pests and pathogens, tempting hypotheses that colony collapses arise from exposure to new or resurgent pathogens. Here we explore the incidence and abundance of currently known honey bee pathogens in colonies suffering from Colony Collapse Disorder (CCD), otherwise weak colonies, and strong colonies from across the United States. Although pathogen identities differed between the eastern and western United States, there was a greater incidence and abundance of pathogens in CCD colonies. Pathogen loads were highly covariant in CCD but not control hives, suggesting that CCD colonies rapidly become susceptible to a diverse set of pathogens, or that co-infections can act synergistically to produce the rapid depletion of workers that characterizes the disorder. We also tested workers from a CCD-free apiary to confirm that significant positive correlations among pathogen loads can develop at the level of individual bees and not merely as a secondary effect of CCD. This observation and other recent data highlight pathogen interactions as important components of bee disease. Finally, we used deep RNA sequencing to further characterize microbial diversity in CCD and non-CCD hives. We identified novel strains of the recently described Lake Sinai viruses (LSV) and found evidence of a shift in gut bacterial composition that may be a biomarker of CCD. The results are discussed with respect to host-parasite interactions and other environmental stressors of honey bees. PMID:22927991

  19. Application of artificial bee colony (ABC) algorithm in search of optimal release of Aswan High Dam

    NASA Astrophysics Data System (ADS)

    Hossain, Md S.; El-shafie, A.

    2013-04-01

    The paper presents a study on developing an optimum reservoir release policy by using ABC algorithm. The decision maker of a reservoir system always needs a guideline to operate the reservoir in an optimal way. Release curves have developed for high, medium and low inflow category that can answer how much water need to be release for a month by observing the reservoir level (storage condition). The Aswan high dam of Egypt has considered as the case study. 18 years of historical inflow data has used for simulation purpose and the general system performance measuring indices has measured. The application procedure and problem formulation of ABC is very simple and can be used in optimizing reservoir system. After using the actual historical inflow, the release policy succeeded in meeting demand for about 98% of total time period.

  20. Allee effects and colony collapse disorder in honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We propose a mathematical model to quantify the hypothesis that a major ultimate cause of Colony Collapse Disorder (CCD) in honey bees is the presence of an Allee effect in the growth dynamics of honey bee colonies. In the model, both recruitment of adult bees as well as mortality of adult bees have...

  1. Genetic diversity affects colony survivorship in commercial honey bee colonies

    NASA Astrophysics Data System (ADS)

    Tarpy, David R.; vanEngelsdorp, Dennis; Pettis, Jeffrey S.

    2013-08-01

    Honey bee ( Apis mellifera) queens mate with unusually high numbers of males (average of approximately 12 drones), although there is much variation among queens. One main consequence of such extreme polyandry is an increased diversity of worker genotypes within a colony, which has been shown empirically to confer significant adaptive advantages that result in higher colony productivity and survival. Moreover, honey bees are the primary insect pollinators used in modern commercial production agriculture, and their populations have been in decline worldwide. Here, we compare the mating frequencies of queens, and therefore, intracolony genetic diversity, in three commercial beekeeping operations to determine how they correlate with various measures of colony health and productivity, particularly the likelihood of queen supersedure and colony survival in functional, intensively managed beehives. We found the average effective paternity frequency ( m e ) of this population of honey bee queens to be 13.6 ± 6.76, which was not significantly different between colonies that superseded their queen and those that did not. However, colonies that were less genetically diverse (headed by queens with m e ≤ 7.0) were 2.86 times more likely to die by the end of the study when compared to colonies that were more genetically diverse (headed by queens with m e > 7.0). The stark contrast in colony survival based on increased genetic diversity suggests that there are important tangible benefits of increased queen mating number in managed honey bees, although the exact mechanism(s) that govern these benefits have not been fully elucidated.

  2. Genetic diversity affects colony survivorship in commercial honey bee colonies.

    PubMed

    Tarpy, David R; Vanengelsdorp, Dennis; Pettis, Jeffrey S

    2013-08-01

    Honey bee (Apis mellifera) queens mate with unusually high numbers of males (average of approximately 12 drones), although there is much variation among queens. One main consequence of such extreme polyandry is an increased diversity of worker genotypes within a colony, which has been shown empirically to confer significant adaptive advantages that result in higher colony productivity and survival. Moreover, honey bees are the primary insect pollinators used in modern commercial production agriculture, and their populations have been in decline worldwide. Here, we compare the mating frequencies of queens, and therefore, intracolony genetic diversity, in three commercial beekeeping operations to determine how they correlate with various measures of colony health and productivity, particularly the likelihood of queen supersedure and colony survival in functional, intensively managed beehives. We found the average effective paternity frequency (m e ) of this population of honey bee queens to be 13.6 ± 6.76, which was not significantly different between colonies that superseded their queen and those that did not. However, colonies that were less genetically diverse (headed by queens with m e  ≤ 7.0) were 2.86 times more likely to die by the end of the study when compared to colonies that were more genetically diverse (headed by queens with m e  > 7.0). The stark contrast in colony survival based on increased genetic diversity suggests that there are important tangible benefits of increased queen mating number in managed honey bees, although the exact mechanism(s) that govern these benefits have not been fully elucidated. PMID:23728203

  3. Classification of Medical Datasets Using SVMs with Hybrid Evolutionary Algorithms Based on Endocrine-Based Particle Swarm Optimization and Artificial Bee Colony Algorithms.

    PubMed

    Lin, Kuan-Cheng; Hsieh, Yi-Hsiu

    2015-10-01

    The classification and analysis of data is an important issue in today's research. Selecting a suitable set of features makes it possible to classify an enormous quantity of data quickly and efficiently. Feature selection is generally viewed as a problem of feature subset selection, such as combination optimization problems. Evolutionary algorithms using random search methods have proven highly effective in obtaining solutions to problems of optimization in a diversity of applications. In this study, we developed a hybrid evolutionary algorithm based on endocrine-based particle swarm optimization (EPSO) and artificial bee colony (ABC) algorithms in conjunction with a support vector machine (SVM) for the selection of optimal feature subsets for the classification of datasets. The results of experiments using specific UCI medical datasets demonstrate that the accuracy of the proposed hybrid evolutionary algorithm is superior to that of basic PSO, EPSO and ABC algorithms, with regard to classification accuracy using subsets with a reduced number of features. PMID:26289628

  4. Genetic diversity affects colony survivorship in commercial honey bee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee (Apis mellifera) queens mate with unusually high numbers of males (average of approximately 12 drones), although there is much variation among queens. One main consequence of such extreme polyandry is an increased diversity of worker genotypes within a colony, which has been shown empirica...

  5. Metatranscriptomic analyses of honey bee colonies

    PubMed Central

    Tozkar, Cansu Ö.; Kence, Meral; Kence, Aykut; Huang, Qiang; Evans, Jay D.

    2015-01-01

    Honey bees face numerous biotic threats from viruses to bacteria, fungi, protists, and mites. Here we describe a thorough analysis of microbes harbored by worker honey bees collected from field colonies in geographically distinct regions of Turkey. Turkey is one of the World's most important centers of apiculture, harboring five subspecies of Apis mellifera L., approximately 20% of the honey bee subspecies in the world. We use deep ILLUMINA-based RNA sequencing to capture RNA species for the honey bee and a sampling of all non-endogenous species carried by bees. After trimming and mapping these reads to the honey bee genome, approximately 10% of the sequences (9–10 million reads per library) remained. These were then mapped to a curated set of public sequences containing ca. Sixty megabase-pairs of sequence representing known microbial species associated with honey bees. Levels of key honey bee pathogens were confirmed using quantitative PCR screens. We contrast microbial matches across different sites in Turkey, showing new country recordings of Lake Sinai virus, two Spiroplasma bacterium species, symbionts Candidatus Schmidhempelia bombi, Frischella perrara, Snodgrassella alvi, Gilliamella apicola, Lactobacillus spp.), neogregarines, and a trypanosome species. By using metagenomic analysis, this study also reveals deep molecular evidence for the presence of bacterial pathogens (Melissococcus plutonius, Paenibacillus larvae), Varroa destructor-1 virus, Sacbrood virus, and fungi. Despite this effort we did not detect KBV, SBPV, Tobacco ringspot virus, VdMLV (Varroa Macula like virus), Acarapis spp., Tropilaeleps spp. and Apocephalus (phorid fly). We discuss possible impacts of management practices and honey bee subspecies on microbial retinues. The described workflow and curated microbial database will be generally useful for microbial surveys of healthy and declining honey bees. PMID:25852743

  6. Metatranscriptomic analyses of honey bee colonies.

    PubMed

    Tozkar, Cansu Ö; Kence, Meral; Kence, Aykut; Huang, Qiang; Evans, Jay D

    2015-01-01

    Honey bees face numerous biotic threats from viruses to bacteria, fungi, protists, and mites. Here we describe a thorough analysis of microbes harbored by worker honey bees collected from field colonies in geographically distinct regions of Turkey. Turkey is one of the World's most important centers of apiculture, harboring five subspecies of Apis mellifera L., approximately 20% of the honey bee subspecies in the world. We use deep ILLUMINA-based RNA sequencing to capture RNA species for the honey bee and a sampling of all non-endogenous species carried by bees. After trimming and mapping these reads to the honey bee genome, approximately 10% of the sequences (9-10 million reads per library) remained. These were then mapped to a curated set of public sequences containing ca. Sixty megabase-pairs of sequence representing known microbial species associated with honey bees. Levels of key honey bee pathogens were confirmed using quantitative PCR screens. We contrast microbial matches across different sites in Turkey, showing new country recordings of Lake Sinai virus, two Spiroplasma bacterium species, symbionts Candidatus Schmidhempelia bombi, Frischella perrara, Snodgrassella alvi, Gilliamella apicola, Lactobacillus spp.), neogregarines, and a trypanosome species. By using metagenomic analysis, this study also reveals deep molecular evidence for the presence of bacterial pathogens (Melissococcus plutonius, Paenibacillus larvae), Varroa destructor-1 virus, Sacbrood virus, and fungi. Despite this effort we did not detect KBV, SBPV, Tobacco ringspot virus, VdMLV (Varroa Macula like virus), Acarapis spp., Tropilaeleps spp. and Apocephalus (phorid fly). We discuss possible impacts of management practices and honey bee subspecies on microbial retinues. The described workflow and curated microbial database will be generally useful for microbial surveys of healthy and declining honey bees. PMID:25852743

  7. Application of the artificial bee colony algorithm for solving the set covering problem.

    PubMed

    Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

    2014-01-01

    The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem. PMID:24883356

  8. Honey Bees Inspired Optimization Method: The Bees Algorithm.

    PubMed

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

    2013-01-01

    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. PMID:26462528

  9. How Can Bee Colony Algorithm Serve Medicine?

    PubMed Central

    Salehahmadi, Zeinab; Manafi, Amir

    2014-01-01

    Healthcare professionals usually should make complex decisions with far reaching consequences and associated risks in health care fields. As it was demonstrated in other industries, the ability to drill down into pertinent data to explore knowledge behind the data can greatly facilitate superior, informed decisions to ensue the facts. Nature has always inspired researchers to develop models of solving the problems. Bee colony algorithm (BCA), based on the self-organized behavior of social insects is one of the most popular member of the family of population oriented, nature inspired meta-heuristic swarm intelligence method which has been proved its superiority over some other nature inspired algorithms. The objective of this model was to identify valid novel, potentially useful, and understandable correlations and patterns in existing data. This review employs a thematic analysis of online series of academic papers to outline BCA in medical hive, reducing the response and computational time and optimizing the problems. To illustrate the benefits of this model, the cases of disease diagnose system are presented. PMID:25489530

  10. How can bee colony algorithm serve medicine?

    PubMed

    Salehahmadi, Zeinab; Manafi, Amir

    2014-07-01

    Healthcare professionals usually should make complex decisions with far reaching consequences and associated risks in health care fields. As it was demonstrated in other industries, the ability to drill down into pertinent data to explore knowledge behind the data can greatly facilitate superior, informed decisions to ensue the facts. Nature has always inspired researchers to develop models of solving the problems. Bee colony algorithm (BCA), based on the self-organized behavior of social insects is one of the most popular member of the family of population oriented, nature inspired meta-heuristic swarm intelligence method which has been proved its superiority over some other nature inspired algorithms. The objective of this model was to identify valid novel, potentially useful, and understandable correlations and patterns in existing data. This review employs a thematic analysis of online series of academic papers to outline BCA in medical hive, reducing the response and computational time and optimizing the problems. To illustrate the benefits of this model, the cases of disease diagnose system are presented. PMID:25489530

  11. A Quantitative Model of Honey Bee Colony Population Dynamics

    PubMed Central

    Khoury, David S.; Myerscough, Mary R.; Barron, Andrew B.

    2011-01-01

    Since 2006 the rate of honey bee colony failure has increased significantly. As an aid to testing hypotheses for the causes of colony failure we have developed a compartment model of honey bee colony population dynamics to explore the impact of different death rates of forager bees on colony growth and development. The model predicts a critical threshold forager death rate beneath which colonies regulate a stable population size. If death rates are sustained higher than this threshold rapid population decline is predicted and colony failure is inevitable. The model also predicts that high forager death rates draw hive bees into the foraging population at much younger ages than normal, which acts to accelerate colony failure. The model suggests that colony failure can be understood in terms of observed principles of honey bee population dynamics, and provides a theoretical framework for experimental investigation of the problem. PMID:21533156

  12. Iridovirus and Microsporidian Linked to Honey Bee Colony Decline

    PubMed Central

    Bromenshenk, Jerry J.; Henderson, Colin B.; Wick, Charles H.; Stanford, Michael F.; Zulich, Alan W.; Jabbour, Rabih E.; Deshpande, Samir V.; McCubbin, Patrick E.; Seccomb, Robert A.; Welch, Phillip M.; Williams, Trevor; Firth, David R.; Skowronski, Evan; Lehmann, Margaret M.; Bilimoria, Shan L.; Gress, Joanna; Wanner, Kevin W.; Cramer, Robert A.

    2010-01-01

    Background In 2010 Colony Collapse Disorder (CCD), again devastated honey bee colonies in the USA, indicating that the problem is neither diminishing nor has it been resolved. Many CCD investigations, using sensitive genome-based methods, have found small RNA bee viruses and the microsporidia, Nosema apis and N. ceranae in healthy and collapsing colonies alike with no single pathogen firmly linked to honey bee losses. Methodology/Principal Findings We used Mass spectrometry-based proteomics (MSP) to identify and quantify thousands of proteins from healthy and collapsing bee colonies. MSP revealed two unreported RNA viruses in North American honey bees, Varroa destructor-1 virus and Kakugo virus, and identified an invertebrate iridescent virus (IIV) (Iridoviridae) associated with CCD colonies. Prevalence of IIV significantly discriminated among strong, failing, and collapsed colonies. In addition, bees in failing colonies contained not only IIV, but also Nosema. Co-occurrence of these microbes consistently marked CCD in (1) bees from commercial apiaries sampled across the U.S. in 2006–2007, (2) bees sequentially sampled as the disorder progressed in an observation hive colony in 2008, and (3) bees from a recurrence of CCD in Florida in 2009. The pathogen pairing was not observed in samples from colonies with no history of CCD, namely bees from Australia and a large, non-migratory beekeeping business in Montana. Laboratory cage trials with a strain of IIV type 6 and Nosema ceranae confirmed that co-infection with these two pathogens was more lethal to bees than either pathogen alone. Conclusions/Significance These findings implicate co-infection by IIV and Nosema with honey bee colony decline, giving credence to older research pointing to IIV, interacting with Nosema and mites, as probable cause of bee losses in the USA, Europe, and Asia. We next need to characterize the IIV and Nosema that we detected and develop management practices to reduce honey bee losses

  13. A balance-evolution artificial bee colony algorithm for protein structure optimization based on a three-dimensional AB off-lattice model.

    PubMed

    Li, Bai; Chiong, Raymond; Lin, Mu

    2015-02-01

    Protein structure prediction is a fundamental issue in the field of computational molecular biology. In this paper, the AB off-lattice model is adopted to transform the original protein structure prediction scheme into a numerical optimization problem. We present a balance-evolution artificial bee colony (BE-ABC) algorithm to address the problem, with the aim of finding the structure for a given protein sequence with the minimal free-energy value. This is achieved through the use of convergence information during the optimization process to adaptively manipulate the search intensity. Besides that, an overall degradation procedure is introduced as part of the BE-ABC algorithm to prevent premature convergence. Comprehensive simulation experiments based on the well-known artificial Fibonacci sequence set and several real sequences from the database of Protein Data Bank have been carried out to compare the performance of BE-ABC against other algorithms. Our numerical results show that the BE-ABC algorithm is able to outperform many state-of-the-art approaches and can be effectively employed for protein structure optimization. PMID:25463349

  14. Chaotic Artificial Bee Colony Used for Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Yudong; Wu, Lenan; Wang, Shuihua; Huo, Yuankai

    A new approach based on artificial bee colony (ABC) with chaotic theory was proposed to solve the partitional clustering problem. We first investigate the optimization model including both the encoding strategy and the variance ratio criterion (VRC). Second, a chaotic ABC algorithm was developed based on the Rossler attractor. Experiments on three types of artificial data of different degrees of overlapping all demonstrate the CABC is superior to both genetic algorithm (GA) and combinatorial particle swarm optimization (CPSO) in terms of robustness and computation time.

  15. Varroa-Virus Interaction in Collapsing Honey Bee Colonies

    PubMed Central

    Francis, Roy M.; Nielsen, Steen L.; Kryger, Per

    2013-01-01

    Varroa mites and viruses are the currently the high-profile suspects in collapsing bee colonies. Therefore, seasonal variation in varroa load and viruses (Acute-Kashmir-Israeli complex (AKI) and Deformed Wing Virus (DWV)) were monitored in a year-long study. We investigated the viral titres in honey bees and varroa mites from 23 colonies (15 apiaries) under three treatment conditions: Organic acids (11 colonies), pyrethroid (9 colonies) and untreated (3 colonies). Approximately 200 bees were sampled every month from April 2011 to October 2011, and April 2012. The 200 bees were split to 10 subsamples of 20 bees and analysed separately, which allows us to determine the prevalence of virus-infected bees. The treatment efficacy was often low for both treatments. In colonies where varroa treatment reduced the mite load, colonies overwintered successfully, allowing the mites and viruses to be carried over with the bees into the next season. In general, AKI and DWV titres did not show any notable response to the treatment and steadily increased over the season from April to October. In the untreated control group, titres increased most dramatically. Viral copies were correlated to number of varroa mites. Most colonies that collapsed over the winter had significantly higher AKI and DWV titres in October compared to survivors. Only treated colonies survived the winter. We discuss our results in relation to the varroa-virus model developed by Stephen Martin. PMID:23526946

  16. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.

    PubMed

    Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

    2016-01-01

    A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

  17. Rapid behavioral maturation accelerates failure of stressed honey bee colonies.

    PubMed

    Perry, Clint J; Søvik, Eirik; Myerscough, Mary R; Barron, Andrew B

    2015-03-17

    Many complex factors have been linked to the recent marked increase in honey bee colony failure, including pests and pathogens, agrochemicals, and nutritional stressors. It remains unclear, however, why colonies frequently react to stressors by losing almost their entire adult bee population in a short time, resulting in a colony population collapse. Here we examine the social dynamics underlying such dramatic colony failure. Bees respond to many stressors by foraging earlier in life. We manipulated the demography of experimental colonies to induce precocious foraging in bees and used radio tag tracking to examine the consequences of precocious foraging for their performance. Precocious foragers completed far fewer foraging trips in their life, and had a higher risk of death in their first flights. We constructed a demographic model to explore how this individual reaction of bees to stress might impact colony performance. In the model, when forager death rates were chronically elevated, an increasingly younger forager force caused a positive feedback that dramatically accelerated terminal population decline in the colony. This resulted in a breakdown in division of labor and loss of the adult population, leaving only brood, food, and few adults in the hive. This study explains the social processes that drive rapid depopulation of a colony, and we explore possible strategies to prevent colony failure. Understanding the process of colony failure helps identify the most effective strategies to improve colony resilience. PMID:25675508

  18. Rapid behavioral maturation accelerates failure of stressed honey bee colonies

    PubMed Central

    Perry, Clint J.; Myerscough, Mary R.; Barron, Andrew B.

    2015-01-01

    Many complex factors have been linked to the recent marked increase in honey bee colony failure, including pests and pathogens, agrochemicals, and nutritional stressors. It remains unclear, however, why colonies frequently react to stressors by losing almost their entire adult bee population in a short time, resulting in a colony population collapse. Here we examine the social dynamics underlying such dramatic colony failure. Bees respond to many stressors by foraging earlier in life. We manipulated the demography of experimental colonies to induce precocious foraging in bees and used radio tag tracking to examine the consequences of precocious foraging for their performance. Precocious foragers completed far fewer foraging trips in their life, and had a higher risk of death in their first flights. We constructed a demographic model to explore how this individual reaction of bees to stress might impact colony performance. In the model, when forager death rates were chronically elevated, an increasingly younger forager force caused a positive feedback that dramatically accelerated terminal population decline in the colony. This resulted in a breakdown in division of labor and loss of the adult population, leaving only brood, food, and few adults in the hive. This study explains the social processes that drive rapid depopulation of a colony, and we explore possible strategies to prevent colony failure. Understanding the process of colony failure helps identify the most effective strategies to improve colony resilience. PMID:25675508

  19. The colony environment modulates sleep in honey bee workers.

    PubMed

    Eban-Rothschild, Ada; Bloch, Guy

    2015-02-01

    One of the most important and evolutionarily conserved roles of sleep is the processing and consolidation of information acquired during wakefulness. In both insects and mammals, environmental and social stimuli can modify sleep physiology and behavior, yet relatively little is known about the specifics of the wake experiences and their relative contribution to experience-dependent modulation of sleep. Honey bees provide an excellent model system in this regard because their behavioral repertoire is well characterized and the environment they experience during the day can be manipulated while keeping an ecologically and sociobiologically relevant context. We examined whether social experience modulates sleep in honey bees, and evaluated the relative contribution of different social signals. We exposed newly emerged bees to different components of their natural social environment and then monitored their sleep behavior in individual cages in a constant lab environment. We found that rich waking experience modulates subsequent sleep. Bees that experienced the colony environment for 1 or 2 days slept more than same-age sister bees that were caged individually or in small groups in the lab. Furthermore, bees placed in mesh-enclosures in the colony, that prevented direct contact with nestmates, slept similarly to bees freely moving in the colony. These results suggest that social signals that do not require direct or close distance interactions between bees are sufficiently rich to encompass almost the entire effect of the colony on sleep. Our findings provide a remarkable example of social experience-dependent modulation of an essential biological process. PMID:25524987

  20. Automatic image enhancement by artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Yimit, Adiljan; Hagihara, Yoshihiro; Miyoshi, Tasuku; Hagihara, Yukari

    2013-03-01

    With regard to the improvement of image quality, image enhancement is an important process to assist human with better perception. This paper presents an automatic image enhancement method based on Artificial Bee Colony (ABC) algorithm. In this method, ABC algorithm is applied to find the optimum parameters of a transformation function, which is used in the enhancement by utilizing the local and global information of the image. In order to solve the optimization problem by ABC algorithm, an objective criterion in terms of the entropy and edge information is introduced to measure the image quality to make the enhancement as an automatic process. Several images are utilized in experiments to make a comparison with other enhancement methods, which are genetic algorithm-based and particle swarm optimization algorithm-based image enhancement methods.

  1. The Importance of Microbes in Nutrition and Health of Honey Bee Colonies Part-2: Factors Affecting the Microbial Community in Honey Bee Colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee colonies have innumerable symbiotic bacteria and fungi that are essential to the health of the colony. In the first part of this series, we discussed the importance of microbes in maintaining the health of honey bee colonies. The bacteria, yeasts and molds that live in a healthy colony a...

  2. Winter Survival of Individual Honey Bees and Honey Bee Colonies Depends on Level of Varroa destructor Infestation

    PubMed Central

    van Dooremalen, Coby; Gerritsen, Lonne; Cornelissen, Bram; van der Steen, Jozef J. M.; van Langevelde, Frank; Blacquière, Tjeerd

    2012-01-01

    Background Recent elevated winter loss of honey bee colonies is a major concern. The presence of the mite Varroa destructor in colonies places an important pressure on bee health. V. destructor shortens the lifespan of individual bees, while long lifespan during winter is a primary requirement to survive until the next spring. We investigated in two subsequent years the effects of different levels of V. destructor infestation during the transition from short-lived summer bees to long-lived winter bees on the lifespan of individual bees and the survival of bee colonies during winter. Colonies treated earlier in the season to reduce V. destructor infestation during the development of winter bees were expected to have longer bee lifespan and higher colony survival after winter. Methodology/Principal Findings Mite infestation was reduced using acaricide treatments during different months (July, August, September, or not treated). We found that the number of capped brood cells decreased drastically between August and November, while at the same time, the lifespan of the bees (marked cohorts) increased indicating the transition to winter bees. Low V. destructor infestation levels before and during the transition to winter bees resulted in an increase in lifespan of bees and higher colony survival compared to colonies that were not treated and that had higher infestation levels. A variety of stress-related factors could have contributed to the variation in longevity and winter survival that we found between years. Conclusions/Significance This study contributes to theory about the multiple causes for the recent elevated colony losses in honey bees. Our study shows the correlation between long lifespan of winter bees and colony loss in spring. Moreover, we show that colonies treated earlier in the season had reduced V. destructor infestation during the development of winter bees resulting in longer bee lifespan and higher colony survival after winter. PMID:22558421

  3. Colonies of Bumble Bees (Bombus impatiens) Produce Fewer Workers, Less Bee Biomass, and Have Smaller Mother Queens Following Fungicide Exposure

    PubMed Central

    Bernauer, Olivia M.; Gaines-Day, Hannah R.; Steffan, Shawn A.

    2015-01-01

    Bees provide vital pollination services to the majority of flowering plants in both natural and agricultural systems. Unfortunately, both native and managed bee populations are experiencing declines, threatening the persistence of these plants and crops. Agricultural chemicals are one possible culprit contributing to bee declines. Even fungicides, generally considered safe for bees, have been shown to disrupt honey bee development and impair bumble bee behavior. Little is known, however, how fungicides may affect bumble bee colony growth. We conducted a controlled cage study to determine the effects of fungicide exposure on colonies of a native bumble bee species (Bombus impatiens). Colonies of B. impatiens were exposed to flowers treated with field-relevant levels of the fungicide chlorothalonil over the course of one month. Colony success was assessed by the number and biomass of larvae, pupae, and adult bumble bees. Bumble bee colonies exposed to fungicide produced fewer workers, lower total bee biomass, and had lighter mother queens than control colonies. Our results suggest that fungicides negatively affect the colony success of a native bumble bee species and that the use of fungicides during bloom has the potential to severely impact the success of native bumble bee populations foraging in agroecosystems. PMID:26463198

  4. Colonies of Bumble Bees (Bombus impatiens) Produce Fewer Workers, Less Bee Biomass, and Have Smaller Mother Queens Following Fungicide Exposure.

    PubMed

    Bernauer, Olivia M; Gaines-Day, Hannah R; Steffan, Shawn A

    2015-01-01

    Bees provide vital pollination services to the majority of flowering plants in both natural and agricultural systems. Unfortunately, both native and managed bee populations are experiencing declines, threatening the persistence of these plants and crops. Agricultural chemicals are one possible culprit contributing to bee declines. Even fungicides, generally considered safe for bees, have been shown to disrupt honey bee development and impair bumble bee behavior. Little is known, however, how fungicides may affect bumble bee colony growth. We conducted a controlled cage study to determine the effects of fungicide exposure on colonies of a native bumble bee species (Bombus impatiens). Colonies of B. impatiens were exposed to flowers treated with field-relevant levels of the fungicide chlorothalonil over the course of one month. Colony success was assessed by the number and biomass of larvae, pupae, and adult bumble bees. Bumble bee colonies exposed to fungicide produced fewer workers, lower total bee biomass, and had lighter mother queens than control colonies. Our results suggest that fungicides negatively affect the colony success of a native bumble bee species and that the use of fungicides during bloom has the potential to severely impact the success of native bumble bee populations foraging in agroecosystems. PMID:26463198

  5. A multiuser detector based on artificial bee colony algorithm for DS-UWB systems.

    PubMed

    Yin, Zhendong; Liu, Xiaohui; Wu, Zhilu

    2013-01-01

    Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the problem of finding the best parameter which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solutions and then iteratively improve them by employing the behavior: moving towards better solutions by means of a neighbor search mechanism while abandoning poor solutions. In this paper, an efficient multiuser detector based on a suboptimal code mapping multiuser detector and artificial bee colony algorithm (SCM-ABC-MUD) is proposed and implemented in direct-sequence ultra-wideband (DS-UWB) systems under the additive white Gaussian noise (AWGN) channel. The simulation results demonstrate that the BER and the near-far effect resistance performances of this proposed algorithm are quite close to those of the optimum multiuser detector (OMD) while its computational complexity is much lower than that of OMD. Furthermore, the BER performance of SCM-ABC-MUD is not sensitive to the number of active users and can obtain a large system capacity. PMID:23983638

  6. Training Spiking Neural Models Using Artificial Bee Colony

    PubMed Central

    Vazquez, Roberto A.; Garro, Beatriz A.

    2015-01-01

    Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

  7. Training spiking neural models using artificial bee colony.

    PubMed

    Vazquez, Roberto A; Garro, Beatriz A

    2015-01-01

    Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

  8. Population dynamics of Varroa destructor (Acari: Varroidae) in commercial honey bee colonies and implications for control

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Treatment schedules to maintain low levels of Varroa mites in honey bee colonies were tested in hives started from either package bees or splits of larger colonies. The schedules were developed based on predictions of Varroa population growth generated from a mathematical model of honey bee colony ...

  9. A non-policing honey bee colony (Apis mellifera capensis)

    NASA Astrophysics Data System (ADS)

    Beekman, Madeleine; Good, Gregory; Allsopp, Mike; Radloff, Sarah; Pirk, Chris; Ratnieks, Francis

    2002-09-01

    In the Cape honey bee Apis mellifera capensis, workers lay female eggs without mating by thelytokous parthenogenesis. As a result, workers are as related to worker-laid eggs as they are to queen-laid eggs and therefore worker policing is expected to be lower, or even absent. This was tested by transferring worker- and queen-laid eggs into three queenright A. m. capensis discriminator colonies and monitoring their removal. Our results show that worker policing is variable in A. m. capensis and that in one colony worker-laid eggs were not removed. This is the first report of a non-policing queenright honey bee colony. DNA microsatellite and morphometric analysis suggests that the racial composition of the three discriminator colonies was different. The variation in policing rates could be explained by differences in degrees of hybridisation between A. m. capensis and A. m. scutellata, although a larger survey is needed to confirm this.

  10. Behavioral Modulation of Infestation by Varroa destructor in Bee Colonies. Implications for Colony Stability.

    PubMed

    de Figueiró Santos, Joyce; Coelho, Flávio Codeço; Bliman, Pierre-Alexandre

    2016-01-01

    Colony Collapse Disorder (CCD) has become a global problem for beekeepers and for the crops that depend on bee pollination. While many factors are known to increase the risk of colony collapse, the ectoparasitic mite Varroa destructor is considered to be the most serious one. Although this mite is unlikely to cause the collapse of hives itself, it is the vector for many viral diseases which are among the likely causes for Colony Collapse Disorder. The effects of V. destructor infestation differ from one part of the world to another, with greater morbidity and higher colony losses in European honey bees (EHB) in Europe, Asia and North America. Although this mite has been present in Brazil for many years, there have been no reports of colony losses amongst Africanized Honey Bees (AHB). Studies carried out in Mexico have highlighted different behavioral responses by the AHB to the presence of the mite, notably as far as grooming and hygienic behavior are concerned. Could these explain why the AHB are less susceptible to Colony Collapse Disorder? In order to answer this question, we have developed a mathematical model of the infestation dynamics to analyze the role of resistance behavior by bees in the overall health of the colony, and as a consequence, its ability to face epidemiological challenges. PMID:27583438

  11. Genetic Stock Identification Of Production Colonies Of Russian Honey Bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The prevalence of Nosema ceranae in managed honey bee colonies has increased dramatically in the past 10 – 20 years worldwide. A variety of genetic testing methods for species identification and prevalence are now available. However sample size and preservation method of samples prior to testing hav...

  12. A metagenomic survey of microbes in honey bee colony collapse disorder

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In Colony Collapse Disorder (CCD), honey bee colonies inexplicably lose all of their workers. CCD has resulted in a loss of 50-90% of colonies in beekeeping operations across the United States. The observation that irradiated combs from affected colonies can be repopulated with naïve bees suggests a...

  13. Probabilistic dynamic deployment of wireless sensor networks by artificial bee colony algorithm.

    PubMed

    Ozturk, Celal; Karaboga, Dervis; Gorkemli, Beyza

    2011-01-01

    As the usage and development of wireless sensor networks are increasing, the problems related to these networks are being realized. Dynamic deployment is one of the main topics that directly affect the performance of the wireless sensor networks. In this paper, the artificial bee colony algorithm is applied to the dynamic deployment of stationary and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A probabilistic detection model is considered to obtain more realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the particle swarm optimization algorithm, which is also a swarm based optimization technique and formerly used in wireless sensor network deployment. Results show artificial bee colony algorithm can be preferable in the dynamic deployment of wireless sensor networks. PMID:22163942

  14. Intracolonial genetic diversity in honey bee (Apis mellifera) colonies increases pollen foraging efficiency

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multiple mating by honey bee queens results in colonies of genotypically diverse workers. Recent studies have demonstrated that increased genetic diversity within a honey bee colony increases the variation in the frequency of tasks performed by workers. We show that genotypically diverse colonies, ...

  15. Flight activity of 4-lb Australian package bee colonies used for almond pollination.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Increasing acreage of almonds in California has increased the demand for honey bee colonies for pollination. Since 2005, domestic U.S. colonies have been supplemented with colonies started from package bees imported from Australia. The need for almond pollination in late winter in California fits we...

  16. Pathogenesis of varroosis at the level of the honey bee (Apis mellifera) colony.

    PubMed

    Wegener, J; Ruhnke, H; Scheller, K; Mispagel, S; Knollmann, U; Kamp, G; Bienefeld, K

    2016-01-01

    The parasitic mite Varroa destructor, in interaction with different viruses, is the main cause of honey bee colony mortality in most parts of the world. Here we studied how effects of individual-level parasitization are reflected by the bee colony as a whole. We measured disease progression in an apiary of 24 hives with differing degree of mite infestation, and investigated its relationship to 28 biometrical, physiological and biochemical indicators. In early summer, when the most heavily infested colonies already showed reduced growth, an elevated ratio of brood to bees, as well as a strong presence of phenoloxidase/prophenoloxidase in hive bees were found to be predictors of the time of colony collapse. One month later, the learning performance of worker bees as well as the activity of glucose oxidase measured from head extracts were significantly linked to the timing of colony collapse. Colonies at the brink of collapse were characterized by reduced weight of winter bees and a strong increase in their relative body water content. Our data confirm the importance of the immune system, known from studies of individually-infested bees, for the pathogenesis of varroosis at colony level. However, they also show that single-bee effects cannot always be extrapolated to the colony as a whole. This fact, together with the prominent role of colony-level factors like the ratio between brood and bees for disease progression, stress the importance of the superorganismal dimension of Varroa research. PMID:27296894

  17. No intracolonial nepotism during colony fissioning in honey bees.

    PubMed

    Rangel, Juliana; Mattila, Heather R; Seeley, Thomas D

    2009-11-01

    Most species of social insects have singly mated queens, but in some species each queen mates with numerous males to create a colony whose workers belong to multiple patrilines. This colony genetic structure creates a potential for intracolonial nepotism. One context with great potential for such nepotism arises in species, like honey bees, whose colonies reproduce by fissioning. During fissioning, workers might nepotistically choose between serving a young (sister) queen or the old (mother) queen, preferring the former if she is a full-sister but the latter if the young queen is only a half-sister. We examined three honeybee colonies that swarmed, and performed paternity analyses on the young (immature) queens and samples of workers who either stayed with the young queens in the nest or left with the mother queen in the swarm. For each colony, we checked whether patrilines represented by immature queens had higher proportions of staying workers than patrilines not represented by immature queens. We found no evidence of this. The absence of intracolonial nepotism during colony fissioning could be because the workers cannot discriminate between full-sister and half-sister queens when they are immature, or because the costs of behaving nepotistically outweigh the benefits. PMID:19692398

  18. No intracolonial nepotism during colony fissioning in honey bees

    PubMed Central

    Rangel, Juliana; Mattila, Heather R.; Seeley, Thomas D.

    2009-01-01

    Most species of social insects have singly mated queens, but in some species each queen mates with numerous males to create a colony whose workers belong to multiple patrilines. This colony genetic structure creates a potential for intracolonial nepotism. One context with great potential for such nepotism arises in species, like honey bees, whose colonies reproduce by fissioning. During fissioning, workers might nepotistically choose between serving a young (sister) queen or the old (mother) queen, preferring the former if she is a full-sister but the latter if the young queen is only a half-sister. We examined three honeybee colonies that swarmed, and performed paternity analyses on the young (immature) queens and samples of workers who either stayed with the young queens in the nest or left with the mother queen in the swarm. For each colony, we checked whether patrilines represented by immature queens had higher proportions of staying workers than patrilines not represented by immature queens. We found no evidence of this. The absence of intracolonial nepotism during colony fissioning could be because the workers cannot discriminate between full-sister and half-sister queens when they are immature, or because the costs of behaving nepotistically outweigh the benefits. PMID:19692398

  19. Fungicide contamination reduces beneficial fungi in bee bread based on an area-wide field study in honey bee, Apis mellifera, colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fermentation by fungi converts stored pollen into bee bread that is fed to and eaten by honey bee larvae, Apis mellifera. To explore the relationship between fungicide spraying and bee bread fungi, samples of bee bread collected from bee colonies pollinating orchards from seven locations over two y...

  20. Differential gene expression of two extreme honey bee (Apis mellifera) colonies showing varroa tolerance and susceptibility.

    PubMed

    Jiang, S; Robertson, T; Mostajeran, M; Robertson, A J; Qiu, X

    2016-06-01

    Varroa destructor, an ectoparasitic mite of honey bees (Apis mellifera), is the most serious pest threatening the apiculture industry. In our honey bee breeding programme, two honey bee colonies showing extreme phenotypes for varroa tolerance/resistance (S88) and susceptibility (G4) were identified by natural selection from a large gene pool over a 6-year period. To investigate potential defence mechanisms for honey bee tolerance to varroa infestation, we employed DNA microarray and real time quantitative (PCR) analyses to identify differentially expressed genes in the tolerant and susceptible colonies at pupa and adult stages. Our results showed that more differentially expressed genes were identified in the tolerant bees than in bees from the susceptible colony, indicating that the tolerant colony showed an increased genetic capacity to respond to varroa mite infestation. In both colonies, there were more differentially expressed genes identified at the pupa stage than at the adult stage, indicating that pupa bees are more responsive to varroa infestation than adult bees. Genes showing differential expression in the colony phenotypes were categorized into several groups based on their molecular functions, such as olfactory signalling, detoxification processes, exoskeleton formation, protein degradation and long-chain fatty acid metabolism, suggesting that these biological processes play roles in conferring varroa tolerance to naturally selected colonies. Identification of differentially expressed genes between the two colony phenotypes provides potential molecular markers for selecting and breeding varroa-tolerant honey bees. PMID:26919127

  1. Discrete artificial bee colony algorithm for lot-streaming flowshop with total flowtime minimization

    NASA Astrophysics Data System (ADS)

    Sang, Hongyan; Gao, Liang; Pan, Quanke

    2012-09-01

    Unlike a traditional flowshop problem where a job is assumed to be indivisible, in the lot-streaming flowshop problem, a job is allowed to overlap its operations between successive machines by splitting it into a number of smaller sub-lots and moving the completed portion of the sub-lots to downstream machine. In this way, the production is accelerated. This paper presents a discrete artificial bee colony (DABC) algorithm for a lot-streaming flowshop scheduling problem with total flowtime criterion. Unlike the basic ABC algorithm, the proposed DABC algorithm represents a solution as a discrete job permutation. An efficient initialization scheme based on the extended Nawaz-Enscore-Ham heuristic is utilized to produce an initial population with a certain level of quality and diversity. Employed and onlooker bees generate new solutions in their neighborhood, whereas scout bees generate new solutions by performing insert operator and swap operator to the best solution found so far. Moreover, a simple but effective local search is embedded in the algorithm to enhance local exploitation capability. A comparative experiment is carried out with the existing discrete particle swarm optimization, hybrid genetic algorithm, threshold accepting, simulated annealing and ant colony optimization algorithms based on a total of 160 randomly generated instances. The experimental results show that the proposed DABC algorithm is quite effective for the lot-streaming flowshop with total flowtime criterion in terms of searching quality, robustness and effectiveness. This research provides the references to the optimization research on lot-streaming flowshop.

  2. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    PubMed

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. PMID:25880524

  3. Protein-ligand docking using fitness learning-based artificial bee colony with proximity stimuli.

    PubMed

    Uehara, Shota; Fujimoto, Kazuhiro J; Tanaka, Shigenori

    2015-07-01

    Protein-ligand docking is an optimization problem, which aims to identify the binding pose of a ligand with the lowest energy in the active site of a target protein. In this study, we employed a novel optimization algorithm called fitness learning-based artificial bee colony with proximity stimuli (FlABCps) for docking. Simulation results revealed that FlABCps improved the success rate of docking, compared to four state-of-the-art algorithms. The present results also showed superior docking performance of FlABCps, in particular for dealing with highly flexible ligands and proteins with a wide and shallow binding pocket. PMID:26050878

  4. Seasonal inconsistencies in the relationship between honey bee longevity in field colonies and laboratory cages

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee longevity during winter might be improved through selective breeding. Measuring winter longevity in field colonies is difficult and might be accomplished using laboratory cages. Hence, The relationship between honey bee longevity in field colonies and laboratory cages was investigated. T...

  5. An artificial bee colony algorithm for locating the critical slip surface in slope stability analysis

    NASA Astrophysics Data System (ADS)

    Kang, Fei; Li, Junjie; Ma, Zhenyue

    2013-02-01

    Determination of the critical slip surface with the minimum factor of safety of a slope is a difficult constrained global optimization problem. In this article, an artificial bee colony algorithm with a multi-slice adjustment method is proposed for locating the critical slip surfaces of soil slopes, and the Spencer method is employed to calculate the factor of safety. Six benchmark examples are presented to illustrate the reliability and efficiency of the proposed technique, and it is also compared with some well-known or recent algorithms for the problem. The results show that the new algorithm is promising in terms of accuracy and efficiency.

  6. An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection

    PubMed Central

    Chen, Wei

    2014-01-01

    Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm. PMID:25089292

  7. Artificial Bee Colony Algorithm Based on Information Learning.

    PubMed

    Gao, Wei-Feng; Huang, Ling-Ling; Liu, San-Yang; Dai, Cai

    2015-12-01

    Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of subpopulation is dynamically adjusted based on the last search experience, which results in a clear division of labor. Furthermore, the two search mechanisms are designed to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively, which acts as the cooperation. Finally, the comparison results on a number of benchmark functions demonstrate that the proposed method performs competitively and effectively when compared to the selected state-of-the-art algorithms. PMID:25594992

  8. Improved artificial bee colony algorithm based gravity matching navigation method.

    PubMed

    Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

    2014-01-01

    Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019

  9. Lévy flight artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Sharma, Harish; Bansal, Jagdish Chand; Arya, K. V.; Yang, Xin-She

    2016-08-01

    Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.

  10. Enhanced probability-selection artificial bee colony algorithm for economic load dispatch: A comprehensive analysis

    NASA Astrophysics Data System (ADS)

    Ghani Abro, Abdul; Mohamad-Saleh, Junita

    2014-10-01

    The prime motive of economic load dispatch (ELD) is to optimize the production cost of electrical power generation through appropriate division of load demand among online generating units. Bio-inspired optimization algorithms have outperformed classical techniques for optimizing the production cost. Probability-selection artificial bee colony (PS-ABC) algorithm is a recently proposed variant of ABC optimization algorithm. PS-ABC generates optimal solutions using three different mutation equations simultaneously. The results show improved performance of PS-ABC over the ABC algorithm. Nevertheless, all the mutation equations of PS-ABC are excessively self-reinforced and, hence, PS-ABC is prone to premature convergence. Therefore, this research work has replaced the mutation equations and has improved the scout-bee stage of PS-ABC for enhancing the algorithm's performance. The proposed algorithm has been compared with many ABC variants and numerous other optimization algorithms on benchmark functions and ELD test cases. The adapted ELD test cases comprise of transmission losses, multiple-fuel effect, valve-point effect and toxic gases emission constraints. The results reveal that the proposed algorithm has the best capability to yield the optimal solution for the problem among the compared algorithms.

  11. A scientific note on the comparison of airborne volatiles produced by commercial bumble bee (Bombus impatiens) and honey bee (Apis mellifera) colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Small hive beetles have been documented as being able to successfully invade commercial bumble bee colonies and find the hives through odors produced by the colonies. We tested the hypothesis that volatiles emanating from Bumble bee and Honeybee colonies were similar by collecting volatiles from wo...

  12. Heat Shielding: A Novel Method of Colonial Thermoregulation in Honey Bees

    NASA Astrophysics Data System (ADS)

    Starks, Philip T.; Gilley, David C.

    Honey bees, Apis mellifera, maintain constant colony temperatures throughout the year. Honey bees fan their wings to cool the colony, and often spread fluid in conjunction with this behavior to induce evaporative cooling. We present an additional, previously undescribed mechanism used by the honey bee to maintain constant colony temperature in response to localized temperature increases. Worker bees shield the comb from external heat sources by positioning themselves on hot interior regions of the hive's walls. Although honey comb and brood comb were both shielded, the temperature-sensitive brood received a greater number of heat shielders and was thus better protected from overheating. Heat shielding appears to be a context-dependent adaptive behavior performed by worker bees who would previously have been considered "unemployed."

  13. Infestation by Pyemotes tritici (Acari, Pyemotidae) causes death of stingless bee colonies (Hymenoptera: Meliponina).

    PubMed

    Menezes, C; Coletto-Silva, A; Gazeta, G S; Kerr, W E

    2009-01-01

    We report the infestation of stingless bee nests by the mite Pyemotes tritici, which killed four colonies of Tetragonisca angustula and one colony of Frieseomelitta varia in Brazil. The first infected colony, a colony of T. angustula, came from an area between Uberlândia and Araguari, Minas Gerais. The transfer of the mites to the other colonies occurred through the transfer of infected combs and subsequent manipulations. Other colonies in the same meliponary, which had not been manipulated, were not infected. The infestation was terminated by isolating the dead colonies from the meliponary. PMID:19554756

  14. An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas

    PubMed Central

    Shao, Jing; Yang, Lina; Peng, Ling; Chi, Tianhe; Wang, Xiaomeng

    2015-01-01

    China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC)-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining “replace” and “alter” operations, and the third is a “swap” strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China), and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing) was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures. PMID:26394148

  15. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps

    PubMed Central

    Mao, Wei; Li, Hao-ru

    2016-01-01

    As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426

  16. An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas.

    PubMed

    Shao, Jing; Yang, Lina; Peng, Ling; Chi, Tianhe; Wang, Xiaomeng

    2015-01-01

    China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC)-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining "replace" and "alter" operations, and the third is a "swap" strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China), and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing) was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures. PMID:26394148

  17. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps.

    PubMed

    Mao, Wei; Lan, Heng-You; Li, Hao-Ru

    2016-01-01

    As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426

  18. Varroa destructor and viruses association in honey bee colonies under different climatic conditions.

    PubMed

    Giacobino, Agostina; Molineri, Ana I; Pacini, Adriana; Fondevila, Norberto; Pietronave, Hernán; Rodríguez, Graciela; Palacio, Alejandra; Bulacio Cagnolo, Natalia; Orellano, Emanuel; Salto, César E; Signorini, Marcelo L; Merke, Julieta

    2016-06-01

    Honey bee colonies are threatened by multiple factors including complex interactions between environmental and diseases such as parasitic mites and viruses. We compared the presence of honeybee-pathogenic viruses and Varroa infestation rate in four apiaries: commercial colonies that received treatment against Varroa and non-treated colonies that did not received any treatment for the last 4 years located in temperate and subtropical climate. In addition, we evaluated the effect of climate and Varroa treatment on deformed wing virus (DWV) amounts. In both climates, DWV was the most prevalent virus, being the only present virus in subtropical colonies. Moreover, colonies from subtropical climate also showed reduced DWV amounts and lower Varroa infestation rates than colonies from temperate climate. Nevertheless, non-treated colonies in both climate conditions are able to survive several years. Environment appears as a key factor interacting with local bee populations and influencing colony survival beyond Varroa and virus presence. PMID:27083139

  19. Effective gene silencing of a microsporidian parasite associated with honey bee (Apis mellifera) colony declines

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee colonies are vulnerable to parasites and pathogens ranging from viruses to vertebrates. An increasingly prevalent disease of managed honey bees is caused by the microsporidian, Nosema ceranae. Microsporidia are basal fungi and obligate parasites with much reduced genomic and cellular compo...

  20. Bumble bee colony dynamics: quantifying the importance of land use and floral resources for colony growth and queen production.

    PubMed

    Crone, Elizabeth E; Williams, Neal M

    2016-04-01

    Bumble bee (Bombus) species are ecologically and economically important pollinators, and many species are in decline. In this article, we develop a mechanistic model to analyse growth trajectories of Bombus vosnesenskii colonies in relation to floral resources and land use. Queen production increased with floral resources and was higher in semi-natural areas than on conventional farms. However, the most important parameter for queen production was the colony growth rate per flower, as opposed to the average number of available flowers. This result indicates the importance of understanding mechanisms of colony growth, in order to predict queen production and enhance bumble bee population viability. Our work highlights the importance of interpreting bumble bee conservation efforts in the context of overall population dynamics and provides a framework for doing so. PMID:26913696

  1. Pathogens as Predictors of Honey Bee Colony Strength in England and Wales

    PubMed Central

    Budge, Giles E.; Pietravalle, Stéphane; Brown, Mike; Laurenson, Lynn; Jones, Ben; Tomkies, Victoria; Delaplane, Keith S.

    2015-01-01

    Inspectors with the UK National Bee Unit were asked for 2007-2008 to target problem apiaries in England and Wales for pathogen screening and colony strength measures. Healthy colonies were included in the sampling to provide a continuum of health conditions. A total of 406 adult bee samples was screened and yielded 7 viral, 1 bacterial, and 2 microsporidial pathogens and 1 ectoparasite (Acarapis woodi). In addition, 108 samples of brood were screened and yielded 4 honey bee viruses. Virus prevalence varied from common (deformed wing virus, black queen cell virus) to complete absence (Israeli acute paralysis virus). When colonies were forced into one of two classes, strong or weak, the weak colonies contained more pathogens in adult bees. Among observed pathogens, only deformed wing virus was able to predict colony strength. The effect was negative such that colonies testing positive for deformed wing virus were likely to have fewer combs of bees or brood. This study constitutes the first record for Nosema ceranae in Great Britain. These results contribute to the growing body of evidence linking pathogens to poor honey bee health. PMID:26186735

  2. Pathogens as Predictors of Honey Bee Colony Strength in England and Wales.

    PubMed

    Budge, Giles E; Pietravalle, Stéphane; Brown, Mike; Laurenson, Lynn; Jones, Ben; Tomkies, Victoria; Delaplane, Keith S

    2015-01-01

    Inspectors with the UK National Bee Unit were asked for 2007-2008 to target problem apiaries in England and Wales for pathogen screening and colony strength measures. Healthy colonies were included in the sampling to provide a continuum of health conditions. A total of 406 adult bee samples was screened and yielded 7 viral, 1 bacterial, and 2 microsporidial pathogens and 1 ectoparasite (Acarapis woodi). In addition, 108 samples of brood were screened and yielded 4 honey bee viruses. Virus prevalence varied from common (deformed wing virus, black queen cell virus) to complete absence (Israeli acute paralysis virus). When colonies were forced into one of two classes, strong or weak, the weak colonies contained more pathogens in adult bees. Among observed pathogens, only deformed wing virus was able to predict colony strength. The effect was negative such that colonies testing positive for deformed wing virus were likely to have fewer combs of bees or brood. This study constitutes the first record for Nosema ceranae in Great Britain. These results contribute to the growing body of evidence linking pathogens to poor honey bee health. PMID:26186735

  3. Seasonal benefits of a natural propolis envelope to honey bee immunity and colony health.

    PubMed

    Borba, Renata S; Klyczek, Karen K; Mogen, Kim L; Spivak, Marla

    2015-11-01

    Honey bees, as social insects, rely on collective behavioral defenses that produce a colony-level immune phenotype, or social immunity, which in turn impacts the immune response of individuals. One behavioral defense is the collection and deposition of antimicrobial plant resins, or propolis, in the nest. We tested the effect of a naturally constructed propolis envelope within standard beekeeping equipment on the pathogen and parasite load of large field colonies, and on immune system activity, virus and storage protein levels of individual bees over the course of a year. The main effect of the propolis envelope was a decreased and more uniform baseline expression of immune genes in bees during summer and autumn months each year, compared with the immune activity in bees with no propolis envelope in the colony. The most important function of the propolis envelope may be to modulate costly immune system activity. As no differences were found in levels of bacteria, pathogens and parasites between the treatment groups, the propolis envelope may act directly on the immune system, reducing the bees' need to activate the physiologically costly production of humoral immune responses. Colonies with a natural propolis envelope had increased colony strength and vitellogenin levels after surviving the winter in one of the two years of the study, despite the fact that the biological activity of the propolis diminished over the winter. A natural propolis envelope acts as an important antimicrobial layer enshrouding the colony, benefiting individual immunity and ultimately colony health. PMID:26449975

  4. A Novel Artificial Bee Colony Based Clustering Algorithm for Categorical Data

    PubMed Central

    2015-01-01

    Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data. PMID:25993469

  5. A novel artificial bee colony based clustering algorithm for categorical data.

    PubMed

    Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

    2015-01-01

    Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data. PMID:25993469

  6. Changes in transcript abundance relating to colony collapse disorder in honey bees (Apis mellifera)

    PubMed Central

    Johnson, Reed M.; Evans, Jay D.; Robinson, Gene E.; Berenbaum, May R.

    2009-01-01

    Colony collapse disorder (CCD) is a mysterious disappearance of honey bees that has beset beekeepers in the United States since late 2006. Pathogens and other environmental stresses, including pesticides, have been linked to CCD, but a causal relationship has not yet been demonstrated. Because the gut acts as a primary interface between the honey bee and its environment as a site of entry for pathogens and toxins, we used whole-genome microarrays to compare gene expression between guts of bees from CCD colonies originating on both the east and west coasts of the United States and guts of bees from healthy colonies sampled before the emergence of CCD. Considerable variation in gene expression was associated with the geographical origin of bees, but a consensus list of 65 transcripts was identified as potential markers for CCD status. Overall, elevated expression of pesticide response genes was not observed. Genes involved in immune response showed no clear trend in expression pattern despite the increased prevalence of viruses and other pathogens in CCD colonies. Microarray analysis revealed unusual ribosomal RNA fragments that were conspicuously more abundant in the guts of CCD bees. The presence of these fragments may be a possible consequence of picorna-like viral infection, including deformed wing virus and Israeli acute paralysis virus, and may be related to arrested translation. Ribosomal fragment abundance and presence of multiple viruses may prove to be useful diagnostic markers for colonies afflicted with CCD. PMID:19706391

  7. Changes in transcript abundance relating to colony collapse disorder in honey bees (Apis mellifera).

    PubMed

    Johnson, Reed M; Evans, Jay D; Robinson, Gene E; Berenbaum, May R

    2009-09-01

    Colony collapse disorder (CCD) is a mysterious disappearance of honey bees that has beset beekeepers in the United States since late 2006. Pathogens and other environmental stresses, including pesticides, have been linked to CCD, but a causal relationship has not yet been demonstrated. Because the gut acts as a primary interface between the honey bee and its environment as a site of entry for pathogens and toxins, we used whole-genome microarrays to compare gene expression between guts of bees from CCD colonies originating on both the east and west coasts of the United States and guts of bees from healthy colonies sampled before the emergence of CCD. Considerable variation in gene expression was associated with the geographical origin of bees, but a consensus list of 65 transcripts was identified as potential markers for CCD status. Overall, elevated expression of pesticide response genes was not observed. Genes involved in immune response showed no clear trend in expression pattern despite the increased prevalence of viruses and other pathogens in CCD colonies. Microarray analysis revealed unusual ribosomal RNA fragments that were conspicuously more abundant in the guts of CCD bees. The presence of these fragments may be a possible consequence of picorna-like viral infection, including deformed wing virus and Israeli acute paralysis virus, and may be related to arrested translation. Ribosomal fragment abundance and presence of multiple viruses may prove to be useful diagnostic markers for colonies afflicted with CCD. PMID:19706391

  8. Weighted Global Artificial Bee Colony Algorithm Makes Gas Sensor Deployment Efficient

    PubMed Central

    Jiang, Ye; He, Ziqing; Li, Yanhai; Xu, Zhengyi; Wei, Jianming

    2016-01-01

    This paper proposes an improved artificial bee colony algorithm named Weighted Global ABC (WGABC) algorithm, which is designed to improve the convergence speed in the search stage of solution search equation. The new method not only considers the effect of global factors on the convergence speed in the search phase, but also provides the expression of global factor weights. Experiment on benchmark functions proved that the algorithm can improve the convergence speed greatly. We arrive at the gas diffusion concentration based on the theory of CFD and then simulate the gas diffusion model with the influence of buildings based on the algorithm. Simulation verified the effectiveness of the WGABC algorithm in improving the convergence speed in optimal deployment scheme of gas sensors. Finally, it is verified that the optimal deployment method based on WGABC algorithm can improve the monitoring efficiency of sensors greatly as compared with the conventional deployment methods. PMID:27322262

  9. Weighted Global Artificial Bee Colony Algorithm Makes Gas Sensor Deployment Efficient.

    PubMed

    Jiang, Ye; He, Ziqing; Li, Yanhai; Xu, Zhengyi; Wei, Jianming

    2016-01-01

    This paper proposes an improved artificial bee colony algorithm named Weighted Global ABC (WGABC) algorithm, which is designed to improve the convergence speed in the search stage of solution search equation. The new method not only considers the effect of global factors on the convergence speed in the search phase, but also provides the expression of global factor weights. Experiment on benchmark functions proved that the algorithm can improve the convergence speed greatly. We arrive at the gas diffusion concentration based on the theory of CFD and then simulate the gas diffusion model with the influence of buildings based on the algorithm. Simulation verified the effectiveness of the WGABC algorithm in improving the convergence speed in optimal deployment scheme of gas sensors. Finally, it is verified that the optimal deployment method based on WGABC algorithm can improve the monitoring efficiency of sensors greatly as compared with the conventional deployment methods. PMID:27322262

  10. First analysis of risk factors associated with bee colony collapse disorder by classification and regression trees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sudden losses of managed honey bee (Apis mellifera L.) colonies are considered an important problem worldwide but the underlying cause or causes of these losses are currently unknown. In the United States, this syndrome was termed Colony Collapse Disorder (CCD), since the defining trait was a rapid ...

  11. A survey of managed honey bee colony losses in the USA, fall 2009 to winter 2010

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study records the fourth consecutive year of high winter losses in managed honey bee (Apis mellifera) colonies in the USA. Over the winter of 2009-2010, US beekeepers responding to this survey lost an average of 42.2% of their colonies, for a total loss of 34.4%. Commercial beekeepers (those op...

  12. Intrinsic colony conditions affect the provisioning and oviposition process in the stingless bee Melipona scutellaris.

    PubMed

    Pereira, R A; Morais, M M; Nascimento, F S; Bego, L R

    2009-01-01

    The cell provisioning and oviposition process (POP) is a unique characteristic of stingless bees (Meliponini), in which coordinated interactions between workers and queen regulate the filling of brood cells with larval resources and subsequent egg laying. Environmental conditions seem to regulate reproduction in stingless bees; however, little is known about how the amount of food affects quantitative sequences of the process. We examined intrinsic variables by comparing three colonies in distinct conditions (strong, intermediate and weak state). We predicted that some of these variables are correlated with temporal events of POP in Melipona scutellaris colonies. The results demonstrated that the strong colony had shorter periods of POP. PMID:19554772

  13. Application of Artificial Bee Colony algorithm in TEC seismo-ionospheric anomalies detection

    NASA Astrophysics Data System (ADS)

    Akhoondzadeh, M.

    2015-09-01

    In this study, the efficiency of Artificial Bee Colony (ABC) algorithm is investigated to detect the TEC (Total Electron Content) seismo-ionospheric anomalies around the time of some strong earthquakes including Chile (27 February 2010; 01 April 2014), Varzeghan (11 August 2012), Saravan (16 April 2013) and Papua New Guinea (29 March 2015). In comparison with other anomaly detection algorithms, ABC has a number of advantages which can be numerated as (1) detection of discord patterns in a large non linear data during a short time, (2) simplicity, (3) having less control parameters and (4) efficiently for solving multimodal and multidimensional optimization problems. Also the results of this study acknowledge the TEC time-series as a robust earthquake precursor.

  14. Critical aspects of the Nosema spp. diagnostic sampling in honey bee (Apis mellifera L.) colonies.

    PubMed

    Botías, Cristina; Martín-Hernández, Raquel; Meana, Aránzazu; Higes, Mariano

    2012-06-01

    Nosemosis is one of the most widespread of the adult honey bee diseases and causes major economic losses to beekeepers. Two microsporidia have been described infecting honey bees worldwide, Nosema apis and Nosema ceranae, whose seasonality and pathology differ markedly. An increasing prevalence of microsporidian infections in honey bees has been observed worldwide during the last years. Because nosemosis has detrimental effects on both strength and productivity of the infected colonies, an accurate and reliable method to evaluate the presence of Nosema in honey bee colonies is needed. In this study a high degree of variability in the detection of microsporidia depending on the random subsample analyzed was found, suggesting that both sample size and the time of collection (month and day of sampling) notably affect the diagnosis. PMID:22193523

  15. Colony size evolution and the origin of eusociality in corbiculate bees (Hymenoptera: Apinae).

    PubMed

    Rodriguez-Serrano, Enrique; Inostroza-Michael, Oscar; Avaria-Llautureo, Jorge; Hernandez, Cristian E

    2012-01-01

    Recently, it has been proposed that the one of the main determinants of complex societies in Hymenoptera is colony size, since the existence of large colonies reduces the direct reproductive success of an average individual, given a decreased chance of being part of the reproductive caste. In this study, we evaluate colony size evolution in corbiculate bees and their relationship with the sociality level shown by these bees. Specifically i) the correlation between colony size and level of sociality considering the phylogenetic relationship to evaluate a general evolutionary tendency, and ii) the hypothetical ancestral forms of several clades within a phylogeny of corbiculate bees, to address idiosyncratic process occurring at important nodes. We found that the level of social complexity in corbiculate bees is phylogenetically correlated with colony size. Additionally, another process is invoked to propose why colony size evolved concurrently with the level of social complexity. The study of this trait improves the understanding of the evolutionary transition from simple to complex societies, and highlights the importance of explicit probabilistic models to test the evolution of other important characters involved in the origin of eusociality. PMID:22808274

  16. Colony Size Evolution and the Origin of Eusociality in Corbiculate Bees (Hymenoptera: Apinae)

    PubMed Central

    Rodriguez-Serrano, Enrique; Inostroza-Michael, Oscar; Avaria-Llautureo, Jorge; Hernandez, Cristian E.

    2012-01-01

    Recently, it has been proposed that the one of the main determinants of complex societies in Hymenoptera is colony size, since the existence of large colonies reduces the direct reproductive success of an average individual, given a decreased chance of being part of the reproductive caste. In this study, we evaluate colony size evolution in corbiculate bees and their relationship with the sociality level shown by these bees. Specifically i) the correlation between colony size and level of sociality considering the phylogenetic relationship to evaluate a general evolutionary tendency, and ii) the hypothetical ancestral forms of several clades within a phylogeny of corbiculate bees, to address idiosyncratic process occurring at important nodes. We found that the level of social complexity in corbiculate bees is phylogenetically correlated with colony size. Additionally, another process is invoked to propose why colony size evolved concurrently with the level of social complexity. The study of this trait improves the understanding of the evolutionary transition from simple to complex societies, and highlights the importance of explicit probabilistic models to test the evolution of other important characters involved in the origin of eusociality. PMID:22808274

  17. Influence of pesticide residues on honey bee (Hymenoptera: Apidae) colony health in France.

    PubMed

    Chauzat, Marie-Pierre; Carpentier, Patrice; Martel, Anne-Claire; Bougeard, Stéphanie; Cougoule, Nicolas; Porta, Philippe; Lachaize, Julie; Madec, François; Aubert, Michel; Faucon, Jean-Paul

    2009-06-01

    A 3-yr field survey was carried out in France, from 2002 to 2005, to study honey bee (Apis mellifera L.) colony health in relation to pesticide residues found in the colonies. This study was motivated by recent massive losses of honey bee colonies, and our objective was to examine the possible relationship between low levels of pesticide residues in apicultural matrices (honey, pollen collected by honey bees, beeswax) and colony health as measured by colony mortality and adult and brood population abundance. When all apicultural matrices were pooled together, the number of pesticide residue detected per sampling period (four sampling periods per year) and per apiary ranged from 0 to 9, with the most frequent being two (29.6%). No pesticide residues were detected during 12.7% of the sampling periods. Residues of imidacloprid and 6- chloronicotinic acid were the most frequently detected in pollen loads, honey, and honey bee matrices. Several pairs of active ingredients were present concurrently within honey bees and in pollen loads but not in beeswax and honey samples. No statistical relationship was found between colony mortality and pesticide residues. When pesticide residues from all matrices were pooled together, a mixed model analysis did not show a significant relationship between the presence of pesticide residues and the abundance of brood and adults, and no statistical relationship was found between colony mortality and pesticide residues. Thus, although certain pesticide residues were detected in apicultural matrices and occasionally with another pesticide residual, more work is needed to determine the role these residues play in affecting colony health. PMID:19508759

  18. Organization model for Mobile Wireless Sensor Networks inspired in Artificial Bee Colony

    NASA Astrophysics Data System (ADS)

    Freire Roberto, Guilherme; Castilho Maschi, Luis Fernando; Pigatto, Daniel Fernando; Jaquie Castelo Branco, Kalinka Regina Lucas; Alves Neves, Leandro; Montez, Carlos; Sandro Roschildt Pinto, Alex

    2015-01-01

    The purpose of this study is to find a self-organizing model for MWSN based on bee colonies in order to reduce the number of messages transmitted among nodes, and thus reduce the overall consumption energy while maintaining the efficiency of message delivery. The results obtained in this article are originated from simulations carried out with SINALGO software, which demonstrates the effectiveness of the proposed approach. The BeeAODV (Bee Ad-Hoc On Demand Distance Vector) proposed in this paper allows to considerably reduce message exchanges whether compared to AODV (Ad-Hoc On Demand Distance Vector).

  19. The Effects of Hive Size, Feeding, and Nosema ceranae on the Size of Winter Clusters of Russian Honey Bee Colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    USDA-ARS Russian honey bees are naturally inclined to produce smaller colonies during winter than Italian honey bees. Consequently, fewer of them are likely to meet the size standards necessary for almond pollination in February. Management procedures may result in more Russian colonies grading well...

  20. Israeli acute paralysis virus: epidemiology, pathogenesis and implications for honey bee health and Colony Collapse Disorder (CCD)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Israeli acute paralysis virus (IAPV) is a widespread RNA virus that was linked with honey bee Colony Collapse Disorder (CCD), the sudden and massive die-off of honey bee colonies in the U.S. in 2006-2007. Here we describe the transmission, prevalence and genetic diversity of IAPV, host transcripti...

  1. Characterization of viral siRNA populations in honey bee colony collapse disorder.

    PubMed

    Chejanovsky, Nor; Ophir, Ron; Schwager, Michal Sharabi; Slabezki, Yossi; Grossman, Smadar; Cox-Foster, Diana

    2014-04-01

    Colony Collapse Disorder (CCD), a special case of collapse of honey bee colonies, has resulted in significant losses for beekeepers. CCD-colonies show abundance of pathogens which suggests that they have a weakened immune system. Since honey bee viruses are major players in colony collapse and given the important role of viral RNA interference (RNAi) in combating viral infections we investigated if CCD-colonies elicit an RNAi response. Deep-sequencing analysis of samples from CCD-colonies from US and Israel revealed abundant small interfering RNAs (siRNA) of 21-22 nucleotides perfectly matching the Israeli acute paralysis virus (IAPV), Kashmir virus and Deformed wing virus genomes. Israeli colonies showed high titers of IAPV and a conserved RNAi-pattern of matching the viral genome. That was also observed in sample analysis from colonies experimentally infected with IAPV. Our results suggest that CCD-colonies set out a siRNA response that is specific against predominant viruses associated with colony losses. PMID:24725944

  2. UHPLC-DAD method for the determination of neonicotinoid insecticides in single bees and its relevance in honeybee colony loss investigations.

    PubMed

    Tapparo, Andrea; Giorio, Chiara; Soldà, Lidia; Bogialli, Sara; Marton, Daniele; Marzaro, Matteo; Girolami, Vincenzo

    2013-01-01

    In the understanding of colony loss phenomena, a worldwide crisis of honeybee colonies which has serious consequences for both apiculture and bee-pollination-dependent farm production, analytical chemistry can play an important role. For instance, rapid and accurate analytical procedures are currently required to better assess the effects of neonicotinoid insecticides on honeybee health. Since their introduction in agriculture, neonicotinoid insecticides have been blamed for being highly toxic to honeybees, possibly at the nanogram per bee level or lower. As a consequence, most of the analytical methods recently optimized have focused on the analysis of ultratraces of neonicotinoids using liquid chromatography-mass spectrometry techniques to study the effects of sublethal doses. However, recent evidences on two novel routes-seedling guttations and seed coating particulate, both associated with corn crops-that may expose honeybees to huge amounts of neonicotinoids in the field, with instantly lethal effects, suggest that selected procedures need optimizing. In the present work, a simplified ultra-high-performance liquid chromatography-diode-array detection method for the determination of neonicotinoids in single bees has been optimized and validated. The method ensures good selectivity, good accuracy, and adequate detection limits, which make it suitable for the purpose, while maintaining its ability to evaluate exposure variability of individual bees. It has been successfully applied to the analysis of bees in free flight over an experimental sowing field, with the bees therefore being exposed to seed coating particulate released by the pneumatic drilling machine. PMID:22965530

  3. The behavioral regulation of thirst, water collection and water storage in honey bee colonies.

    PubMed

    Ostwald, Madeleine M; Smith, Michael L; Seeley, Thomas D

    2016-07-15

    This study investigated how a honey bee colony develops and quenches its collective thirst when it experiences hyperthermia of its broodnest. We found that a colony must strongly boost its water intake because evaporative cooling is critical to relieving broodnest hyperthermia, and that it must rapidly boost its water intake because a colony maintains only a small water reserve. We also clarified how a colony's water collectors know when to spring into action - by sensing either more frequent requests for fluid or greater personal thirst, or both. Finally, we found that the behavioral flexibility of a colony's water collectors enables them not only to satisfy their colony's current water needs but also to buffer their colony against future extreme water stresses by storing water in their crops and in their combs. PMID:27445400

  4. Stable genetic diversity despite parasite and pathogen spread in honey bee colonies

    NASA Astrophysics Data System (ADS)

    Jara, Laura; Muñoz, Irene; Cepero, Almudena; Martín-Hernández, Raquel; Serrano, José; Higes, Mariano; De la Rúa, Pilar

    2015-10-01

    In the last decades, the rapid spread of diseases, such as varroosis and nosemosis, associated with massive honey bee colonies mortality around the world has significantly decreased the number and size of honey bee populations and possibly their genetic diversity. Here, we compare the genetic diversity of Iberian honey bee colonies in two samplings performed in 2006 and 2010 in relation to the presence of the pathogenic agents Nosema apis, Nosema ceranae, and Varroa destructor in order to determine whether parasite and pathogen spread in honey bee colonies reflects changes in genetic diversity. We found that the genetic diversity remained similar, while the incidence of N. ceranae increased and the incidence of N. apis and V. destructor decreased slightly. These results indicate that the genetic diversity was not affected by the presence of these pathogenic agents in the analyzed period. However, the two groups of colonies with and without Nosema/Varroa detected showed significant genetic differentiation (G test). A detailed analysis of the allelic segregation of microsatellite loci in Nosema/Varroa-negative colonies and parasitized ones revealed two outlier loci related to genes involved in immune response.

  5. Stable genetic diversity despite parasite and pathogen spread in honey bee colonies.

    PubMed

    Jara, Laura; Muñoz, Irene; Cepero, Almudena; Martín-Hernández, Raquel; Serrano, José; Higes, Mariano; De la Rúa, Pilar

    2015-10-01

    In the last decades, the rapid spread of diseases, such as varroosis and nosemosis, associated with massive honey bee colonies mortality around the world has significantly decreased the number and size of honey bee populations and possibly their genetic diversity. Here, we compare the genetic diversity of Iberian honey bee colonies in two samplings performed in 2006 and 2010 in relation to the presence of the pathogenic agents Nosema apis, Nosema ceranae, and Varroa destructor in order to determine whether parasite and pathogen spread in honey bee colonies reflects changes in genetic diversity. We found that the genetic diversity remained similar, while the incidence of N. ceranae increased and the incidence of N. apis and V. destructor decreased slightly. These results indicate that the genetic diversity was not affected by the presence of these pathogenic agents in the analyzed period. However, the two groups of colonies with and without Nosema/Varroa detected showed significant genetic differentiation (G test). A detailed analysis of the allelic segregation of microsatellite loci in Nosema/Varroa-negative colonies and parasitized ones revealed two outlier loci related to genes involved in immune response. PMID:26306398

  6. A novel bee swarm optimization algorithm for numerical function optimization

    NASA Astrophysics Data System (ADS)

    Akbari, Reza; Mohammadi, Alireza; Ziarati, Koorush

    2010-10-01

    The optimization algorithms which are inspired from intelligent behavior of honey bees are among the most recently introduced population based techniques. In this paper, a novel algorithm called bee swarm optimization, or BSO, and its two extensions for improving its performance are presented. The BSO is a population based optimization technique which is inspired from foraging behavior of honey bees. The proposed approach provides different patterns which are used by the bees to adjust their flying trajectories. As the first extension, the BSO algorithm introduces different approaches such as repulsion factor and penalizing fitness (RP) to mitigate the stagnation problem. Second, to maintain efficiently the balance between exploration and exploitation, time-varying weights (TVW) are introduced into the BSO algorithm. The proposed algorithm (BSO) and its two extensions (BSO-RP and BSO-RPTVW) are compared with existing algorithms which are based on intelligent behavior of honey bees, on a set of well known numerical test functions. The experimental results show that the BSO algorithms are effective and robust; produce excellent results, and outperform other algorithms investigated in this consideration.

  7. Changes in Learning and Foraging Behaviour within Developing Bumble Bee (Bombus terrestris) Colonies

    PubMed Central

    Evans, Lisa J.; Raine, Nigel E.

    2014-01-01

    Organisation in eusocial insect colonies emerges from the decisions and actions of its individual members. In turn, these decisions and actions are influenced by the individual's behaviour (or temperament). Although there is variation in the behaviour of individuals within a colony, we know surprisingly little about how (or indeed if) the types of behaviour present in a colony change over time. Here, for the first time, we assessed potential changes in the behavioural type of foragers during colony development. Using an ecologically relevant foraging task, we measured the decision speed and learning ability of bumble bees (Bombus terrestris) at different stages of colony development. We determined whether individuals that forage early in the colony life cycle (the queen and early emerging workers) behaved differently from workers that emerge and forage at the end of colony development. Whilst we found no overall change in the foraging behaviour of workers with colony development, there were strong differences in foraging behaviour between queens and their workers. Queens appeared to forage more cautiously than their workers and were also quicker to learn. These behaviours could allow queens to maximise their nectar collecting efficiency whilst avoiding predation. Because the foundress queen is crucial to the survival and success of a bumble bee colony, more efficient foraging behaviour in queens may have strong adaptive value. PMID:24599144

  8. Superinfection exclusion and the long-term survival of honey bees in Varroa-infested colonies.

    PubMed

    Mordecai, Gideon J; Brettell, Laura E; Martin, Stephen J; Dixon, David; Jones, Ian M; Schroeder, Declan C

    2016-05-01

    Over the past 50 years, many millions of European honey bee (Apis mellifera) colonies have died as the ectoparasitic mite, Varroa destructor, has spread around the world. Subsequent studies have indicated that the mite's association with a group of RNA viral pathogens (Deformed Wing Virus, DWV) correlates with colony death. Here, we propose a phenomenon known as superinfection exclusion that provides an explanation of how certain A. mellifera populations have survived, despite Varroa infestation and high DWV loads. Next-generation sequencing has shown that a non-lethal DWV variant 'type B' has become established in these colonies and that the lethal 'type A' DWV variant fails to persist in the bee population. We propose that this novel stable host-pathogen relationship prevents the accumulation of lethal variants, suggesting that this interaction could be exploited for the development of an effective treatment that minimises colony losses in the future. PMID:26505829

  9. Population growth of Varroa destructor (Acari: Varroidae) in commercial honey bee colonies treated with beta plant acids.

    PubMed

    DeGrandi-Hoffman, Gloria; Ahumada, Fabiana; Curry, Robert; Probasco, Gene; Schantz, Lloyd

    2014-10-01

    Varroa (Varroa destuctor Anderson and Trueman) populations in honey bee (Apis mellifera L.) colonies might be kept at low levels by well-timed miticide applications. HopGuard(®) (HG) that contains beta plant acids as the active ingredient was used to reduce mite populations. Schedules for applications of the miticide that could maintain low mite levels were tested in hives started from either package bees or splits of larger colonies. The schedules were developed based on defined parameters for efficacy of the miticide and predictions of varroa population growth generated from a mathematical model of honey bee colony-varroa population dynamics. Colonies started from package bees and treated with HG in the package only or with subsequent HG treatments in the summer had 1.2-2.1 mites per 100 bees in August. Untreated controls averaged significantly more mites than treated colonies (3.3 mites per 100 bees). By October, mite populations ranged from 6.3 to 15.0 mites per 100 bees with the lowest mite numbers in colonies treated with HG in August. HG applications in colonies started from splits in April reduced mite populations to 0.12 mites per 100 bees. In September, the treated colonies had significantly fewer mites than the untreated controls. Subsequent HG applications in September that lasted for 3 weeks reduced mite populations to levels in November that were significantly lower than in colonies that were untreated or had an HG treatment that lasted for 1 week. The model accurately predicted colony population growth and varroa levels until the fall when varroa populations measured in colonies established from package bees or splits were much greater than predicted. Possible explanations for the differences between actual and predicted mite populations are discussed. PMID:24828399

  10. Organophosphorus insecticides in honey, pollen and bees (Apis mellifera L.) and their potential hazard to bee colonies in Egypt.

    PubMed

    Al Naggar, Yahya; Codling, Garry; Vogt, Anja; Naiem, Elsaied; Mona, Mohamed; Seif, Amal; Giesy, John P

    2015-04-01

    There is no clear single factor to date that explains colony loss in bees, but one factor proposed is the wide-spread application of agrochemicals. Concentrations of 14 organophosphorous insecticides (OPs) in honey bees (Apis mellifera) and hive matrices (honey and pollen) were measured to assess their hazard to honey bees. Samples were collected during spring and summer of 2013, from 5 provinces in the middle delta of Egypt. LC/MS-MS was used to identify and quantify individual OPs by use of a modified Quick Easy Cheap Effective Rugged Safe (QuEChERS) method. Pesticides were detected more frequently in samples collected during summer. Pollen contained the greatest concentrations of OPs. Profenofos, chlorpyrifos, malation and diazinon were the most frequently detected OPs. In contrast, ethoprop, phorate, coumaphos and chlorpyrifos-oxon were not detected. A toxic units approach, with lethality as the endpoint was used in an additive model to assess the cumulative potential for adverse effects posed by OPs. Hazard quotients (HQs) in honey and pollen ranged from 0.01-0.05 during spring and from 0.02-0.08 during summer, respectively. HQs based on lethality due to direct exposure of adult worker bees to OPs during spring and summer ranged from 0.04 to 0.1 for best and worst case respectively. It is concluded that direct exposure and/or dietary exposure to OPs in honey and pollen pose little threat due to lethality of bees in Egypt. PMID:25574845

  11. Influence of Honey Bee Genotype and Wintering Method on Wintering Performance of Varroa destructor (Parasitiformes: Varroidae)-Infected Honey Bee (Hymenoptera: Apidae) Colonies in a Northern Climate.

    PubMed

    Bahreini, Rassol; Currie, Robert W

    2015-08-01

    The objective of this study was to assess the effectiveness of a cooperative breeding program designed to enhance winter survival of honey bees (Apis mellifera L.) when exposed to high levels of varroa (Varroa destructor Anderson and Trueman) in outdoor-wintered and indoor-wintered colonies. Half of the colonies from selected and unselected stocks were randomly assigned to be treated with late autumn oxalic acid treatment or to be left untreated. Colonies were then randomly assigned to be wintered either indoors (n = 37) or outdoors (n = 40). Late autumn treatment with oxalic acid did not improve wintering performance. However, genotype of bees affected colony survival and the proportion of commercially viable colonies in spring, as indicated by greater rates of colony survival and commercially viable colonies for selected stock (43% survived and 33% were viable) in comparison to unselected stock (19% survived and 9% were viable) across all treatment groups. Indoor wintering improved spring bee population score, proportion of colonies surviving, and proportion of commercially viable colonies relative to outdoor wintering (73% of selected stock and 41% of unselected stock survived during indoor wintering). Selected stock showed better "tolerance" to varroa as the selected stock also maintained higher bee populations relative to unselected stock. However, there was no evidence of "resistance" in selected colonies (reduced mite densities). Collectively, this experiment showed that breeding can improve tolerance to varroa and this can help minimize colony loss through winter and improve colony wintering performance. Overall, colony wintering success of both genotypes of bees was better when colonies were wintered indoors than when colonies were wintered outdoors. PMID:26470288

  12. Characterization of the Active Microbiotas Associated with Honey Bees Reveals Healthier and Broader Communities when Colonies are Genetically Diverse

    PubMed Central

    Mattila, Heather R.; Rios, Daniela; Walker-Sperling, Victoria E.; Roeselers, Guus; Newton, Irene L. G.

    2012-01-01

    Recent losses of honey bee colonies have led to increased interest in the microbial communities that are associated with these important pollinators. A critical function that bacteria perform for their honey bee hosts, but one that is poorly understood, is the transformation of worker-collected pollen into bee bread, a nutritious food product that can be stored for long periods in colonies. We used 16S rRNA pyrosequencing to comprehensively characterize in genetically diverse and genetically uniform colonies the active bacterial communities that are found on honey bees, in their digestive tracts, and in bee bread. This method provided insights that have not been revealed by past studies into the content and benefits of honey bee-associated microbial communities. Colony microbiotas differed substantially between sampling environments and were dominated by several anaerobic bacterial genera never before associated with honey bees, but renowned for their use by humans to ferment food. Colonies with genetically diverse populations of workers, a result of the highly promiscuous mating behavior of queens, benefited from greater microbial diversity, reduced pathogen loads, and increased abundance of putatively helpful bacteria, particularly species from the potentially probiotic genus Bifidobacterium. Across all colonies, Bifidobacterium activity was negatively correlated with the activity of genera that include pathogenic microbes; this relationship suggests a possible target for understanding whether microbes provide protective benefits to honey bees. Within-colony diversity shapes microbiotas associated with honey bees in ways that may have important repercussions for colony function and health. Our findings illuminate the importance of honey bee-bacteria symbioses and examine their intersection with nutrition, pathogen load, and genetic diversity, factors that are considered key to understanding honey bee decline. PMID:22427917

  13. Characterization of the active microbiotas associated with honey bees reveals healthier and broader communities when colonies are genetically diverse.

    PubMed

    Mattila, Heather R; Rios, Daniela; Walker-Sperling, Victoria E; Roeselers, Guus; Newton, Irene L G

    2012-01-01

    Recent losses of honey bee colonies have led to increased interest in the microbial communities that are associated with these important pollinators. A critical function that bacteria perform for their honey bee hosts, but one that is poorly understood, is the transformation of worker-collected pollen into bee bread, a nutritious food product that can be stored for long periods in colonies. We used 16S rRNA pyrosequencing to comprehensively characterize in genetically diverse and genetically uniform colonies the active bacterial communities that are found on honey bees, in their digestive tracts, and in bee bread. This method provided insights that have not been revealed by past studies into the content and benefits of honey bee-associated microbial communities. Colony microbiotas differed substantially between sampling environments and were dominated by several anaerobic bacterial genera never before associated with honey bees, but renowned for their use by humans to ferment food. Colonies with genetically diverse populations of workers, a result of the highly promiscuous mating behavior of queens, benefited from greater microbial diversity, reduced pathogen loads, and increased abundance of putatively helpful bacteria, particularly species from the potentially probiotic genus Bifidobacterium. Across all colonies, Bifidobacterium activity was negatively correlated with the activity of genera that include pathogenic microbes; this relationship suggests a possible target for understanding whether microbes provide protective benefits to honey bees. Within-colony diversity shapes microbiotas associated with honey bees in ways that may have important repercussions for colony function and health. Our findings illuminate the importance of honey bee-bacteria symbioses and examine their intersection with nutrition, pathogen load, and genetic diversity, factors that are considered key to understanding honey bee decline. PMID:22427917

  14. Combined pesticide exposure severely affects individual- and colony-level traits in bees

    PubMed Central

    Gill, Richard J.; Ramos-Rodriguez, Oscar; Raine, Nigel E.

    2012-01-01

    Reported widespread declines of wild and managed insect pollinators have serious consequences for global ecosystem services and agricultural production1-3. Bees contribute around 80% of insect pollination, so it is imperative we understand and mitigate the causes of current declines4-6. Recent studies have implicated the role of pesticides as exposure to these chemicals has been associated with changes in bee behaviour7-11 and reductions in colony queen production12. However the key link between changes in individual behaviour and consequent impact at the colony level has not been shown. Social bee colonies depend on the collective performance of numerous individual workers. So whilst field-level pesticide concentrations can have a subtle/sublethal effect at the individual level8, it is not known whether bee societies can buffer such effects or if it results in a severe cumulative effect at the colony level. Furthermore, widespread agricultural intensification means bees are exposed to numerous pesticides when foraging13-15, yet the possible combinatorial effects of pesticide exposure have rarely been investigated16,17. Here we show that chronic exposure of bumblebees to two pesticides (neonicotinoid and pyrethroid) at concentrations that could approximate field-level exposure impairs natural foraging behaviour and increases worker mortality leading to significant reductions in brood development and colony success. We found worker foraging performance, particularly pollen collecting efficiency, was significantly reduced with observed knock-on effects for forager recruitment, worker losses and overall worker productivity. Moreover, we provide evidence that combinatorial exposure to pesticides increases the propensity of colonies to fail. PMID:23086150

  15. Paratransgenesis: an approach to improve colony health and molecular insight in honey bees (Apis mellifera)?

    PubMed

    Rangberg, Anbjørg; Diep, Dzung B; Rudi, Knut; Amdam, Gro V

    2012-07-01

    The honey bee (Apis mellifera) is highly valued as a commercial crop pollinator and a model animal in research. Over the past several years, governments, beekeepers, and the general public in the United States and Europe have become concerned by increased losses of honey bee colonies, calling for more research on how to keep colonies healthy while still employing them extensively in agriculture. The honey bee, like virtually all multicellular organisms, has a mutually beneficial relationship with specific microbes. The microbiota of the gut can contribute essential nutrients and vitamins and prevent colonization by non-indigenous and potentially harmful species. The gut microbiota is also of interest as a resource for paratransgenesis; a Trojan horse strategy based on genetically modified symbiotic microbes that express effector molecules antagonizing development or transmission of pathogens. Paratransgenesis was originally engineered to combat human diseases and agricultural pests that are vectored by insects. We suggest an alternative use, as a method to promote health of honey bees and to expand the molecular toolbox for research on this beneficial social insect. The honey bees' gut microbiota contains lactic acid bacteria including the genus Lactobacillus that has paratransgenic potential. We present a strategy for transforming one Lactobacillus species, L. kunkeei, for use as a vector to promote health of honey bees and functional genetic research. PMID:22659204

  16. Changes in Gene Expression Relating to Colony Collapse Disorder in honey bees, Apis mellifera

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Colony collapse disorder (CCD) is a mysterious disappearance of honey bees that has beset beekeepers in the United States since late in 2006. Pathogens and other environmental stresses, including pesticides, have been linked to CCD, but a causal relationship has not yet been demonstrated. The gut,...

  17. Acceptance of mated Queens and Queen Cells in Colonies of Russian and Italian Honey Bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Requeening colonies is a standard beekeeping practice with both mated queens and queen cells. More beekeepers are requeening with Russian honey bees queens because of their significantly higher resistance to varroa and tracheal mites, their good honey production and their overwintering abilities. ...

  18. Bigger is better: honey bee colonies as distributed information-gathering systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In collectively foraging groups, communication about food resources can play an important role in the organization of the group’s activity. For example, the honey bee waggle dance allows colonies to selectively allocate foragers among different floral resources according to their quality. Because ...

  19. Assessment of chronic sublethal effects of imidacloprid on honey bee colony health

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Here we present results of a three-year study to determine the fate of imidacloprid residues in hive matrices and to assess chronic sublethal effects on whole honey bee colonies fed supplemental pollen diet containing imidacloprid at 5, 20 and 100 µg/kg over multiple brood cycles. Various endpoints ...

  20. SONIC DIGITIZER AS AN ALTERNATIVE METHOD TO ASSESS HONEY BEE (HYMENOPTERA: APIDAE) COLONY DYNAMICS

    EPA Science Inventory

    Areas of comb can be used to assess qualities of honey bee, Apis mellifera L., colony dynamics such as brood rearing, hoarding behavior, and food stores. isual estimates, grid overlays, photography, and combinations of these methods have been used to approximate measurements of c...

  1. The Importance of Microbes in Nutrition and Health of Honey Bee Colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microbes play an essential role in the health of nearly every organism. Humans have innumerable microbes in their digestive system to help with the processing of food. Honey bee colonies also have an array of bacteria and fungi that are essential for the storing and processing of food (especially ...

  2. A novel artificial bee colony approach of live virtual machine migration policy using Bayes theorem.

    PubMed

    Xu, Gaochao; Ding, Yan; Zhao, Jia; Hu, Liang; Fu, Xiaodong

    2013-01-01

    Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful. PMID:24385877

  3. A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

    PubMed Central

    Xu, Gaochao; Hu, Liang; Fu, Xiaodong

    2013-01-01

    Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful. PMID:24385877

  4. Detect Nosema parasite in time to save bee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nosema is an intracellular pathogenic fungus that causes infection in adult honey bees. In contrast with N. apis, nosemosis produced by N. ceranae is not readily detectable and often goes unnoticed for long periods of time. Here we describe production of a new genomic antibody (Ab) developed against...

  5. Four Categories of Viral Infection Describe the Health Status of Honey Bee Colonies.

    PubMed

    Amiri, Esmaeil; Meixner, Marina; Nielsen, Steen Lykke; Kryger, Per

    2015-01-01

    Honey bee virus prevalence data are an essential prerequisite for managing epidemic events in a population. A survey study was carried out for seven viruses in colonies representing a healthy Danish honey bee population. In addition, colonies from apiaries with high level Varroa infestation or high level of winter mortality were also surveyed. Results from RT-qPCR showed a considerable difference of virus levels between healthy and sick colonies. In the group of healthy colonies, no virus was detected in 36% of cases, while at least one virus was found in each of the sick colonies. Virus titers varied among the samples, and multiple virus infections were common in both groups with a high prevalence of Sacbrood virus (SBV), Black queen cell virus (BQCV) and Deformed wing virus (DWV). Based on the distribution of virus titers, we established four categories of infection: samples free of virus (C = 0), samples with low virus titer (estimated number of virus copies 0 < C < 103), samples with medium virus titer (103 ≤ C < 107) and samples with high virus titer (C ≥ 107). This allowed us to statistically compare virus levels in healthy and sick colonies. Using categories to communicate virus diagnosis results to beekeepers may help them to reach an informed decision on management strategies to prevent further spread of viruses among colonies. PMID:26448627

  6. Four Categories of Viral Infection Describe the Health Status of Honey Bee Colonies

    PubMed Central

    Amiri, Esmaeil; Meixner, Marina; Nielsen, Steen Lykke; Kryger, Per

    2015-01-01

    Honey bee virus prevalence data are an essential prerequisite for managing epidemic events in a population. A survey study was carried out for seven viruses in colonies representing a healthy Danish honey bee population. In addition, colonies from apiaries with high level Varroa infestation or high level of winter mortality were also surveyed. Results from RT-qPCR showed a considerable difference of virus levels between healthy and sick colonies. In the group of healthy colonies, no virus was detected in 36% of cases, while at least one virus was found in each of the sick colonies. Virus titers varied among the samples, and multiple virus infections were common in both groups with a high prevalence of Sacbrood virus (SBV), Black queen cell virus (BQCV) and Deformed wing virus (DWV). Based on the distribution of virus titers, we established four categories of infection: samples free of virus (C = 0), samples with low virus titer (estimated number of virus copies 0 < C < 103), samples with medium virus titer (103 ≤ C < 107) and samples with high virus titer (C ≥ 107). This allowed us to statistically compare virus levels in healthy and sick colonies. Using categories to communicate virus diagnosis results to beekeepers may help them to reach an informed decision on management strategies to prevent further spread of viruses among colonies. PMID:26448627

  7. Colony failure linked to low sperm viability in honey bee (Apis mellifera) queens and an exploration of potential causative factors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Queen health is closely linked to colony performance in honey bees as a single queen is normally responsible for all egg laying and brood production within the colony. In the U. S. in recent years, queens have been failing at a high rate; with 50% or greater of queens replaced in colonies within 6 m...

  8. Comparison of productivity of colonies of honey bees, Apis mellifera, supplemented with sucrose or high fructose corn syrup

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee colony feeding trials were conducted to determine whether differential effects of carbohydrate feeding (sucrose syrup vs. high fructose corn syrups) were detected between colonies fed exclusively on these syrups. In one experiment, colonies installed within a closed arena had increased pr...

  9. The Potential of Bee-Generated Carbon Dioxide for Control of Varroa Mite (Mesostigmata: Varroidae) in Indoor Overwintering Honey bee (Hymenoptera: Apidae) Colonies.

    PubMed

    Bahreini, Rassol; Currie, Robert W

    2015-10-01

    The objective of this study was to manipulate ventilation rate to characterize interactions between stocks of honey bees (Apis mellifera L.) and ventilation setting on varroa mite (Varroa destructor Anderson and Trueman) mortality in honey bee colonies kept indoors over winter. The first experiment used colonies established from stock selected locally for wintering performance under exposure to varroa (n = 6) and unselected bees (n = 6) to assess mite and bee mortality and levels of carbon dioxide (CO2) and oxygen (O2) in the bee cluster when kept under a simulated winter condition at 5°C. The second experiment, used colonies from selected bees (n = 10) and unselected bees (n = 12) that were exposed to either standard ventilation (14.4 liter/min per hive) or restricted ventilation (0.24 liter/min per hive, in a Plexiglas ventilation chamber) during a 16-d treatment period to assess the influence of restricted air flow on winter mortality rates of varroa mites and honey bees. Experiment 2 was repeated in early, mid-, and late winter. The first experiment showed that under unrestricted ventilation with CO2 concentrations averaging <2% there was no correlation between CO2 and varroa mite mortality when colonies were placed under low temperature. CO2 was negatively correlated with O2 in the bee cluster in both experiments. When ventilation was restricted, mean CO2 level (3.82 ± 0.31%, range 0.43-8.44%) increased by 200% relative to standard ventilation (1.29 ± 0.31%; range 0.09-5.26%) within the 16-d treatment period. The overall mite mortality rates and the reduction in mean abundance of varroa mite over time was greater under restricted ventilation (37 ± 4.2%) than under standard ventilation (23 ± 4.2%) but not affected by stock of bees during the treatment period. Selected bees showed overall greater mite mortality relative to unselected bees in both experiments. Restricting ventilation increased mite mortality, but did not

  10. Chronic exposure of a honey bee colony to 2.45 GHz continuous wave microwaves

    NASA Technical Reports Server (NTRS)

    Westerdahl, B. B.; Gary, N. E.

    1981-01-01

    A honey bee colony (Apis mellifera L.) was exposed 28 days to 2.45 GHz continuous wave microwaves at a power density (1 mW/sq cm) expected to be associated with rectennae in the solar power satellite power transmission system. Differences found between the control and microwave-treated colonies were not large, and were in the range of normal variation among similar colonies. Thus, there is an indication that microwave treatment had little, if any, effect on (1) flight and pollen foraging activity, (2) maintenance of internal colony temperature, (3) brood rearing activity, (4) food collection and storage, (5) colony weight, and (6) adult populations. Additional experiments are necessary before firm conclusions can be made.

  11. Chronic exposure of a honey bee colony to 2. 45 GHz continuous wave microwaves

    SciTech Connect

    Westerdahl, B.B.; Gary, N.E.

    1981-01-01

    A honey bee colony (Apis mellifera L.) was exposed 28 days to 2.45 GHz continuous wave microwaves at a power density (1 mW/sq cm) expected to be associated with rectennae in the solar power satellite power transmission system. Differences found between the control and microwave-treated colonies were not large, and were in the range of normal variation among similar colonies. Thus, there is an indication that microwave treatment had little, if any, effect on (1) flight and pollen foraging activity, (2) maintenance of internal colony temperature, (3) brood rearing activity, (4) food collection and storage, (5) colony weight, and (6) adult populations. Additional experiments are necessary before firm conclusions can be made.

  12. Pathogens, pests, and economics: drivers of honey bee colony declines and losses.

    PubMed

    Smith, Kristine M; Loh, Elizabeth H; Rostal, Melinda K; Zambrana-Torrelio, Carlos M; Mendiola, Luciana; Daszak, Peter

    2013-12-01

    The Western honey bee (Apis mellifera) is responsible for ecosystem services (pollination) worth US$215 billion annually worldwide and the number of managed colonies has increased 45% since 1961. However, in Europe and the U.S., two distinct phenomena; long-term declines in colony numbers and increasing annual colony losses, have led to significant interest in their causes and environmental implications. The most important drivers of a long-term decline in colony numbers appear to be socioeconomic and political pressure on honey production. In contrast, annual colony losses seem to be driven mainly by the spread of introduced pathogens and pests, and management problems due to a long-term intensification of production and the transition from large numbers of small apiaries to fewer, larger operations. We conclude that, while other causal hypotheses have received substantial interest, the role of pests, pathogens, and management issues requires increased attention. PMID:24496582

  13. Estimating reproductive success of Aethina tumida (Coleoptera: Nitidulidae) in honey bee colonies by trapping emigrating larvae.

    PubMed

    Arbogast, Richard T; Torto, Baldwyn; Willms, Steve; Fombong, Ayuka T; Duehl, Adrian; Teal, Peter E A

    2012-02-01

    The small hive beetle (Aethina tumida Murray) is a scavenger and facultative predator in honey bee colonies, where it feeds on pollen, honey, and bee brood. Although a minor problem in its native Africa, it is an invasive pest of honey bees in the United States and Australia. Adult beetles enter bee hives to oviposit and feed. Larval development occurs within the hive, but mature larvae leave the hive to pupate in soil. The numbers leaving, which can be estimated by trapping, measure the reproductive success of adult beetles in the hive over any given period of time. We describe a trap designed to intercept mature larvae as they reach the end of the bottom board on their way to the ground. Trap efficiency was estimated by releasing groups of 100 larvae into empty brood boxes and counting the numbers trapped. Some larvae escaped, but mean efficiency ranged from 87.2 to 94.2%. We envision the trap as a research tool for study of beetle population dynamics, and we used it to track numbers of larvae leaving active hives for pupation in the soil. The traps detected large increases and then decreases in numbers of larvae leaving colonies that weakened and died. They also detected small numbers of larvae leaving strong European and African colonies, even when no larvae were observed in the hives. PMID:22525070

  14. An efficient artificial bee colony algorithm with application to nonlinear predictive control

    NASA Astrophysics Data System (ADS)

    Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed

    2016-05-01

    In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.

  15. Enhanced ant colony optimization for multiscale problems

    NASA Astrophysics Data System (ADS)

    Hu, Nan; Fish, Jacob

    2016-03-01

    The present manuscript addresses the issue of computational complexity of optimizing nonlinear composite materials and structures at multiple scales. Several solutions are detailed to meet the enormous computational challenge of optimizing nonlinear structures at multiple scales including: (i) enhanced sampling procedure that provides superior performance of the well-known ant colony optimization algorithm, (ii) a mapping-based meshing of a representative volume element that unlike unstructured meshing permits sensitivity analysis on coarse meshes, and (iii) a multilevel optimization procedure that takes advantage of possible weak coupling of certain scales. We demonstrate the proposed optimization procedure on elastic and inelastic laminated plates involving three scales.

  16. Linking Measures of Colony and Individual Honey Bee Health to Survival among Apiaries Exposed to Varying Agricultural Land Use

    PubMed Central

    Smart, Matthew; Pettis, Jeff; Rice, Nathan; Browning, Zac; Spivak, Marla

    2016-01-01

    We previously characterized and quantified the influence of land use on survival and productivity of colonies positioned in six apiaries and found that colonies in apiaries surrounded by more land in uncultivated forage experienced greater annual survival, and generally more honey production. Here, detailed metrics of honey bee health were assessed over three years in colonies positioned in the same six apiaries. The colonies were located in North Dakota during the summer months and were transported to California for almond pollination every winter. Our aim was to identify relationships among measures of colony and individual bee health that impacted and predicted overwintering survival of colonies. We tested the hypothesis that colonies in apiaries surrounded by more favorable land use conditions would experience improved health. We modeled colony and individual bee health indices at a critical time point (autumn, prior to overwintering) and related them to eventual spring survival for California almond pollination. Colony measures that predicted overwintering apiary survival included the amount of pollen collected, brood production, and Varroa destructor mite levels. At the individual bee level, expression of vitellogenin, defensin1, and lysozyme2 were important markers of overwinter survival. This study is a novel first step toward identifying pertinent physiological responses in honey bees that result from their positioning near varying landscape features in intensive agricultural environments. PMID:27027871

  17. Linking Measures of Colony and Individual Honey Bee Health to Survival among Apiaries Exposed to Varying Agricultural Land Use.

    PubMed

    Smart, Matthew; Pettis, Jeff; Rice, Nathan; Browning, Zac; Spivak, Marla

    2016-01-01

    We previously characterized and quantified the influence of land use on survival and productivity of colonies positioned in six apiaries and found that colonies in apiaries surrounded by more land in uncultivated forage experienced greater annual survival, and generally more honey production. Here, detailed metrics of honey bee health were assessed over three years in colonies positioned in the same six apiaries. The colonies were located in North Dakota during the summer months and were transported to California for almond pollination every winter. Our aim was to identify relationships among measures of colony and individual bee health that impacted and predicted overwintering survival of colonies. We tested the hypothesis that colonies in apiaries surrounded by more favorable land use conditions would experience improved health. We modeled colony and individual bee health indices at a critical time point (autumn, prior to overwintering) and related them to eventual spring survival for California almond pollination. Colony measures that predicted overwintering apiary survival included the amount of pollen collected, brood production, and Varroa destructor mite levels. At the individual bee level, expression of vitellogenin, defensin1, and lysozyme2 were important markers of overwinter survival. This study is a novel first step toward identifying pertinent physiological responses in honey bees that result from their positioning near varying landscape features in intensive agricultural environments. PMID:27027871

  18. A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences.

    PubMed

    Karaboga, D; Aslan, S

    2016-01-01

    The great majority of biological sequences share significant similarity with other sequences as a result of evolutionary processes, and identifying these sequence similarities is one of the most challenging problems in bioinformatics. In this paper, we present a discrete artificial bee colony (ABC) algorithm, which is inspired by the intelligent foraging behavior of real honey bees, for the detection of highly conserved residue patterns or motifs within sequences. Experimental studies on three different data sets showed that the proposed discrete model, by adhering to the fundamental scheme of the ABC algorithm, produced competitive or better results than other metaheuristic motif discovery techniques. PMID:27173272

  19. Sub-lethal effects of dietary neonicotinoid insecticide exposure on honey bee queen fecundity and colony development

    PubMed Central

    Wu-Smart, Judy; Spivak, Marla

    2016-01-01

    Many factors can negatively affect honey bee (Apis mellifera L.) health including the pervasive use of systemic neonicotinoid insecticides. Through direct consumption of contaminated nectar and pollen from treated plants, neonicotinoids can affect foraging, learning, and memory in worker bees. Less well studied are the potential effects of neonicotinoids on queen bees, which may be exposed indirectly through trophallaxis, or food-sharing. To assess effects on queen productivity, small colonies of different sizes (1500, 3000, and 7000 bees) were fed imidacloprid (0, 10, 20, 50, and 100 ppb) in syrup for three weeks. We found adverse effects of imidacloprid on queens (egg-laying and locomotor activity), worker bees (foraging and hygienic activities), and colony development (brood production and pollen stores) in all treated colonies. Some effects were less evident as colony size increased, suggesting that larger colony populations may act as a buffer to pesticide exposure. This study is the first to show adverse effects of imidacloprid on queen bee fecundity and behavior and improves our understanding of how neonicotinoids may impair short-term colony functioning. These data indicate that risk-mitigation efforts should focus on reducing neonicotinoid exposure in the early spring when colonies are smallest and queens are most vulnerable to exposure. PMID:27562025

  20. Sub-lethal effects of dietary neonicotinoid insecticide exposure on honey bee queen fecundity and colony development.

    PubMed

    Wu-Smart, Judy; Spivak, Marla

    2016-01-01

    Many factors can negatively affect honey bee (Apis mellifera L.) health including the pervasive use of systemic neonicotinoid insecticides. Through direct consumption of contaminated nectar and pollen from treated plants, neonicotinoids can affect foraging, learning, and memory in worker bees. Less well studied are the potential effects of neonicotinoids on queen bees, which may be exposed indirectly through trophallaxis, or food-sharing. To assess effects on queen productivity, small colonies of different sizes (1500, 3000, and 7000 bees) were fed imidacloprid (0, 10, 20, 50, and 100 ppb) in syrup for three weeks. We found adverse effects of imidacloprid on queens (egg-laying and locomotor activity), worker bees (foraging and hygienic activities), and colony development (brood production and pollen stores) in all treated colonies. Some effects were less evident as colony size increased, suggesting that larger colony populations may act as a buffer to pesticide exposure. This study is the first to show adverse effects of imidacloprid on queen bee fecundity and behavior and improves our understanding of how neonicotinoids may impair short-term colony functioning. These data indicate that risk-mitigation efforts should focus on reducing neonicotinoid exposure in the early spring when colonies are smallest and queens are most vulnerable to exposure. PMID:27562025

  1. Assessment of Chronic Sublethal Effects of Imidacloprid on Honey Bee Colony Health

    PubMed Central

    Dively, Galen P.; Embrey, Michael S.; Kamel, Alaa; Hawthorne, David J.; Pettis, Jeffery S.

    2015-01-01

    Here we present results of a three-year study to determine the fate of imidacloprid residues in hive matrices and to assess chronic sublethal effects on whole honey bee colonies fed supplemental pollen diet containing imidacloprid at 5, 20 and 100 μg/kg over multiple brood cycles. Various endpoints of colony performance and foraging behavior were measured during and after exposure, including winter survival. Imidacloprid residues became diluted or non-detectable within colonies due to the processing of beebread and honey and the rapid metabolism of the chemical. Imidacloprid exposure doses up to 100 μg/kg had no significant effects on foraging activity or other colony performance indicators during and shortly after exposure. Diseases and pest species did not affect colony health but infestations of Varroa mites were significantly higher in exposed colonies. Honey stores indicated that exposed colonies may have avoided the contaminated food. Imidacloprid dose effects was delayed later in the summer, when colonies exposed to 20 and 100 μg/kg experienced higher rates of queen failure and broodless periods, which led to weaker colonies going into the winter. Pooled over two years, winter survival of colonies averaged 85.7, 72.4, 61.2 and 59.2% in the control, 5, 20 and 100 μg/kg treatment groups, respectively. Analysis of colony survival data showed a significant dose effect, and all contrast tests comparing survival between control and treatment groups were significant, except for colonies exposed to 5 μg/kg. Given the weight of evidence, chronic exposure to imidacloprid at the higher range of field doses (20 to 100 μg/kg) in pollen of certain treated crops could cause negative impacts on honey bee colony health and reduced overwintering success, but the most likely encountered high range of field doses relevant for seed-treated crops (5 μg/kg) had negligible effects on colony health and are unlikely a sole cause of colony declines. PMID:25786127

  2. Assessment of chronic sublethal effects of imidacloprid on honey bee colony health.

    PubMed

    Dively, Galen P; Embrey, Michael S; Kamel, Alaa; Hawthorne, David J; Pettis, Jeffery S

    2015-01-01

    Here we present results of a three-year study to determine the fate of imidacloprid residues in hive matrices and to assess chronic sublethal effects on whole honey bee colonies fed supplemental pollen diet containing imidacloprid at 5, 20 and 100 μg/kg over multiple brood cycles. Various endpoints of colony performance and foraging behavior were measured during and after exposure, including winter survival. Imidacloprid residues became diluted or non-detectable within colonies due to the processing of beebread and honey and the rapid metabolism of the chemical. Imidacloprid exposure doses up to 100 μg/kg had no significant effects on foraging activity or other colony performance indicators during and shortly after exposure. Diseases and pest species did not affect colony health but infestations of Varroa mites were significantly higher in exposed colonies. Honey stores indicated that exposed colonies may have avoided the contaminated food. Imidacloprid dose effects was delayed later in the summer, when colonies exposed to 20 and 100 μg/kg experienced higher rates of queen failure and broodless periods, which led to weaker colonies going into the winter. Pooled over two years, winter survival of colonies averaged 85.7, 72.4, 61.2 and 59.2% in the control, 5, 20 and 100 μg/kg treatment groups, respectively. Analysis of colony survival data showed a significant dose effect, and all contrast tests comparing survival between control and treatment groups were significant, except for colonies exposed to 5 μg/kg. Given the weight of evidence, chronic exposure to imidacloprid at the higher range of field doses (20 to 100 μg/kg) in pollen of certain treated crops could cause negative impacts on honey bee colony health and reduced overwintering success, but the most likely encountered high range of field doses relevant for seed-treated crops (5 μg/kg) had negligible effects on colony health and are unlikely a sole cause of colony declines. PMID:25786127

  3. Effects of Wintering Environment and Parasite–Pathogen Interactions on Honey Bee Colony Loss in North Temperate Regions

    PubMed Central

    Currie, Robert W.

    2016-01-01

    Extreme winter losses of honey bee colonies are a major threat to beekeeping but the combinations of factors underlying colony loss remain debatable. We monitored colonies in two environments (colonies wintered indoors or outdoors) and characterized the effects of two parasitic mites, seven viruses, and Nosema on honey bee colony mortality and population loss over winter. Samples were collected from two locations within hives in fall, mid-winter and spring of 2009/2010. Although fall parasite and pathogen loads were similar in outdoor and indoor-wintered colonies, the outdoor-wintered colonies had greater relative reductions in bee population score over winter. Seasonal patterns in deformed wing virus (DWV), black queen cell virus (BQCV), and Nosema level also differed with the wintering environment. DWV and Nosema levels decreased over winter for indoor-wintered colonies but BQCV did not. Both BQCV and Nosema concentration increased over winter in outdoor-wintered colonies. The mean abundance of Varroa decreased and concentration of Sacbrood virus (SBV), Kashmir bee virus (KBV), and Chronic bee paralysis virus (CBPV) increased over winter but seasonal patterns were not affected by wintering method. For most viruses, either entrance or brood area samples were reasonable predictors of colony virus load but there were significant season*sample location interactions for Nosema and BQCV, indicating that care must be taken when selecting samples from a single location. For Nosema spp., the fall entrance samples were better predictors of future infestation levels than were fall brood area samples. For indoor-wintered colonies, Israeli acute paralysis virus IAPV concentration was negatively correlated with spring population size. For outdoor-wintered hives, spring Varroa abundance and DWV concentration were positively correlated with bee loss and negatively correlated with spring population size. Multivariate analyses for fall collected samples indicated higher DWV was

  4. Effects of Wintering Environment and Parasite-Pathogen Interactions on Honey Bee Colony Loss in North Temperate Regions.

    PubMed

    Desai, Suresh D; Currie, Robert W

    2016-01-01

    Extreme winter losses of honey bee colonies are a major threat to beekeeping but the combinations of factors underlying colony loss remain debatable. We monitored colonies in two environments (colonies wintered indoors or outdoors) and characterized the effects of two parasitic mites, seven viruses, and Nosema on honey bee colony mortality and population loss over winter. Samples were collected from two locations within hives in fall, mid-winter and spring of 2009/2010. Although fall parasite and pathogen loads were similar in outdoor and indoor-wintered colonies, the outdoor-wintered colonies had greater relative reductions in bee population score over winter. Seasonal patterns in deformed wing virus (DWV), black queen cell virus (BQCV), and Nosema level also differed with the wintering environment. DWV and Nosema levels decreased over winter for indoor-wintered colonies but BQCV did not. Both BQCV and Nosema concentration increased over winter in outdoor-wintered colonies. The mean abundance of Varroa decreased and concentration of Sacbrood virus (SBV), Kashmir bee virus (KBV), and Chronic bee paralysis virus (CBPV) increased over winter but seasonal patterns were not affected by wintering method. For most viruses, either entrance or brood area samples were reasonable predictors of colony virus load but there were significant season*sample location interactions for Nosema and BQCV, indicating that care must be taken when selecting samples from a single location. For Nosema spp., the fall entrance samples were better predictors of future infestation levels than were fall brood area samples. For indoor-wintered colonies, Israeli acute paralysis virus IAPV concentration was negatively correlated with spring population size. For outdoor-wintered hives, spring Varroa abundance and DWV concentration were positively correlated with bee loss and negatively correlated with spring population size. Multivariate analyses for fall collected samples indicated higher DWV was

  5. The Importance of Microbes in Nutrition and Health of Honey Bee Colonies Part-3: Where Do We Go From Here?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microbial communities in honey bee colonies are essential for food processing and digestion. Symbiotic microbes also might contribute to the reduction of pathogens in the hive by synthesizing antimicrobial compounds. Environmental contaminants such as pesticides, fungicides and antibiotics could c...

  6. Statistical methods to quantify the effect of mite parasitism on the probability of death in honey bee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Varroa destructor is a mite parasite of European honey bees, Apis mellifera, that weakens the population, can lead to the death of an entire honey bee colony, and is believed to be the parasite with the most economic impact on beekeeping. The purpose of this study was to estimate the probability of ...

  7. Phenotypic and genetic analyses of the Varroa Sensitive Hygienic trait in Russian Honey Bee (Hymenoptera: Apidae) colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Varroa destructor continues to threaten colonies of European honey bees. General hygiene and more specific VarroaVarroa Sensitive Hygiene (VSH) provide resistance toward the Varroa mite in a number of stocks. In this study, Russian (RHB) and Italian honey bees were assessed for the VSH trait. Two...

  8. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch

    PubMed Central

    Yurtkuran, Alkın

    2016-01-01

    The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature. PMID:26819591

  9. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch.

    PubMed

    Yurtkuran, Alkın; Emel, Erdal

    2016-01-01

    The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature. PMID:26819591

  10. A novel artificial bee colony algorithm based on modified search equation and orthogonal learning.

    PubMed

    Gao, Wei-feng; Liu, San-yang; Huang, Ling-ling

    2013-06-01

    The artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, ABC has an insufficiency regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we first propose an improved ABC method called as CABC where a modified search equation is applied to generate a candidate solution to improve the search ability of ABC. Furthermore, we use the orthogonal experimental design (OED) to form an orthogonal learning (OL) strategy for variant ABCs to discover more useful information from the search experiences. Owing to OED's good character of sampling a small number of well representative combinations for testing, the OL strategy can construct a more promising and efficient candidate solution. In this paper, the OL strategy is applied to three versions of ABC, i.e., the standard ABC, global-best-guided ABC (GABC), and CABC, which yields OABC, OGABC, and OCABC, respectively. The experimental results on a set of 22 benchmark functions demonstrate the effectiveness and efficiency of the modified search equation and the OL strategy. The comparisons with some other ABCs and several state-of-the-art algorithms show that the proposed algorithms significantly improve the performance of ABC. Moreover, OCABC offers the highest solution quality, fastest global convergence, and strongest robustness among all the contenders on almost all the test functions. PMID:23086528

  11. A modified artificial bee colony algorithm for p-center problems.

    PubMed

    Yurtkuran, Alkın; Emel, Erdal

    2014-01-01

    The objective of the p-center problem is to locate p-centers on a network such that the maximum of the distances from each node to its nearest center is minimized. The artificial bee colony algorithm is a swarm-based meta-heuristic algorithm that mimics the foraging behavior of honey bee colonies. This study proposes a modified ABC algorithm that benefits from a variety of search strategies to balance exploration and exploitation. Moreover, random key-based coding schemes are used to solve the p-center problem effectively. The proposed algorithm is compared to state-of-the-art techniques using different benchmark problems, and computational results reveal that the proposed approach is very efficient. PMID:24616648

  12. Fumagillin control of Nosema ceranae (Microsporidia:Nosematidae) infection in honey bee (Hymenoptera:Apidae) colonies in Argentina.

    PubMed

    Giacobino, Agostina; Rivero, Rocio; Molineri, Ana Ines; Cagnolo, Natalia Bulacio; Merke, Julieta; Orellano, Emanuel; Salto, Cesar; Signorini, Marcelo

    2016-06-30

    Information on the long‑term consequences of Nosema ceranae to honey bee lifespan and effectiveness of Nosema control with fumagillin is scarce and not always consistent. Our objective in this study was to evaluate the effectiveness of the antibiotic fumagillin to control N. ceranae in hives in East‑Central Argentina. Honey bee hives were assigned to 3 experimental treatments, a control group with un‑treated hives, a preventive strategy group with hives treated monthly, and a monitoring strategy group with hives treated according to a N. ceranae threshold level. Apiaries were monitored monthly during Fall‑Winter 2009 and 2010 and N. ceranae spore intensity and honey bee colony strength measures were estimated. Fumagillin‑treated colonies had reduced N. ceranae spores load in 2010 compared to control colonies. However, there was no significant difference between treated and control groups for colony strength measures including adult bee population, bee brood availability, honey, or pollen. Fumagillin treatment reduced N. ceranae intensities but had little effect on colonies. The bee population during Winter was reduced in treated as well as in control colonies. Our results clarify that fumagillin treatment should be at least reviewed and that further research should be conducted to acquire a more complete perspective of Nosemosis disease. PMID:27393876

  13. Higher prevalence and levels of Nosema ceranae than Nosema apis infections in Canadian honey bee colonies.

    PubMed

    Emsen, Berna; Guzman-Novoa, Ernesto; Hamiduzzaman, Mollah Md; Eccles, Les; Lacey, Brian; Ruiz-Pérez, Rosario A; Nasr, Medhat

    2016-01-01

    This study was conducted to determine the prevalence and infection levels of the microsporidia fungi Nosema apis and/or Nosema ceranae in honey bee colonies of two Canadian provinces. Three surveys were conducted in the springs of 2008, 2010 and 2012 and PCR identification of Nosema species were performed in samples from 169 and 181 Ontario colonies and from 76 Alberta colonies that tested positive to Nosema spp. Infection levels of positive colonies were determined by microscopy and analyzed by Nosema spp. Results showed that N. ceranae was the dominant species in all three surveys (prevalence range of 41-91 vs. 4-34 % for N. apis), whereas mixed infections were less frequent than single infections (5-25 %). Infection levels of colonies parasitized by N. ceranae were three to five times higher than those of colonies parasitized by N. apis in the three surveys whereas mixed infections showed the highest spore counts. This is the first field study demonstrating significantly higher infection levels in colonies parasitized with either N. ceranae only or with both, N. ceranae and N. apis, than in colonies parasitized with N. apis only. Taken together, these results suggest that N. ceranae may be more virulent and better adapted than N. apis in cold climates such as Canadian environments. PMID:26358102

  14. Comparison of within hive sampling and seasonal activity of Nosema ceranae in honey bee colonies.

    PubMed

    Traver, Brenna E; Williams, Matthew R; Fell, Richard D

    2012-02-01

    Nosema ceranae is a microsporidian parasite of the European honey bee, Apis mellifera, that is found worldwide and in multiple Apis spp.; however, little is known about the effects of N. ceranae on A. mellifera. Previous studies using spore counts suggest that there is no longer a seasonal cycle for N. ceranae and that it is found year round with little variation in infection intensity among months. Our goal was to determine whether infection levels differ in bees collected from different areas of the hive and if there may be seasonal differences in N. ceranae infections. A multiplex species-specific real-time PCR assay was used for the detection and quantification of N. ceranae. Colonies were sampled monthly from September 2009-2010 by collecting workers from honey supers, the fringe of the brood nest, and the brood nest. We found that all bees sampled were infected with N. ceranae and that there was no significant difference in infection levels among the different groups of bees sampled (P=0.74). However, significant differences in colony infection levels were found at different times of the year (P<0.01) with the highest levels in April-June and lower levels in the fall and winter. While our study was only performed for one year, it sheds light on the fact that there may be a seasonality to N. ceranae infections. Being able to predict future N. ceranae infections can be used to better advise beekeepers on N. ceranae management. PMID:22085836

  15. Pteridine levels and head weights are correlated with age and colony task in the honey bee, Apis mellifera.

    PubMed

    Rinkevich, Frank D; Margotta, Joseph W; Pittman, Jean M; Ottea, James A; Healy, Kristen B

    2016-01-01

    Background. The age of an insect strongly influences many aspects of behavior and reproduction. The interaction of age and behavior is epitomized in the temporal polyethism of honey bees in which young adult bees perform nurse and maintenance duties within the colony, while older bees forage for nectar and pollen. Task transition is dynamic and driven by colony needs. However, an abundance of precocious foragers or overage nurses may have detrimental effects on the colony. Additionally, honey bee age affects insecticide sensitivity. Therefore, determining the age of a set of individual honey bees would be an important measurement of colony health. Pteridines are purine-based pigment molecules found in many insect body parts. Pteridine levels correlate well with age, and wild caught insects may be accurately aged by measuring pteridine levels. The relationship between pteridines and age varies with a number of internal and external factors among many species. Thus far, no studies have investigated the relationship of pteridines with age in honey bees. Methods. We established single-cohort colonies to obtain age-matched nurse and forager bees. Bees of known ages were also sampled from colonies with normal demographics. Nurses and foragers were collected every 3-5 days for up to 42 days. Heads were removed and weighed before pteridines were purified and analyzed using previously established fluorometric methods. Results. Our analysis showed that pteridine levels significantly increased with age in a linear manner in both single cohort colonies and colonies with normal demography. Pteridine levels were higher in foragers than nurses of the same age in bees from single cohort colonies. Head weight significantly increased with age until approximately 28-days of age and then declined for both nurse and forager bees in single cohort colonies. A similar pattern of head weight in bees from colonies with normal demography was observed but head weight was highest in 8-day old

  16. Pteridine levels and head weights are correlated with age and colony task in the honey bee, Apis mellifera

    PubMed Central

    Rinkevich, Frank D.; Margotta, Joseph W.; Pittman, Jean M.; Ottea, James A.

    2016-01-01

    Background. The age of an insect strongly influences many aspects of behavior and reproduction. The interaction of age and behavior is epitomized in the temporal polyethism of honey bees in which young adult bees perform nurse and maintenance duties within the colony, while older bees forage for nectar and pollen. Task transition is dynamic and driven by colony needs. However, an abundance of precocious foragers or overage nurses may have detrimental effects on the colony. Additionally, honey bee age affects insecticide sensitivity. Therefore, determining the age of a set of individual honey bees would be an important measurement of colony health. Pteridines are purine-based pigment molecules found in many insect body parts. Pteridine levels correlate well with age, and wild caught insects may be accurately aged by measuring pteridine levels. The relationship between pteridines and age varies with a number of internal and external factors among many species. Thus far, no studies have investigated the relationship of pteridines with age in honey bees. Methods. We established single-cohort colonies to obtain age-matched nurse and forager bees. Bees of known ages were also sampled from colonies with normal demographics. Nurses and foragers were collected every 3–5 days for up to 42 days. Heads were removed and weighed before pteridines were purified and analyzed using previously established fluorometric methods. Results. Our analysis showed that pteridine levels significantly increased with age in a linear manner in both single cohort colonies and colonies with normal demography. Pteridine levels were higher in foragers than nurses of the same age in bees from single cohort colonies. Head weight significantly increased with age until approximately 28-days of age and then declined for both nurse and forager bees in single cohort colonies. A similar pattern of head weight in bees from colonies with normal demography was observed but head weight was highest in 8-day

  17. Ant colony optimization and stochastic gradient descent.

    PubMed

    Meuleau, Nicolas; Dorigo, Marco

    2002-01-01

    In this article, we study the relationship between the two techniques known as ant colony optimization (ACO) and stochastic gradient descent. More precisely, we show that some empirical ACO algorithms approximate stochastic gradient descent in the space of pheromones, and we propose an implementation of stochastic gradient descent that belongs to the family of ACO algorithms. We then use this insight to explore the mutual contributions of the two techniques. PMID:12171633

  18. Cuticular hydrocarbons in the stingless bee Schwarziana quadripunctata (Hymenoptera, Apidae, Meliponini): differences between colonies, castes and age.

    PubMed

    Nunes, T M; Turatti, I C C; Mateus, S; Nascimento, F S; Lopes, N P; Zucchi, R

    2009-01-01

    Chemical communication is of fundamental importance to maintain the integration of insect colonies. In honey bees, cuticular lipids differ in their composition between queens, workers and drones. Little is known, however, about cuticular hydrocarbons in stingless bees. We investigated chemical differences in cuticular hydrocarbons between different colonies, castes and individuals of different ages in Schwarziana quadripunctata. The epicuticle of the bees was extracted using the non-polar solvent hexane, and was analyzed by means of a gas chromatograph coupled with a mass spectrometer. The identified compounds were alkanes, branched-alkanes and alkenes with chains of 19 to 33 carbon atoms. Discriminant analyses showed clear differences between all the groups analyzed. There were significant differences between bees from different colonies, workers of different age and between workers and virgin queens. PMID:19551647

  19. Acaricide treatment affects viral dynamics in Varroa destructor-infested honey bee colonies via both host physiology and mite control.

    PubMed

    Locke, Barbara; Forsgren, Eva; Fries, Ingemar; de Miranda, Joachim R

    2012-01-01

    Honey bee (Apis mellifera) colonies are declining, and a number of stressors have been identified that affect, alone or in combination, the health of honey bees. The ectoparasitic mite Varroa destructor, honey bee viruses that are often closely associated with the mite, and pesticides used to control the mite population form a complex system of stressors that may affect honey bee health in different ways. During an acaricide treatment using Apistan (plastic strips coated with tau-fluvalinate), we analyzed the infection dynamics of deformed wing virus (DWV), sacbrood virus (SBV), and black queen cell virus (BQCV) in adult bees, mite-infested pupae, their associated Varroa mites, and uninfested pupae, comparing these to similar samples from untreated control colonies. Titers of DWV increased initially with the onset of the acaricide application and then slightly decreased progressively coinciding with the removal of the Varroa mite infestation. This initial increase in DWV titers suggests a physiological effect of tau-fluvalinate on the host's susceptibility to viral infection. DWV titers in adult bees and uninfested pupae remained higher in treated colonies than in untreated colonies. The titers of SBV and BQCV did not show any direct relationship with mite infestation and showed a variety of possible effects of the acaricide treatment. The results indicate that other factors besides Varroa mite infestation may be important to the development and maintenance of damaging DWV titers in colonies. Possible biochemical explanations for the observed synergistic effects between tau-fluvalinate and virus infections are discussed. PMID:22020517

  20. An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning

    PubMed Central

    Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555

  1. An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

    PubMed

    Li, Bai; Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555

  2. Recruitment-dance signals draw larger audiences when honey bee colonies have multiple patrilines

    PubMed Central

    Mattila, H. R.; Seeley, T. D.

    2010-01-01

    Honey bee queens (Apis mellifera) who mate with multiple males produce colonies that are filled with numerous genetically distinct patrilines of workers. A genetically diverse colony benefits from an enhanced foraging effort, fuelled in part by an increase in the number of recruitment signals that are produced by foragers. However, the influence of patriline diversity on the attention paid to these signals by audiences of potentially receptive workers remains unexplored. To determine whether recruitment dances performed by foragers in multiple-patriline colonies attract a greater number of dance followers than dances in colonies that lack patriline diversity, we trained workers from multiple- and single-patriline colonies to forage in a greenhouse and monitored their dance-following activity back in the hives. On average, more workers followed a dance if it was performed in a multiple-patriline colony rather than a single-patriline colony (33% increase), and for a greater number of dance circuits per follower. Furthermore, dance-following workers in multiple-patriline colonies were more likely to exit their hive after following a dance, although this did not translate to a difference in colony-level exit rates between treatment types. Recruiting nest mates to profitable food sources through dance communication is critical to a colony’s foraging success and long-term fitness; polyandrous queens produce colonies that benefit not only from increased recruitment signalling, but also from the generation of larger and more attentive audiences of signal receivers. This study highlights the importance of integrating responses of both signal senders and receivers to understand more fully the success of animal-communication systems. PMID:21350596

  3. Evaluation of apicultural characteristics of first-year colonies initiated from packaged honey bees (Hymenoptera: Apidae).

    PubMed

    Strange, James P; Calderone, Nicholas W

    2009-04-01

    We evaluated the performance of six named types of package honey bees, Apis mellifera L (Hymenoptera: Apidae), from four commercial producers. We examined the effects of levels of the parasitic mite Varroa destructor Anderson & Trueman, the endoparasitic mite Acarapis woodi (Rennie), the gut parasite Nosema (species not determined) in samples from bees in 48 packages, and levels of adult drones in the same packages on corresponding levels of those same traits in the fall in colonies that developed from those 48 packages. After package installation, we measured the rate of queen failure, the removal of freeze-killed brood (an assay to assess hygienic behavior), varroa-sensitive hygiene, and short-term weight gain in all colonies. We examined the correlations among these traits and the effect of initial package conditions and package-type on the expression of these traits. In general, differences among sources were not significant, except that we did observe significant differences in the proportion of mite infected worker brood in the fall. There was no significant difference in weight gain in colonies established from nosema-infected packages versus those established from noninfected packages. Freeze-killed hygienic behavior and varroa-sensitive hygienic behavior were positively correlated, suggesting that both traits could be selected simultaneously. Neither trait was correlated with colony weight gain, suggesting that both traits could be selected without compromising honey production. PMID:19449626

  4. Population growth of Varroa destructor (Acari: Varroidae) in honey bee colonies is affected by the number of foragers with mites

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Varroa mites are a serious pest of honey bees and the leading cause of colony losses. Varroa have relatively low reproductive rates, so populations should not increase rapidly, but often they do. Other factors might contribute to the growth of Varroa populations including mite migration into colonie...

  5. Nosema spp. infection and its negative effects on honey bees (Apis mellifera iberiensis) at the colony level

    PubMed Central

    2013-01-01

    Nosemosis caused by the microsporidia Nosema apis and Nosema ceranae are among the most common pathologies affecting adult honey bees. N. apis infection has been associated with a reduced lifespan of infected bees and increased winter mortality, and its negative impact on colony strength and productivity has been described in several studies. By contrast, when the effects of nosemosis type C, caused by N. ceranae infection, have been analysed at the colony level, these studies have largely focused on collapse as a response to infection without addressing the potential sub-clinical effects on colony strength and productivity. Given the spread and prevalence of N. ceranae worldwide, we set out here to characterize the sub-clinical and clinical signs of N. ceranae infection on colony strength and productivity. We evaluated the evolution of 50 honey bee colonies naturally infected by Nosema (mainly N. ceranae) over a one year period. Under our experimental conditions, N. ceranae infection was highly pathogenic for honey bee colonies, producing significant reductions in colony size, brood rearing and honey production. These deleterious effects at the colony level may affect beekeeping profitability and have serious consequences on pollination. Further research is necessary to identify possible treatments or beekeeping techniques that will limit the rapid spread of this dangerous emerging disease. PMID:23574888

  6. Assessing the health of colonies and individual honey bees (Apis mellifera L.) in a commercial beekeeping operation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metrics of honey bee health were assessed every six weeks over three years in colonies owned by a migratory beekeeper. The colonies were located in six apiaries during the summer months in North Dakota and were transported to California for almond pollination every winter. We previously characteri...

  7. [Chaotic artificial bee colony algorithm: a new approach to the problem of minimization of energy of the 3D protein structure].

    PubMed

    Wang, Y; Guo, G D; Chen, L F

    2013-01-01

    Frediction of the three-dimensional structure of a protein from its amino acid sequence can be considered as a global optimization problem. In this paper, the Chaotic Artificial Bee Colony (CABC) algorithm was introduced and applied to 3D protein structure prediction. Based on the 3D off-lattice AB model, the CABC algorithm combines global search and local search of the Artificial Bee Colony (ABC) algorithm with the Chaotic search algorithm to avoid the problem of premature convergence and easily trapping the local optimum solution. The experiments carried out with the popular Fibonacci sequences demonstrate that the proposed algorithm provides an effective and high-performance method for protein structure prediction. PMID:25509864

  8. Maternal influence on the acceptance of virgin queens introduced into Africanized honey bee (Apis mellifera) colonies.

    PubMed

    Moretto, G; Guerra, J C V; Kalvelage, H; Espindola, E

    2004-01-01

    The oviposition potential of honey bee queens decreases with age, therefore it is important to replace old queens with younger ones on a periodic basis. However, queen replacement is problematic, especially in Africanized honey bee colonies, since many introduced queens are not accepted, and virgin queens are less easily accepted than are mated queens. We assessed the influence of genetic origin (queen mother) on the acceptance of queens, when they were introduced as virgins into Africanized honey bee colonies. For this purpose, 12 daughter queens from each of 11 mother queens with no degree of kinship among themselves were introduced. Introductions were made monthly, for 12 months, though the winter months of June and July were not included, as there is little brood and drones are rare in winter. There was some seasonal variation in the acceptance rates; generally there was greater acceptance in months with good honey flows. However, the acceptance of introduced queens was influenced by their origin. The rate of acceptance of daughter queens from the 11 different mother queens varied significantly, ranging from 33 to 75%. There appears to be a genetic influence of the mother queen on the introduced queen acceptance rate. PMID:15614734

  9. Modified artificial bee colony for the vehicle routing problems with time windows.

    PubMed

    Alzaqebah, Malek; Abdullah, Salwani; Jawarneh, Sana

    2016-01-01

    The natural behaviour of the honeybee has attracted the attention of researchers in recent years and several algorithms have been developed that mimic swarm behaviour to solve optimisation problems. This paper introduces an artificial bee colony (ABC) algorithm for the vehicle routing problem with time windows (VRPTW). A Modified ABC algorithm is proposed to improve the solution quality of the original ABC. The high exploration ability of the ABC slows-down its convergence speed, which may due to the mechanism used by scout bees in replacing abandoned (unimproved) solutions with new ones. In the Modified ABC a list of abandoned solutions is used by the scout bees to memorise the abandoned solutions, then the scout bees select a solution from the list based on roulette wheel selection and replace by a new solution with random routs selected from the best solution. The performance of the Modified ABC is evaluated on Solomon benchmark datasets and compared with the original ABC. The computational results demonstrate that the Modified ABC outperforms the original ABC also produce good solutions when compared with the best-known results in the literature. Computational investigations show that the proposed algorithm is a good and promising approach for the VRPTW. PMID:27547672

  10. How Honey Bee Colonies Survive in the Wild: Testing the Importance of Small Nests and Frequent Swarming.

    PubMed

    Loftus, J Carter; Smith, Michael L; Seeley, Thomas D

    2016-01-01

    The ectoparasitic mite, Varroa destructor, and the viruses that it transmits, kill the colonies of European honey bees (Apis mellifera) kept by beekeepers unless the bees are treated with miticides. Nevertheless, there exist populations of wild colonies of European honey bees that are persisting without being treated with miticides. We hypothesized that the persistence of these wild colonies is due in part to their habits of nesting in small cavities and swarming frequently. We tested this hypothesis by establishing two groups of colonies living either in small hives (42 L) without swarm-control treatments or in large hives (up to 168 L) with swarm-control treatments. We followed the colonies for two years and compared the two groups with respect to swarming frequency, Varroa infesttion rate, disease incidence, and colony survival. Colonies in small hives swarmed more often, had lower Varroa infestation rates, had less disease, and had higher survival compared to colonies in large hives. These results indicate that the smaller nest cavities and more frequent swarming of wild colonies contribute to their persistence without mite treatments. PMID:26968000

  11. How Honey Bee Colonies Survive in the Wild: Testing the Importance of Small Nests and Frequent Swarming

    PubMed Central

    Loftus, J. Carter; Smith, Michael L.; Seeley, Thomas D.

    2016-01-01

    The ectoparasitic mite, Varroa destructor, and the viruses that it transmits, kill the colonies of European honey bees (Apis mellifera) kept by beekeepers unless the bees are treated with miticides. Nevertheless, there exist populations of wild colonies of European honey bees that are persisting without being treated with miticides. We hypothesized that the persistence of these wild colonies is due in part to their habits of nesting in small cavities and swarming frequently. We tested this hypothesis by establishing two groups of colonies living either in small hives (42 L) without swarm-control treatments or in large hives (up to 168 L) with swarm-control treatments. We followed the colonies for two years and compared the two groups with respect to swarming frequency, Varroa infesttion rate, disease incidence, and colony survival. Colonies in small hives swarmed more often, had lower Varroa infestation rates, had less disease, and had higher survival compared to colonies in large hives. These results indicate that the smaller nest cavities and more frequent swarming of wild colonies contribute to their persistence without mite treatments. PMID:26968000

  12. Bee poison

    MedlinePlus

    ... is caused by a sting from a bee, wasp , or yellow jacket. This article is for information ... Bee, wasp, and yellow jacket stings contain a substance called venom. Africanized bee colonies are very sensitive to being ...

  13. Fearful foragers: honey bees tune colony and individual foraging to multi-predator presence and food quality.

    PubMed

    Tan, Ken; Hu, Zongwen; Chen, Weiwen; Wang, Zhengwei; Wang, Yuchong; Nieh, James C

    2013-01-01

    Fear can have strong ecosystem effects by giving predators a role disproportionate to their actual kill rates. In bees, fear is shown through foragers avoiding dangerous food sites, thereby reducing the fitness of pollinated plants. However, it remains unclear how fear affects pollinators in a complex natural scenario involving multiple predator species and different patch qualities. We studied hornets, Vespa velutina (smaller) and V. tropica (bigger) preying upon the Asian honey bee, Apis cerana in China. Hornets hunted bees on flowers and were attacked by bee colonies. Bees treated the bigger hornet species (which is 4 fold more massive) as more dangerous. It received 4.5 fold more attackers than the smaller hornet species. We tested bee responses to a three-feeder array with different hornet species and varying resource qualities. When all feeders offered 30% sucrose solution (w/w), colony foraging allocation, individual visits, and individual patch residence times were reduced according to the degree of danger. Predator presence reduced foraging visits by 55-79% and residence times by 17-33%. When feeders offered different reward levels (15%, 30%, or 45% sucrose), colony and individual foraging favored higher sugar concentrations. However, when balancing food quality against multiple threats (sweeter food corresponding to higher danger), colonies exhibited greater fear than individuals. Colonies decreased foraging at low and high danger patches. Individuals exhibited less fear and only decreased visits to the high danger patch. Contrasting individual with emergent colony-level effects of fear can thus illuminate how predators shape pollination by social bees. PMID:24098734

  14. Fearful Foragers: Honey Bees Tune Colony and Individual Foraging to Multi-Predator Presence and Food Quality

    PubMed Central

    Tan, Ken; Hu, Zongwen; Chen, Weiwen; Wang, Zhengwei; Wang, Yuchong; Nieh, James C.

    2013-01-01

    Fear can have strong ecosystem effects by giving predators a role disproportionate to their actual kill rates. In bees, fear is shown through foragers avoiding dangerous food sites, thereby reducing the fitness of pollinated plants. However, it remains unclear how fear affects pollinators in a complex natural scenario involving multiple predator species and different patch qualities. We studied hornets, Vespa velutina (smaller) and V. tropica (bigger) preying upon the Asian honey bee, Apis cerana in China. Hornets hunted bees on flowers and were attacked by bee colonies. Bees treated the bigger hornet species (which is 4 fold more massive) as more dangerous. It received 4.5 fold more attackers than the smaller hornet species. We tested bee responses to a three-feeder array with different hornet species and varying resource qualities. When all feeders offered 30% sucrose solution (w/w), colony foraging allocation, individual visits, and individual patch residence times were reduced according to the degree of danger. Predator presence reduced foraging visits by 55–79% and residence times by 17–33%. When feeders offered different reward levels (15%, 30%, or 45% sucrose), colony and individual foraging favored higher sugar concentrations. However, when balancing food quality against multiple threats (sweeter food corresponding to higher danger), colonies exhibited greater fear than individuals. Colonies decreased foraging at low and high danger patches. Individuals exhibited less fear and only decreased visits to the high danger patch. Contrasting individual with emergent colony-level effects of fear can thus illuminate how predators shape pollination by social bees. PMID:24098734

  15. Differential Proteomics in Dequeened Honeybee Colonies Reveals Lower Viral Load in Hemolymph of Fertile Worker Bees

    PubMed Central

    Cardoen, Dries; Ernst, Ulrich R.; Van Vaerenbergh, Matthias; Boerjan, Bart; de Graaf, Dirk C.; Wenseleers, Tom; Schoofs, Liliane; Verleyen, Peter

    2011-01-01

    The eusocial societies of honeybees, where the queen is the only fertile female among tens of thousands sterile worker bees, have intrigued scientists for centuries. The proximate factors, which cause the inhibition of worker bee ovaries, remain largely unknown; as are the factors which cause the activation of worker ovaries upon the loss of queen and brood in the colony. In an attempt to reveal key players in the regulatory network, we made a proteomic comparison of hemolymph profiles of workers with completely activated ovaries vs. rudimentary ovaries. An unexpected finding of this study is the correlation between age matched worker sterility and the enrichment of Picorna-like virus proteins. Fertile workers, on the other hand, show the upregulation of potential components of the immune system. It remains to be investigated whether viral infections contribute to worker sterility directly or are the result of a weaker immune system of sterile workers. PMID:21698281

  16. Dancing Bees Improve Colony Foraging Success as Long-Term Benefits Outweigh Short-Term Costs

    PubMed Central

    Schürch, Roger; Grüter, Christoph

    2014-01-01

    Waggle dancing bees provide nestmates with spatial information about high quality resources. Surprisingly, attempts to quantify the benefits of this encoded spatial information have failed to find positive effects on colony foraging success under many ecological circumstances. Experimental designs have often involved measuring the foraging success of colonies that were repeatedly switched between oriented dances versus disoriented dances (i.e. communicating vectors versus not communicating vectors). However, if recruited bees continue to visit profitable food sources for more than one day, this procedure would lead to confounded results because of the long-term effects of successful recruitment events. Using agent-based simulations, we found that spatial information was beneficial in almost all ecological situations. Contrary to common belief, the benefits of recruitment increased with environmental stability because benefits can accumulate over time to outweigh the short-term costs of recruitment. Furthermore, we found that in simulations mimicking previous experiments, the benefits of communication were considerably underestimated (at low food density) or not detected at all (at medium and high densities). Our results suggest that the benefits of waggle dance communication are currently underestimated and that different experimental designs, which account for potential long-term benefits, are needed to measure empirically how spatial information affects colony foraging success. PMID:25141306

  17. Secondary biomarkers of insecticide-induced stress of honey bee colonies and their relevance for overwintering strength.

    PubMed

    Wegener, Jakob; Ruhnke, Haike; Milchreit, Kathrin; Kleebaum, Katharina; Franke, Monique; Mispagel, Sebastian; Bischoff, Gabriela; Kamp, Günter; Bienefeld, Kaspar

    2016-10-01

    The evaluation of pesticide side-effects on honeybees is hampered by a lack of colony-level bioassays that not only are sensitive to physiological changes, but also allow predictions about the consequences of exposure for longer-term colony productivity and survival. Here we measured 28 biometrical, biochemical and behavioural indicators in a field study with 63 colonies and 3 apiaries. Colonies were stressed in early summer by feeding them for five days with either the carbamate growth regulator fenoxycarb or the neurotoxic neonicotinoid imidacloprid, or left untreated. Candidate stress indicators were measured 8-64 days later. We determined which of the indicators were influenced by the treatments, and which could be used as predictors in regression analyses of overwintering strength. Among the indicators influenced by fenoxycarb were the amount of brood in colonies as well as the learning performance and 24h-memory of bees, and the concentration of the brood food component 10HDA in head extracts. Imidacloprid significantly affected honey production, total number of bees and activity of the immune-related enzyme phenoloxidase in forager bee extracts. Indicators predictive of overwintering strength but unrelated to insecticide feeding included vitellogenin titer and glucose oxidase-activity in haemolymph/whole body-extracts of hive bees. Apart from variables that were themselves components of colony strength (numbers of bees/brood cells), the only indicator that was both influenced by an insecticide and predictive of overwintering strength was the concentration of 10HDA in worker bee heads. Our results show that physiological and biochemical bioassays can be used to study effects of insecticides at the colony level and assess the vitality of bee colonies. At the same time, most bioassays evaluated here appear of limited use for predicting pesticide effects on colony overwintering strength, because those that were sensitive to the insecticides were not identical

  18. Nutritional aspects of honey bee-collected pollen and constraints on colony development in the eastern Mediterranean.

    PubMed

    Avni, Dorit; Hendriksma, Harmen P; Dag, Arnon; Uni, Zehava; Shafir, Sharoni

    2014-10-01

    Pollen is the main protein and lipid source for honey bees (Apis mellifera), and nutritionally impoverished landscapes pose a threat to colony development. To determine colony nutritional demands, we analyzed a yearly cycle of bee-collected pollen from colonies in the field and compared it to colony worker production and honey bee body composition, for the first time in social insects. We monitored monthly bee production in ten colonies at each of seven sites throughout Israel, and trapped pollen bi-monthly in five additional colonies at each of four of these sites. Pollen mixtures from each sampling date and site were analyzed for weight, total protein, total fatty acids (FAs), and FA composition. Compared to more temperate climates, the eastern Mediterranean allows a relatively high yearly colony growth of ca. 300,000-400,000 bees. Colonies at higher elevation above sea level showed lower growth rates. Queen egg-laying rate did not seem to limit growth, as peaks in capped brood areas showed that queens lay a prolific 2000 eggs a day on average, with up to 3300 eggs in individual cases. Pollen uptake varied significantly among sites and seasons, with an overall annual mean total 16.8kg per colony, containing 7.14kg protein and 677g fat. Overall mean pollen protein content was high (39.8%), and mean total FA content was 3.8%. Production cost, as expressed by the amount of nutrient used per bee, was least variable for linoleic acid and protein, suggesting these as the best descriptive variables for total number of bees produced. Linolenic acid levels in pollen during the autumn were relatively low, and supplementing colonies with this essential FA may mitigate potential nutritional deficiency. The essentiality of linoleic and linolenic acids was consistent with these FAs' tendency to be present at higher levels in collected pollen than in the expected nutrients in bee bodies, demonstrating a well-developed adjustment between pollinator nutritional demands and the

  19. Entombed pollen: A new condition in honey bee colonies associated with increased risk of colony mortality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Here we describe a new phenomenon, entombed pollen, which is highly associated with increased colony mortality. Entombed pollen appears as sunken, wax-covered cells amidst “normal”, uncapped cells of stored pollen, and the pollen contained within these cells is brick red in color. There appears to b...

  20. Effects of brood pheromone (SuperBoost) on consumption of protein supplement and growth of honey bee (Hymenoptera: Apidae) colonies during fall in a northern temperate climate.

    PubMed

    Sagili, Ramesh R; Breece, Carolyn R

    2012-08-01

    Honey bee, Apis mellifera L. (Hymenoptera: Apidae), nutrition is vital for colony growth and maintenance of a robust immune system. Brood rearing in honey bee colonies is highly dependent on protein availability. Beekeepers in general provide protein supplement to colonies during periods of pollen dearth. Honey bee brood pheromone is a blend of methyl and ethyl fatty acid esters extractable from cuticle of honey bee larvae that communicates the presence of larvae in a colony. Honey bee brood pheromone has been shown to increase protein supplement consumption and growth of honey bee colonies in a subtropical winter climate. Here, we tested the hypothesis that synthetic brood pheromone (SuperBoost) has the potential to increase protein supplement consumption during fall in a temperate climate and thus increase colony growth. The experiments were conducted in two locations in Oregon during September and October 2009. In both the experiments, colonies receiving brood pheromone treatment consumed significantly higher protein supplement and had greater brood area and adult bees than controls. Results from this study suggest that synthetic brood pheromone may be used to stimulate honey bee colony growth by stimulating protein supplement consumption during fall in a northern temperate climate, when majority of the beekeepers feed protein supplement to their colonies. PMID:22928289

  1. Prediction of social structure and genetic relatedness in colonies of the facultative polygynous stingless bee Melipona bicolor (Hymenoptera, Apidae)

    PubMed Central

    dos Reis, Evelyze Pinheiro; de Oliveira Campos, Lucio Antonio; Tavares, Mara Garcia

    2011-01-01

    Stingless bee colonies typically consist of one single-mated mother queen and her worker offspring. The stingless bee Melipona bicolor (Hymenoptera: Apidae) shows facultative polygyny, which makes this species particularly suitable for testing theoretical expectations concerning social behavior. In this study, we investigated the social structure and genetic relatedness among workers from eight natural and six manipulated colonies of M. bicolor over a period of one year. The populations of M. bicolor contained monogynous and polygynous colonies. The estimated genetic relatedness among workers from monogynous and polygynous colonies was 0.75 ± 0.12 and 0.53 ± 0.16 (mean ± SEM), respectively. Although the parental genotypes had significant effects on genetic relatedness in monogynous and polygynous colonies, polygyny markedly decreased the relatedness among nestmate workers. Our findings also demonstrate that polygyny in M. bicolor may arise from the adoption of related or unrelated queens. PMID:21734839

  2. Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme. PMID:24744773

  3. Research on WNN modeling for gold price forecasting based on improved artificial bee colony algorithm.

    PubMed

    Li, Bai

    2014-01-01

    Gold price forecasting has been a hot issue in economics recently. In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue. In this improved algorithm, the conventional roulette selection strategy is discarded. Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle. Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme. PMID:24744773

  4. 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.

  5. Correlations between land covers and honey bee colony losses in a country with industrialized and rural regions.

    PubMed

    Clermont, Antoine; Eickermann, Michael; Kraus, François; Hoffmann, Lucien; Beyer, Marco

    2015-11-01

    High levels of honey bee colony losses were recently reported from Canada, China, Europe, Israel, Turkey and the United States, raising concerns of a global pollinator decline and questioning current land use practices, in particular intense agricultural cropping systems. Sixty-seven crops (data from the years 2010-2012) and 66 mid-term stable land cover classes (data from 2007) were analysed for statistical relationships with the honey bee colony losses experienced over the winters 2010/11-2012/13 in Luxembourg (Western Europe). The area covered by each land cover class, the shortest distance between each land cover class and the respective apiary, the number of plots covered by each land use class and the size of the biggest plot of each land cover class within radii of 2 km and 5 km around 166 apiaries (2010), 184 apiaries (2011) and 188 apiaries (2012) were tested for correlations with honey bee colony losses (% per apiary) experienced in the winter following the season when the crops were grown. Artificial water bodies, open urban areas, large industrial facilities including heavy industry, railways and associated installations, buildings and installations with socio-cultural purpose, camping-, sports-, playgrounds, golf courts, oilseed crops other than oilseed rape like sunflower or linseed, some spring cereals and former forest clearcuts or windthrows were the land cover classes most frequently associated with high honey bee colony losses. Grain maize, mixed forest and mixed coniferous forest were the land cover classes most frequently associated with low honey bee colony losses. The present data suggest that land covers related to transport, industry and leisure may have made a more substantial contribution to winter honey bee colony losses in developed countries than anticipated so far. Recommendations for the positioning of apiaries are discussed. PMID:26057621

  6. Aethina tumida (Coleoptera: Nitidulidae) and Oplostomus haroldi (Coleoptera: Scarabaeidae): Occurrence in Kenya, Distribution within Honey Bee Colonies, and Response to Host Odors

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aethina tumida Murray is considered a minor parasitic pest of African honey bee colonies, but little information is available on other coleopteran pests. We surveyed for A. tumida and other beetles in honey bee colonies at four major beekeeping locations: Watamu, Chawia-Taita, Matuu, and Nairobi in...

  7. The effect of queen pheromone status on Varroa mite removal from honey bee colonies with different grooming ability.

    PubMed

    Bahreini, Rassol; Currie, Robert W

    2015-07-01

    The objective of this study was to assess the effects of honey bees (Apis mellifera L.) with different grooming ability and queen pheromone status on mortality rates of Varroa mites (Varroa destructor Anderson and Trueman), mite damage, and mortality rates of honey bees. Twenty-four small queenless colonies containing either stock selected for high rates of mite removal (n = 12) or unselected stock (n = 12) were maintained under constant darkness at 5 °C. Colonies were randomly assigned to be treated with one of three queen pheromone status treatments: (1) caged, mated queen, (2) a synthetic queen mandibular pheromone lure (QMP), or (3) queenless with no queen substitute. The results showed overall mite mortality rate was greater in stock selected for grooming than in unselected stock. There was a short term transitory increase in bee mortality rates in selected stock when compared to unselected stock. The presence of queen pheromone from either caged, mated queens or QMP enhanced mite removal from clusters of bees relative to queenless colonies over short periods of time and increased the variation in mite mortality over time relative to colonies without queen pheromone, but did not affect the proportion of damaged mites. The effects of source of bees on mite damage varied with time but damage to mites was not reliably related to mite mortality. In conclusion, this study showed differential mite removal of different stocks was possible under low temperature. Queen status should be considered when designing experiments using bioassays for grooming response. PMID:25860860

  8. Mating Frequencies of Honey Bee Queens (Apis mellifera L.) in a Population of Feral Colonies in the Northeastern United States

    PubMed Central

    Tarpy, David R.; Delaney, Deborah A.; Seeley, Thomas D.

    2015-01-01

    Across their introduced range in North America, populations of feral honey bee (Apis mellifera L.) colonies have supposedly declined in recent decades as a result of exotic parasites, most notably the ectoparasitic mite Varroa destructor. Nonetheless, recent studies have documented several wild populations of colonies that have persisted. The extreme polyandry of honey bee queens—and the increased intracolony genetic diversity it confers—has been attributed, in part, to improved disease resistance and may be a factor in the survival of these populations of feral colonies. We estimated the mating frequencies of queens in feral colonies in the Arnot Forest in New York State to determine if the level of polyandry of these queens is especially high and so might contribute to their survival success. We genotyped the worker offspring from 10 feral colonies in the Arnot Forest of upstate New York, as well as those from 20 managed colonies closest to this forest. We found no significant differences in mean mating frequency between the feral and managed queens, suggesting that queens in the remote, low-density population of colonies in the Arnot Forest are neither mate-limited nor adapted to mate at an especially high frequency. These findings support the hypothesis that the hyperpolyandry of honey bees has been shaped on an evolutionary timescale rather than on an ecological one. PMID:25775410

  9. Mating frequencies of honey bee queens (Apis mellifera L.) in a population of feral colonies in the Northeastern United States.

    PubMed

    Tarpy, David R; Delaney, Deborah A; Seeley, Thomas D

    2015-01-01

    Across their introduced range in North America, populations of feral honey bee (Apis mellifera L.) colonies have supposedly declined in recent decades as a result of exotic parasites, most notably the ectoparasitic mite Varroa destructor. Nonetheless, recent studies have documented several wild populations of colonies that have persisted. The extreme polyandry of honey bee queens-and the increased intracolony genetic diversity it confers-has been attributed, in part, to improved disease resistance and may be a factor in the survival of these populations of feral colonies. We estimated the mating frequencies of queens in feral colonies in the Arnot Forest in New York State to determine if the level of polyandry of these queens is especially high and so might contribute to their survival success. We genotyped the worker offspring from 10 feral colonies in the Arnot Forest of upstate New York, as well as those from 20 managed colonies closest to this forest. We found no significant differences in mean mating frequency between the feral and managed queens, suggesting that queens in the remote, low-density population of colonies in the Arnot Forest are neither mate-limited nor adapted to mate at an especially high frequency. These findings support the hypothesis that the hyperpolyandry of honey bees has been shaped on an evolutionary timescale rather than on an ecological one. PMID:25775410

  10. Robustness of Ant Colony Optimization to Noise.

    PubMed

    Friedrich, Tobias; Kötzing, Timo; Krejca, Martin S; Sutton, Andrew M

    2016-01-01

    Recently, ant colony optimization (ACO) algorithms have proven to be efficient in uncertain environments, such as noisy or dynamically changing fitness functions. Most of these analyses have focused on combinatorial problems such as path finding. We rigorously analyze an ACO algorithm optimizing linear pseudo-Boolean functions under additive posterior noise. We study noise distributions whose tails decay exponentially fast, including the classical case of additive Gaussian noise. Without noise, the classical [Formula: see text] EA outperforms any ACO algorithm, with smaller [Formula: see text] being better; however, in the case of large noise, the [Formula: see text] EA fails, even for high values of [Formula: see text] (which are known to help against small noise). In this article, we show that ACO is able to deal with arbitrarily large noise in a graceful manner; that is, as long as the evaporation factor [Formula: see text] is small enough, dependent on the variance [Formula: see text] of the noise and the dimension n of the search space, optimization will be successful. We also briefly consider the case of prior noise and prove that ACO can also efficiently optimize linear functions under this noise model. PMID:26928850

  11. Comparison of Productivity of Colonies of Honey Bees, Apis mellifera, Supplemented with Sucrose or High Fructose Corn Syrup

    PubMed Central

    Sammataro, Diana; Weiss, Milagra

    2013-01-01

    Honey bee colony feeding trials were conducted to determine whether differential effects of carbohydrate feeding (sucrose syrup (SS) vs. high fructose corn syrup, or HFCS) could be measured between colonies fed exclusively on these syrups. In one experiment, there was a significant difference in mean wax production between the treatment groups and a significant interaction between time and treatment for the colonies confined in a flight arena. On average, the colonies supplied with SS built 7916.7 cm2 ± 1015.25 cm2 honeycomb, while the colonies supplied with HFCS built 4571.63 cm2 ± 786.45 cm2. The mean mass of bees supplied with HFCS was 4.65 kg (± 0.97 kg), while those supplied with sucrose had a mean of 8.27 kg (± 1.26). There was no significant difference between treatment groups in terms of brood rearing. Differences in brood production were complicated due to possible nutritional deficiencies experienced by both treatment groups. In the second experiment, colonies supplemented with SS through the winter months at a remote field site exhibited increased spring brood production when compared to colonies fed with HFCS. The differences in adult bee populations were significant, having an overall average of 10.0 ± 1.3 frames of bees fed the sucrose syrup between November 2008 and April 2009, compared to 7.5 ± 1.6 frames of bees fed exclusively on HFCS. For commercial queen beekeepers, feeding the right supplementary carbohydrates could be especially important, given the findings of this study. PMID:23886010

  12. Comparison of productivity of colonies of honey bees, Apis mellifera, supplemented with sucrose or high fructose corn syrup.

    PubMed

    Sammataro, Diana; Weiss, Milagra

    2013-01-01

    Honey bee colony feeding trials were conducted to determine whether differential effects of carbohydrate feeding (sucrose syrup (SS) vs. high fructose corn syrup, or HFCS) could be measured between colonies fed exclusively on these syrups. In one experiment, there was a significant difference in mean wax production between the treatment groups and a significant interaction between time and treatment for the colonies confined in a flight arena. On average, the colonies supplied with SS built 7916.7 cm(2) ± 1015.25 cm(2) honeycomb, while the colonies supplied with HFCS built 4571.63 cm(2) ± 786.45 cm(2). The mean mass of bees supplied with HFCS was 4.65 kg (± 0.97 kg), while those supplied with sucrose had a mean of 8.27 kg (± 1.26). There was no significant difference between treatment groups in terms of brood rearing. Differences in brood production were complicated due to possible nutritional deficiencies experienced by both treatment groups. In the second experiment, colonies supplemented with SS through the winter months at a remote field site exhibited increased spring brood production when compared to colonies fed with HFCS. The differences in adult bee populations were significant, having an overall average of 10.0 ± 1.3 frames of bees fed the sucrose syrup between November 2008 and April 2009, compared to 7.5 ± 1.6 frames of bees fed exclusively on HFCS. For commercial queen beekeepers, feeding the right supplementary carbohydrates could be especially important, given the findings of this study. PMID:23886010

  13. Honey bee colonies act as reservoirs for two Spiroplasma facultative symbionts and incur complex, multiyear infection dynamics

    PubMed Central

    Schwarz, Ryan S; Teixeira, Érica Weinstein; Tauber, James P; Birke, Juliane M; Martins, Marta Fonseca; Fonseca, Isabela; Evans, Jay D

    2014-01-01

    Two species of Spiroplasma (Mollicutes) bacteria were isolated from and described as pathogens of the European honey bee, Apis mellifera, ∼30 years ago but recent information on them is lacking despite global concern to understand bee population declines. Here we provide a comprehensive survey for the prevalence of these two Spiroplasma species in current populations of honey bees using improved molecular diagnostic techniques to assay multiyear colony samples from North America (U.S.A.) and South America (Brazil). Significant annual and seasonal fluctuations of Spiroplasma apis and Spiroplasma melliferum prevalence in colonies from the U.S.A. (n = 616) and Brazil (n = 139) occurred during surveys from 2011 through 2013. Overall, 33% of U.S.A. colonies and 54% of Brazil colonies were infected by Spiroplasma spp., where S. melliferum predominated over S. apis in both countries (25% vs. 14% and 44% vs. 38% frequency, respectively). Colonies were co-infected by both species more frequently than expected in both countries and at a much higher rate in Brazil (52%) compared to the U.S.A. (16.5%). U.S.A. samples showed that both species were prevalent not only during spring, as expected from prior research, but also during other seasons. These findings demonstrate that the model of honey bee spiroplasmas as springtime-restricted pathogens needs to be broadened and their role as occasional pathogens considered in current contexts. PMID:24771723

  14. An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization.

    PubMed

    Celik, Yuksel; Ulker, Erkan

    2013-01-01

    Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416

  15. An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization

    PubMed Central

    Celik, Yuksel; Ulker, Erkan

    2013-01-01

    Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416

  16. Ant colony optimization algorithm for continuous domains based on position distribution model of ant colony foraging.

    PubMed

    Liu, Liqiang; Dai, Yuntao; Gao, Jinyu

    2014-01-01

    Ant colony optimization algorithm for continuous domains is a major research direction for ant colony optimization algorithm. In this paper, we propose a distribution model of ant colony foraging, through analysis of the relationship between the position distribution and food source in the process of ant colony foraging. We design a continuous domain optimization algorithm based on the model and give the form of solution for the algorithm, the distribution model of pheromone, the update rules of ant colony position, and the processing method of constraint condition. Algorithm performance against a set of test trials was unconstrained optimization test functions and a set of optimization test functions, and test results of other algorithms are compared and analyzed to verify the correctness and effectiveness of the proposed algorithm. PMID:24955402

  17. Lower Virus Infections in Varroa destructor-Infested and Uninfested Brood and Adult Honey Bees (Apis mellifera) of a Low Mite Population Growth Colony Compared to a High Mite Population Growth Colony

    PubMed Central

    Emsen, Berna; Hamiduzzaman, Mollah Md.; Goodwin, Paul H.; Guzman-Novoa, Ernesto

    2015-01-01

    A comparison was made of the prevalence and relative quantification of deformed wing virus (DWV), Israeli acute paralysis virus (IAPV), black queen cell virus (BQCV), Kashmir bee virus (KBV), acute bee paralysis virus (ABPV) and sac brood virus (SBV) in brood and adult honey bees (Apis mellifera) from colonies selected for high (HMP) and low (LMP) Varroa destructor mite population growth. Two viruses, ABPV and SBV, were never detected. For adults without mite infestation, DWV, IAPV, BQCV and KBV were detected in the HMP colony; however, only BQCV was detected in the LMP colony but at similar levels as in the HMP colony. With mite infestation, the four viruses were detected in adults of the HMP colony but all at higher amounts than in the LMP colony. For brood without mite infestation, DWV and IAPV were detected in the HMP colony, but no viruses were detected in the LMP colony. With mite infestation of brood, the four viruses were detected in the HMP colony, but only DWV and IAPV were detected and at lower amounts in the LMP colony. An epidemiological explanation for these results is that pre-experiment differences in virus presence and levels existed between the HMP and LMP colonies. It is also possible that low V. destructor population growth in the LMP colony resulted in the bees being less exposed to the mite and thus less likely to have virus infections. LMP and HMP bees may have also differed in susceptibility to virus infection. PMID:25723540

  18. Lower virus infections in Varroa destructor-infested and uninfested brood and adult honey bees (Apis mellifera) of a low mite population growth colony compared to a high mite population growth colony.

    PubMed

    Emsen, Berna; Hamiduzzaman, Mollah Md; Goodwin, Paul H; Guzman-Novoa, Ernesto

    2015-01-01

    A comparison was made of the prevalence and relative quantification of deformed wing virus (DWV), Israeli acute paralysis virus (IAPV), black queen cell virus (BQCV), Kashmir bee virus (KBV), acute bee paralysis virus (ABPV) and sac brood virus (SBV) in brood and adult honey bees (Apis mellifera) from colonies selected for high (HMP) and low (LMP) Varroa destructor mite population growth. Two viruses, ABPV and SBV, were never detected. For adults without mite infestation, DWV, IAPV, BQCV and KBV were detected in the HMP colony; however, only BQCV was detected in the LMP colony but at similar levels as in the HMP colony. With mite infestation, the four viruses were detected in adults of the HMP colony but all at higher amounts than in the LMP colony. For brood without mite infestation, DWV and IAPV were detected in the HMP colony, but no viruses were detected in the LMP colony. With mite infestation of brood, the four viruses were detected in the HMP colony, but only DWV and IAPV were detected and at lower amounts in the LMP colony. An epidemiological explanation for these results is that pre-experiment differences in virus presence and levels existed between the HMP and LMP colonies. It is also possible that low V. destructor population growth in the LMP colony resulted in the bees being less exposed to the mite and thus less likely to have virus infections. LMP and HMP bees may have also differed in susceptibility to virus infection. PMID:25723540

  19. An Observational Study of Honey Bee Colony Winter Losses and Their Association with Varroa destructor, Neonicotinoids and Other Risk Factors

    PubMed Central

    van der Zee, Romée; Gray, Alison; Pisa, Lennard; de Rijk, Theo

    2015-01-01

    This article presents results of an analysis of honey bee losses over the winter of 2011-2012 in the Netherlands, from a sample of 86 colonies, located at 43 apiaries. The apiaries were selected using spatially stratified random sampling. Colony winter loss data were collected and related to various measures of colony strength recorded in summer, as well as data from laboratory analysis of sample material taken from two selected colonies in each of the 43 apiaries. The logistic regression model which best explained the risk of winter loss included, in order of statistical importance, the variables (1) Varroa destructor mite infestation rate in October 2011, (2) presence of the cyano-substituted neonicotinoids acetamiprid or thiacloprid in the first 2 weeks of August 2011 in at least one of the honey bee matrices honey, bees or bee bread (pollen), (3) presence of Brassica napus (oilseed rape) or Sinapis arvensis (wild mustard) pollen in bee bread in early August 2011, and (4) a measure of the unexplained winter losses for the postal code area where the colonies were located, obtained from a different dataset. We consider in the discussion that reduced opportunities for foraging in July and August because of bad weather may have added substantially to the adverse effects of acetamiprid and thiacloprid. A novel feature of this work is its use of postal code random effects from two other independent datasets collected in the annual national monitoring by questionnaires of winter losses of honey bees in the Netherlands. These were used to plan the sample selection and also in the model fitting of the data in this study. It should however be noted that the results of the present pilot study are based on limited data, which may consequently reveal strong factors but fail to demonstrate possible interaction effects. PMID:26154346

  20. An Observational Study of Honey Bee Colony Winter Losses and Their Association with Varroa destructor, Neonicotinoids and Other Risk Factors.

    PubMed

    van der Zee, Romée; Gray, Alison; Pisa, Lennard; de Rijk, Theo

    2015-01-01

    This article presents results of an analysis of honey bee losses over the winter of 2011-2012 in the Netherlands, from a sample of 86 colonies, located at 43 apiaries. The apiaries were selected using spatially stratified random sampling. Colony winter loss data were collected and related to various measures of colony strength recorded in summer, as well as data from laboratory analysis of sample material taken from two selected colonies in each of the 43 apiaries. The logistic regression model which best explained the risk of winter loss included, in order of statistical importance, the variables (1) Varroa destructor mite infestation rate in October 2011, (2) presence of the cyano-substituted neonicotinoids acetamiprid or thiacloprid in the first 2 weeks of August 2011 in at least one of the honey bee matrices honey, bees or bee bread (pollen), (3) presence of Brassica napus (oilseed rape) or Sinapis arvensis (wild mustard) pollen in bee bread in early August 2011, and (4) a measure of the unexplained winter losses for the postal code area where the colonies were located, obtained from a different dataset. We consider in the discussion that reduced opportunities for foraging in July and August because of bad weather may have added substantially to the adverse effects of acetamiprid and thiacloprid. A novel feature of this work is its use of postal code random effects from two other independent datasets collected in the annual national monitoring by questionnaires of winter losses of honey bees in the Netherlands. These were used to plan the sample selection and also in the model fitting of the data in this study. It should however be noted that the results of the present pilot study are based on limited data, which may consequently reveal strong factors but fail to demonstrate possible interaction effects. PMID:26154346

  1. Modeling the dynamics of ant colony optimization.

    PubMed

    Merkle, Daniel; Middendorf, Martin

    2002-01-01

    The dynamics of Ant Colony Optimization (ACO) algorithms is studied using a deterministic model that assumes an average expected behavior of the algorithms. The ACO optimization metaheuristic is an iterative approach, where in every iteration, artificial ants construct solutions randomly but guided by pheromone information stemming from former ants that found good solutions. The behavior of ACO algorithms and the ACO model are analyzed for certain types of permutation problems. It is shown analytically that the decisions of an ant are influenced in an intriguing way by the use of the pheromone information and the properties of the pheromone matrix. This explains why ACO algorithms can show a complex dynamic behavior even when there is only one ant per iteration and no competition occurs. The ACO model is used to describe the algorithm behavior as a combination of situations with different degrees of competition between the ants. This helps to better understand the dynamics of the algorithm when there are several ants per iteration as is always the case when using ACO algorithms for optimization. Simulations are done to compare the behavior of the ACO model with the ACO algorithm. Results show that the deterministic model describes essential features of the dynamics of ACO algorithms quite accurately, while other aspects of the algorithms behavior cannot be found in the model. PMID:12227995

  2. Within-Colony Variation in the Immunocompetency of Managed and Feral Honey Bees (Apis mellifera L.) in Different Urban Landscapes

    PubMed Central

    Appler, R. Holden; Frank, Steven D.; Tarpy, David R.

    2015-01-01

    Urbanization has the potential to dramatically affect insect populations worldwide, although its effects on pollinator populations are just beginning to be understood. We compared the immunocompetency of honey bees sampled from feral (wild-living) and managed (beekeeper-owned) honey bee colonies. We sampled foragers from feral and managed colonies in rural, suburban, and urban landscapes in and around Raleigh, NC, USA. We then analyzed adult workers using two standard bioassays for insect immune function (encapsulation response and phenoloxidase activity). We found that there was far more variation within colonies for encapsulation response or phenoloxidase activity than among rural to urban landscapes, and we did not observe any significant difference in immune response between feral and managed bees. These findings suggest that social pollinators, like honey bees, may be sufficiently robust or variable in their immune responses to obscure any subtle effects of urbanization. Additional studies of immune physiology and disease ecology of social and solitary bees in urban, suburban, and natural ecosystems will provide insights into the relative effects of changing urban environments on several important factors that influence pollinator productivity and health. PMID:26529020

  3. Individual responsiveness to shock and colony-level aggression in honey bees: evidence for a genetic component

    PubMed Central

    Avalos, Arian; Rodríguez-Cruz, Yoselyn; Giray, Tugrul

    2015-01-01

    The phenotype of the social group is related to phenotypes of individuals that form that society. We examined how honey bee colony aggressiveness relates to individual response of male drones and foraging workers. Although the natural focus in colony aggression has been on the worker caste, the sterile females engaged in colony maintenance and defense, males carry the same genes. We measured aggressiveness scores of colonies and examined components of individual aggressive behavior in workers and haploid sons of workers from the same colony. We describe for the first time, that males, although they have no stinger, do bend their abdomen (abdominal flexion) in a posture similar to stinging behavior of workers in response to electric shock. Individual worker sting response and movement rates in response to shock were significantly correlated with colony scores. In the case of drones, sons of workers from the same colonies, abdominal flexion significantly correlated but their movement rates did not correlate with colony aggressiveness. Furthermore, the number of workers responding at increasing levels of voltage exhibits a threshold-like response, whereas the drones respond in increasing proportion to shock. We conclude that there are common and caste-specific components to aggressive behavior in honey bees. We discuss implications of these results on social and behavioral regulation and genetics of aggressive response. PMID:25729126

  4. Comparisons of Pollen Substitute Diets for Honey bees: Consumprion Rates by Colonies and Effects on Brood and Adult Populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Commercially available pollen substitute diets for honey bees (Apis mellifera L.) were evaluated for consumption and colony growth (brood and adult populations) and compared with pollen cake and high fructose corn syrup (HFCS). Two trials were conducted; the first for 4 months during the fall and wi...

  5. Comparisons of pollen substitute diets for honey bees: consumption rates by colonies and effects on brood and adult populations.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Commercially available pollen substitute diets for honey bees (Apis mellifera L.) were evaluated for consumption and colony growth (brood and adult populations) and compared with pollen cake and high fructose corn syrup (HFCS). Two trials were conducted; the first for 3 months during the fall and w...

  6. 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.

  7. Phenotypic and Genetic Analyses of the Varroa Sensitive Hygienic Trait in Russian Honey Bee (Hymenoptera: Apidae) Colonies

    PubMed Central

    Kirrane, Maria J.; de Guzman, Lilia I.; Holloway, Beth; Frake, Amanda M.; Rinderer, Thomas E.; Whelan, Pádraig M.

    2015-01-01

    Varroa destructor continues to threaten colonies of European honey bees. General hygiene, and more specific Varroa Sensitive Hygiene (VSH), provide resistance towards the Varroa mite in a number of stocks. In this study, 32 Russian (RHB) and 14 Italian honey bee colonies were assessed for the VSH trait using two different assays. Firstly, colonies were assessed using the standard VSH behavioural assay of the change in infestation of a highly infested donor comb after a one-week exposure. Secondly, the same colonies were assessed using an “actual brood removal assay” that measured the removal of brood in a section created within the donor combs as a potential alternative measure of hygiene towards Varroa-infested brood. All colonies were then analysed for the recently discovered VSH quantitative trait locus (QTL) to determine whether the genetic mechanisms were similar across different stocks. Based on the two assays, RHB colonies were consistently more hygienic toward Varroa-infested brood than Italian honey bee colonies. The actual number of brood cells removed in the defined section was negatively correlated with the Varroa infestations of the colonies (r2 = 0.25). Only two (percentages of brood removed and reproductive foundress Varroa) out of nine phenotypic parameters showed significant associations with genotype distributions. However, the allele associated with each parameter was the opposite of that determined by VSH mapping. In this study, RHB colonies showed high levels of hygienic behaviour towards Varroa -infested brood. The genetic mechanisms are similar to those of the VSH stock, though the opposite allele associates in RHB, indicating a stable recombination event before the selection of the VSH stock. The measurement of brood removal is a simple, reliable alternative method of measuring hygienic behaviour towards Varroa mites, at least in RHB stock. PMID:25909856

  8. Phenotypic and genetic analyses of the varroa sensitive hygienic trait in Russian honey bee (hymenoptera: apidae) colonies.

    PubMed

    Kirrane, Maria J; de Guzman, Lilia I; Holloway, Beth; Frake, Amanda M; Rinderer, Thomas E; Whelan, Pádraig M

    2014-01-01

    Varroa destructor continues to threaten colonies of European honey bees. General hygiene, and more specific Varroa Sensitive Hygiene (VSH), provide resistance towards the Varroa mite in a number of stocks. In this study, 32 Russian (RHB) and 14 Italian honey bee colonies were assessed for the VSH trait using two different assays. Firstly, colonies were assessed using the standard VSH behavioural assay of the change in infestation of a highly infested donor comb after a one-week exposure. Secondly, the same colonies were assessed using an "actual brood removal assay" that measured the removal of brood in a section created within the donor combs as a potential alternative measure of hygiene towards Varroa-infested brood. All colonies were then analysed for the recently discovered VSH quantitative trait locus (QTL) to determine whether the genetic mechanisms were similar across different stocks. Based on the two assays, RHB colonies were consistently more hygienic toward Varroa-infested brood than Italian honey bee colonies. The actual number of brood cells removed in the defined section was negatively correlated with the Varroa infestations of the colonies (r2 = 0.25). Only two (percentages of brood removed and reproductive foundress Varroa) out of nine phenotypic parameters showed significant associations with genotype distributions. However, the allele associated with each parameter was the opposite of that determined by VSH mapping. In this study, RHB colonies showed high levels of hygienic behaviour towards Varroa -infested brood. The genetic mechanisms are similar to those of the VSH stock, though the opposite allele associates in RHB, indicating a stable recombination event before the selection of the VSH stock. The measurement of brood removal is a simple, reliable alternative method of measuring hygienic behaviour towards Varroa mites, at least in RHB stock. PMID:25909856

  9. Effect of formic acid formulations on honey bee (Hymenoptera: Apidae) colonies and influence of colony and ambient conditions on formic acid concentration in the hive.

    PubMed

    Ostermann, David J; Currie, Robert W

    2004-10-01

    The interaction between the effects of varroa, Varroa destructor Anderson & Trueman, and formic acid treatments on colonies of honey bees, Apis mellifera L., were examined in two field experiments. In experiment 1, colonies with low varroa levels were exposed to two different slow-release formulations and compared with untreated colonies. In experiment 2, colonies inoculated with varroa and uninoculated colonies were exposed to a slow-release formulation, a pour-on formulation, or were left untreated. The effects of treatments, hive temperature, and hive relative humidity on formic acid concentration in hive air also were examined. Slow-release formic acid application improved colony development in colonies that had been inoculated with varroa. However, in uninoculated colonies where the mean abundance of varroa was low, slow-release formic acid application suppressed colony development. The pour-on application did not have a negative impact on worker population growth in uninoculated colonies, but also it was not as effective as the slow-release treatment in improving population growth in varroa-inoculated colonies. Equivalent volumes of acid applied in pour-on and slow-release formulations provided the same cumulative dose in hive air but differed in the daily pattern of formic acid release. Colonies that were not inoculated with varroa had higher concentrations of formic acid in hive air than colonies that were inoculated with varroa on three of the five pour-on application dates. The data suggest that reductions in worker population and/or activity caused by varroa can interact with ambient conditions to affect the volatilization or sorption of formic acid in the hive. PMID:15568335

  10. Autumn invasion rates of Varroa destructor (Mesostigmata: Varroidae) into honey bee (Hymenoptera: Apidae) colonies and the resulting increase in mite populations.

    PubMed

    Frey, Eva; Rosenkranz, Peter

    2014-04-01

    The honey bee parasite Varroa destructor Anderson & Trueman can disperse and invade honey bee colonies by attaching to "drifting" and "robbing" honey bees that move into nonnatal colonies. We quantified the weekly invasion rates and the subsequent mite population growth from the end of July to November 2011 in 28 honey bee colonies kept in two apiaries that had high (HBD) and low (LBD) densities of neighboring colonies. At each apiary, half (seven) of the colonies were continuously treated with acaricides to kill all Varroa mites and thereby determine the invasion rates. The other group of colonies was only treated before the beginning of the experiment and then left untreated to record Varroa population growth until a final treatment in November. The numbers of bees and brood cells of all colonies were estimated according to the Liebefeld evaluation method. The invasion rates varied among individual colonies but revealed highly significant differences between the study sites. The average invasion rate per colony over the entire 3.5-mo period ranged from 266 to 1,171 mites at the HBD site compared with only 72 to 248 mites at the LBD apiary. In the untreated colonies, the Varroa population reached an average final infestation in November of 2,082 mites per colony (HBD) and 340 mites per colony (LBD). All colonies survived the winter; however, the higher infested colonies lost about three times more bees compared with the lower infested colonies. Therefore, mite invasion and late-year population growth must be considered more carefully for future treatment concepts in temperate regions. PMID:24772528

  11. Honey Bee Mating Optimization Vector Quantization Scheme in Image Compression

    NASA Astrophysics Data System (ADS)

    Horng, Ming-Huwi

    The vector quantization is a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, particle swarm optimization (PSO) is adapted to obtain the near-global optimal codebook of vector quantization. In this paper, we applied a new swarm algorithm, honey bee mating optimization, to construct the codebook of vector quantization. The proposed method is called the honey bee mating optimization based LBG (HBMO-LBG) algorithm. The results were compared with the other two methods that are LBG and PSO-LBG algorithms. Experimental results showed that the proposed HBMO-LBG algorithm is more reliable and the reconstructed images get higher quality than those generated form the other three methods.

  12. An Improved Artificial Bee Colony Algorithm for Solving Hybrid Flexible Flowshop With Dynamic Operation Skipping.

    PubMed

    Li, Jun-Qing; Pan, Quan-Ke; Duan, Pei-Yong

    2016-06-01

    In this paper, we propose an improved discrete artificial bee colony (DABC) algorithm to solve the hybrid flexible flowshop scheduling problem with dynamic operation skipping features in molten iron systems. First, each solution is represented by a two-vector-based solution representation, and a dynamic encoding mechanism is developed. Second, a flexible decoding strategy is designed. Next, a right-shift strategy considering the problem characteristics is developed, which can clearly improve the solution quality. In addition, several skipping and scheduling neighborhood structures are presented to balance the exploration and exploitation ability. Finally, an enhanced local search is embedded in the proposed algorithm to further improve the exploitation ability. The proposed algorithm is tested on sets of the instances that are generated based on the realistic production. Through comprehensive computational comparisons and statistical analysis, the highly effective performance of the proposed DABC algorithm is favorably compared against several presented algorithms, both in solution quality and efficiency. PMID:26126292

  13. Small and Dim Target Detection via Lateral Inhibition Filtering and Artificial Bee Colony Based Selective Visual Attention

    PubMed Central

    Duan, Haibin; Deng, Yimin; Wang, Xiaohua; Xu, Chunfang

    2013-01-01

    This paper proposed a novel bionic selective visual attention mechanism to quickly select regions that contain salient objects to reduce calculations. Firstly, lateral inhibition filtering, inspired by the limulus’ ommateum, is applied to filter low-frequency noises. After the filtering operation, we use Artificial Bee Colony (ABC) algorithm based selective visual attention mechanism to obtain the interested object to carry through the following recognition operation. In order to eliminate the camera motion influence, this paper adopted ABC algorithm, a new optimization method inspired by swarm intelligence, to calculate the motion salience map to integrate with conventional visual attention. To prove the feasibility and effectiveness of our method, several experiments were conducted. First the filtering results of lateral inhibition filter were shown to illustrate its noise reducing effect, then we applied the ABC algorithm to obtain the motion features of the image sequence. The ABC algorithm is proved to be more robust and effective through the comparison between ABC algorithm and popular Particle Swarm Optimization (PSO) algorithm. Except for the above results, we also compared the classic visual attention mechanism and our ABC algorithm based visual attention mechanism, and the experimental results of which further verified the effectiveness of our method. PMID:23991033

  14. Small and dim target detection via lateral inhibition filtering and Artificial Bee colony based selective visual attention.

    PubMed

    Duan, Haibin; Deng, Yimin; Wang, Xiaohua; Xu, Chunfang

    2013-01-01

    This paper proposed a novel bionic selective visual attention mechanism to quickly select regions that contain salient objects to reduce calculations. Firstly, lateral inhibition filtering, inspired by the limulus' ommateum, is applied to filter low-frequency noises. After the filtering operation, we use Artificial Bee Colony (ABC) algorithm based selective visual attention mechanism to obtain the interested object to carry through the following recognition operation. In order to eliminate the camera motion influence, this paper adopted ABC algorithm, a new optimization method inspired by swarm intelligence, to calculate the motion salience map to integrate with conventional visual attention. To prove the feasibility and effectiveness of our method, several experiments were conducted. First the filtering results of lateral inhibition filter were shown to illustrate its noise reducing effect, then we applied the ABC algorithm to obtain the motion features of the image sequence. The ABC algorithm is proved to be more robust and effective through the comparison between ABC algorithm and popular Particle Swarm Optimization (PSO) algorithm. Except for the above results, we also compared the classic visual attention mechanism and our ABC algorithm based visual attention mechanism, and the experimental results of which further verified the effectiveness of our method. PMID:23991033

  15. The hyper-cube framework for ant colony optimization.

    PubMed

    Blum, Christian; Dorigo, Marco

    2004-04-01

    Ant colony optimization is a metaheuristic approach belonging to the class of model-based search algorithms. In this paper, we propose a new framework for implementing ant colony optimization algorithms called the hyper-cube framework for ant colony optimization. In contrast to the usual way of implementing ant colony optimization algorithms, this framework limits the pheromone values to the interval [0,1]. This is obtained by introducing changes in the pheromone value update rule. These changes can in general be applied to any pheromone value update rule used in ant colony optimization. We discuss the benefits coming with this new framework. The benefits are twofold. On the theoretical side, the new framework allows us to prove that in Ant System, the ancestor of all ant colony optimization algorithms, the average quality of the solutions produced increases in expectation over time when applied to unconstrained problems. On the practical side, the new framework automatically handles the scaling of the objective function values. We experimentally show that this leads on average to a more robust behavior of ant colony optimization algorithms. PMID:15376861

  16. Bees for development: Brazilian survey reveals how to optimize stingless beekeeping.

    PubMed

    Jaffé, Rodolfo; Pope, Nathaniel; Torres Carvalho, Airton; Madureira Maia, Ulysses; Blochtein, Betina; de Carvalho, Carlos Alfredo Lopes; Carvalho-Zilse, Gislene Almeida; Freitas, Breno Magalhães; Menezes, Cristiano; Ribeiro, Márcia de Fátima; Venturieri, Giorgio Cristino; Imperatriz-Fonseca, Vera Lucia

    2015-01-01

    Stingless bees are an important asset to assure plant biodiversity in many natural ecosystems, and fulfill the growing agricultural demand for pollination. However, across developing countries stingless beekeeping remains an essentially informal activity, technical knowledge is scarce, and management practices lack standardization. Here we profited from the large diversity of stingless beekeepers found in Brazil to assess the impact of particular management practices on productivity and economic revenues from the commercialization of stingless bee products. Our study represents the first large-scale effort aiming at optimizing stingless beekeeping for honey/colony production based on quantitative data. Survey data from 251 beekeepers scattered across 20 Brazilian States revealed the influence of specific management practices and other confounding factors over productivity and income indicators. Specifically, our results highlight the importance of teaching beekeepers how to inspect and feed their colonies, how to multiply them and keep track of genetic lineages, how to harvest and preserve the honey, how to use vinegar traps to control infestation by parasitic flies, and how to add value by labeling honey containers. Furthermore, beekeeping experience and the network of known beekeepers were found to be key factors influencing productivity and income. Our work provides clear guidelines to optimize stingless beekeeping and help transform the activity into a powerful tool for sustainable development. PMID:25826402

  17. Bees for Development: Brazilian Survey Reveals How to Optimize Stingless Beekeeping

    PubMed Central

    Jaffé, Rodolfo; Pope, Nathaniel; Carvalho, Airton Torres; Maia, Ulysses Madureira; Blochtein, Betina; de Carvalho, Carlos Alfredo Lopes; Carvalho-Zilse, Gislene Almeida; Freitas, Breno Magalhães; Menezes, Cristiano; de Fátima Ribeiro, Márcia; Venturieri, Giorgio Cristino; Imperatriz-Fonseca, Vera Lucia

    2015-01-01

    Stingless bees are an important asset to assure plant biodiversity in many natural ecosystems, and fulfill the growing agricultural demand for pollination. However, across developing countries stingless beekeeping remains an essentially informal activity, technical knowledge is scarce, and management practices lack standardization. Here we profited from the large diversity of stingless beekeepers found in Brazil to assess the impact of particular management practices on productivity and economic revenues from the commercialization of stingless bee products. Our study represents the first large-scale effort aiming at optimizing stingless beekeeping for honey/colony production based on quantitative data. Survey data from 251 beekeepers scattered across 20 Brazilian States revealed the influence of specific management practices and other confounding factors over productivity and income indicators. Specifically, our results highlight the importance of teaching beekeepers how to inspect and feed their colonies, how to multiply them and keep track of genetic lineages, how to harvest and preserve the honey, how to use vinegar traps to control infestation by parasitic flies, and how to add value by labeling honey containers. Furthermore, beekeeping experience and the network of known beekeepers were found to be key factors influencing productivity and income. Our work provides clear guidelines to optimize stingless beekeeping and help transform the activity into a powerful tool for sustainable development. PMID:25826402

  18. Effect of Lactobacillus johnsonii CRL1647 on different parameters of honeybee colonies and bacterial populations of the bee gut.

    PubMed

    Audisio, M C; Sabaté, D C; Benítez-Ahrendts, M R

    2015-01-01

    Lactobacillus johnsonii CRL1647, isolated from the intestinal tract of a worker-bee in Salta, Argentina, was delivered to Apis mellifera L. honey bee colonies according to two different administration schedules: 1×10(5) cfu/ml every 15 days (2011) or monthly (2012). The effect of each treatment on the bee-colony performance was monitored by measuring honey production, and the prevalence of varroasis and nosemosis. Worker bees from each assay were randomly captured 3 days after administration and assayed for the following intestinal culturable and defined bacterial populations: total aerobic microorganisms, Bacillus spp. spores, Lactobacillus spp., Enterococcus spp. and enterobacteria. Interestingly, both treatments generated a similar increase in honey production in treated colonies compared to controls: 36.8% (every 15 days) and 36.3% (monthly). Nosema index always exhibited a reduction when lactobacilli were administered; in turn, Varroa incidence was lower when the lactobacilli were administered once a month. Moreover, the administration of L. johnsonii CRL1647 every 15 days produced an increase in the total number of aerobic microorganisms and in bacteria belonging to the genera Lactobacillus and Enterococcus; at the same time, a decrease was observed in the number of total spores at the end of the treatment. The number of enterobacteria was constant and remained below that of control hives at the end of the assay. On the other hand, the delivery of lactobacilli once a month only showed an increase in the number of bacteria belonging to the genus Lactobacillus; meanwhile, viable counts of the remaining microorganisms assayed were reduced. Even though it seems that both treatments were similar, those bee colonies that received L. johnsonii CRL1647 every 15 days became so strong that they swarmed. PMID:25809216

  19. Pheromone-modulated behavioral suites influence colony growth in the honey bee (Apis mellifera)

    NASA Astrophysics Data System (ADS)

    Pankiw, Tanya; Roman, Roman; Sagili, Ramesh R.; Zhu-Salzman, Keyan

    2004-12-01

    The success of a species depends on its ability to assess its environment and to decide accordingly which behaviors are most appropriate. Many animal species, from bacteria to mammals, are able to communicate using interspecies chemicals called pheromones. In addition to exerting physiological effects on individuals, for social species, pheromones communicate group social structure. Communication of social structure is important to social insects for the allocation of its working members into coordinated suites of behaviors. We tested effects of long-term treatment with brood pheromone on suites of honey bee brood rearing and foraging behaviors. Pheromone-treated colonies reared significantly greater brood areas and more adults than controls, while amounts of stored pollen and honey remained statistically similar. Brood pheromone increased the number of pollen foragers and the pollen load weights they returned. It appeared that the pheromone-induced increase in pollen intake was directly canalized into more brood rearing. A two-way pheromone priming effect was observed, such that some workers from the same age cohorts showed an increased and extended capacity to rear larvae, while others were recruited at significantly younger ages into pollen-specific foraging. Brood pheromone affected suites of nursing and foraging behaviors allocating worker and pollen resources associated with an important fitness trait, colony growth.

  20. Discover for Yourself: An Optimal Control Model in Insect Colonies

    ERIC Educational Resources Information Center

    Winkel, Brian

    2013-01-01

    We describe the enlightening path of self-discovery afforded to the teacher of undergraduate mathematics. This is demonstrated as we find and develop background material on an application of optimal control theory to model the evolutionary strategy of an insect colony to produce the maximum number of queen or reproducer insects in the colony at…

  1. Colonies of bumble bees (Bombus impatiens) produce fewer workers, less bee biomass, and have smaller mother queens following fungicide exposure

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bees provide vital pollination services to the majority of flowering plants in both natural and agricultural systems. Unfortunately, both native and managed bee populations are experiencing serious declines, threatening the persistence of these plants and crops. Agricultural chemicals are one possib...

  2. Managed European-Derived Honey Bee, Apis mellifera sspp, Colonies Reduce African-Matriline Honey Bee, A. m. scutellata, Drones at Regional Mating Congregations

    PubMed Central

    Mortensen, Ashley N.; Ellis, James D.

    2016-01-01

    African honey bees (Apis mellifera scutellata) dramatically changed the South American beekeeping industry as they rapidly spread through the Americas following their introduction into Brazil. In the present study, we aimed to determine if the management of European-derived honey bees (A. mellifera sspp.) could reduce the relative abundance of African-matriline drones at regional mating sites known as drone congregation areas (DCAs). We collected 2,400 drones at six DCAs either 0.25 km or >2.8 km from managed European-derived honey bee apiaries. The maternal ancestry of each drone was determined by Bgl II enzyme digestion of an amplified portion of the mitochondrial Cytochrome b gene. Furthermore, sibship reconstruction via nuclear microsatellites was conducted for a subset of 1,200 drones to estimate the number of colonies contributing drones to each DCA. Results indicate that DCAs distant to managed European apiaries (>2.8 km) had significantly more African−matriline drones (34.33% of the collected drones had African mitochondrial DNA) than did DCAs close (0.25 km) to managed European apiaries (1.83% of the collected drones had African mitochondrial DNA). Furthermore, nuclear sibship reconstruction demonstrated that the reduction in the proportion of African matriline drones at DCAs near apiaries was not simply an increase in the number of European matriline drones at the DCAs but also the result of fewer African matriline colonies contributing drones to the DCAs. Our data demonstrate that the management of European honey bee colonies can dramatically influence the proportion of drones with African matrilines at nearby drone congregation areas, and would likely decreasing the probability that virgin European queens will mate with African drones at those drone congregation areas. PMID:27518068

  3. Managed European-Derived Honey Bee, Apis mellifera sspp, Colonies Reduce African-Matriline Honey Bee, A. m. scutellata, Drones at Regional Mating Congregations.

    PubMed

    Mortensen, Ashley N; Ellis, James D

    2016-01-01

    African honey bees (Apis mellifera scutellata) dramatically changed the South American beekeeping industry as they rapidly spread through the Americas following their introduction into Brazil. In the present study, we aimed to determine if the management of European-derived honey bees (A. mellifera sspp.) could reduce the relative abundance of African-matriline drones at regional mating sites known as drone congregation areas (DCAs). We collected 2,400 drones at six DCAs either 0.25 km or >2.8 km from managed European-derived honey bee apiaries. The maternal ancestry of each drone was determined by Bgl II enzyme digestion of an amplified portion of the mitochondrial Cytochrome b gene. Furthermore, sibship reconstruction via nuclear microsatellites was conducted for a subset of 1,200 drones to estimate the number of colonies contributing drones to each DCA. Results indicate that DCAs distant to managed European apiaries (>2.8 km) had significantly more African-matriline drones (34.33% of the collected drones had African mitochondrial DNA) than did DCAs close (0.25 km) to managed European apiaries (1.83% of the collected drones had African mitochondrial DNA). Furthermore, nuclear sibship reconstruction demonstrated that the reduction in the proportion of African matriline drones at DCAs near apiaries was not simply an increase in the number of European matriline drones at the DCAs but also the result of fewer African matriline colonies contributing drones to the DCAs. Our data demonstrate that the management of European honey bee colonies can dramatically influence the proportion of drones with African matrilines at nearby drone congregation areas, and would likely decreasing the probability that virgin European queens will mate with African drones at those drone congregation areas. PMID:27518068

  4. The distribution of Paenibacillus larvae spores in adult bees and honey and larval mortality, following the addition of American foulbrood diseased brood or spore-contaminated honey in honey bee (Apis mellifera) colonies.

    PubMed

    Lindström, Anders; Korpela, Seppo; Fries, Ingemar

    2008-09-01

    Within colony transmission of Paenibacillus larvae spores was studied by giving spore-contaminated honey comb or comb containing 100 larvae killed by American foulbrood to five experimental colonies respectively. We registered the impact of the two treatments on P. larvae spore loads in adult bees and honey and on larval mortality by culturing for spores in samples of adult bees and honey, respectively, and by measuring larval survival. The results demonstrate a direct effect of treatment on spore levels in adult bees and honey as well as on larval mortality. Colonies treated with dead larvae showed immediate high spore levels in adult bee samples, while the colonies treated with contaminated honey showed a comparable spore load but the effect was delayed until the bees started to utilize the honey at the end of the flight season. During the winter there was a build up of spores in the adult bees, which may increase the risk for infection in spring. The results confirm that contaminated honey can act as an environmental reservoir of P. larvae spores and suggest that less spores may be needed in honey, compared to in diseased brood, to produce clinically diseased colonies. The spore load in adult bee samples was significantly related to larval mortality but the spore load of honey samples was not. PMID:18640122

  5. Development of a user-friendly delivery method for the fungus Metarhizium anisopliac to control the ectoparasitic mite Varroa destructor in honey bee, Apis mellifera, colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A user-friendly method to deliver Metarhizium spores to honey bee colonies for control of Varroa mites was developed and tested. Patty blend formulations protected the fungal spores at brood nest temperatures and served as an improved delivery system of the fungus to bee hives. Field trials conducte...

  6. An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

    NASA Astrophysics Data System (ADS)

    Hsu, Chih-Ming

    2014-12-01

    Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

  7. Modeling design iteration in product design and development and its solution by a novel artificial bee colony algorithm.

    PubMed

    Chen, Tinggui; Xiao, Renbin

    2014-01-01

    Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584

  8. Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm

    PubMed Central

    2014-01-01

    Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584

  9. Out with the garbage: the parasitic strategy of the mantisfly Plega hagenella mass-infesting colonies of the eusocial bee Melipona subnitida in northeastern Brazil

    NASA Astrophysics Data System (ADS)

    Maia-Silva, Camila; Hrncir, Michael; Koedam, Dirk; Machado, Renato Jose Pires; Imperatriz-Fonseca, Vera Lucia

    2013-01-01

    Between April and June of 2012 mantisflies ( Plega hagenella) were found to be extensively parasitizing the nests of two groups of managed colonzies of eusocial stingless bees ( Melipona subnitida) in the semi-arid region of northeastern Brazil. The mantisfly larvae developed inside closed brood cells of the bee comb, where each mantispid larva fed on the bee larva or pupa present in a single brood cell. Mature mantispid larvae pupated inside silken cocoons spun in place within their hosts' brood cells then emerged as pharate adults inside the bee colony. Pharate adults were never attacked and killed by host colony workers. Instead, colony workers picked up the pharates and removed them from the nest unharmed, treating them similar to the way that the general refuse is removed from the nest. Adult mantispids subsequently eclosed from their pupal exuviae outside the nest. Manipulative experiments showed that post-eclosion adult mantispids placed back within active bee colonies were quickly attacked and killed. These observations demonstrate that pharate and post-eclosion adults of P. hagenella are perceived differently by colony workers and that delayed adult eclosion is an important functional element in the parasitic life strategy of P. hagenella, allowing adults to escape without injury from the bee colonies they parasitize.

  10. Overview of pesticide residues in stored pollen and their potential effect on bee colony (Apis mellifera) losses in Spain.

    PubMed

    Bernal, J; Garrido-Bailón, E; Del Nozal, M J; González-Porto, A V; Martín-Hernández, R; Diego, J C; Jiménez, J J; Bernal, J L; Higes, M

    2010-12-01

    In the last decade, an increase in honey bee (Apis mellifera L.) colony losses has been reported in several countries. The causes of this decline are still not clear. This study was set out to evaluate the pesticide residues in stored pollen from honey bee colonies and their possible impact on honey bee losses in Spain. In total, 1,021 professional apiaries were randomly selected. All pollen samples were subjected to multiresidue analysis by gas chromatography-mass spectrometry (MS) and liquid chromatography-MS; moreover, specific methods were applied for neonicotinoids and fipronil. A palynological analysis also was carried out to confirm the type of foraging crop. Pesticide residues were detected in 42% of samples collected in spring, and only in 31% of samples collected in autumn. Fluvalinate and chlorfenvinphos were the most frequently detected pesticides in the analyzed samples. Fipronil was detected in 3.7% of all the spring samples but never in autumn samples, and neonicotinoid residues were not detected. More than 47.8% of stored pollen samples belonged to wild vegetation, and sunflower (Heliantus spp.) pollen was only detected in 10.4% of the samples. A direct relation between pesticide residues found in stored pollen samples and colony losses was not evident accordingly to the obtained results. Further studies are necessary to determine the possible role of the most frequent and abundant pesticides (such as acaricides) and the synergism among them and with other pathogens more prevalent in Spain. PMID:21309214

  11. Population growth of Varroa destructor (Acari: Varroidae) in honey bee colonies is affected by the number of foragers with mites.

    PubMed

    DeGrandi-Hoffman, Gloria; Ahumada, Fabiana; Zazueta, Victor; Chambers, Mona; Hidalgo, Geoffrey; deJong, Emily Watkins

    2016-05-01

    Varroa mites are a serious pest of honey bees and the leading cause of colony losses. Varroa have relatively low reproductive rates, so populations should not increase rapidly, but often they do. Other factors might contribute to the growth of varroa populations including mite migration into colonies on foragers from other hives. We measured the proportion of foragers carrying mites on their bodies while entering and leaving hives, and determined its relationship to the growth of varroa populations in those hives at two apiary sites. We also compared the estimates of mite population growth with predictions from a varroa population dynamics model that generates estimates of mite population growth based on mite reproduction. Samples of capped brood and adult bees indicated that the proportion of brood cells infested with mites and adult bees with phoretic mites was low through the summer but increased sharply in the fall especially at site 1. The frequency of capturing foragers with mites on their bodies while entering or leaving hives also increased in the fall. The growth of varroa populations at both sites was not significantly related to our colony estimates of successful mite reproduction, but instead to the total number of foragers with mites (entering and leaving the colony). There were more foragers with mites at site 1 than site 2, and mite populations at site 1 were larger especially in the fall. The model accurately estimated phoretic mite populations and infested brood cells until November when predictions were much lower than those measured in colonies. The rapid growth of mite populations particularly in the fall being a product of mite migration rather than mite reproduction only is discussed. PMID:26910522

  12. Modeling discharge-sediment relationship using neural networks with artificial bee colony algorithm

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Ozkan, Coskun; Akay, Bahriye

    2012-03-01

    SummaryEstimation of suspended sediment concentration carried by a river is very important for many water resources projects. The accuracy of artificial neural networks (ANN) with artificial bee colony (ABC) algorithm is investigated in this paper for modeling discharge-suspended sediment relationship. The ANN-ABC was compared with those of the neural differential evolution, adaptive neuro-fuzzy, neural networks and rating curve models. The daily stream flow and suspended sediment concentration data from two stations, Rio Valenciano Station and Quebrada Blanca Station, were used as case studies. For evaluating the ability of the models, mean square error and determination coefficient criteria were used. Comparison results showed that the ANN-ABC was able to produce better results than the neural differential evolution, neuro-fuzzy, neural networks and rating curve models. The logarithm transformed data were also used as input to the proposed ANN-ABC models. It was found that the logarithm transform significantly increased accuracy of the models in suspended sediment estimation.

  13. Hyperspectral image clustering method based on artificial bee colony algorithm and Markov random fields

    NASA Astrophysics Data System (ADS)

    Sun, Xu; Yang, Lina; Gao, Lianru; Zhang, Bing; Li, Shanshan; Li, Jun

    2015-01-01

    Center-oriented hyperspectral image clustering methods have been widely applied to hyperspectral remote sensing image processing; however, the drawbacks are obvious, including the over-simplicity of computing models and underutilized spatial information. In recent years, some studies have been conducted trying to improve this situation. We introduce the artificial bee colony (ABC) and Markov random field (MRF) algorithms to propose an ABC-MRF-cluster model to solve the problems mentioned above. In this model, a typical ABC algorithm framework is adopted in which cluster centers and iteration conditional model algorithm's results are considered as feasible solutions and objective functions separately, and MRF is modified to be capable of dealing with the clustering problem. Finally, four datasets and two indices are used to show that the application of ABC-cluster and ABC-MRF-cluster methods could help to obtain better image accuracy than conventional methods. Specifically, the ABC-cluster method is superior when used for a higher power of spectral discrimination, whereas the ABC-MRF-cluster method can provide better results when used for an adjusted random index. In experiments on simulated images with different signal-to-noise ratios, ABC-cluster and ABC-MRF-cluster showed good stability.

  14. Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows

    PubMed Central

    Jawarneh, Sana; Abdullah, Salwani

    2015-01-01

    This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon’s 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results. PMID:26132158

  15. Improved artificial bee colony algorithm for wavefront sensor-less system in free space optical communication

    NASA Astrophysics Data System (ADS)

    Niu, Chaojun; Han, Xiang'e.

    2015-10-01

    Adaptive optics (AO) technology is an effective way to alleviate the effect of turbulence on free space optical communication (FSO). A new adaptive compensation method can be used without a wave-front sensor. Artificial bee colony algorithm (ABC) is a population-based heuristic evolutionary algorithm inspired by the intelligent foraging behaviour of the honeybee swarm with the advantage of simple, good convergence rate, robust and less parameter setting. In this paper, we simulate the application of the improved ABC to correct the distorted wavefront and proved its effectiveness. Then we simulate the application of ABC algorithm, differential evolution (DE) algorithm and stochastic parallel gradient descent (SPGD) algorithm to the FSO system and analyze the wavefront correction capabilities by comparison of the coupling efficiency, the error rate and the intensity fluctuation in different turbulence before and after the correction. The results show that the ABC algorithm has much faster correction speed than DE algorithm and better correct ability for strong turbulence than SPGD algorithm. Intensity fluctuation can be effectively reduced in strong turbulence, but not so effective in week turbulence.

  16. Protein structure optimization with a "Lamarckian" ant colony algorithm.

    PubMed

    Oakley, Mark T; Richardson, E Grace; Carr, Harriet; Johnston, Roy L

    2013-01-01

    We describe the LamarckiAnt algorithm: a search algorithm that combines the features of a "Lamarckian" genetic algorithm and ant colony optimization. We have implemented this algorithm for the optimization of BLN model proteins, which have frustrated energy landscapes and represent a challenge for global optimization algorithms. We demonstrate that LamarckiAnt performs competitively with other state-of-the-art optimization algorithms. PMID:24407312

  17. The Effects of Pollen-Enriched Pollen Substitute on Winter Cluster Size and the Prevalence of Nosema ceranae in Russian Honey Bee Colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study determined the effects of feeding a pollen substitute enriched with pollen and feeding protein in plastic frames placed directly in the brood nest on the growth of Russian honey bee colonies through the winter. Colonies were fed: 1) a mixture of 1/2 pollen and 1/2 commercial pollen substi...

  18. Associations of Parameters Related to the Fall of Varroa destructor (Mesostigmata: Varroidae) in Russian and Italian Honey Bee (Hymenoptera: Apidae) Colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Varroa destructor (Anderson and Truman) trapped on bottom boards were assessed as indirect measurements of colony mite populations and mite fall in colonies of Russian (RHB) and Italian (I) honey bees using 29 candidate measurements. Measurements included damaged and non-damaged younger mites, damag...

  19. Honey Bee Colonies Headed by Hyperpolyandrous Queens Have Improved Brood Rearing Efficiency and Lower Infestation Rates of Parasitic Varroa Mites.

    PubMed

    Delaplane, Keith S; Pietravalle, Stéphane; Brown, Mike A; Budge, Giles E

    2015-01-01

    A honey bee queen mates on wing with an average of 12 males and stores their sperm to produce progeny of mixed paternity. The degree of a queen's polyandry is positively associated with measures of her colony's fitness, and observed distributions of mating number are evolutionary optima balancing risks of mating flights against benefits to the colony. Effective mating numbers as high as 40 have been documented, begging the question of the upper bounds of this behavior that can be expected to confer colony benefit. In this study we used instrumental insemination to create three classes of queens with exaggerated range of polyandry--15, 30, or 60 drones. Colonies headed by queens inseminated with 30 or 60 drones produced more brood per bee and had a lower proportion of samples positive for Varroa destructor mites than colonies whose queens were inseminated with 15 drones, suggesting benefits of polyandry at rates higher than those normally obtaining in nature. Our results are consistent with two hypotheses that posit conditions that reward such high expressions of polyandry: (1) a queen may mate with many males in order to promote beneficial non-additive genetic interactions among subfamilies, and (2) a queen may mate with many males in order to capture a large number of rare alleles that regulate resistance to pathogens and parasites in a breeding population. Our results are unique for identifying the highest levels of polyandry yet detected that confer colony-level benefit and for showing a benefit of polyandry in particular toward the parasitic mite V. destructor. PMID:26691845

  20. Monitoring Aethina tumida (Coleoptera: Nitidulidae) with baited bottom board traps: occurrence and seasonal abundance in honey bee colonies in Kenya.

    PubMed

    Torto, Baldwyn; Fombong, Ayuka T; Arbogast, Richard T; Teal, Peter E A

    2010-12-01

    The population dynamics of the honey bee pest Aethina tumida Murray (small hive beetle) have been studied in the United States with flight and Langstroth hive bottom board traps baited with pollen dough inoculated with a yeast Kodamaea ohmeri associated with the beetle. However, little is known about the population dynamics of the beetle in its native host range. Similarly baited Langstroth hive bottom board traps were used to monitor the occurrence and seasonal abundance of the beetle in honey bee colonies at two beekeeping locations in Kenya. Trap captures indicated that the beetle was present in honey bee colonies in low numbers all year round, but it was most abundant during the rainy season, with over 80% trapped during this period. The survival of larvae was tested in field releases under dry and wet soil conditions, and predators of larvae were identified. The actvity and survival of the beetle were strongly influenced by a combination of abiotic and biotic factors. Larval survival was higher during wet (28%) than dry (1.1%) conditions, with pupation occurring mostly at 0-15 cm and 11-20 cm, respectively, beneath the surface soil during these periods. The ant Pheidole megacephala was identified as a key predator of larvae at this site, and more active during the dry than wet seasons. These observations imply that intensive trapping during the rainy season could reduce the population of beetles infesting hives in subsequent seasons especially in places where the beetle is a serious pest. PMID:22182536

  1. Honey Bee Inhibitory Signaling Is Tuned to Threat Severity and Can Act as a Colony Alarm Signal

    PubMed Central

    Li, Xinyu; Liu, Xiwen; Wang, Chao; Li, Jianjun

    2016-01-01

    Alarm communication is a key adaptation that helps social groups resist predation and rally defenses. In Asia, the world’s largest hornet, Vespa mandarinia, and the smaller hornet, Vespa velutina, prey upon foragers and nests of the Asian honey bee, Apis cerana. We attacked foragers and colony nest entrances with these predators and provide the first evidence, in social insects, of an alarm signal that encodes graded danger and attack context. We show that, like Apis mellifera, A. cerana possesses a vibrational “stop signal,” which can be triggered by predator attacks upon foragers and inhibits waggle dancing. Large hornet attacks were more dangerous and resulted in higher bee mortality. Per attack at the colony level, large hornets elicited more stop signals than small hornets. Unexpectedly, stop signals elicited by large hornets (SS large hornet) had a significantly higher vibrational fundamental frequency than those elicited by small hornets (SS small hornet) and were more effective at inhibiting waggle dancing. Stop signals resulting from attacks upon the nest entrance (SS nest) were produced by foragers and guards and were significantly longer in pulse duration than stop signals elicited by attacks upon foragers (SS forager). Unlike SS forager, SS nest were targeted at dancing and non-dancing foragers and had the common effect, tuned to hornet threat level, of inhibiting bee departures from the safe interior of the nest. Meanwhile, nest defenders were triggered by the bee alarm pheromone and live hornet presence to heat-ball the hornet. In A. cerana, sophisticated recruitment communication that encodes food location, the waggle dance, is therefore matched with an inhibitory/alarm signal that encodes information about the context of danger and its threat level. PMID:27014876

  2. Honey Bee Inhibitory Signaling Is Tuned to Threat Severity and Can Act as a Colony Alarm Signal.

    PubMed

    Tan, Ken; Dong, Shihao; Li, Xinyu; Liu, Xiwen; Wang, Chao; Li, Jianjun; Nieh, James C

    2016-03-01

    Alarm communication is a key adaptation that helps social groups resist predation and rally defenses. In Asia, the world's largest hornet, Vespa mandarinia, and the smaller hornet, Vespa velutina, prey upon foragers and nests of the Asian honey bee, Apis cerana. We attacked foragers and colony nest entrances with these predators and provide the first evidence, in social insects, of an alarm signal that encodes graded danger and attack context. We show that, like Apis mellifera, A. cerana possesses a vibrational "stop signal," which can be triggered by predator attacks upon foragers and inhibits waggle dancing. Large hornet attacks were more dangerous and resulted in higher bee mortality. Per attack at the colony level, large hornets elicited more stop signals than small hornets. Unexpectedly, stop signals elicited by large hornets (SS large hornet) had a significantly higher vibrational fundamental frequency than those elicited by small hornets (SS small hornet) and were more effective at inhibiting waggle dancing. Stop signals resulting from attacks upon the nest entrance (SS nest) were produced by foragers and guards and were significantly longer in pulse duration than stop signals elicited by attacks upon foragers (SS forager). Unlike SS forager, SS nest were targeted at dancing and non-dancing foragers and had the common effect, tuned to hornet threat level, of inhibiting bee departures from the safe interior of the nest. Meanwhile, nest defenders were triggered by the bee alarm pheromone and live hornet presence to heat-ball the hornet. In A. cerana, sophisticated recruitment communication that encodes food location, the waggle dance, is therefore matched with an inhibitory/alarm signal that encodes information about the context of danger and its threat level. PMID:27014876

  3. Determinants of between-year burrow re-occupation in a colony of the European bee-eater Merops apiaster.

    PubMed

    Brust, Vera; Bastian, Hans-Valentin; Bastian, Anita; Schmoll, Tim

    2015-08-01

    Re-occupation of existing nesting burrows in the European bee-eater Merops apiaster has only rarely - and if so mostly anecdotically - been documented in the literature record, although such behavior would substantially save time and energy. In this study, we quantify burrow re-occupation in a German colony over a period of eleven years and identify ecological variables determining reuse probability. Of 179 recorded broods, 54% took place in a reused burrow and the overall probability that one of 75 individually recognized burrows would be reused in a given subsequent year was estimated as 26.4%. This indicates that between-year burrow reuse is a common behavior in the study colony which contrasts with findings from studies in other colonies. Furthermore, burrow re-occupation probability declined highly significantly with increasing age of the breeding wall. Statistical separation of within- and between-burrow effects of the age of the breeding wall revealed that a decline in re-occupation probability with individual burrow age was responsible for this and not a selective disappearance of burrows with high re-occupation probability over time. Limited duty cycles of individual burrows may be caused by accumulating detritus or decreasing stability with increasing burrow age. Alternatively, burrow fidelity may presuppose pair fidelity which may also explain the observed restricted burrow reuse duty cycles. A consequent next step would be to extend our within-colony approach to other colonies and compare the ecological circumstances under which bee-eaters reuse breeding burrows. PMID:26355473

  4. Determinants of between-year burrow re-occupation in a colony of the European bee-eater Merops apiaster

    PubMed Central

    Brust, Vera; Bastian, Hans-Valentin; Bastian, Anita; Schmoll, Tim

    2015-01-01

    Re-occupation of existing nesting burrows in the European bee-eater Merops apiaster has only rarely – and if so mostly anecdotically – been documented in the literature record, although such behavior would substantially save time and energy. In this study, we quantify burrow re-occupation in a German colony over a period of eleven years and identify ecological variables determining reuse probability. Of 179 recorded broods, 54% took place in a reused burrow and the overall probability that one of 75 individually recognized burrows would be reused in a given subsequent year was estimated as 26.4%. This indicates that between-year burrow reuse is a common behavior in the study colony which contrasts with findings from studies in other colonies. Furthermore, burrow re-occupation probability declined highly significantly with increasing age of the breeding wall. Statistical separation of within- and between-burrow effects of the age of the breeding wall revealed that a decline in re-occupation probability with individual burrow age was responsible for this and not a selective disappearance of burrows with high re-occupation probability over time. Limited duty cycles of individual burrows may be caused by accumulating detritus or decreasing stability with increasing burrow age. Alternatively, burrow fidelity may presuppose pair fidelity which may also explain the observed restricted burrow reuse duty cycles. A consequent next step would be to extend our within-colony approach to other colonies and compare the ecological circumstances under which bee-eaters reuse breeding burrows. PMID:26355473

  5. Honey Bee Colonies Headed by Hyperpolyandrous Queens Have Improved Brood Rearing Efficiency and Lower Infestation Rates of Parasitic Varroa Mites

    PubMed Central

    Delaplane, Keith S.; Pietravalle, Stéphane; Brown, Mike A.; Budge, Giles E.

    2015-01-01

    A honey bee queen mates on wing with an average of 12 males and stores their sperm to produce progeny of mixed paternity. The degree of a queen’s polyandry is positively associated with measures of her colony’s fitness, and observed distributions of mating number are evolutionary optima balancing risks of mating flights against benefits to the colony. Effective mating numbers as high as 40 have been documented, begging the question of the upper bounds of this behavior that can be expected to confer colony benefit. In this study we used instrumental insemination to create three classes of queens with exaggerated range of polyandry– 15, 30, or 60 drones. Colonies headed by queens inseminated with 30 or 60 drones produced more brood per bee and had a lower proportion of samples positive for Varroa destructor mites than colonies whose queens were inseminated with 15 drones, suggesting benefits of polyandry at rates higher than those normally obtaining in nature. Our results are consistent with two hypotheses that posit conditions that reward such high expressions of polyandry: (1) a queen may mate with many males in order to promote beneficial non-additive genetic interactions among subfamilies, and (2) a queen may mate with many males in order to capture a large number of rare alleles that regulate resistance to pathogens and parasites in a breeding population. Our results are unique for identifying the highest levels of polyandry yet detected that confer colony-level benefit and for showing a benefit of polyandry in particular toward the parasitic mite V. destructor. PMID:26691845

  6. Molecular genetic analysis of tracheal mite resistance of colonies and individual honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee resistance to the potentially damaging parasitic tracheal mite is known to be mediated by autogrooming. During autogrooming bees use their midlegs to remove migrating foundress mites, thereby reducing infestation rates in their trachea. We investigated the relationship between markers iden...

  7. Risk factors associated with the presence of Varroa destructor in honey bee colonies from east-central Argentina.

    PubMed

    Giacobino, A; Bulacio Cagnolo, N; Merke, J; Orellano, E; Bertozzi, E; Masciangelo, G; Pietronave, H; Salto, C; Signorini, M

    2014-08-01

    Varroa destructor is considered one of the major threats for worldwide apiculture. Damage caused by varroa mite includes body weight loss, malformation and weakening of the bees. It was also suggested as the main cause associated with colony winter mortality and as an important vector for several honey bee viruses. Little is known about multiple factors and their interaction affecting V. destructor prevalence in apiaries from South America. The aim of this study was to identify risk factors associated with V. destructor prevalence in east-central Argentina. Parasitic mite infestation level and colony strength measures were evaluated in 63 apiaries distributed in 4 different regions in east-central Argentina in a cross sectional study. Data regarding management practices in each apiary were collected by means of a questionnaire. A mixed-effects logistic regression model was constructed to associate management variables with the risk of achieving mite infestation higher than 3%. Colonies owned by beekeepers who indicated that they did not monitor colonies after mite treatment (OR=2.305; 95% CI: 0.944-5.629) nor disinfect hives woodenware material (OR=2.722; 95% CI: 1.380-5.565) were associated with an increased risk of presenting high intensity infestation with V. destructor (>3%). On the other hand, beekeepers who reported replacing more than 50% of the queens in their operation (OR=0.305; 95% CI: 0.107-0.872), feeding colonies protein substitute containing natural pollen (OR=0.348; 95% CI: 0.129-0.941) and feeding colonies High Fructose Corn Syrup (HFCS) (OR=0.108; 95% CI: 0.032-0.364), had colonies that were less likely to have V. destructor infestations above 3%, than beekeepers who did not report using these management practices. Further research should be conducted considering that certain management practices were associated to mite infestation level in order to improve the sanitary condition in the colonies. Epidemiological studies provide key information to

  8. A Hybrid Ant Colony Algorithm for Loading Pattern Optimization

    NASA Astrophysics Data System (ADS)

    Hoareau, F.

    2014-06-01

    Electricité de France (EDF) operates 58 nuclear power plant (NPP), of the Pressurized Water Reactor (PWR) type. The loading pattern (LP) optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R&D has developed automatic optimization tools that assist the experts. The latter can resort, for instance, to a loading pattern optimization software based on ant colony algorithm. This paper presents an analysis of the search space of a few realistic loading pattern optimization problems. This analysis leads us to introduce a hybrid algorithm based on ant colony and a local search method. We then show that this new algorithm is able to generate loading patterns of good quality.

  9. All-Optical Implementation of the Ant Colony Optimization Algorithm.

    PubMed

    Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I; Soci, Cesare

    2016-01-01

    We report all-optical implementation of the optimization algorithm for the famous "ant colony" problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems. PMID:27222098

  10. Colony Failure Linked to Low Sperm Viability in Honey Bee (Apis mellifera) Queens and an Exploration of Potential Causative Factors.

    PubMed

    Pettis, Jeffery S; Rice, Nathan; Joselow, Katie; vanEngelsdorp, Dennis; Chaimanee, Veeranan

    2016-01-01

    Queen health is closely linked to colony performance in honey bees as a single queen is normally responsible for all egg laying and brood production within the colony. In the U. S. in recent years, queens have been failing at a high rate; with 50% or greater of queens replaced in colonies within 6 months when historically a queen might live one to two years. This high rate of queen failure coincides with the high mortality rates of colonies in the US, some years with >50% of colonies dying. In the current study, surveys of sperm viability in US queens were made to determine if sperm viability plays a role in queen or colony failure. Wide variation was observed in sperm viability from four sets of queens removed from colonies that beekeepers rated as in good health (n = 12; average viability = 92%), were replacing as part of normal management (n = 28; 57%), or where rated as failing (n = 18 and 19; 54% and 55%). Two additional paired set of queens showed a statistically significant difference in viability between colonies rated by the beekeeper as failing or in good health from the same apiaries. Queens removed from colonies rated in good health averaged high viability (ca. 85%) while those rated as failing or in poor health had significantly lower viability (ca. 50%). Thus low sperm viability was indicative of, or linked to, colony performance. To explore the source of low sperm viability, six commercial queen breeders were surveyed and wide variation in viability (range 60-90%) was documented between breeders. This variability could originate from the drones the queens mate with or temperature extremes that queens are exposed to during shipment. The role of shipping temperature as a possible explanation for low sperm viability was explored. We documented that during shipment queens are exposed to temperature spikes (<8 and > 40°C) and these spikes can kill 50% or more of the sperm stored in queen spermathecae in live queens. Clearly low sperm viability is linked

  11. Colony Failure Linked to Low Sperm Viability in Honey Bee (Apis mellifera) Queens and an Exploration of Potential Causative Factors

    PubMed Central

    Pettis, Jeffery S.; Rice, Nathan; Joselow, Katie; vanEngelsdorp, Dennis; Chaimanee, Veeranan

    2016-01-01

    Queen health is closely linked to colony performance in honey bees as a single queen is normally responsible for all egg laying and brood production within the colony. In the U. S. in recent years, queens have been failing at a high rate; with 50% or greater of queens replaced in colonies within 6 months when historically a queen might live one to two years. This high rate of queen failure coincides with the high mortality rates of colonies in the US, some years with >50% of colonies dying. In the current study, surveys of sperm viability in US queens were made to determine if sperm viability plays a role in queen or colony failure. Wide variation was observed in sperm viability from four sets of queens removed from colonies that beekeepers rated as in good health (n = 12; average viability = 92%), were replacing as part of normal management (n = 28; 57%), or where rated as failing (n = 18 and 19; 54% and 55%). Two additional paired set of queens showed a statistically significant difference in viability between colonies rated by the beekeeper as failing or in good health from the same apiaries. Queens removed from colonies rated in good health averaged high viability (ca. 85%) while those rated as failing or in poor health had significantly lower viability (ca. 50%). Thus low sperm viability was indicative of, or linked to, colony performance. To explore the source of low sperm viability, six commercial queen breeders were surveyed and wide variation in viability (range 60–90%) was documented between breeders. This variability could originate from the drones the queens mate with or temperature extremes that queens are exposed to during shipment. The role of shipping temperature as a possible explanation for low sperm viability was explored. We documented that during shipment queens are exposed to temperature spikes (<8 and > 40°C) and these spikes can kill 50% or more of the sperm stored in queen spermathecae in live queens. Clearly low sperm viability is

  12. Ant Colony Optimization With Combining Gaussian Eliminations for Matrix Multiplication.

    PubMed

    Zhou, Yuren; Lai, Xinsheng; Li, Yuanxiang; Dong, Wenyong

    2013-02-01

    One of the main unsolved problems in computer algebra is to determine the minimal number of multiplications which is necessary to compute the product of two matrices. For practical value, the small format is of special interest. This leads to a combinatorial optimization problem which is unlikely solved in polynomial time. In this paper, we present a method called combining Gaussian eliminations to reduce the number of variables in this optimization problem and use heuristic ant colony algorithm to solve the problem. The results of experiments on 2 × 2 case show that our algorithm achieves significant performance gains. Extending this algorithm from 2 × 2 case to 3 × 3 case is also discussed. Index Terms—Ant colony optimization (ACO), evolutionary algorithms, Gaussian eliminations, matrix multiplication, multiplicative complexity, Strassen's algorithm. PMID:22835561

  13. Response Ant Colony Optimization of end milling surface roughness.

    PubMed

    Kadirgama, K; Noor, M M; Abd Alla, Ahmed N

    2010-01-01

    Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using milling mould aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant Colony Optimization (ACO). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness. PMID:22294914

  14. Response Ant Colony Optimization of End Milling Surface Roughness

    PubMed Central

    Kadirgama, K.; Noor, M. M.; Abd Alla, Ahmed N.

    2010-01-01

    Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using milling mould aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant Colony Optimization (ACO). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness. PMID:22294914

  15. A discrete artificial bee colony algorithm incorporating differential evolution for the flow-shop scheduling problem with blocking

    NASA Astrophysics Data System (ADS)

    Han, Yu-Yan; Gong, Dunwei; Sun, Xiaoyan

    2015-07-01

    A flow-shop scheduling problem with blocking has important applications in a variety of industrial systems but is underrepresented in the research literature. In this study, a novel discrete artificial bee colony (ABC) algorithm is presented to solve the above scheduling problem with a makespan criterion by incorporating the ABC with differential evolution (DE). The proposed algorithm (DE-ABC) contains three key operators. One is related to the employed bee operator (i.e. adopting mutation and crossover operators of discrete DE to generate solutions with good quality); the second is concerned with the onlooker bee operator, which modifies the selected solutions using insert or swap operators based on the self-adaptive strategy; and the last is for the local search, that is, the insert-neighbourhood-based local search with a small probability is adopted to improve the algorithm's capability in exploitation. The performance of the proposed DE-ABC algorithm is empirically evaluated by applying it to well-known benchmark problems. The experimental results show that the proposed algorithm is superior to the compared algorithms in minimizing the makespan criterion.

  16. Bee Swarm Optimization for Medical Web Information Foraging.

    PubMed

    Drias, Yassine; Kechid, Samir; Pasi, Gabriella

    2016-02-01

    The present work is related to Web intelligence and more precisely to medical information foraging. We present here a novel approach based on agents technology for information foraging. An architecture is proposed, in which we distinguish two important phases. The first one is a learning process for localizing the most relevant pages that might interest the user. This is performed on a fixed instance of the Web. The second takes into account the openness and the dynamicity of the Web. It consists on an incremental learning starting from the result of the first phase and reshaping the outcomes taking into account the changes that undergoes the Web. The whole system offers a tool to help the user undertaking information foraging. We implemented the system using a group of cooperative reactive agents and more precisely a colony of artificial bees. In order to validate our proposal, experiments were conducted on MedlinePlus, a benchmark dedicated for research in the domain of Health. The results are promising either for those related to Web regularities and for the response time, which is very short and hence complies the real time constraint. PMID:26590978

  17. Evaluation of spring organic treatments against Varroa destructor (Acari: Varroidae) in honey bee Apis mellifera (Hymenoptera: Apidae) colonies in eastern Canada.

    PubMed

    Giovenazzo, Pierre; Dubreuil, Pascal

    2011-09-01

    The objective of this study was to measure the efficacy of two organic acid treatments, formic acid (FA) and oxalic acid (OA) for the spring control of Varroa destructor (Anderson and Trueman) in honey bee (Apis mellifera L.) colonies. Forty-eight varroa-infested colonies were randomly distributed amongst six experimental groups (n = 8 colonies per group): one control group (G1); two groups tested applications of different dosages of a 40 g OA/l sugar solution 1:1 trickled on bees (G2 and G3); three groups tested different applications of FA: 35 ml of 65% FA in an absorbent Dri-Loc(®) pad (G4); 35 ml of 65% FA poured directly on the hive bottom board (G5) and MiteAwayII™ (G6). The efficacy of treatments (varroa drop), colony development, honey yield and hive survival were monitored from May until September. Five honey bee queens died during this research, all of which were in the FA treated colonies (G4, G5 and G6). G6 colonies had significantly lower brood build-up during the beekeeping season. Brood populations at the end of summer were significantly higher in G2 colonies. Spring honey yield per colony was significantly lower in G6 and higher in G1. Summer honey flow was significantly lower in G6 and higher in G3 and G5. During the treatment period, there was an increase of mite drop in all the treated colonies. Varroa daily drop at the end of the beekeeping season (September) was significantly higher in G1 and significantly lower in G6. The average number of dead bees found in front of hives during treatment was significantly lower in G1, G2 and G3 versus G4, G5 and G6. Results suggest that varroa control is obtained from all spring treatment options. However, all groups treated with FA showed slower summer hive population build-up resulting in reduced honey flow and weaker hives at the end of summer. FA had an immediate toxic effect on bees that resulted in queen death in five colonies. The OA treatments that were tested have minimal toxic impacts on the

  18. A large-scale field study examining effects of exposure to clothianidin seed-treated canola on honey bee colony health, development, and overwintering success.

    PubMed

    Cutler, G Christopher; Scott-Dupree, Cynthia D; Sultan, Maryam; McFarlane, Andrew D; Brewer, Larry

    2014-01-01

    In summer 2012, we initiated a large-scale field experiment in southern Ontario, Canada, to determine whether exposure to clothianidin seed-treated canola (oil seed rape) has any adverse impacts on honey bees. Colonies were placed in clothianidin seed-treated or control canola fields during bloom, and thereafter were moved to an apiary with no surrounding crops grown from seeds treated with neonicotinoids. Colony weight gain, honey production, pest incidence, bee mortality, number of adults, and amount of sealed brood were assessed in each colony throughout summer and autumn. Samples of honey, beeswax, pollen, and nectar were regularly collected, and samples were analyzed for clothianidin residues. Several of these endpoints were also measured in spring 2013. Overall, colonies were vigorous during and after the exposure period, and we found no effects of exposure to clothianidin seed-treated canola on any endpoint measures. Bees foraged heavily on the test fields during peak bloom and residue analysis indicated that honey bees were exposed to low levels (0.5-2 ppb) of clothianidin in pollen. Low levels of clothianidin were detected in a few pollen samples collected toward the end of the bloom from control hives, illustrating the difficulty of conducting a perfectly controlled field study with free-ranging honey bees in agricultural landscapes. Overwintering success did not differ significantly between treatment and control hives, and was similar to overwintering colony loss rates reported for the winter of 2012-2013 for beekeepers in Ontario and Canada. Our results suggest that exposure to canola grown from seed treated with clothianidin poses low risk to honey bees. PMID:25374790

  19. A large-scale field study examining effects of exposure to clothianidin seed-treated canola on honey bee colony health, development, and overwintering success

    PubMed Central

    Scott-Dupree, Cynthia D.; Sultan, Maryam; McFarlane, Andrew D.; Brewer, Larry

    2014-01-01

    In summer 2012, we initiated a large-scale field experiment in southern Ontario, Canada, to determine whether exposure to clothianidin seed-treated canola (oil seed rape) has any adverse impacts on honey bees. Colonies were placed in clothianidin seed-treated or control canola fields during bloom, and thereafter were moved to an apiary with no surrounding crops grown from seeds treated with neonicotinoids. Colony weight gain, honey production, pest incidence, bee mortality, number of adults, and amount of sealed brood were assessed in each colony throughout summer and autumn. Samples of honey, beeswax, pollen, and nectar were regularly collected, and samples were analyzed for clothianidin residues. Several of these endpoints were also measured in spring 2013. Overall, colonies were vigorous during and after the exposure period, and we found no effects of exposure to clothianidin seed-treated canola on any endpoint measures. Bees foraged heavily on the test fields during peak bloom and residue analysis indicated that honey bees were exposed to low levels (0.5–2 ppb) of clothianidin in pollen. Low levels of clothianidin were detected in a few pollen samples collected toward the end of the bloom from control hives, illustrating the difficulty of conducting a perfectly controlled field study with free-ranging honey bees in agricultural landscapes. Overwintering success did not differ significantly between treatment and control hives, and was similar to overwintering colony loss rates reported for the winter of 2012–2013 for beekeepers in Ontario and Canada. Our results suggest that exposure to canola grown from seed treated with clothianidin poses low risk to honey bees. PMID:25374790

  20. Bee

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bee, Claire Preston, is a book written generally for the layperson, but may be of interest to those working in entomology. This review seeks to help entomologists who may have interest in the subject to decide whether or not to invest time into reading the book. The review is generally positive an...

  1. Improved Clonal Selection Algorithm Combined with Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Gao, Shangce; Wang, Wei; Dai, Hongwei; Li, Fangjia; Tang, Zheng

    Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit and explore the solution space parallely and effectively. However, it can not use enough environment feedback information and thus has to do a large redundancy repeat during search. On the other hand, ACO is based on the concept of indirect cooperative foraging process via secreting pheromones. Its positive feedback ability is nice but its convergence speed is slow because of the little initial pheromones. In this paper, we propose a pheromone-linker to combine these two algorithms. The proposed hybrid clonal selection and ant colony optimization (CSA-ACO) reasonably utilizes the superiorities of both algorithms and also overcomes their inherent disadvantages. Simulation results based on the traveling salesman problems have demonstrated the merit of the proposed algorithm over some traditional techniques.

  2. Field trials using the fungal pathogen, Metarhizium anisopliae (Deuteromycetes: Hyphomycetes) to control the ectoparasitic mite, Varroa destructor (Acari: Varroidae) in honey bee, Apis mellifera (Hymenoptera: Apidae) colonies.

    PubMed

    Kanga, Lambert Houssou Ble; Jones, Walker A; James, Rosalind R

    2003-08-01

    The potential for Metarhizium anisopliae (Metschinkoff) to control the parasitic mite, Varroa destructor (Anderson and Trueman) in honey bee colonies was evaluated in field trials against the miticide, tau-fluvalinate (Apistan). Peak mortality of V. destructor occurred 3-4 d after the conidia were applied; however, the mites were still infected 42 d posttreatments. Two application methods were tested: dusts and strips coated with the fungal conidia, and both methods resulted in successful control of mite populations. The fungal treatments were as effective as the Apistan, at the end of the 42-d period of the experiment. The data suggested that optimum mite control could be achieved when no brood is being produced, or when brood production is low, such as in the early spring or late fall. M. anisopliae was harmless to the honey bees (adult bees, or brood) and colony development was not affected. Mite mortality was highly correlated with mycosis in dead mites collected from sticky traps, indicating that the fungus was infecting and killing the mites. Because workers and drones drift between hives, the adult bees were able to spread the fungus between honey bee colonies in the apiary, a situation that could be beneficial to beekeepers. PMID:14503579

  3. THE INFLUENCE OF SEASON AND VOLATILE COMPOUNDS ON ACCEPTANCE RATES OF INTRODUCED EUROPEAN HONEY BEE (APIS MELLIFERA L.) QUEENS INTO EUROPEAN AND AFRICANIZED COLONIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We introduced mated European honey bee (Apis mellifera L.) queens into Africanized and European colonies during three different seasons to determine if there were differences in queen acceptance rates. We also sampled volatile compounds emitted by the queens prior to their introduction to determine...

  4. Effects of multiple applications of a Beauveria based biopesticide on Varroa destructor (Acari: Varroidae) densities in honey bee (Hymenoptera: Apidae) colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A biopesticide, formulated with a strain of Beauveria bassiana isolated from varroa mites, was tested in an experiment in southern France and the results were were compared to published results from previous experiments with the same biopesticide. Bee colonies were treated either with biopesticide, ...

  5. A scientific note on detection of honey bee viruses in the darkling beetle (Alphitobius diaperinus), an inhabitant in Apis cerana colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The darkling beetles, Alphitobius diaperinus (Panzer), are omnivorous arthropods and pose significant danger to the poultry industry by acting as reservoir and vector of poultry pathogens. Here, the A. diaperinus was first found in the Asian honey bee Apis cerana colonies, and 10 of the 29 hives wer...

  6. The impact of insecticides to local honey bee colony Apis cerana indica in laboratory condition

    NASA Astrophysics Data System (ADS)

    Putra, Ramadhani E.; Permana, Agus D.; Nuriyah, Syayidah

    2014-03-01

    Heavy use of insecticides considered as one of common practice at local farming systems. Even though many Indonesian researchers had stated the possible detrimental effect of insecticide on agriculture environment and biodiversity, researches on this subject had been neglected. Therefore, our purpose in this research is observing the impact of insecticides usage by farmer to non target organisme like local honey bee (Apis cerana indica), which commonly kept in area near agriculture system. This research consisted of field observations out at Ciburial, Dago Pakar, Bandung and laboratory tests at School of Life Sciences and Technology, Institut Teknologi Bandung. The field observations recorded visited agriculture corps and types of pollen carried by bees to the nest while laboratory test recorderd the effect of common insecticide to mortality and behavior of honey bees. Three types of insecticides used in this research were insecticides A with active agent Chlorantraniliprol 50 g/l, insecticide B with active agent Profenofos 500 g/l, and insecticides C with active agent Chlorantraniliprol 100 g/l and λ-cyhalotrin 50g/l. The results show that during one week visit, wild flower, Wedelia montana, visited by most honey bees with average visit 60 honey bees followed by corn, Zea mays, with 21 honey bees. The most pollen carried by foragers was Wedelia montana, Calliandra callothyrsus, and Zea mays. Preference test show that honeybees tend move to flowers without insecticides as the preference to insecticides A was 12.5%, insecticides B was 0%, and insecticides was C 4.2%. Mortality test showed that insecticides A has LD50 value 0.01 μg/μl, insecticide B 0.31 μg/μl, and insecticides C 0.09 μg/μl which much lower than suggested dosage recommended by insecticides producer. This research conclude that the use of insecticide could lower the pollination service provide by honey bee due to low visitation rate to flowers and mortality of foraging bees.

  7. Modeling Honey Bee Populations

    PubMed Central

    Torres, David J.; Ricoy, Ulises M.; Roybal, Shanae

    2015-01-01

    Eusocial honey bee populations (Apis mellifera) employ an age stratification organization of egg, larvae, pupae, hive bees and foraging bees. Understanding the recent decline in honey bee colonies hinges on understanding the factors that impact each of these different age castes. We first perform an analysis of steady state bee populations given mortality rates within each bee caste and find that the honey bee colony is highly susceptible to hive and pupae mortality rates. Subsequently, we study transient bee population dynamics by building upon the modeling foundation established by Schmickl and Crailsheim and Khoury et al. Our transient model based on differential equations accounts for the effects of pheromones in slowing the maturation of hive bees to foraging bees, the increased mortality of larvae in the absence of sufficient hive bees, and the effects of food scarcity. We also conduct sensitivity studies and show the effects of parameter variations on the colony population. PMID:26148010

  8. All-Optical Implementation of the Ant Colony Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I.; Soci, Cesare

    2016-05-01

    We report all-optical implementation of the optimization algorithm for the famous “ant colony” problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems.

  9. All-Optical Implementation of the Ant Colony Optimization Algorithm

    PubMed Central

    Hu, Wenchao; Wu, Kan; Shum, Perry Ping; Zheludev, Nikolay I.; Soci, Cesare

    2016-01-01

    We report all-optical implementation of the optimization algorithm for the famous “ant colony” problem. Ant colonies progressively optimize pathway to food discovered by one of the ants through identifying the discovered route with volatile chemicals (pheromones) secreted on the way back from the food deposit. Mathematically this is an important example of graph optimization problem with dynamically changing parameters. Using an optical network with nonlinear waveguides to represent the graph and a feedback loop, we experimentally show that photons traveling through the network behave like ants that dynamically modify the environment to find the shortest pathway to any chosen point in the graph. This proof-of-principle demonstration illustrates how transient nonlinearity in the optical system can be exploited to tackle complex optimization problems directly, on the hardware level, which may be used for self-routing of optical signals in transparent communication networks and energy flow in photonic systems. PMID:27222098

  10. Wavelet phase estimation using ant colony optimization algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Shangxu; Yuan, Sanyi; Ma, Ming; Zhang, Rui; Luo, Chunmei

    2015-11-01

    Eliminating seismic wavelet is important in seismic high-resolution processing. However, artifacts may arise in seismic interpretation when the wavelet phase is inaccurately estimated. Therefore, we propose a frequency-dependent wavelet phase estimation method based on the ant colony optimization (ACO) algorithm with global optimization capacity. The wavelet phase can be optimized with the ACO algorithm by fitting nearby-well seismic traces with well-log data. Our proposed method can rapidly produce a frequency-dependent wavelet phase and optimize the seismic-to-well tie, particularly for weak signals. Synthetic examples demonstrate the effectiveness of the proposed ACO-based wavelet phase estimation method, even in the presence of a colored noise. Real data example illustrates that seismic deconvolution using an optimum mixed-phase wavelet can provide more information than that using an optimum constant-phase wavelet.

  11. A morphologically specialized soldier caste improves colony defense in a neotropical eusocial bee

    PubMed Central

    Grüter, Christoph; Menezes, Cristiano; Imperatriz-Fonseca, Vera L.; Ratnieks, Francis L. W.

    2012-01-01

    Division of labor among workers is common in insect societies and is thought to be important in their ecological success. In most species, division of labor is based on age (temporal castes), but workers in some ants and termites show morphological specialization for particular tasks (physical castes). Large-headed soldier ants and termites are well-known examples of this specialization. However, until now there has been no equivalent example of physical worker subcastes in social bees or wasps. Here we provide evidence for a physical soldier subcaste in a bee. In the neotropical stingless bee Tetragonisca angustula, nest defense is performed by two groups of guards, one hovering near the nest entrance and the other standing on the wax entrance tube. We show that both types of guards are 30% heavier than foragers and of different shape; foragers have relatively larger heads, whereas guards have larger legs. Low variation within each subcaste results in negligible size overlap between guards and foragers, further indicating that they are distinct physical castes. In addition, workers that remove garbage from the nest are of intermediate size, suggesting that they might represent another unrecognized caste. Guards or soldiers are reared in low but sufficient numbers (1–2% of emerging workers), considering that <1% usually perform this task. When challenged by the obligate robber bee Lestrimelitta limao, an important natural enemy, larger workers were able to fight for longer before being defeated by the much larger robber. This discovery opens up opportunities for the comparative study of physical castes in social insects, including the question of why soldiers appear to be so much rarer in bees than in ants or termites. PMID:22232688

  12. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

    PubMed Central

    Yilmaz, Nihat; Inan, Onur

    2013-01-01

    This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications. PMID:23983632

  13. A novel kernel extreme learning machine algorithm based on self-adaptive artificial bee colony optimisation strategy

    NASA Astrophysics Data System (ADS)

    Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Ji, Jin-Chao

    2016-04-01

    In this paper, we propose a novel learning algorithm, named SABC-MKELM, based on a kernel extreme learning machine (KELM) method for single-hidden-layer feedforward networks. In SABC-MKELM, the combination of Gaussian kernels is used as the activate function of KELM instead of simple fixed kernel learning, where the related parameters of kernels and the weights of kernels can be optimised by a novel self-adaptive artificial bee colony (SABC) approach simultaneously. SABC-MKELM outperforms six other state-of-the-art approaches in general, as it could effectively determine solution updating strategies and suitable parameters to produce a flexible kernel function involved in SABC. Simulations have demonstrated that the proposed algorithm not only self-adaptively determines suitable parameters and solution updating strategies learning from the previous experiences, but also achieves better generalisation performances than several related methods, and the results show good stability of the proposed algorithm.

  14. New Miticides for Integrated Pest Management of Varroa destructor (Acari: Varroidae) in Honey Bee Colonies on the Canadian Prairies.

    PubMed

    Vandervalk, L P; Nasr, M E; Dosdall, L M

    2014-12-01

    Varroa destructor Anderson and Trueman 2000 (Acari: Varroidae) is an ectoparasitic mite of the honey bee, Apis mellifera L. (Hymenoptera: Apidae). Honey bee colonies require extensive management to prevent mortality caused by varroa mites and the viruses they vector. New miticides (Thymovar and HopGuard) to manage varroa mites were evaluated during the spring and fall treatment windows of the Canadian prairies to determine their effectiveness as part of an integrated management strategy. Thymovar and HopGuard were evaluated alongside the currently used industry standards: Apivar and formic acid. Results demonstrated that Apivar and formic acid remain effective V. destructor management options under spring and fall conditions. Applications of Thymovar during spring were associated with a reduction in brood area, and therefore should be limited to the fall season. The miticide HopGuard was not effective in managing V. destructor, and alteration of the current delivery system is necessary. This study demonstrates the potential for new effective treatment options to supplement currently used V. destructor integrated pest management systems. PMID:26470066

  15. Metal contaminant accumulation in the hive: Consequences for whole-colony health and brood production in the honey bee (Apis mellifera L.).

    PubMed

    Hladun, Kristen R; Di, Ning; Liu, Tong-Xian; Trumble, John T

    2016-02-01

    Metal pollution has been increasing rapidly over the past century, and at the same time, the human population has continued to rise and produce contaminants that may negatively impact pollinators. Honey bees (Apis mellifera L.) forage over large areas and can collect contaminants from the environment. The primary objective of the present study was to determine whether the metal contaminants cadmium (Cd), copper (Cu), lead (Pb), and selenium (Se) can have a detrimental effect on whole-colony health in the managed pollinator A. mellifera. The authors isolated small nucleus colonies under large cages and fed them an exclusive diet of sugar syrup and pollen patty spiked with Cd, Cu, Pb, and Se or a control (no additional metal). Treatment levels were based on concentrations in honey and pollen from contaminated hives around the world. They measured whole-colony health including wax, honey, and brood production; colony weight; brood survival; and metal accumulation in various life stages. Colonies treated with Cd or Cu contained more dead pupae within capped cells compared with control, and Se-treated colonies had lower total worker weights compared to control. Lead had a minimal effect on colony performance, although many members of the hive accumulated significant quantities of the metal. By examining the honey bee as a social organism through whole-colony assessments of toxicity, the authors found that the distribution of toxicants throughout the colony varied from metal to metal, some caste members were more susceptible to certain metals, and the colony's ability to grow over time may have been reduced in the presence of Se. Apiaries residing near metal-contaminated areas may be at risk and can suffer changes in colony dynamics and survival. PMID:26448590

  16. A Four-Year Field Program Investigating Long-Term Effects of Repeated Exposure of Honey Bee Colonies to Flowering Crops Treated with Thiamethoxam

    PubMed Central

    Pilling, Edward; Campbell, Peter; Coulson, Mike; Ruddle, Natalie; Tornier, Ingo

    2013-01-01

    Neonicotinoid residues in nectar and pollen from crop plants have been implicated as one of the potential factors causing the declines of honey bee populations. Median residues of thiamethoxam in pollen collected from honey bees after foraging on flowering seed treated maize were found to be between 1 and 7 µg/kg, median residues of the metabolite CGA322704 (clothianidin) in the pollen were between 1 and 4 µg/kg. In oilseed rape, median residues of thiamethoxam found in pollen collected from bees were between <1 and 3.5 µg/kg and in nectar from foraging bees were between 0.65 and 2.4 µg/kg. Median residues of CGA322704 in pollen and nectar in the oilseed rape trials were all below the limit of quantification (1 µg/kg). Residues in the hive were even lower in both the maize and oilseed rape trials, being at or below the level of detection of 1 µg/kg for bee bread in the hive and at or below the level of detection of 0.5 µg/kg for hive nectar, honey and royal jelly samples. The long-term risk to honey bee colonies in the field was also investigated, including the sensitive overwintering stage, from four years consecutive single treatment crop exposures to flowering maize and oilseed rape grown from thiamethoxam treated seeds at rates recommended for insect control. Throughout the study, mortality, foraging behavior, colony strength, colony weight, brood development and food storage levels were similar between treatment and control colonies. Detailed examination of brood development throughout the year demonstrated that colonies exposed to the treated crop were able to successfully overwinter and had a similar health status to the control colonies in the following spring. We conclude that these data demonstrate there is a low risk to honey bees from systemic residues in nectar and pollen following the use of thiamethoxam as a seed treatment on oilseed rape and maize. PMID:24194871

  17. A four-year field program investigating long-term effects of repeated exposure of honey bee colonies to flowering crops treated with thiamethoxam.

    PubMed

    Pilling, Edward; Campbell, Peter; Coulson, Mike; Ruddle, Natalie; Tornier, Ingo

    2013-01-01

    Neonicotinoid residues in nectar and pollen from crop plants have been implicated as one of the potential factors causing the declines of honey bee populations. Median residues of thiamethoxam in pollen collected from honey bees after foraging on flowering seed treated maize were found to be between 1 and 7 µg/kg, median residues of the metabolite CGA322704 (clothianidin) in the pollen were between 1 and 4 µg/kg. In oilseed rape, median residues of thiamethoxam found in pollen collected from bees were between <1 and 3.5 µg/kg and in nectar from foraging bees were between 0.65 and 2.4 µg/kg. Median residues of CGA322704 in pollen and nectar in the oilseed rape trials were all below the limit of quantification (1 µg/kg). Residues in the hive were even lower in both the maize and oilseed rape trials, being at or below the level of detection of 1 µg/kg for bee bread in the hive and at or below the level of detection of 0.5 µg/kg for hive nectar, honey and royal jelly samples. The long-term risk to honey bee colonies in the field was also investigated, including the sensitive overwintering stage, from four years consecutive single treatment crop exposures to flowering maize and oilseed rape grown from thiamethoxam treated seeds at rates recommended for insect control. Throughout the study, mortality, foraging behavior, colony strength, colony weight, brood development and food storage levels were similar between treatment and control colonies. Detailed examination of brood development throughout the year demonstrated that colonies exposed to the treated crop were able to successfully overwinter and had a similar health status to the control colonies in the following spring. We conclude that these data demonstrate there is a low risk to honey bees from systemic residues in nectar and pollen following the use of thiamethoxam as a seed treatment on oilseed rape and maize. PMID:24194871

  18. New approach for determination of an optimum honeybee colony's carrying capacity based on productivity and nectar secretion potential of bee forage species.

    PubMed

    Al-Ghamdi, Ahmed; Adgaba, Nuru; Getachew, Awraris; Tadesse, Yilma

    2016-01-01

    The present study was carried out to determine an optimum honeybee colony's carrying capacity of selected valleys dominated by Ziziphus spina-christi and Acacia tortilis in the Al-Baha region, Kingdom of Saudi Arabia. The study was conducted based on the assessment of the number of colonies kept, their productivities and the existing productive bee forage resources in the target valleys with its economic implication. In the existing beekeeping practice, the average number of managed honeybee colonies introduced per square kilometer was 530 and 317 during the flowering period of Z. spina-christi and A. tortilis, respectively. Furthermore, the overall ratios of productive bee forage plants to the number of honeybee colonies introduced were 0.55 and 11.12 to Ziziphus trees and A. tortilis shrubs respectively. In the existing situation the average honey production potential of 5.21 and 0.34 kg was recorded per Ziziphus and A. tortilis plants per flowering season, respectively. The present study, revealed that the number of honeybee colonies introduced in relation to the existing bee forage potential was extremely overcrowding which is beyond the carrying capacity of bee forage resources in selected valleys and it has been observed to affect the productivities and subsequent profitability of beekeeping. The study infers that, by keeping the optimum honeybee colony's carrying capacity of valleys (88 traditional hives/km(2) or 54 Langstroth hives/km(2) in Ziziphus field and 72 traditional hives/km(2) or 44 Langstroth hives/km(2) in A. tortilis field), profitability of beekeeping can be boosted up to 130.39% and 207.98% during Z. spina-christi and A. tortilis, flowering seasons, respectively. PMID:26858544

  19. Application of ant colony optimization to optimal foragaing theory: comparison of simulation and field results

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ant Colony Optimization (ACO) refers to the family of algorithms inspired by the behavior of real ants and used to solve combinatorial problems such as the Traveling Salesman Problem (TSP).Optimal Foraging Theory (OFT) is an evolutionary principle wherein foraging organisms or insect parasites seek ...

  20. Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

    PubMed Central

    Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

    2012-01-01

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

  1. Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

    PubMed

    Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

    2012-01-01

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

  2. Pesticide use within a pollinator-dependent crop has negative effects on the abundance and species richness of sweat bees, Lasioglossum spp., and on bumble bee colony growth.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Pesticides are implicated in current bee declines. Wild bees that nest or forage within agroecosystems may be exposed to numerous pesticides applied throughout their life cycles, with potential additive or synergistic effects. In pollinator-dependent crops, pesticides may reduce bee populations, cre...

  3. An evaluation of the associations of parameters related to the fall of Varroa destructor (Acari: Varroidae) from commercial honey bee (Hymenoptera: Apidae) colonies as tools for selective breeding for mite resistance.

    PubMed

    Rinderer, Thomas E; De Guzman, Lilia I; Frake, Amanda M; Tarver, Matthew R; Khongphinitbunjong, Kitiphong

    2014-04-01

    Varroa destructor (Anderson and Trueman) trapped on bottom boards were assessed as indirect measurements of colony mite population differences and potential indicators of mite resistance in commercial colonies of Russian and Italian honey bees (Apis mellifera L.) by using 35 candidate measurements. Measurements included numbers of damaged and nondamaged younger mites, nymphs, damaged and nondamaged older mites, fresh mites, and all mites, each as a proportion of total mites in the colonies and as a proportion of all trapped mites or all trapped fresh mites. Several measurements differed strongly between the stocks, suggesting that the detailed characteristics of trapped mites may reflect the operation of resistance mechanisms in the Russian honey bees. Regression analyses were used to determine the relationships of these candidate measurements with the number of mites in the colonies. The largest positive regressions differed for the two stocks (Italian honey bees: trapped mites and trapped younger mites; Russian honey bees: trapped younger mites and trapped fresh mites). Also, the regressions for Italian honey bees were substantially stronger. The largest negative regressions with colony mites for both stocks were for the proportion of older mites out of all trapped mites. Although these regressions were statistically significant and consistent with those previously reported, they were weaker than those previously reported. The numbers of mites in the colonies were low, especially in the Russian honey bee colonies, which may have negatively influenced the precision of the regressions. PMID:24772529

  4. Ant colony optimization as a method for strategic genotype sampling.

    PubMed

    Spangler, M L; Robbins, K R; Bertrand, J K; Macneil, M; Rekaya, R

    2009-06-01

    A simulation study was carried out to develop an alternative method of selecting animals to be genotyped. Simulated pedigrees included 5000 animals, each assigned genotypes for a bi-allelic single nucleotide polymorphism (SNP) based on assumed allelic frequencies of 0.7/0.3 and 0.5/0.5. In addition to simulated pedigrees, two beef cattle pedigrees, one from field data and the other from a research population, were used to test selected methods using simulated genotypes. The proposed method of ant colony optimization (ACO) was evaluated based on the number of alleles correctly assigned to ungenotyped animals (AK(P)), the probability of assigning true alleles (AK(G)) and the probability of correctly assigning genotypes (APTG). The proposed animal selection method of ant colony optimization was compared to selection using the diagonal elements of the inverse of the relationship matrix (A(-1)). Comparisons of these two methods showed that ACO yielded an increase in AK(P) ranging from 4.98% to 5.16% and an increase in APTG from 1.6% to 1.8% using simulated pedigrees. Gains in field data and research pedigrees were slightly lower. These results suggest that ACO can provide a better genotyping strategy, when compared to A(-1), with different pedigree sizes and structures. PMID:19220227

  5. CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET

    PubMed Central

    Bajwa, Khalid Bashir; Khan, Salabat; Chaudary, Nadeem Majeed; Akram, Adeel

    2016-01-01

    A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO. PMID:27149517

  6. Particle Swarm and Ant Colony Approaches in Multiobjective Optimization

    NASA Astrophysics Data System (ADS)

    Rao, S. S.

    2010-10-01

    The social behavior of groups of birds, ants, insects and fish has been used to develop evolutionary algorithms known as swarm intelligence techniques for solving optimization problems. This work presents the development of strategies for the application of two of the popular swarm intelligence techniques, namely the particle swarm and ant colony methods, for the solution of multiobjective optimization problems. In a multiobjective optimization problem, the objectives exhibit a conflicting nature and hence no design vector can minimize all the objectives simultaneously. The concept of Pareto-optimal solution is used in finding a compromise solution. A modified cooperative game theory approach, in which each objective is associated with a different player, is used in this work. The applicability and computational efficiencies of the proposed techniques are demonstrated through several illustrative examples involving unconstrained and constrained problems with single and multiple objectives and continuous and mixed design variables. The present methodologies are expected to be useful for the solution of a variety of practical continuous and mixed optimization problems involving single or multiple objectives with or without constraints.

  7. CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET.

    PubMed

    Aadil, Farhan; Bajwa, Khalid Bashir; Khan, Salabat; Chaudary, Nadeem Majeed; Akram, Adeel

    2016-01-01

    A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO. PMID:27149517

  8. Detection of diploid males in a natural colony of the cleptobiotic bee Lestrimelitta sp (Hymenoptera, Apidae)

    PubMed Central

    2010-01-01

    When working at quantifying the genome size of stingless bees, it was observed that males of Lestrimelitta sp possessed the same amount of nuclear DNA as the females. Thus, we used flow cytometry (FCM) and cytogenetic analysis to confirm the ploidy of these individuals. The males analyzed proved to be diploid, since, through cytometric analysis, it was demonstrated that the mean genome size of both males and females was the same (C = 0.463 pg), and, furthermore, cytogenetic analysis demonstrated that both had 2n = 28 chromosomes. PMID:21637422

  9. An emerging paradigm of colony health: Microbial balance of the honey bee and hive (Apis mellifera)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Symbiotic microbes have played a major role in the evolution of many eukaryotes including insects. Among the social insects, many are best characterized as extended superorganisms wherein social behaviors, group generated physiology and symbiotic microbes contribute to colony nutrition and pathogen ...

  10. Pixel-based ant colony algorithm for source mask optimization

    NASA Astrophysics Data System (ADS)

    Kuo, Hung-Fei; Wu, Wei-Chen; Li, Frederick

    2015-03-01

    Source mask optimization (SMO) was considered to be one of the key resolution enhancement techniques for node technology below 20 nm prior to the availability of extreme-ultraviolet tools. SMO has been shown to enlarge the process margins for the critical layer in SRAM and memory cells. In this study, a new illumination shape optimization approach was developed on the basis of the ant colony optimization (ACO) principle. The use of this heuristic pixel-based ACO method in the SMO process provides an advantage over the extant SMO method because of the gradient of the cost function associated with the rapid and stable searching capability of the proposed method. This study was conducted to provide lithographic engineers with references for the quick determination of the optimal illumination shape for complex mask patterns. The test pattern used in this study was a contact layer for SRAM design, with a critical dimension and a minimum pitch of 55 and 110 nm, respectively. The optimized freeform source shape obtained using the ACO method was numerically verified by performing an aerial image investigation, and the result showed that the optimized freeform source shape generated an aerial image profile different from the nominal image profile and with an overall error rate of 9.64%. Furthermore, the overall average critical shape difference was determined to be 1.41, which was lower than that for the other off-axis illumination exposure. The process window results showed an improvement in exposure latitude (EL) and depth of focus (DOF) for the ACO-based freeform source shape compared with those of the Quasar source shape. The maximum EL of the ACO-based freeform source shape reached 7.4% and the DOF was 56 nm at an EL of 5%.

  11. Improved ant colony optimization for optimal crop and irrigation water allocation by incorporating domain knowledge

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An improved ant colony optimization (ACO) formulation for the allocation of crops and water to different irrigation areas is developed. The formulation enables dynamic adjustment of decision variable options and makes use of visibility factors (VFs, the domain knowledge that can be used to identify ...

  12. Reconstruction of phylogenetic trees using the ant colony optimization paradigm.

    PubMed

    Perretto, Mauricio; Lopes, Heitor Silvério

    2005-01-01

    We developed a new approach for the reconstruction of phylogenetic trees using ant colony optimization metaheuristics. A tree is constructed using a fully connected graph and the problem is approached similarly to the well-known traveling salesman problem. This methodology was used to develop an algorithm for constructing a phylogenetic tree using a pheromone matrix. Two data sets were tested with the algorithm: complete mitochondrial genomes from mammals and DNA sequences of the p53 gene from several eutherians. This new methodology was found to be superior to other well-known softwares, at least for this data set. These results are very promising and suggest more efforts for further developments. PMID:16342043

  13. Automated selection of appropriate pheromone representations in ant colony optimization.

    PubMed

    Montgomery, James; Randall, Marcus; Hendtlass, Tim

    2005-01-01

    Ant colony optimization (ACO) is a constructive metaheuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. Critically, the pheromone representation for a particular problem is usually chosen intuitively rather than by following any systematic process. In some representations, distinct solutions appear multiple times, increasing the effective size of the search space and potentially misleading ants as to the true learned value of those solutions. In this article, we present a novel system for automatically generating appropriate pheromone representations, based on the characteristics of the problem model that ensures unique pheromone representation of solutions. This is the first stage in the development of a generalized ACO system that could be applied to a wide range of problems with little or no modification. However, the system we propose may be used in the development of any problem-specific ACO algorithm. PMID:16053571

  14. A binary ant colony optimization classifier for molecular activities.

    PubMed

    Hammann, Felix; Suenderhauf, Claudia; Huwyler, Jörg

    2011-10-24

    Chemical fingerprints encode the presence or absence of molecular features and are available in many large databases. Using a variation of the Ant Colony Optimization (ACO) paradigm, we describe a binary classifier based on feature selection from fingerprints. We discuss the algorithm and possible cross-validation procedures. As a real-world example, we use our algorithm to analyze a Plasmodium falciparum inhibition assay and contrast its performance with other machine learning paradigms in use today (decision tree induction, random forests, support vector machines, artificial neural networks). Our algorithm matches established paradigms in predictive power, yet supplies the medicinal chemist and basic researcher with easily interpretable results. Furthermore, models generated with our paradigm are easy to implement and can complement virtual screenings by additionally exploiting the precalculated fingerprint information. PMID:21854036

  15. 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.

  16. Land-use change reduces habitat suitability for supporting managed honey bee colonies in the Northern Great Plains.

    PubMed

    Otto, Clint R V; Roth, Cali L; Carlson, Benjamin L; Smart, Matthew D

    2016-09-13

    Human reliance on insect pollination services continues to increase even as pollinator populations exhibit global declines. Increased commodity crop prices and federal subsidies for biofuel crops, such as corn and soybeans, have contributed to rapid land-use change in the US Northern Great Plains (NGP), changes that may jeopardize habitat for honey bees in a part of the country that supports >40% of the US colony stock. We investigated changes in biofuel crop production and grassland land covers surrounding ∼18,000 registered commercial apiaries in North and South Dakota from 2006 to 2014. We then developed habitat selection models to identify remotely sensed land-cover and land-use features that influence apiary site selection by Dakota beekeepers. Our study demonstrates a continual increase in biofuel crops, totaling 1.2 Mha, around registered apiary locations in North and South Dakota. Such crops were avoided by commercial beekeepers when selecting apiary sites in this region. Furthermore, our analysis reveals how grasslands that beekeepers target when selecting commercial apiary locations are becoming less common in eastern North and South Dakota, changes that may have lasting impact on pollinator conservation efforts. Our study highlights how land-use change in the NGP is altering the landscape in ways that are seemingly less conducive to beekeeping. Our models can be used to guide future conservation efforts highlighted in the US national pollinator health strategy by identifying areas that support high densities of commercial apiaries and that have exhibited significant land-use changes. PMID:27573824

  17. Land-use change reduces habitat suitability for supporting managed honey bee colonies in the Northern Great Plains

    USGS Publications Warehouse

    Otto, Clint R.; Roth, Cali; Carlson, Benjamin; Smart, Matthew

    2016-01-01

    Human reliance on insect pollination services continues to increase even as pollinator populations exhibit global declines. Increased commodity crop prices and federal subsidies for biofuel crops, such as corn and soybeans, have contributed to rapid land-use change in the US Northern Great Plains (NGP), changes that may jeopardize habitat for honey bees in a part of the country that supports >40% of the US colony stock. We investigated changes in biofuel crop production and grassland land covers surrounding ∼18,000 registered commercial apiaries in North and South Dakota from 2006 to 2014. We then developed habitat selection models to identify remotely sensed land-cover and land-use features that influence apiary site selection by Dakota beekeepers. Our study demonstrates a continual increase in biofuel crops, totaling 1.2 Mha, around registered apiary locations in North and South Dakota. Such crops were avoided by commercial beekeepers when selecting apiary sites in this region. Furthermore, our analysis reveals how grasslands that beekeepers target when selecting commercial apiary locations are becoming less common in eastern North and South Dakota, changes that may have lasting impact on pollinator conservation efforts. Our study highlights how land-use change in the NGP is altering the landscape in ways that are seemingly less conducive to beekeeping. Our models can be used to guide future conservation efforts highlighted in the US national pollinator health strategy by identifying areas that support high densities of commercial apiaries and that have exhibited significant land-use changes.

  18. Key management practices to prevent high infestation levels of Varroa destructor in honey bee colonies at the beginning of the honey yield season.

    PubMed

    Giacobino, Agostina; Molineri, Ana; Bulacio Cagnolo, Natalia; Merke, Julieta; Orellano, Emanuel; Bertozzi, Ezequiel; Masciangelo, Germán; Pietronave, Hernán; Pacini, Adriana; Salto, Cesar; Signorini, Marcelo

    2016-09-01

    Varroa destructor is considered one of the main threats to worldwide apiculture causing a variety of physiological effects at individual and colony level. Also, Varroa mites are often associated with several honey bee viruses presence. Relatively low levels of Varroa during the spring, at the beginning of the honey yield season, can have a significant economic impact on honey production and colony health. Winter treatments against Varroa and certain management practices may delay mite population growth during following spring and summer improving colonies performance during the honey yield season. The aim of this study was to identify risk factors associated with the presence of Varroa destructor in late spring in apiaries from temperate climate. A longitudinal study was carried out in 48 apiaries, randomly selected to evaluate V. destructor infestation level throughout the year. The percentage of infestation with V. destructor was assessed four times during one year and the beekeepers answered a survey concerning all management practices applied in the colonies. We used a generalized linear mixed model to determine association between risk of achieving 2% infestation on adult bees at the beginning of the honey yield season and all potential explanatory variables. The complete dataset was scanned to identify colonies clusters with a higher probability of achieving damage thresholds throughout the year. Colonies that achieved ≥2% of infestation with V. destructor during spring were owned by less experienced beekeepers. Moreover, as Varroa populations increase exponentially during spring and summer, if the spring sampling time is later this growth remains unobserved. Monitoring and winter treatment can be critical for controlling mite population during the honey production cycle. Spatial distribution of colonies with a higher risk of achieving high Varroa levels seems to be better explained by management practices than a geographical condition. PMID:27544258

  19. Multitrophic interaction facilitates parasite-host relationship between an invasive beetle and the honey bee.

    PubMed

    Torto, Baldwyn; Boucias, Drion G; Arbogast, Richard T; Tumlinson, James H; Teal, Peter E A

    2007-05-15

    Colony defense by honey bees, Apis mellifera, is associated with stinging and mass attack, fueled by the release of alarm pheromones. Thus, alarm pheromones are critically important to survival of honey bee colonies. Here we report that in the parasitic relationship between the European honey bee and the small hive beetle, Aethina tumida, the honey bee's alarm pheromones serve a negative function because they are potent attractants for the beetle. Furthermore, we discovered that the beetles from both Africa and the United States vector a strain of Kodamaea ohmeri yeast, which produces these same honey bee alarm pheromones when grown on pollen in hives. The beetle is not a pest of African honey bees because African bees have evolved effective methods to mitigate beetle infestation. However, European honey bees, faced with disease and pest management stresses different from those experienced by African bees, are unable to effectively inhibit beetle infestation. Therefore, the environment of the European honey bee colony provides optimal conditions to promote the unique bee-beetle-yeast-pollen multitrophic interaction that facilitates effective infestation of hives at the expense of the European honey bee. PMID:17483478

  20. An evaluation of the associations of parameters related to the fall of Varroa destructor (Acari: Varroidae) from commercial honey bee (Hymenoptera: Apidae) colonies as tools for selective breeding for mite resistance.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Varroa destructor (Anderson and Trueman) trapped on bottom boards were assessed as indirect measurements of colony mite population differences in commercial colonies of Russian and Italian honey bees (Apis mellifera L.) using 35 candidate measurements. Measurements included numbers of damaged and no...

  1. Enhanced ant colony optimization for inventory routing problem

    NASA Astrophysics Data System (ADS)

    Wong, Lily; Moin, Noor Hasnah

    2015-10-01

    The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.

  2. Ant colony optimization-based firewall anomaly mitigation engine.

    PubMed

    Penmatsa, Ravi Kiran Varma; Vatsavayi, Valli Kumari; Samayamantula, Srinivas Kumar

    2016-01-01

    A firewall is the most essential component of network perimeter security. Due to human error and the involvement of multiple administrators in configuring firewall rules, there exist common anomalies in firewall rulesets such as Shadowing, Generalization, Correlation, and Redundancy. There is a need for research on efficient ways of resolving such anomalies. The challenge is also to see that the reordered or resolved ruleset conforms to the organization's framed security policy. This study proposes an ant colony optimization (ACO)-based anomaly resolution and reordering of firewall rules called ACO-based firewall anomaly mitigation engine. Modified strategies are also introduced to automatically detect these anomalies and to minimize manual intervention of the administrator. Furthermore, an adaptive reordering strategy is proposed to aid faster reordering when a new rule is appended. The proposed approach was tested with different firewall policy sets. The results were found to be promising in terms of the number of conflicts resolved, with minimal availability loss and marginal security risk. This work demonstrated the application of a metaheuristic search technique, ACO, in improving the performance of a packet-filter firewall with respect to mitigating anomalies in the rules, and at the same time demonstrated conformance to the security policy. PMID:27441151

  3. Routing in Ad Hoc Network Using Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Khanpara, Pimal; Valiveti, Sharada; Kotecha, K.

    The ad hoc networks have dynamic topology and are infrastructure less. So it is required to implement a new network protocol for providing efficient end to end communication based on TCP/IP structure. There is a need to re-define or modify the functions of each layer of TCP/IP model to provide end to end communication between nodes. The mobility of the nodes and the limited resources are the main reason for this change. The main challenge in ad hoc networks is routing. Due to the mobility of the nodes in the ad hoc networks, routing becomes very difficult. Ant based algorithms are suitable for routing in ad hoc networks due to its dynamic nature and adaptive behavior. There are number of routing algorithms based on the concept of ant colony optimizations. It is quite difficult to determine the best ant based algorithm for routing as these algorithms perform differently under various circumstances such as the traffic distribution and network topology. In this paper, the overview of such routing algorithms is given.

  4. New Paenibacillus larvae bacterial isolates from honey bee colonies infected with American foulbrood disease in Egypt

    PubMed Central

    Masry, Saad Hamdy Daif; Kabeil, Sanaa Soliman; Hafez, Elsayed Elsayed

    2014-01-01

    The American foulbrood disease is widely distributed all over the world and causes a serious problem for the honeybee industry. Different infected larvae were collected from different apiaries, ground in phosphate saline buffer (PSB) and bacterial isolation was carried out on nutrient agar medium. Different colonies were observed and were characterized biologically. Two bacterial isolates (SH11 and SH33) were subjected to molecular identification using 16S rRNA gene and the sequence analysis revealed that the two isolates are Paenibacillus larvae with identity not exceeding 83%. The DNA sequence alignment between the other P. larvae bacterial strains and the two identified bacterial isolates showed that all the examined bacterial strains have the same ancestor, i.e. they have the same origin. The SH33 isolate was closely related to the P. larvae isolated from Germany, whereas the isolate SH11 was close to the P. larvae isolated from India. The phylogenetic tree constructed for 20 different Bacillus sp. and the two isolates SH11 and SH33 demonstrated that the two isolates are Bacillus sp. and they are new isolates. The bacterial isolates will be subjected to more tests for more confirmations. PMID:26740757

  5. Hot spots in the bee hive

    NASA Astrophysics Data System (ADS)

    Bujok, Brigitte; Kleinhenz, Marco; Fuchs, Stefan; Tautz, Jürgen

    2002-06-01

    Honeybee colonies (Apis mellifera) maintain temperatures of 35-36°C in their brood nest because the brood needs high and constant temperature conditions for optimal development. We show that incubation of the brood at the level of individual honeybees is done by worker bees performing a particular and not yet specified behaviour: such bees raise the brood temperature by pressing their warm thoraces firmly onto caps under which the pupae develop. The bees stay motionless in a characteristic posture and have significantly higher thoracic temperatures than bees not assuming this posture in the brood area. The surface of the brood caps against which warm bees had pressed their thorax were up to 3.2°C warmer than the surrounding area, confirming that effective thermal transfer had taken place.

  6. A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

    PubMed Central

    Othman, Zulaiha Ali

    2014-01-01

    Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748

  7. SamACO: variable sampling ant colony optimization algorithm for continuous optimization.

    PubMed

    Hu, Xiao-Min; Zhang, Jun; Chung, Henry Shu-Hung; Li, Yun; Liu, Ou

    2010-12-01

    An ant colony optimization (ACO) algorithm offers algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution constructions and to realize a pheromone laying-and-following mechanism. Although ACO is first designed for solving discrete (combinatorial) optimization problems, the ACO procedure is also applicable to continuous optimization. This paper presents a new way of extending ACO to solving continuous optimization problems by focusing on continuous variable sampling as a key to transforming ACO from discrete optimization to continuous optimization. The proposed SamACO algorithm consists of three major steps, i.e., the generation of candidate variable values for selection, the ants' solution construction, and the pheromone update process. The distinct characteristics of SamACO are the cooperation of a novel sampling method for discretizing the continuous search space and an efficient incremental solution construction method based on the sampled values. The performance of SamACO is tested using continuous numerical functions with unimodal and multimodal features. Compared with some state-of-the-art algorithms, including traditional ant-based algorithms and representative computational intelligence algorithms for continuous optimization, the performance of SamACO is seen competitive and promising. PMID:20371409

  8. Honey Bees: Sweetness and Mites

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bee colony losses have been in the news lately and the potential reasons for these losses have taken up much space in the news media. In order to clarify what role mites play in the current loss (2006-2007) of bee colonies, called Colony Collapse Disorder, a better understanding of what a mit...

  9. Optimal Selection of Parameters for Nonuniform Embedding of Chaotic Time Series Using Ant Colony Optimization.

    PubMed

    Shen, Meie; Chen, Wei-Neng; Zhang, Jun; Chung, Henry Shu-Hung; Kaynak, Okyay

    2013-04-01

    The optimal selection of parameters for time-delay embedding is crucial to the analysis and the forecasting of chaotic time series. Although various parameter selection techniques have been developed for conventional uniform embedding methods, the study of parameter selection for nonuniform embedding is progressed at a slow pace. In nonuniform embedding, which enables different dimensions to have different time delays, the selection of time delays for different dimensions presents a difficult optimization problem with combinatorial explosion. To solve this problem efficiently, this paper proposes an ant colony optimization (ACO) approach. Taking advantage of the characteristic of incremental solution construction of the ACO, the proposed ACO for nonuniform embedding (ACO-NE) divides the solution construction procedure into two phases, i.e., selection of embedding dimension and selection of time delays. In this way, both the embedding dimension and the time delays can be optimized, along with the search process of the algorithm. To accelerate search speed, we extract useful information from the original time series to define heuristics to guide the search direction of ants. Three geometry- or model-based criteria are used to test the performance of the algorithm. The optimal embeddings found by the algorithm are also applied in time-series forecasting. Experimental results show that the ACO-NE is able to yield good embedding solutions from both the viewpoints of optimization performance and prediction accuracy. PMID:23144038

  10. The effects of hive color and feeding on the size of winter clusters of Russian honey bee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study determined the effects of hive color (black or white) and its interaction with feeding on colony growth of Russian colonies through the winter. One hundred and forty two colonies with pure-mated Russian queens were established. One half of them were in hives painted white and one half o...

  11. An improved ant colony optimization approach for optimization of process planning.

    PubMed

    Wang, JinFeng; Fan, XiaoLiang; Ding, Haimin

    2014-01-01

    Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach. PMID:25097874

  12. An Improved Ant Colony Optimization Approach for Optimization of Process Planning

    PubMed Central

    Wang, JinFeng; Fan, XiaoLiang; Ding, Haimin

    2014-01-01

    Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach. PMID:25097874

  13. Inverse transient radiation analysis in one-dimensional participating slab using improved Ant Colony Optimization algorithms

    NASA Astrophysics Data System (ADS)

    Zhang, B.; Qi, H.; Ren, Y. T.; Sun, S. C.; Ruan, L. M.

    2014-01-01

    As a heuristic intelligent optimization algorithm, the Ant Colony Optimization (ACO) algorithm was applied to the inverse problem of a one-dimensional (1-D) transient radiative transfer in present study. To illustrate the performance of this algorithm, the optical thickness and scattering albedo of the 1-D participating slab medium were retrieved simultaneously. The radiative reflectance simulated by Monte-Carlo Method (MCM) and Finite Volume Method (FVM) were used as measured and estimated value for the inverse analysis, respectively. To improve the accuracy and efficiency of the Basic Ant Colony Optimization (BACO) algorithm, three improved ACO algorithms, i.e., the Region Ant Colony Optimization algorithm (RACO), Stochastic Ant Colony Optimization algorithm (SACO) and Homogeneous Ant Colony Optimization algorithm (HACO), were developed. By the HACO algorithm presented, the radiative parameters could be estimated accurately, even with noisy data. In conclusion, the HACO algorithm is demonstrated to be effective and robust, which had the potential to be implemented in various fields of inverse radiation problems.

  14. An adaptive ant colony system algorithm for continuous-space optimization problems.

    PubMed

    Li, Yan-jun; Wu, Tie-jun

    2003-01-01

    Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is proposed in this paper to tackle continuous-space optimization problems, using a new objective-function-based heuristic pheromone assignment approach for pheromone update to filtrate solution candidates. Global optimal solutions can be reached more rapidly by self-adjusting the path searching behaviors of the ants according to objective values. The performance of the proposed algorithm is compared with a basic ant colony algorithm and a Square Quadratic Programming approach in solving two benchmark problems with multiple extremes. The results indicated that the efficiency and reliability of the proposed algorithm were greatly improved. PMID:12656341

  15. Evaluating pure Africanized honey bees and hybrid crosses for colony health and resistance to varroa mites in a subtropical climate

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Different honey bee, Apis mellifera L., breeds were evaluated for overall health and for resistance to the parastic mite, Varroa destructor Oud. in the subtropical Lower Rio Grande Valley (LRGV) in south Texas from June 2005 through October 2006. Breeds examined that have shown genetic resistance ...

  16. Honey bee colonies act as reservoirs for two Spiroplasma facultative symbionts and incur complex multiyear infection dynamics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Approximately 30 years ago, two species of mollicute bacteria in the genus Spiroplasma were isolated and described from adult Western honey bees (Apis mellifera). Denominated for their host as Spiroplasma apis and Spiroplasma melliferum, these bacteria were uniquely isolated during springtime and h...

  17. Evaluation of apicultural characteristics of first year colonies initiated from packaged honey bees, Apis mellifera L. (Hymenoptera: Apidae)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We evaluated six stocks of the honey bee, Apis mellifera, from four producers. We examined the effects of initial levels of the parasitic mite Varroa destructor Anderson and Trueman, the endoparasitic mite Acarapis woodi (Rennie), the intestinal parasite Nosema (species not determined) and levels of...

  18. Differential Bees Flux Balance Analysis with OptKnock for In Silico Microbial Strains Optimization

    PubMed Central

    Choon, Yee Wen; Mohamad, Mohd Saberi; Deris, Safaai; Illias, Rosli Md.; Chong, Chuii Khim; Chai, Lian En; Omatu, Sigeru; Corchado, Juan Manuel

    2014-01-01

    Microbial strains optimization for the overproduction of desired phenotype has been a popular topic in recent years. The strains can be optimized through several techniques in the field of genetic engineering. Gene knockout is a genetic engineering technique that can engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, the complexities of the metabolic networks have made the process to identify the effects of genetic modification on the desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to the combinatorial problem in obtaining optimal gene deletion strategy. Basically, the size of a genome-scale metabolic model is usually large. As the size of the problem increases, the computation time increases exponentially. In this paper, we propose Differential Bees Flux Balance Analysis (DBFBA) with OptKnock to identify optimal gene knockout strategies for maximizing the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by improving the performance of a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA) by hybridizing Differential Evolution (DE) algorithm into neighborhood searching strategy of BAFBA. In addition, DBFBA is integrated with OptKnock to validate the results for improving the reliability the work. Through several experiments conducted on Escherichia coli, Bacillus subtilis, and Clostridium thermocellum as the model organisms, DBFBA has shown a better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes compared to the methods used in previous works. PMID:25047076

  19. Karyotypic description of the stingless bee Oxytrigona cf. flaveola (Hymenoptera, Apidae, Meliponina) of a colony from Tangará da Serra, Mato Grosso State, Brazil

    PubMed Central

    2010-01-01

    The aim was to broaden knowledge on the cytogenetics of the subtribe Meliponina, by furnishing cytogenetic data as a contribution to the characterization of bees from the genus Oxytrigona. Individuals of the species Oxytrigona cf. flaveola, members of a colony from Tangará da Serra, Mato Grosso State, Brazil, were studied. The chromosome number was 2n = 34, distributed among four chromosomal morphologies, with the karyotype formula 8m+8sm+16st+2t. Size heteromorphism in the first metacentric pair, subsequently confirmed by sequential staining with fluorochrome (DA/DAPI/CMA3 ), was apparent in all the examined individuals The nucleolar organizing regions (NORs) are possibly located in this metacentric chromosome pair. These data will contribute towards a better understanding of the genus Oxytrigona. Given that species in this group are threatened, the importance of their preservation and conservation can be shown in a sensible, concise fashion through studies such as this. PMID:21637423

  20. Karyotypic description of the stingless bee Oxytrigona cf. flaveola (Hymenoptera, Apidae, Meliponina) of a colony from Tangará da Serra, Mato Grosso State, Brazil.

    PubMed

    Krinski, Diones; Fernandes, Anderson; Rocha, Marla Piumbini; Pompolo, Silvia das Graças

    2010-07-01

    The aim was to broaden knowledge on the cytogenetics of the subtribe Meliponina, by furnishing cytogenetic data as a contribution to the characterization of bees from the genus Oxytrigona. Individuals of the species Oxytrigona cf. flaveola, members of a colony from Tangará da Serra, Mato Grosso State, Brazil, were studied. The chromosome number was 2n = 34, distributed among four chromosomal morphologies, with the karyotype formula 8m+8sm+16st+2t. Size heteromorphism in the first metacentric pair, subsequently confirmed by sequential staining with fluorochrome (DA/DAPI/CMA(3) ), was apparent in all the examined individuals The nucleolar organizing regions (NORs) are possibly located in this metacentric chromosome pair. These data will contribute towards a better understanding of the genus Oxytrigona. Given that species in this group are threatened, the importance of their preservation and conservation can be shown in a sensible, concise fashion through studies such as this. PMID:21637423

  1. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence.

    PubMed

    Srinivasan, Thenmozhi; Palanisamy, Balasubramanie

    2015-01-01

    Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM), with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets. PMID:26495413

  2. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

    PubMed Central

    Srinivasan, Thenmozhi; Palanisamy, Balasubramanie

    2015-01-01

    Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM), with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets. PMID:26495413

  3. Production of workers, queens and males in Plebeia remota colonies (Hymenoptera, Apidae, Meliponini), a stingless bee with reproductive diapause.

    PubMed

    Alves, D A; Imperatriz-Fonseca, V L; Santos-Filho, P S

    2009-01-01

    Queen, male and worker production was studied during one year in three Plebeia remota colonies from Atlantic Rainforest in Cunha, São Paulo State, and two from a subtropical Araucaria forest in Prudentópolis, Paraná State. All the colonies were kept in São Paulo city during our study. Plebeia remota has reproductive diapause during autumn and winter, which makes its biology of special interest. Brood production begins before spring, renewing the colony cycle. We sampled brood combs monthly in these five colonies. The number of cells in each comb varied significantly with time of the year; the smallest brood combs appear to be a consequence of reduced food availability. However, worker, queen and male frequencies did not differ significantly in time, and this presumably is due to the fact that they all are necessary for the growth, maintenance and reproduction of the colony. Although some molecular, morphological and behavioral differences have been detected in several studies comparing populations from Cunha and from Prudentópolis, we did not find significant differences between the colonies from these two localities in number of brood cells and worker, queen and male production. PMID:19554766

  4. Chalkbrood disease in honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Chalkbrood is an invasive mycosis in honey bees (Apis mellifera L.) produced by Ascosphaera apis (Maassen ex Claussen) Olive and Spiltoir (Spiltoir, 1955) that exclusively affects bee brood. Although fatal to individual larvae, the disease does not usually destroy an entire bee colony. However, it c...

  5. 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

  6. Ant colony optimization analysis on overall stability of high arch dam basis of field monitoring.

    PubMed

    Lin, Peng; 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

  7. 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…

  8. A graph-based ant colony optimization approach for process planning.

    PubMed

    Wang, JinFeng; Fan, XiaoLiang; Wan, Shuting

    2014-01-01

    The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach. PMID:24995355

  9. A Graph-Based Ant Colony Optimization Approach for Process Planning

    PubMed Central

    Wang, JinFeng; Fan, XiaoLiang; Wan, Shuting

    2014-01-01

    The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach. PMID:24995355

  10. Displacement back analysis for underground engineering based on immunized continuous ant colony optimization

    NASA Astrophysics Data System (ADS)

    Gao, Wei

    2016-05-01

    The objective function of displacement back analysis for rock parameters in underground engineering is a very complicated nonlinear multiple hump function. The global optimization method can solve this problem very well. However, many numerical simulations must be performed during the optimization process, which is very time consuming. Therefore, it is important to improve the computational efficiency of optimization back analysis. To improve optimization back analysis, a new global optimization, immunized continuous ant colony optimization, is proposed. This is an improved continuous ant colony optimization using the basic principles of an artificial immune system and evolutionary algorithm. Based on this new global optimization, a new displacement optimization back analysis for rock parameters is proposed. The computational performance of the new back analysis is verified through a numerical example and a real engineering example. The results show that this new method can be used to obtain suitable parameters of rock mass with higher accuracy and less effort than previous methods. Moreover, the new back analysis is very robust.

  11. 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. PMID:25954768

  12. Routing in Wireless Sensor Networks Using an Ant Colony Optimization (ACO) Router Chip.

    PubMed

    Okdem, Selcuk; Karaboga, Dervis

    2009-01-01

    Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. A novel routing approach using an Ant Colony Optimization algorithm is proposed for Wireless Sensor Networks consisting of stable nodes. Illustrative examples, detailed descriptions and comparative performance test results of the proposed approach are included. The approach is also implemented to a small sized hardware component as a router chip. Simulation results show that proposed algorithm provides promising solutions allowing node designers to efficiently operate routing tasks. PMID:22399947

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

    PubMed Central

    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. PMID:25954768

  14. Ant colony optimization image registration algorithm based on wavelet transform and mutual information

    NASA Astrophysics Data System (ADS)

    Zhang, Hong; Sun, Yanfeng; Zhai, Bing; Wang, Yiding

    2013-07-01

    This paper studies on the image registration of the medical images. Wavelet transform is adopted to decompose the medical images because the resolution of the medical image is high and the computational amount of the registration is large. Firstly, the low frequency sub-images are matched. Then source images are matched. The image registration was fulfilled by the ant colony optimization algorithm to search the extremum of the mutual information. The experiment result demonstrates the proposed approach can not only reduce calculation amount, but also skip from the local extremum during optimization process, and search the optimization value.

  15. 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. PMID:24783812

  16. Chronic bee paralysis virus and Nosema ceranae experimental co-infection of winter honey bee workers (Apis mellifera L.)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Chronic bee paralysis virus (CBPV) is an important viral disease of adult bees which induces significant losses in honey bee colonies. In this study winter worker bees were experimentally infected using three different experiments. Bees were inoculated orally or topically with CBPV to evaluate the l...

  17. Inverse problem for the solidification of binary alloy in the casting mould solved by using the bee optimization algorithm

    NASA Astrophysics Data System (ADS)

    Hetmaniok, Edyta

    2015-08-01

    In this paper the procedure for solving the inverse problem for the binary alloy solidification in the casting mould is presented. Proposed approach is based on the mathematical model suitable for describing the investigated solidification process, the lever arm model describing the macrosegregation process, the finite element method for solving the direct problem and the artificial bee colony algorithm for minimizing the functional expressing the error of approximate solution. Goal of the discussed inverse problem is the reconstruction of heat transfer coefficient and distribution of temperature in investigated region on the basis of known measurements of temperature.

  18. Inverse problem for the solidification of binary alloy in the casting mould solved by using the bee optimization algorithm

    NASA Astrophysics Data System (ADS)

    Hetmaniok, Edyta

    2016-07-01

    In this paper the procedure for solving the inverse problem for the binary alloy solidification in the casting mould is presented. Proposed approach is based on the mathematical model suitable for describing the investigated solidification process, the lever arm model describing the macrosegregation process, the finite element method for solving the direct problem and the artificial bee colony algorithm for minimizing the functional expressing the error of approximate solution. Goal of the discussed inverse problem is the reconstruction of heat transfer coefficient and distribution of temperature in investigated region on the basis of known measurements of temperature.

  19. Effects of varroa mites and bee diseases on pollination efficacy of honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Varroa mites and viral diseases are known to affect the efficiency of crop pollination by honey. This study elucidates effects of varroa mites and bee diseases on the foraging behavior of adult bees and the consequences on successful fruit pollination. Four honey bee colonies of about 4,500 bees eac...

  20. Ant colony optimization for biomarker identification from MALDI-TOF mass spectra.

    PubMed

    Ressom, Habtom W; Varghese, Rency S; Orvisky, Eduard; Drake, Steven K; Hortin, Glen L; Abdel-Hamid, Mohamed; Loffredo, Christopher A; Goldman, Radoslav

    2006-01-01

    We present a novel method that combines ant colony optimization with support vector machines (ACO-SVM) to select candidate biomarkers from MALDI-TOF serum profiles of hepatocellular carcinoma (HCC) patients and matched controls. The method identified relevant mass points that achieve high sensitivity and specificity in distinguishing HCC patients from healthy individuals. The results indicate that the MALDI-TOF technology could provide the means to discover novel biomarkers for HCC. PMID:17946638

  1. Coupling ant colony optimization and the extended great deluge algorithm for the discrete facility layout problem

    NASA Astrophysics Data System (ADS)

    Nourelfath, M.; Nahas, N.; Montreuil, B.

    2007-12-01

    This article uses a hybrid optimization approach to solve the discrete facility layout problem (FLP), modelled as a quadratic assignment problem (QAP). The idea of this approach design is inspired by the ant colony meta-heuristic optimization method, combined with the extended great deluge (EGD) local search technique. Comparative computational experiments are carried out on benchmarks taken from the QAP-library and from real life problems. The performance of the proposed algorithm is compared to construction and improvement heuristics such as H63, HC63-66, CRAFT and Bubble Search, as well as other existing meta-heuristics developed in the literature based on simulated annealing (SA), tabu search and genetic algorithms (GAs). This algorithm is compared also to other ant colony implementations for QAP. The experimental results show that the proposed ant colony optimization/extended great deluge (ACO/EGD) performs significantly better than the existing construction and improvement algorithms. The experimental results indicate also that the ACO/EGD heuristic methodology offers advantages over other algorithms based on meta-heuristics in terms of solution quality.

  2. A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

    PubMed Central

    Parmaksızoğlu, Selami; Alçı, Mustafa

    2011-01-01

    Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

  3. Mobility Robustness Optimization in Femtocell Networks Based on Ant Colony Algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Haijun; Liu, Hui; Ma, Wenmin; Zheng, Wei; Wen, Xiangming; Jiang, Chunxiao

    Mobility Robustness Optimization (MRO) is one of the most important goals in LTE-Advanced Self-Organizing Networks (SON). Seamless handover in femtocell network is urgent and challenging, which has not been paid enough attention. Handover decision parameters, such as Time-To-Trigger (TTT), Hysteresis, Cell Individual Offset (CIO), have great effect on mobility performance, which may lead to Radio Link Failures (RLFs) and Unnecessary Handover. This letter proposes a handover parameters optimization approach based on Ant Colony Algorithm in the femtocell networks. The simulation result shows that the proposed scheme has a better performance than the fixed parameters method.

  4. Distributed Bees Algorithm Parameters Optimization for a Cost Efficient Target Allocation in Swarms of Robots

    PubMed Central

    Jevtić, Aleksandar; Gutiérrez, Álvaro

    2011-01-01

    Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677

  5. Distributed bees algorithm parameters optimization for a cost efficient target allocation in swarms of robots.

    PubMed

    Jevtić, Aleksandar; Gutiérrez, Alvaro

    2011-01-01

    Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the distributed bees algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA's control parameters by means of a genetic algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots' distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677

  6. Bee cups: Single-use cages for honey bee experiments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bees face challenges ranging from poor nutrition to exposure to parasites, pathogens, and environmental chemicals. These challenges drain colony resources and have been tied to both subtle and extreme colony declines, including the enigmatic Colony Collapse Disorder (CCD). Understanding how ...

  7. 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

  8. PC BEEPOP - A PERSONAL COMPUTER HONEY BEE POPULATION DYNAMICS MODEL

    EPA Science Inventory

    PC BEEPOP is a computer model that simulates honey bee (Apis mellifera L.) colony population dynamics. he model consists of a system of interdependent elements, including colony condition, environmental variability, colony energetics, and contaminant exposure. t includes a mortal...

  9. Evaluation of Mite-Away-II for fall control of Varroa destructor (Acari: Varroidae) in colonies of the honey bee Apis mellifera (Hymenoptera: Apidae) in the northeastern USA.

    PubMed

    Calderone, Nicholas W

    2010-02-01

    Mite-Away II, a recently-registered product with a proprietary formulation of formic acid, was evaluated under field conditions in commercial apiaries in upstate New York (USA) for the fall control of Varroa destructor Anderson & Trueman in colonies of the honey bee, Apis mellifera L. Ambient temperatures during the treatment period were in the lower half of the range recommended on the label, but were typical for early fall in upstate New York. Average mite mortality was 60.2 +/- 2.2% in the Mite-Away II group and 23.3 +/- 2.6% in the untreated control group. These means were significantly different from each other, but the level of control was only moderate. These results demonstrate that Mite-Away II may not always provide an adequate level of control even when the temperature at the time of application falls within the recommended range stated on the product's label. To make the best use of temperature-sensitive products, I suggest that the current, single-value, economic treatment threshold be replaced with an economic treatment range. The limits for this range are specified by two pest density values. The lower limit is the usual pest density that triggers a treatment. The upper limit is the maximum pest density that one can expect to reduce to a level below the lower limit given the temperatures expected during the treatment period. When the actual pest density exceeds the upper limit, the product should not be recommended; or, a warning should be included indicating that acceptable control may not be achieved. PMID:19588256

  10. An ant colony optimization based algorithm for identifying gene regulatory elements.

    PubMed

    Liu, Wei; Chen, Hanwu; Chen, Ling

    2013-08-01

    It is one of the most important tasks in bioinformatics to identify the regulatory elements in gene sequences. Most of the existing algorithms for identifying regulatory elements are inclined to converge into a local optimum, and have high time complexity. Ant Colony Optimization (ACO) is a meta-heuristic method based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of real ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper designs and implements an ACO based algorithm named ACRI (ant-colony-regulatory-identification) for identifying all possible binding sites of transcription factor from the upstream of co-expressed genes. To accelerate the ants' searching process, a strategy of local optimization is presented to adjust the ants' start positions on the searched sequences. By exploiting the powerful optimization ability of ACO, the algorithm ACRI can not only improve precision of the results, but also achieve a very high speed. Experimental results on real world datasets show that ACRI can outperform other traditional algorithms in the respects of speed and quality of solutions. PMID:23746735

  11. Abnormality detection in retinal images using ant colony optimization and artificial neural networks - biomed 2010.

    PubMed

    Kavitha, Ganesan; Ramakrishnan, Swaminathan

    2010-01-01

    Optic disc and retinal vasculature are important anatomical structures in the retina of the eye and any changes observed in these structures provide vital information on severity of various diseases. Digital retinal images are shown to provide a meaningful way of documenting and assessing some of the key elements inside the eye including the optic nerve and the tiny retinal blood vessels. In this work, an attempt has been made to detect and differentiate abnormalities of the retina using Digital image processing together with Optimization based segmentation and Artificial Neural Network methods. The retinal fundus images were recorded using standard protocols. Ant Colony Optimization is employed to extract the most significant objects namely the optic disc and blood vessel. The features related to these objects are obtained and corresponding indices are also derived. Further, these features are subjected to classification using Radial Basis Function Neural Networks and compared with conventional training algorithms. Results show that the Ant Colony Optimization is efficient in extracting useful information from retinal images. The features derived are effective for classification of normal and abnormal images using Radial basis function networks compared to other methods. As Optic disc and blood vessels are significant markers of abnormality in retinal images, the method proposed appears to be useful for mass screening. In this paper, the objectives of the study, methodology and significant observations are presented. PMID:20467104

  12. 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.

  13. Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

    NASA Astrophysics Data System (ADS)

    Davoodi, M.; Mesgari, M. S.

    2015-12-01

    Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

  14. Integration of GPS and DinSAR for Deformation Monitoring Based on Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Shi, Guoqiang; He, Xiufeng; Xiao, Ruya

    2014-11-01

    To acquire three-dimensional earth surface deformation, a measurement method based on ant colony optimization (ACO) is proposed. It highly integrates high-accuracy GPS observations from sparse ground points with InSAR line-of-sight (LOS) direction information. Two constraints, GPS and DInSAR observations, are employed in constructing the energy function whose minimum value will be searched by the ACO operated in continuous space. Compared with conventional interpolation algorithms, the proposed method increases the three-dimensional deformation observation accuracy, especially showing the improvement in the up direction.

  15. Bee Pollen

    MedlinePlus

    ... Don’t confuse bee pollen with bee venom, honey, or royal jelly. People take bee pollen for ... Pollen, Extrait de Pollen d’Abeille, Honeybee Pollen, Honey Bee Pollen, Maize Pollen, Pine Pollen, Polen de ...

  16. Bees brought to their knees: Microbes affecting honey bee health

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The biology and health of the honey bee, Apis mellifera, has been of interest to human societies since the advent of beekeeping. Descriptive scientific research on pathogens affecting honey bees have been published for nearly a century, but it wasn’t until the recent outbreak of heavy colony losses...

  17. Impact of Orchard Fungicide Spraying on Lowering the Amount of Symbiotic Fungi in Bee Bread and Its Implications for Reduced Colony Resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bee larvae depend on fungi to produce food (bee bread) from stored pollen as a developmental requirement. In the absence of or lower amounts of such fungi, chalkbrood disease (Ascosphaera apis) occurs, which is the highlight observation and the purpose for this chapter. Beebread is a competitive e...

  18. A Review of Bee Virology Progress

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bees play a vital role in global food production and sustainable ecological systems. However, honey bee colony losses at the rate of 20%-30% per year in recent years have been devastating to the agricultural industry and ecosystem that rely on honey bees for pollination. Among biotic and abiot...

  19. A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model.

    PubMed

    Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao

    2014-09-01

    Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. PMID:24613939

  20. Adaptive tracking and compensation of laser spot based on ant colony optimization

    NASA Astrophysics Data System (ADS)

    Yang, Lihong; Ke, Xizheng; Bai, Runbing; Hu, Qidi

    2009-05-01

    Because the effect of atmospheric scattering and atmospheric turbulence on laser signal of atmospheric absorption,laser spot twinkling, beam drift and spot split-up occur ,when laser signal transmits in the atmospheric channel. The phenomenon will be seriously affects the stability and the reliability of laser spot receiving system. In order to reduce the influence of atmospheric turbulence, we adopt optimum control thoughts in the field of artificial intelligence, propose a novel adaptive optical control technology-- model-free optimized adaptive control technology, analyze low-order pattern wave-front error theory, in which an -adaptive optical system is employed to adjust errors, and design its adaptive structure system. Ant colony algorithm is the control core algorithm, which is characteristic of positive feedback, distributed computing and greedy heuristic search. . The ant colony algorithm optimization of adaptive optical phase compensation is simulated. Simulation result shows that, the algorithm can effectively control laser energy distribution, improve laser light beam quality, and enhance signal-to-noise ratio of received signal.

  1. 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.

  2. Evaluation of a real-time two-step RT-PCR assay for quantitation of Chronic bee paralysis virus (CBPV) genome in experimentally-infected bee tissues and in life stages of a symptomatic colony.

    PubMed

    Blanchard, Philippe; Ribière, Magali; Celle, Olivier; Lallemand, Perrine; Schurr, Frank; Olivier, Violaine; Iscache, Anne Laure; Faucon, Jean Paul

    2007-04-01

    A two-step real-time RT-PCR assay, based on TaqMan technology using a fluorescent probe (FAM-TAMRA) was developed to quantify Chronic bee paralysis virus (CBPV) genome in bee samples. Standard curves obtained from a CBPV control RNA and from a plasmid containing a partial sequence of CBPV showed that this assay provided linear detection over a 7-log range (R(2)>0.99) with a limit of detection of 100 copies, and reliable inter-assay and intra-assay reproducibility. Standardisation including RNA purification and cDNAs synthesis was also validated. The CBPV TaqMan methodology was first evaluated by quantifying the CBPV genomic load in bee samples from an experimental infection obtained by topical application. Up to 1.9 x 10(10) CBPV copies per segment of insect body (head, thorax and abdomen) were revealed whereas a lower CBPV genomic load was detected in dissected organs such as mandibular and hypopharyngeal glands, brain and alimentary canal (up to 7.2 x 10(6) CBPV copies). The CBPV genomic loads in different categories of bees from a hive presenting the trembling symptoms typical of Chronic paralysis were then quantified. Significantly higher CBPV loads were found in guard, symptomatic and dead bees (up to 1.9 x 10(13) CBPV copies) than in forager, drones and house bees (up to 3.4 x 10(6) CBPV copies). The results obtained for symptomatic or dead bees support the correlation between high CBPV genomic load and pathology expression. Moreover, the high CBPV genomic load revealed in guard bees highlights the possible pivotal role played by this category of bees in CBPV infection. PMID:17166598

  3. Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  4. Assessing grooming behavior of Russian honey bees toward Varroa destructor.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The grooming behavior of Russian bees was compared to Italian bees. Overall, Russian bees had significantly lower numbers of mites than the Italian bees with a mean of 1,937 ± 366 and 5,088 ± 733 mites, respectively. This low mite population in the Russian colonies was probably due to the increased ...

  5. Effects of long distance transportation on honey bee physiology

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Despite the requirement of long distance transportation of honey bees used for pollination, we understand little how transportation affects honey bees. Three trials were conducted to study the effects of long distance transportation on honey bee physiology. Newly emerged bees from one colony were sp...

  6. 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.

  7. Expression and Control of Codon-Optimized Granulocyte Colony-Stimulating Factor in Pichia pastoris.

    PubMed

    Maity, Nitu; Thawani, Ankita; Sharma, Anshul; Gautam, Ashwani; Mishra, Saroj; Sahai, Vikram

    2016-01-01

    Granulocyte colony-stimulating factor (GCSF) has therapeutic applications due to its proven efficacy in different forms of neutropenia and chemotherapy-induced leucopenia. The original 564-bp nucleotide sequence from NCBI was codon optimized and assembled by overlapping PCR method comprising of 16 oligos of 50-nt length with 15 base overhang. The synthetic gene (CO-GCSF) was cloned under glucose utilizing glyceraldehyde 3-phosphate dehydrogenase (GAP) and methanol-utilizing alcohol oxidase (AOX1) promoters and expressed in Pichia pastoris SMD1168 strain. Constitutive expression under GAP resulted in cellular toxicity while AOX1 promoter controlled expression was stable. Variation in the levels of expression was observed among the transformant colonies with transformant #2 secreting up to ∼4 mg/L of GCSF. The molecular mass of the expressed GCSF in P. pastoris was ∼19.0 kDa. Quatitation of the expressed protein was carried out by a highly reproducible gel densitometric method. Effect of several operational and nutritional conditions was studied on GCSF production and the results suggest a general approach for increasing the yield of GCSF several folds (2- to 5-fold) over the standard conditions employed currently. Cultivation of the single-copy integrant in the chemically defined medium in a 5-L fermenter resulted in a volumetric productivity of ∼0.7 mg/L/h at the end of the induction phase, which was about 4-fold higher than attained in the shake flask. PMID:26410223

  8. Colony Collapse Disorder: A descriptive studey

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the last two winters, there have been large-scale, unexplained losses of managed honey bee (Apis mellifera L.) colonies in the United States. In the absence of a known cause, this syndrome was named Colony Collapse Disorder (CCD) because the main trait was a rapid loss of adult worker bees. We ...

  9. Assessing the Role of Environmental Conditions on Efficacy Rates of Heterorhabditis indica (Nematoda: Heterorhabditidae) for Controlling Aethina tumida (Coleoptera: Nitidulidae) in Honey Bee (Hymenoptera: Apidae) Colonies: a Citizen Science Approach.

    PubMed

    Hill, Elizabeth S; Smythe, Ashleigh B; Delaney, Deborah A

    2016-02-01

    Certain species of entomopathogenic nematodes, such as Heterorhabditis indica Poinar, Karunakar & David, have the potential to be effective controls for Aethina tumida (Murray), or small hive beetles, when applied to the soil surrounding honey bee (Apis mellifera L.) hives. Despite the efficacy of H. indica, beekeepers have struggled to use them successfully as a biocontrol. It is believed that the sensitivity of H. indica to certain environmental conditions is the primary reason for this lack of success. Although research has been conducted to explore the impact of specific environmental conditions--such as soil moisture or soil temperature-on entomopathogenic nematode infectivity, no study to date has taken a comprehensive approach that considers the impact of multiple environmental conditions simultaneously. In exploring this, a multivariate logistic regression model was used to determine what environmental conditions resulted in reductions of A. tumida populations in honey bee colonies. To obtain the sample sizes necessary to run a multivariate logistic regression, this study utilized citizen scientist beekeepers and their hives from across the mid-Atlantic region of the United States. Results suggest that soil moisture, soil temperatures, sunlight exposure, and groundcover contribute to the efficacy of H. indica in reducing A. tumida populations in A. mellifera colonies. The results of this study offer direction for future research on the environmental preferences of H. indica and can be used to educate beekeepers about methods for better utilizing H. indica as a biological control. PMID:26519500

  10. A convenient and robust edge detection method based on ant colony optimization

    NASA Astrophysics Data System (ADS)

    Liu, Xiaochen; Fang, Suping

    2015-10-01

    Edge detection is usually used as a preprocessing operation in many machine vision industrial applications. Recently, ant colony optimization (ACO) as a relatively new meta-heuristic approach has been used to tackle the edge detection problem. In this work, a convenient and robust method for edge detection based on ACO is proposed, which employs a new heuristic function, adopts a user-defined threshold in pheromone update process and provides a group of suitable parameter values. Experimental results clearly demonstrated the effectiveness of the proposed method, and at the same time, in the presence of noise, the proposed approach outperforms other two ACO-based edge detection techniques and four conventional edge detectors.

  11. Semivariogram Estimation Using Ant Colony Optimization and Ensemble Kriging Accounting for Parameter Uncertainty

    NASA Astrophysics Data System (ADS)

    Cardiff, M. A.; Kitanidis, P. K.

    2005-12-01

    In this presentation we revisit the problem of semivariogram estimation and present a modular, reusable, and encapsulated set of MATLAB programs that use a hybrid Ant Colony Optimization (ACO) heuristic to solve the "optimal fit" problem. Though the ACO heuristic involves a stochastic component, advantages of the heuristic over traditional gradient-search methods, like the Gauss-Newton method, include the ability to estimate model semivariogram parameters accurately without initial guesses input by the user. The ACO heuristic is also superiorly suited for strongly nonlinear optimization over spaces that may contain several local minima. The presentation will focus on the application of ACO to existing weighted least squares and restricted maximum likelihood estimation methods with a comparison of results. The presentation will also discuss parameter uncertainty, particularly in the context of restricted maximum likelihood and Bayesian methods. We compare the local linearized parameter estimates (or Cramer-Rao lower bounds) with modern Monte Carlo methods, such as acceptance-rejection. Finally, we present ensemble kriging in which conditional realizations are generated in a way that uncertainty in semi-variogram parameters is fully accounted for. Results for a variety of sample problems will be presented along with a discussion of solution accuracy and computational efficiency.

  12. Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization.

    PubMed

    Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri

    2013-09-01

    Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors. PMID:24065871

  13. Evaluation of Anaerobic Biofilm Reactor Kinetic Parameters Using Ant Colony Optimization

    PubMed Central

    Satya, Eswari Jujjavarapu; Venkateswarlu, Chimmiri

    2013-01-01

    Abstract Fixed bed reactors with naturally attached biofilms are increasingly used for anaerobic treatment of industry wastewaters due their effective treatment performance. The complex nature of biological reactions in biofilm processes often poses difficulty in analyzing them experimentally, and mathematical models could be very useful for their design and analysis. However, effective application of biofilm reactor models to practical problems suffers due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, an inverse modeling approach based on ant colony optimization is proposed and applied to estimate the kinetic and film thickness model parameters of wastewater treatment process in an anaerobic fixed bed biofilm reactor. Experimental data of pharmaceutical industry wastewater treatment process are used to determine the model parameters as a consequence of the solution of the rigorous mathematical models of the process. Results were evaluated for different modeling configurations derived from the combination of mathematical models, kinetic expressions, and optimization algorithms. Analysis of results showed that the two-dimensional mathematical model with Haldane kinetics better represents the pharmaceutical wastewater treatment in the biofilm reactor. The mathematical and kinetic modeling of this work forms a useful basis for the design and optimization of industry wastewater treating biofilm reactors. PMID:24065871

  14. 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. PMID:26868846

  15. Chemical ecology of bumble bees.

    PubMed

    Ayasse, Manfred; Jarau, Stefan

    2014-01-01

    Bumble bees are of major importance, ecologically and economically as pollinators in cool and temperate biomes and as model organisms for scientific research. Chemical signals and cues have been shown to play an outstanding role in intraspecific and interspecific communication systems within and outside of a bumble bee colony. In the present review we compile and critically assess the literature on the chemical ecology of bumble bees, including cuckoo bumble bees. The development of new and more sensitive analytical tools and improvements in sociogenetic methods significantly enhanced our knowledge about chemical compounds that mediate the regulation of reproduction in the social phase of colony development, about the interactions between host bumble bees and their social parasites, about pheromones involved in mating behavior, as well as about the importance of signals, cues and context-dependent learning in foraging behavior. Our review intends to stimulate new studies on the many unresolved questions concerning the chemical ecology of these fascinating insects. PMID:24160431

  16. Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

    PubMed

    Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

    2012-11-21

    We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials. PMID:23181297

  17. Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

    NASA Astrophysics Data System (ADS)

    Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

    2012-11-01

    We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

  18. Optic disc detection in color fundus images using ant colony optimization.

    PubMed

    Pereira, Carla; Gonçalves, Luís; Ferreira, Manuel

    2013-03-01

    Diabetic retinopathy has been revealed as the most common cause of blindness among people of working age in developed countries. However, loss of vision could be prevented by an early detection of the disease and, therefore, by a regular screening program to detect retinopathy. Due to its characteristics, the digital color fundus photographs have been the easiest way to analyze the eye fundus. An important prerequisite for automation is the segmentation of the main anatomical features in the image, particularly the optic disc. Currently, there are many works reported in the literature with the purpose of detecting and segmenting this anatomical structure. Though, none of them performs as needed, especially when dealing with images presenting pathologies and a great variability. Ant colony optimization (ACO) is an optimization algorithm inspired by the foraging behavior of some ant species that has been applied in image processing with different purposes. In this paper, this algorithm preceded by anisotropic diffusion is used for optic disc detection in color fundus images. Experimental results demonstrate the good performance of the proposed approach as the optic disc was detected in most of all the images used, even in the images with great variability. PMID:23160896

  19. Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

    NASA Astrophysics Data System (ADS)

    Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

    2010-10-01

    To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

  20. Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

    PubMed Central

    Ozekes, Serhat; Gultekin, Selahattin; Tarhan, Nevzat

    2014-01-01

    Objective Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new approach for feature subset selection. Methods Feature selection process using ant colony optimization (ACO) for 6 channel pre-treatment electroencephalogram (EEG) data from theta and delta frequency bands is combined with back propagation neural network (BPNN) classification method for 147 major depressive disorder (MDD) subjects. Results BPNN classified R subjects with 91.83% overall accuracy and 95.55% subjects detection sensitivity. Area under ROC curve (AUC) value after feature selection increased from 0.8531 to 0.911. The features selected by the optimization algorithm were Fp1, Fp2, F7, F8, F3 for theta frequency band and eliminated 7 features from 12 to 5 feature subset. Conclusion ACO feature selection algorithm improves the classification accuracy of BPNN. Using other feature selection algorithms or classifiers to compare the performance for each approach is important to underline the validity and versatility of the designed combination. PMID:25110496

  1. Integrating geological uncertainty in long-term open pit mine production planning by ant colony optimization

    NASA Astrophysics Data System (ADS)

    Gilani, Seyed-Omid; Sattarvand, Javad

    2016-02-01

    Meeting production targets in terms of ore quantity and quality is critical for a successful mining operation. In-situ grade uncertainty causes both deviations from production targets and general financial deficits. A new stochastic optimization algorithm based on ant colony optimization (ACO) approach is developed herein to integrate geological uncertainty described through a series of the simulated ore bodies. Two different strategies were developed based on a single predefined probability value (Prob) and multiple probability values (Pro bnt), respectively in order to improve the initial solutions that created by deterministic ACO procedure. Application at the Sungun copper mine in the northwest of Iran demonstrate the abilities of the stochastic approach to create a single schedule and control the risk of deviating from production targets over time and also increase the project value. A comparison between two strategies and traditional approach illustrates that the multiple probability strategy is able to produce better schedules, however, the single predefined probability is more practical in projects requiring of high flexibility degree.

  2. 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.

  3. Special Issue: Honey Bee Viruses

    PubMed Central

    Gisder, Sebastian; Genersch, Elke

    2015-01-01

    Pollination of flowering plants is an important ecosystem service provided by wild insect pollinators and managed honey bees. Hence, losses and declines of pollinating insect species threaten human food security and are of major concern not only for apiculture or agriculture but for human society in general. Honey bee colony losses and bumblebee declines have attracted intensive research interest over the last decade and although the problem is far from being solved we now know that viruses are among the key players of many of these bee losses and bumblebee declines. With this special issue on bee viruses we, therefore, aimed to collect high quality original papers reflecting the current state of bee virus research. To this end, we focused on newly discovered viruses (Lake Sinai viruses, bee macula-like virus), or a so far neglected virus species (Apis mellifera filamentous virus), and cutting edge technologies (mass spectrometry, RNAi approach) applied in the field. PMID:26702462

  4. Honey bee pathology: current threats to honey bees and beekeeping.

    PubMed

    Genersch, Elke

    2010-06-01

    Managed honey bees are the most important commercial pollinators of those crops which depend on animal pollination for reproduction and which account for 35% of the global food production. Hence, they are vital for an economic, sustainable agriculture and for food security. In addition, honey bees also pollinate a variety of wild flowers and, therefore, contribute to the biodiversity of many ecosystems. Honey and other hive products are, at least economically and ecologically rather, by-products of beekeeping. Due to this outstanding role of honey bees, severe and inexplicable honey bee colony losses, which have been reported recently to be steadily increasing, have attracted much attention and stimulated many research activities. Although the phenomenon "decline of honey bees" is far from being finally solved, consensus exists that pests and pathogens are the single most important cause of otherwise inexplicable colony losses. This review will focus on selected bee pathogens and parasites which have been demonstrated to be involved in colony losses in different regions of the world and which, therefore, are considered current threats to honey bees and beekeeping. PMID:20401479

  5. A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors

    PubMed Central

    2011-01-01

    Background Fluorescent protein (FP)-based biosensors based on the principle of intramolecular Förster resonance energy transfer (FRET) enable the visualization of a variety of biochemical events in living cells. The construction of these biosensors requires the genetic insertion of a judiciously chosen molecular recognition element between two distinct hues of FP. When the molecular recognition element interacts with the analyte of interest and undergoes a conformational change, the ratiometric emission of the construct is altered due to a change in the FRET efficiency. The sensitivity of such biosensors is proportional to the change in ratiometric emission, and so there is a pressing need for methods to maximize the ratiometric change of existing biosensor constructs in order to increase the breadth of their utility. Results To accelerate the development and optimization of improved FRET-based biosensors, we have developed a method for function-based high-throughput screening of biosensor variants in colonies of Escherichia coli. We have demonstrated this technology by undertaking the optimization of a biosensor for detection of methylation of lysine 27 of histone H3 (H3K27). This effort involved the construction and screening of 3 distinct libraries: a domain library that included several engineered binding domains isolated by phage-display; a lower-resolution linker library; and a higher-resolution linker library. Conclusion Application of this library screening methodology led to the identification of an optimized H3K27-trimethylation biosensor that exhibited an emission ratio change (66%) that was 2.3 × improved relative to that of the initially constructed biosensor (29%). PMID:22074568

  6. Changes in Honey Bee (Hymenoptera: Apidae) Colony Swarming and Survival Pre- and Post- Arrival of Varroa destructor (Acari: Varroidae) in Louisiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The impact of Varroa destructor Anderson and Trueman on colonies of Apis mellifera L. in southern Louisiana was evaluated by analyzing changes in swarming and longevity of colonies for 17 years. Swarming rates were calculated from yearly captures of swarms in bait hives placed in five areas of Loui...

  7. Short-term fumigation of honey bee (Hymenoptera: Apidae) colonies with formic and acetic acids for the control of Varroa destructor (Acari: Varroidae).

    PubMed

    vanEngelsdorp, Dennis; Underwood, Robyn M; Cox-Foster, Diana L

    2008-04-01

    Controlling populations of varroa mites is crucial for the survival of the beekeeping industry. Many treatments exist, and all are designed to kill mites on adult bees. Because the majority of mites are found under capped brood, most treatments are designed to deliver active ingredients over an extended period to control mites on adult bees, as developing bees and mites emerge. In this study, a 17-h application of 50% formic acid effectively killed mites in capped worker brood and on adult bees without harming queens or uncapped brood. Neither acetic acid nor a combined treatment of formic and acetic acids applied to the West Virginia formic acid fumigator was as effective as formic acid alone in controlling varroa mites. In addition, none of the treatments tested in late summer had an effect on the late-season prevalence of deformed wing virus. The short-term formic acid treatment killed > 60% of varroa mites in capped worker brood; thus, it is a promising tool for beekeepers, especially when such treatments are necessary during the nectar flow. PMID:18459386

  8. Nest Initiation in Three North American Species of Bumble Bees (Bombus): Effects of Gyne Number and Worker Helpers on Colony Size and Establishment Success

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Three species of bumble bees, Bombus appositus, B. bifarius, and B. centralis (Hymenoptera: Apidae) were evaluated for nest initiation success under three sets of initial conditions. In the spring, queens of each species were caught in the wild and introduced to nest boxes in one of three ways. Qu...

  9. 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

  10. 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. PMID:25136678

  11. A multipath routing protocol based on clustering and ant colony optimization for wireless sensor networks.

    PubMed

    Yang, Jing; Xu, Mai; Zhao, Wei; Xu, Baoguo

    2010-01-01

    For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively. PMID:22399890

  12. Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

    PubMed

    Li, Ke; Chen, Peng

    2011-01-01

    Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks. PMID:22163833

  13. Ant Colony Optimization for Mapping, Scheduling and Placing in Reconfigurable Systems

    SciTech Connect

    Ferrandi, Fabrizio; Lanzi, Pier Luca; Pilato, Christian; Sciuto, Donatella; Tumeo, Antonino

    2013-06-24

    Modern heterogeneous embedded platforms, com- posed of several digital signal, application specific and general purpose processors, also include reconfigurable devices support- ing partial dynamic reconfiguration. These devices can change the behavior of some of their parts during execution, allowing hardware acceleration of more sections of the applications. Never- theless, partial dynamic reconfiguration imposes severe overheads in terms of latency. For such systems, a critical part of the design phase is deciding on which processing elements (mapping) and when (scheduling) executing a task, but also how to place them on the reconfigurable device to guarantee the most efficient reuse of the programmable logic. In this paper we propose an algorithm based on Ant Colony Optimization (ACO) that simultaneously executes the scheduling, the mapping and the linear placing of tasks, hiding reconfiguration overheads through prefetching. Our heuristic gradually constructs solutions and then searches around the best ones, cutting out non-promising areas of the design space. We show how to consider the partial dynamic reconfiguration constraints in the scheduling, placing and mapping problems and compare our formulation to other heuristics that address the same problems. We demonstrate that our proposal is more general and robust, and finds better solutions (16.5% in average) with respect to competing solutions.

  14. A modified ant colony optimization to solve multi products inventory routing problem

    NASA Astrophysics Data System (ADS)

    Wong, Lily; Moin, Noor Hasnah

    2014-07-01

    This study considers a one-to-many inventory routing problem (IRP) network consisting of a manufacturer that produces multi products to be transported to many geographically dispersed customers. We consider a finite horizon where a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, transport products from the warehouse to meet the demand specified by the customers in each period. The demand for each product is deterministic and time varying and each customer requests a distinct product. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount on inventory and to construct a delivery schedule that minimizes both the total transportation and inventory holding costs while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer solution) for each problem considered. We propose a modified ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. ACO performs better on large instances compared to the upper bound.

  15. Honey Bee Hemocyte Profiling by Flow Cytometry

    PubMed Central

    Marringa, William J.; Krueger, Michael J.; Burritt, Nancy L.; Burritt, James B.

    2014-01-01

    Multiple stress factors in honey bees are causing loss of bee colonies worldwide. Several infectious agents of bees are believed to contribute to this problem. The mechanisms of honey bee immunity are not completely understood, in part due to limited information about the types and abundances of hemocytes that help bees resist disease. Our study utilized flow cytometry and microscopy to examine populations of hemolymph particulates in honey bees. We found bee hemolymph includes permeabilized cells, plasmatocytes, and acellular objects that resemble microparticles, listed in order of increasing abundance. The permeabilized cells and plasmatocytes showed unexpected differences with respect to properties of the plasma membrane and labeling with annexin V. Both permeabilized cells and plasmatocytes failed to show measurable mitochondrial membrane potential by flow cytometry using the JC-1 probe. Our results suggest hemolymph particulate populations are dynamic, revealing significant differences when comparing individual hive members, and when comparing colonies exposed to diverse conditions. Shifts in hemocyte populations in bees likely represent changing conditions or metabolic differences of colony members. A better understanding of hemocyte profiles may provide insight into physiological responses of honey bees to stress factors, some of which may be related to colony failure. PMID:25285798

  16. PC BEEPOP - AN ECTOXICOLOGICAL SIMULATION MODEL FOR HONEY BEE POPULATIONS

    EPA Science Inventory

    PC BEEPOP is a computer model that simulates honey bee colony population dynamics. he model consists of a feedback system of interdependent elements, including colony condition, environmental variability, and contaminant exposures. t includes a mortality module (BEEKILL) and a ch...

  17. Recursive Ant Colony Global Optimization: a new technique for the inversion of geophysical data

    NASA Astrophysics Data System (ADS)

    Gupta, D. K.; Gupta, J. P.; Arora, Y.; Singh, U. K.

    2011-12-01

    We present a new method called Recursive Ant Colony Global Optimization (RACO) technique, a modified form of general ACO, which can be used to find the best solutions to inversion problems in geophysics. RACO simulates the social behaviour of ants to find the best path between the nest and the food source. A new term depth has been introduced, which controls the extent of recursion. A selective number of cities get qualified for the successive depth. The results of one depth are used to construct the models for the next depth and the range of values for each of the parameters is reduced without any change to the number of models. The three additional steps performed after each depth, are the pheromone tracking, pheromone updating and city selection. One of the advantages of RACO over ACO is that if a problem has multiple solutions, then pheromone accumulation will take place at more than one city thereby leading to formation of multiple nested ACO loops within the ACO loop of the previous depth. Also, while the convergence of ACO is almost linear, RACO shows exponential convergence and hence is faster than the ACO. RACO proves better over some other global optimization techniques, as it does not require any initial values to be assigned to the parameters function. The method has been tested on some mathematical functions, synthetic self-potential (SP) and synthetic gravity data. The obtained results reveal the efficiency and practicability of the method. The method is found to be efficient enough to solve the problems of SP and gravity anomalies due to a horizontal cylinder, a sphere, an inclined sheet and multiple idealized bodies buried inside the earth. These anomalies with and without noise were inverted using the RACO algorithm. The obtained results were compared with those obtained from the conventional methods and it was found that RACO results are more accurate. Finally this optimization technique was applied to real field data collected over the Surda

  18. Antiviral Defense Mechanisms in Honey Bees

    PubMed Central

    Brutscher, Laura M.; Daughenbaugh, Katie F.; Flenniken, Michelle L.

    2015-01-01

    Honey bees are significant pollinators of agricultural crops and other important plant species. High annual losses of honey bee colonies in North America and in some parts of Europe have profound ecological and economic implications. Colony losses have been attributed to multiple factors including RNA viruses, thus understanding bee antiviral defense mechanisms may result in the development of strategies that mitigate colony losses. Honey bee antiviral defense mechanisms include RNA-interference, pathogen-associated molecular pattern (PAMP) triggered signal transduction cascades, and reactive oxygen species generation. However, the relative importance of these and other pathways is largely uncharacterized. Herein we review the current understanding of honey bee antiviral defense mechanisms and suggest important avenues for future investigation. PMID:26273564

  19. [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. PMID:24059192

  20. Ant Colony Optimization detects anomalous aerosol variations associated with the Chile earthquake of 27 February 2010

    NASA Astrophysics Data System (ADS)

    Akhoondzadeh, M.

    2015-04-01

    This study attempts to acknowledge AOD (Aerosol Optical Depth) seismo-atmospheric anomalies around the time of the Chile earthquake of 27 February 2010. Since AOD precursor alone might not be useful as an accurate and stand alone criteria for the earthquake anomalies detection, therefore it would be more appropriate to use and integrate a variety of other precursors to reduce the uncertainty of potential detected seismic anomalies. To achieve this aim, eight other precursors including GPS-TEC (Total Electron Content), H+, He+, O+ densities (cm-3) and total ion density (cm-3) from IAP experiment, electron density (cm-3) and electron temperature (K) from ISL experiment and VLF electric field from ICE experiment have been surveyed to detect unusual variations around the time and location of the Chile earthquake. Moreover, three methods including Interquartile, ANN (Artificial Neural Network) and ACO (Ant Colony Optimization) have been implemented to observe the discord patterns in time series of the AOD precursor. All of the methods indicate a clear abnormal increase in time series of AOD data, 2 days prior to event. Also a striking anomaly is observed in time series of TEC data, 6 days preceding the earthquake. Using the analysis of ICE data, a prominent anomaly is detected in the VLF electric field measurement, 1 day before the earthquake. The time series of H+, He+, O+ densities (cm-3) and total ion density (cm-3) from IAP and also electron density (cm-3) and electron temperature (K) from ISL, illustrate the abnormal behaviors, 3 days before the event. It should be noted that the acknowledgment of the different lead times in outcomes of the implemented precursors strictly depend on the proper understanding of Lithosphere-Atmosphere-Ionosphere (LAI) coupling mechanism during seismic activities. It means that these different anomalies dates between LAI precursors can be a hint of truthfulness of multi-precursors analysis.

  1. Estimating Soil Thermal Properties from Land Surface Temperature Measurements Using Ant Colony Optimization Approach

    NASA Astrophysics Data System (ADS)

    Zamani, K.; Madadgar, S.; Bateni, S.

    2012-12-01

    Soil thermal conductivity and volumetric heat capacity are crucial parameters in land surface hydrology and hydro-climatology. There are several techniques (e.g., heat-source probe, borehole relaxation, and heat-dissipation sensors) for in situ measurement of soil thermal properties. These methods are generally expensive and labor-intensive. In a departure with these in situ approaches, regression-based techniques have been developed to estimate soil thermal properties. They require several input variables such as soil texture, water content, organic content, etc, which are typically unavailable. To overcome the aforementioned drawbacks of these methods, a new approach is developed to estimate soil thermal properties from the sequences of land surface temperature (LST) measurements. Herein, LST measurements are the only required input to estimate soil thermal properties. An objective function describing the misfit between simulated LST from the heat diffusion equation and the corresponding observations is minimized using Ant Colony Optimization (ACO) technique in order to find the optimum values for soil thermal properties. The performance of model is initially tested on a single-layer (homogeneous) soil setup and then a generalized scheme of the multi-layer soil column is explored with two, five and ten of equal thickness sub-layers to account for inhomogeneity in the soil slab. The developed model is applied to the First International Satellite Land Surface Climatology (ISLSCP) Field Experiment in summer of 1987 and 1988. The retrieved soil thermal properties from ACO are used to solve the heat diffusion equation and estimate soil temperature within the soil slab. The soil temperature estimates show relatively good agreement with observations, suggesting that the proposed technique can reliably estimate soil thermal properties.

  2. Ant Colony Optimization Algorithm for Interpretable Bayesian Classifiers Combination: Application to Medical Predictions

    PubMed Central

    Bouktif, Salah; Hanna, Eileen Marie; Zaki, Nazar; Khousa, Eman Abu

    2014-01-01

    Prediction and classification techniques have been well studied by machine learning researchers and developed for several real-word problems. However, the level of acceptance and success of prediction models are still below expectation due to some difficulties such as the low performance of prediction models when they are applied in different environments. Such a problem has been addressed by many researchers, mainly from the machine learning community. A second problem, principally raised by model users in different communities, such as managers, economists, engineers, biologists, and medical practitioners, etc., is the prediction models’ interpretability. The latter is the ability of a model to explain its predictions and exhibit the causality relationships between the inputs and the outputs. In the case of classification, a successful way to alleviate the low performance is to use ensemble classiers. It is an intuitive strategy to activate collaboration between different classifiers towards a better performance than individual classier. Unfortunately, ensemble classifiers method do not take into account the interpretability of the final classification outcome. It even worsens the original interpretability of the individual classifiers. In this paper we propose a novel implementation of classifiers combination approach that does not only promote the overall performance but also preserves the interpretability of the resulting model. We propose a solution based on Ant Colony Optimization and tailored for the case of Bayesian classifiers. We validate our proposed solution with case studies from medical domain namely, heart disease and Cardiotography-based predictions, problems where interpretability is critical to make appropriate clinical decisions. Availability The datasets, Prediction Models and software tool together with supplementary materials are available at http://faculty.uaeu.ac.ae/salahb/ACO4BC.htm. PMID:24498276

  3. 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.

  4. Binary Bees Algorithm - bioinspiration from the foraging mechanism of honeybees to optimize a multiobjective multidimensional assignment problem

    NASA Astrophysics Data System (ADS)

    Xu, Shuo; Ji, Ze; Truong Pham, Duc; Yu, Fan

    2011-11-01

    The simultaneous mission assignment and home allocation for hospital service robots studied is a Multidimensional Assignment Problem (MAP) with multiobjectives and multiconstraints. A population-based metaheuristic, the Binary Bees Algorithm (BBA), is proposed to optimize this NP-hard problem. Inspired by the foraging mechanism of honeybees, the BBA's most important feature is an explicit functional partitioning between global search and local search for exploration and exploitation, respectively. Its key parts consist of adaptive global search, three-step elitism selection (constraint handling, non-dominated solutions selection, and diversity preservation), and elites-centred local search within a Hamming neighbourhood. Two comparative experiments were conducted to investigate its single objective optimization, optimization effectiveness (indexed by the S-metric and C-metric) and optimization efficiency (indexed by computational burden and CPU time) in detail. The BBA outperformed its competitors in almost all the quantitative indices. Hence, the above overall scheme, and particularly the searching history-adapted global search strategy was validated.

  5. The habitat disruption induces immune-suppression and oxidative stress in honey bees

    PubMed Central

    Morimoto, Tomomi; Kojima, Yuriko; Toki, Taku; Komeda, Yayoi; Yoshiyama, Mikio; Kimura, Kiyoshi; Nirasawa, Keijiro; Kadowaki, Tatsuhiko

    2011-01-01

    The honey bee is a major insect used for pollination of many commercial crops worldwide. Although the use of honey bees for pollination can disrupt the habitat, the effects on their physiology have never been determined. Recently, honey bee colonies have often collapsed when introduced in greenhouses for pollination in Japan. Thus, suppressing colony collapses and maintaining the number of worker bees in the colonies is essential for successful long-term pollination in greenhouses and recycling of honey bee colonies. To understand the physiological states of honey bees used for long-term pollination in greenhouses, we characterized their gene expression profiles by microarray. We found that the greenhouse environment changes the gene expression profiles and induces immune-suppression and oxidative stress in honey bees. In fact, the increase of the number of Nosema microsporidia and protein carbonyl content was observed in honey bees during pollination in greenhouses. Thus, honey bee colonies are likely to collapse during pollination in greenhouses when heavily infested with pathogens. Degradation of honey bee habitat by changing the outside environment of the colony, during pollination services for example, imposes negative impacts on honey bees. Thus, worldwide use of honey bees for crop pollination in general could be one of reasons for the decline of managed honey bee colonies. PMID:22393496

  6. Assessing Patterns of Admixture and Ancestry in Canadian Honey Bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Canada has a large beekeeping industry comprised of 8483 beekeepers managing 672094 23 colonies. Canadian honey bees, like all honey bees in the New World, originate from centuries of importation of predominately European honey bees, but their precise ancestry remains unknown. There have been no i...

  7. Parasite pressures on feral honey bees (Apis mellifera sp.).

    PubMed

    Thompson, Catherine E; Biesmeijer, Jacobus C; Allnutt, Theodore R; Pietravalle, Stéphane; Budge, Giles E

    2014-01-01

    Feral honey bee populations have been reported to be in decline due to the spread of Varroa destructor, an ectoparasitic mite that when left uncontrolled leads to virus build-up and colony death. While pests and diseases are known causes of large-scale managed honey bee colony losses, no studies to date have considered the wider pathogen burden in feral colonies, primarily due to the difficulty in locating and sampling colonies, which often nest in inaccessible locations such as church spires and tree tops. In addition, little is known about the provenance of feral colonies and whether they represent a reservoir of Varroa tolerant material that could be used in apiculture. Samples of forager bees were collected from paired feral and managed honey bee colonies and screened for the presence of ten honey bee pathogens and pests using qPCR. Prevalence and quantity was similar between the two groups for the majority of pathogens, however feral honey bees contained a significantly higher level of deformed wing virus than managed honey bee colonies. An assessment of the honey bee race was completed for each colony using three measures of wing venation. There were no apparent differences in wing morphometry between feral and managed colonies, suggesting feral colonies could simply be escapees from the managed population. Interestingly, managed honey bee colonies not treated for Varroa showed similar, potentially lethal levels of deformed wing virus to that of feral colonies. The potential for such findings to explain the large fall in the feral population and the wider context of the importance of feral colonies as potential pathogen reservoirs is discussed. PMID:25126840

  8. First Complete Genome Sequence of Chronic Bee Paralysis Virus Isolated from Honey Bees (Apis mellifera) in China.

    PubMed

    Li, Beibei; Hou, Chunsheng; Deng, Shuai; Zhang, Xuefeng; Chu, Yanna; Yuan, Chunying; Diao, Qingyun

    2016-01-01

    Chronic bee paralysis virus (CBPV) is a serious viral disease affecting adult bees. We report here the complete genome sequence of CBPV, which was isolated from a honey bee colony with the symptom of severe crawling. The genome of CBPV consists of two segments, RNA 1 and RNA 2, containing respective overlapping fragments. PMID:27491983

  9. First Complete Genome Sequence of Chronic Bee Paralysis Virus Isolated from Honey Bees (Apis mellifera) in China

    PubMed Central

    Li, Beibei; Deng, Shuai; Zhang, Xuefeng; Chu, Yanna; Yuan, Chunying

    2016-01-01

    Chronic bee paralysis virus (CBPV) is a serious viral disease affecting adult bees. We report here the complete genome sequence of CBPV, which was isolated from a honey bee colony with the symptom of severe crawling. The genome of CBPV consists of two segments, RNA 1 and RNA 2, containing respective overlapping fragments. PMID:27491983

  10. The Plight of the Honey Bee

    ERIC Educational Resources Information Center

    Hockridge, Emma

    2010-01-01

    The decline of colonies of honey bees across the world is threatening local plant biodiversity and human food supplies. Neonicotinoid pesticides have been implicated as a major cause of the problem and are banned or suspended in several countries. Other factors could also be lowering the resistance of bees to opportunist infections by, for…

  11. The problem of disease when domesticating bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    When disease strikes a hive of bees, it can devastate the colony and spread to the entire beekeeping operation. All bees are susceptible to diseases, and when they are domesticated, their population densities increase to suit human needs, making them more susceptible. Most attempts at disease contro...

  12. Resin collection and social immunity in honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We determined if the use of resins, complex plant secretions with diverse antimicrobial properties, acts as a colony-level immune defense by honey bees. Colonies were enriched with extracts of Brazilian or Minnesotan propolis (a bee mixture of resins and wax) or were left as controls. We measured ge...

  13. A critical number of workers in a honeybee colony triggers investment in reproduction

    NASA Astrophysics Data System (ADS)

    Smith, Michael L.; Ostwald, Madeleine M.; Loftus, J. Carter; Seeley, Thomas D.

    2014-10-01

    Social insect colonies, like individual organisms, must decide as they develop how to allocate optimally their resources among survival, growth, and reproduction. Only when colonies reach a certain state do they switch from investing purely in survival and growth to investing also in reproduction. But how do worker bees within a colony detect that their colony has reached the state where it is adaptive to begin investing in reproduction? Previous work has shown that larger honeybee colonies invest more in reproduction (i.e., the production of drones and queens), however, the term `larger' encompasses multiple colony parameters including number of adult workers, size of the nest, amount of brood, and size of the honey stores. These colony parameters were independently increased in this study to test which one(s) would increase a colony's investment in reproduction via males. This was assayed by measuring the construction of drone comb, the special type of comb in which drones are reared. Only an increase in the number of workers stimulated construction of drone comb. Colonies with over 4,000 workers began building drone comb, independent of the other colony parameters. These results show that attaining a critical number of workers is the key parameter for honeybee colonies to start to shift resources towards reproduction. These findings are relevant to other social systems in which a group's members must adjust their behavior as a function of the group's size.

  14. A critical number of workers in a honeybee colony triggers investment in reproduction.

    PubMed

    Smith, Michael L; Ostwald, Madeleine M; Loftus, J Carter; Seeley, Thomas D

    2014-10-01

    Social insect colonies, like individual organisms, must decide as they develop how to allocate optimally their resources among survival, growth, and reproduction. Only when colonies reach a certain state do they switch from investing purely in survival and growth to investing also in reproduction. But how do worker bees within a colony detect that their colony has reached the state where it is adaptive to begin investing in reproduction? Previous work has shown that larger honeybee colonies invest more in reproduction (i.e., the production of drones and queens), however, the term 'larger' encompasses multiple colony parameters including number of adult workers, size of the nest, amount of brood, and size of the honey stores. These colony parameters were independently increased in this study to test which one(s) would increase a colony's investment in reproduction via males. This was assayed by measuring the construction of drone comb, the special type of comb in which drones are reared. Only an increase in the number of workers stimulated construction of drone comb. Colonies with over 4,000 workers began building drone comb, independent of the other colony parameters. These results show that attaining a critical number of workers is the key parameter for honeybee colonies to start to shift resources towards reproduction. These findings are relevant to other social systems in which a group's members must adjust their behavior as a function of the group's size. PMID:25142633

  15. Molecular genetic analysis of Varroa destructor mites in brood, fallen injured mites and worker bee longevity in honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Two important traits that contribute to honey bee (Apis mellifera) colony survival are resistance to Varroa destructor and longevity of worker bees. We investigated the relationship between a panel of single nucleotide polymorphism (SNP) markers and three phenotypic measurements of colonies: a) perc...

  16. Preliminary observations of autumn feeding of USDA-ARS Russian honey bees to enhance performance during almond pollination

    Technology Transfer Automated Retrieval System (TEKTRAN)

    populous than Italian colonies and thus have less flight activity. We attempted to increase bee populations by feeding two pounds of bee-collected pollen in November to Russian and Italian colonies (n=16 each) and comparing these to unfed colonies. Flight activity of colonies in the four treatment...

  17. Bee poison

    MedlinePlus

    ... is caused by a sting from a bee, wasp , or yellow jacket. This article is for information ... anywhere in the United States. Poisonous Ingredient Bee, wasp, and yellow jacket stings contain a substance called ...

  18. Application of continuous monitoring of honeybee colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Monitoring physical variables associated with honey bee colonies, including weight, temperature, humidity, respiratory gases, vibration, acoustics and forager traffic, in a continuous manner is becoming feasible for most researchers as the cost and size of electronic sensors and dataloggers decrease...

  19. Seed coating with a neonicotinoid insecticide negatively affects wild bees.

    PubMed

    Rundlöf, Maj; Andersson, Georg K S; Bommarco, Riccardo; Fries, Ingemar; Hederström, Veronica; Herbertsson, Lina; Jonsson, Ove; Klatt, Björn K; Pedersen, Thorsten R; Yourstone, Johanna; Smith, Henrik G

    2015-05-01

    Understanding the effects of neonicotinoid insecticides on bees is vital because of reported declines in bee diversity and distribution and the crucial role bees have as pollinators in ecosystems and agriculture. Neonicotinoids are suspected to pose an unacceptable risk to bees, partly because of their systemic uptake in plants, and the European Union has therefore introduced a moratorium on three neonicotinoids as seed coatings in flowering crops that attract bees. The moratorium has been criticized for being based on weak evidence, particularly because effects have mostly been measured on bees that have been artificially fed neonicotinoids. Thus, the key question is how neonicotinoids influence bees, and wild bees in particular, in real-world agricultural landscapes. Here we show that a commonly used insecticide seed coating in a flowering crop can have serious consequences for wild bees. In a study with replicated and matched landscapes, we found that seed coating with Elado, an insecticide containing a combination of the neonicotinoid clothianidin and the non-systemic pyrethroid β-cyfluthrin, applied to oilseed rape seeds, reduced wild bee density, solitary bee nesting, and bumblebee colony growth and reproduction under field conditions. Hence, such insecticidal use can pose a substantial risk to wild bees in agricultural landscapes, and the contribution of pesticides to the global decline of wild bees may have been underestimated. The lack of a significant response in honeybee colonies suggests that reported pesticide effects on honeybees cannot always be extrapolated to wild bees. PMID:25901681

  20. The plight of the bees

    USGS Publications Warehouse

    Spivak, Marla; Mader, Eric; Vaughan, Mace; Euliss, Ned H.

    2011-01-01

    Some environmental issues polarize people, producing weary political stalemates of indecision and inaction. Others, however, grab hold of our most primeval instincts, causing us to reach deeply into our memories of childhood, and our first direct experiences with nature: the bumble bee nest we poked at with a stick; the man at the county fair with the bee beard. Those memories expand backward in time to our barefoot ancestors who climbed trees and robbed honey. They help define the human experience and provide context to our own place in the world.And so the plight of the bees strikes a common chord. For a brief moment simple matters of politics, economics, and nationality seem irrelevant. Colony collapse disorder, the name for the syndrome causing honey bees (Apis mellifera) to suddenly and mysteriously disappear from their hives - thousands of individual worker bees literally flying off to die - captured public consciousness when it was first named in 2007 (1). Since then, the story of vanishing honey bees has become ubiquitous in popular consciousness - driving everything from ice cream marketing campaigns to plots for The Simpsons. The untold story is that these hive losses are simply a capstone to more than a half-century of more prosaic day-to-day losses that beekeepers already faced from parasites, diseases, poor nutrition, and pesticide poisoning (2). The larger story still is that while honey bees are charismatic and important to agriculture, other important bees are also suffering, and in some cases their fates are far worse (3). These other bees are a subset of the roughly 4000 species of wild bumble bees (Bombus), leafcutter bees (Megachile), and others that are native to North America. While the honey bee was originally imported from Europe by colonists in the early 17th century, it is these native bees that have evolved with our local ecosystems, and, along with honey bees, are valuable crop pollinators. People want to know why bees are dying and how

  1. Optimisation of a honeybee-colony's energetics via social learning based on queuing delays

    NASA Astrophysics Data System (ADS)

    Thenius, Ronald; Schmickl, Thomas; Crailsheim, Karl

    2008-06-01

    Natural selection shaped the foraging-related processes of honeybees in such a way that a colony can react to changing environmental conditions optimally. To investigate this complex dynamic social system, we developed a multi-agent model of the nectar flow inside and outside of a honeybee colony. In a honeybee colony, a temporal caste collects nectar in the environment. These foragers bring their harvest into the colony, where they unload their nectar loads to one or more storer bees. Our model predicts that a cohort of foragers, collecting nectar from a single nectar source, is able to detect changes in quality in other food sources they have never visited, via the nectar processing system of the colony. We identified two novel pathways of forager-to-forager communication. Foragers can gain information about changes in the nectar flow in the environment via changes in their mean waiting time for unloadings and the number of experienced multiple unloadings. This way two distinct groups of foragers that forage on different nectar sources and that never communicate directly can share information via a third cohort of worker bees. We show that this noisy and loosely knotted social network allows a colony to perform collective information processing, so that a single forager has all necessary information available to be able to 'tune' its social behaviour, like dancing or dance-following. This way the net nectar gain of the colony is increased.

  2. Protein folding in hydrophobic-polar lattice model: a flexible ant-colony optimization approach.

    PubMed

    Hu, Xiao-Min; Zhang, Jun; Xiao, Jing; Li, Yun

    2008-01-01

    This paper proposes a flexible ant colony (FAC) algorithm for solving protein folding problems based on the hydrophobic-polar square lattice model. Collaborations of novel pheromone and heuristic strategies in the proposed algorithm make it more effective in predicting structures of proteins compared with other state-of-the-art algorithms. PMID:18537736

  3. Colony Collapse Disorder: A Descriptive Study

    PubMed Central

    vanEngelsdorp, Dennis; Evans, Jay D.; Saegerman, Claude; Mullin, Chris; Haubruge, Eric; Nguyen, Bach Kim; Frazier, Maryann; Frazier, Jim; Cox-Foster, Diana; Chen, Yanping; Underwood, Robyn; Tarpy, David R.; Pettis, Jeffery S.

    2009-01-01

    Background Over the last two winters, there have been large-scale, unexplained losses of managed honey bee (Apis mellifera L.) colonies in the United States. In the absence of a known cause, this syndrome was named Colony Collapse Disorder (CCD) because the main trait was a rapid loss of adult worker bees. We initiated a descriptive epizootiological study in order to better characterize CCD and compare risk factor exposure between populations afflicted by and not afflicted by CCD. Methods and Principal Findings Of 61 quantified variables (including adult bee physiology, pathogen loads, and pesticide levels), no single measure emerged as a most-likely cause of CCD. Bees in CCD colonies had higher pathogen loads and were co-infected with a greater number of pathogens than control populations, suggesting either an increased exposure to pathogens or a reduced resistance of bees toward pathogens. Levels of the synthetic acaricide coumaphos (used by beekeepers to control the parasitic mite Varroa destructor) were higher in control colonies than CCD-affected colonies. Conclusions/Significance This is the first comprehensive survey of CCD-affected bee populations that suggests CCD involves an interaction between pathogens and other stress factors. We present evidence that this condition is contagious or the result of exposure to a common risk factor. Potentially important areas for future hypothesis-driven research, including the possible legacy effect of mite parasitism and the role of honey bee resistance to pesticides, are highlighted. PMID:19649264

  4. 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. PMID:26878124

  5. Virus infections in Brazilian honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Brazilian honey bees are famously resistant to disease, perhaps because of long-term introgression from Apis mellifera subsp. scutellata. Recently, colony losses were observed in the Altinópolis region of southeastern Brazil. We sampled 200 colonies from this region for Israeli acute paralysis vir...

  6. Optimization of method for zinc analysis in several bee products on renewable mercury film silver based electrode.

    PubMed

    Opoka, Włodzimierz; Szlósarczyk, Marek; Maślanka, Anna; Piech, Robert; Baś, Bogusław; Włodarczyk, Edyta; Krzek, Jan

    2013-01-01

    Zinc is an interesting target for detection as it is one of the elements necessary for the proper functioning of the human body, its excess and deficiency can cause several symptoms. Several techniques including electrochemistry have been developed but require laboratory equipment, preparative steps and mercury or complex working electrodes. We here described the development of a robust, simple and commercially available electrochemical system. Differential pulse (DP) voltammetry was used for this purpose with the cyclic renewable mercury film silver based electrode (Hg(Ag)FE) and 0.05 M KNO3 solution as a supporting electrolyte. The effect of various factors such as: preconcentration potential and time, pulse amplitude and width, step potential and supporting electrolyte composition are optimized. The limits of detection (LOD) and quantification (LOQ) were 1.62 ng/mL and 4.85 ng/mL, respectively. The repeatability of the method at a concentration level of the analyte as low as 3 ng/mL, expressed as RSD is 3.5% (n = 6). Recovery was determined using certified reference material: Virginia Tobacco Leaves (CTA-VTL-2). The recovery of zinc ranged from 96.6 to 106.5%. The proposed method was successfully applied for determination of zinc in bee products (honey, propolis and diet supplements) after digestion procedure. PMID:24383319

  7. 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.

  8. Differential sensitivity of honey bees and bumble bees to a dietary insecticide (imidacloprid).

    PubMed

    Cresswell, James E; Page, Christopher J; Uygun, Mehmet B; Holmbergh, Marie; Li, Yueru; Wheeler, Jonathan G; Laycock, Ian; Pook, Christopher J; de Ibarra, Natalie Hempel; Smirnoff, Nick; Tyler, Charles R

    2012-12-01

    Currently, there is concern about declining bee populations and the sustainability of pollination services. One potential threat to bees is the unintended impact of systemic insecticides, which are ingested by bees in the nectar and pollen from flowers of treated crops. To establish whether imidacloprid, a systemic neonicotinoid and insect neurotoxin, harms individual bees when ingested at environmentally realistic levels, we exposed adult worker bumble bees, Bombus terrestris L. (Hymenoptera: Apidae), and honey bees, Apis mellifera L. (Hymenoptera: Apidae), to dietary imidacloprid in feeder syrup at dosages between 0.08 and 125μg l(-1). Honey bees showed no response to dietary imidacloprid on any variable that we measured (feeding, locomotion and longevity). In contrast, bumble bees progressively developed over time a dose-dependent reduction in feeding rate with declines of 10-30% in the environmentally relevant range of up to 10μg l(-1), but neither their locomotory activity nor longevity varied with diet. To explain their differential sensitivity, we speculate that honey bees are better pre-adapted than bumble bees to feed on nectars containing synthetic alkaloids, such as imidacloprid, by virtue of their ancestral adaptation to tropical nectars in which natural alkaloids are prevalent. We emphasise that our study does not suggest that honey bee colonies are invulnerable to dietary imidacloprid under field conditions, but our findings do raise new concern about the impact of agricultural neonicotinoids on wild bumble bee populations. PMID:23044068

  9. Hemolymph juvenile hormone titers in worker honey bees under normal and preswarming conditions.

    PubMed

    Zeng, Zhijiang; Huang, Zachary Y; Qin, Yuchuan; Pang, Huizhong

    2005-04-01

    Swarming is an important mechanism by which honey bee, Apis mellifera L., colonies reproduce, yet very little is known about the physiological changes in workers that are preparing to swarm. In this study, we determined the endocrine status of worker honey bees in preswarming colonies and in normal (nonswarming) colonies. Juvenile hormone (JH) titers in worker bees were similar in both groups before queen cells were present, but they became significantly lower in preswarming colonies compared with normal colonies when queen cells occurred in preswarming colonies. The lower JH titers in the preswarming colonies suggest that behavioral development is delayed in these colonies, consistent with previous reports that preswarming colonies have reduced foraging activities. Understanding the endocrine status of bees preparing for swarming will help us to better understand the biology of swarming. PMID:15889713

  10. A multiobjective ant colony optimization approach for scheduling environmental flow management alternatives with application to the River Murray, Australia

    NASA Astrophysics Data System (ADS)

    Szemis, J. M.; Dandy, G. C.; Maier, H. R.

    2013-10-01

    In regulated river systems, such as the River Murray in Australia, the efficient use of water to preserve and restore biota in the river, wetlands, and floodplains is of concern for water managers. Available management options include the timing of river flow releases and operation of wetland flow control structures. However, the optimal scheduling of these environmental flow management alternatives is a difficult task, since there are generally multiple wetlands and floodplains with a range of species, as well as a large number of management options that need to be considered. Consequently, this problem is a multiobjective optimization problem aimed at maximizing ecological benefit while minimizing water allocations within the infrastructure constraints of the system under consideration. This paper presents a multiobjective optimization framework, which is based on a multiobjective ant colony optimization approach, for developing optimal trade-offs between water allocation and ecological benefit. The framework is applied to a reach of the River Murray in South Australia. Two studies are formulated to assess the impact of (i) upstream system flow constraints and (ii) additional regulators on this trade-off. The results indicate that unless the system flow constraints are relaxed, there is limited additional ecological benefit as allocation increases. Furthermore the use of regulators can increase ecological benefits while using less water. The results illustrate the utility of the framework since the impact of flow control infrastructure on the trade-offs between water allocation and ecological benefit can be investigated, thereby providing valuable insight to managers.

  11. Field-Level Sublethal Effects of Approved Bee Hive Chemicals on Honey Bees (Apis mellifera L)

    PubMed Central

    Berry, Jennifer A.; Hood, W. Michael; Pietravalle, Stéphane; Delaplane, Keith S.

    2013-01-01

    In a study replicated across two states and two years, we tested the sublethal effects on honey bees of the miticides Apistan (tau fluvalinate) and Check Mite+ (coumaphos) and the wood preservative copper naphthenate applied at label rates in field conditions. A continuous covariate, a colony Varroa mite index, helped us disambiguate the effects of the chemicals on bees while adjusting for a presumed benefit of controlling mites. Mite levels in colonies treated with Apistan or Check Mite+ were not different from levels in non-treated controls. Experimental chemicals significantly decreased 3-day brood survivorship and increased construction of queen supercedure cells compared to non-treated controls. Bees exposed to Check Mite+ as immatures had higher legacy mortality as adults relative to non-treated controls, whereas bees exposed to Apistan had improved legacy mortality relative to non-treated controls. Relative to non-treated controls, Check Mite+ increased adult emergence weight. Although there was a treatment effect on a test of associative learning, it was not possible to statistically separate the treatment means, but bees treated with Apistan performed comparatively well. And finally, there were no detected effects of bee hive chemical on colony bee population, amount of brood, amount of honey, foraging rate, time required for marked released bees to return to their nest, percentage of released bees that return to the nest, and colony Nosema spore loads. To our knowledge, this is the first study to examine sublethal effects of bee hive chemicals applied at label rates under field conditions while disambiguating the results from mite control benefits realized from the chemicals. Given the poor performance of the miticides at reducing mites and their inconsistent effects on the host, these results defend the use of bee health management practices that minimize use of exotic hive chemicals. PMID:24204638

  12. A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains

    NASA Astrophysics Data System (ADS)

    Szemis, J. M.; Maier, H. R.; Dandy, G. C.

    2012-08-01

    Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.

  13. Semi-quantitative colony immunoassay for determining and optimizing protein expression in Saccharomyces cerevisiae and Escherichia coli.

    PubMed

    Cridge, Andrew G; Visweswaraiah, Jyothsna; Ramesh, Rashmi; Sattlegger, Evelyn

    2014-02-15

    This work describes a quick semi-quantitative colony immunoassay (QSCI) method for immunoblot detection of intracellularly expressed proteins in both yeast and bacterial cells. After induction of protein expression, only 4.5 h is required for cell breakage, protein detection, and data analysis. This protocol was used to screen and unambiguously identify Saccharomyces cerevisiae cells efficiently overexpressing glutathione S-transferase (GST)-tagged Yih1 in addition to cells expressing the myc-tagged large 297-kDa Gcn1 protein. In addition, the method was used to identify Escherichia coli cells efficiently expressing His6-tagged Yih1 and a GST-tagged Gcn1 fragment, respectively. The protocol allows the use of both epitope-specific and protein-specific antibodies. The same colony immunoassay can also be used to determine the minimal concentration of inducing agent sufficient for induction of optimal protein expression (e.g., galactose for yeast, isopropyl β-D-1-thiogalactopyranoside [IPTG] for E. coli). To our knowledge, this is the first report on a rapid low-cost procedure that allows the calibration of inducing agent on solid medium. PMID:24176934

  14. Technological approaches to optimize colonial resistance control for humans in artificial environment

    NASA Astrophysics Data System (ADS)

    Viacheslav, Ilyin; Skedina, Marina; Muokhamedieva, Lana; Gegenava, Anna; Mardanov, Robert

    Infectious safety of humans in confined habitat is one of the most important problems of contem-porary space medicine. It is known that together with increasing of space station exploration increases the risc of nosocomial-like strains formation. Investigations analyzing spaceflights on spaceships Spollo, Soyuz, Saljut, Mir revealed shifts in content of human microflora, decreas-ing of protective microflora and immunity, translocation of conventional pathogens, mainly, spaphylococci, to different biotopes. At present time, control on microbial state of cosmo-nauts is performed on Earth before and after the flight, and once in flight 5 days prior to landing. This seems to me not enough. Together with increasing of spaceflight duration it starts to be mostly actual to develop contemporary technological approaches to perform op-erative control on colonial resistance of cosmonauts. It is preferable that these means and measures should be simple and biologically safe, i.e. non-cultivating. One of such technologies is express-diagnostics of human disbiotic shifts with the aid of automatised method of digital treatment of microscopy microbial images. At present the standardized swab and automatised recognizing of microbial cells with calculation of quantitative rate of different microbial groups in tested materials and it's transformation via telecommunication channels. Knowing content and quantity of microbes in tested biotope, one can forecast risk of infection development and give countermeasures recommendation. Other prospective technology -gaseous chromatomass spectrometry which basing on analysis of different microbial volatile lipid acids can determine quantity and content of microbes. These markers are unique for different microbial specia and allow to isolate them from plenty of bioobjects. This technology was also successfully tested for space crewmembers in groundbase studies and in spaceflight. The data revealed increasing of pathogenicity potential on

  15. Distinctive gut microbiota of honey bees assessed using deep sampling from individual worker bees.

    PubMed

    Moran, Nancy A; Hansen, Allison K; Powell, J Elijah; Sabree, Zakee L

    2012-01-01

    Surveys of 16S rDNA sequences from the honey bee, Apis mellifera, have revealed the presence of eight distinctive bacterial phylotypes in intestinal tracts of adult worker bees. Because previous studies have been limited to relatively few sequences from samples pooled from multiple hosts, the extent of variation in this microbiota among individuals within and between colonies and locations has been unclear. We surveyed the gut microbiota of 40 individual workers from two sites, Arizona and Maryland USA, sampling four colonies per site. Universal primers were used to amplify regions of 16S ribosomal RNA genes, and amplicons were sequenced using 454 pyrotag methods, enabling analysis of about 330,000 bacterial reads. Over 99% of these sequences belonged to clusters for which the first blastn hits in GenBank were members of the known bee phylotypes. Four phylotypes, one within Gammaproteobacteria (corresponding to "Candidatus Gilliamella apicola") one within Betaproteobacteria ("Candidatus Snodgrassella alvi"), and two within Lactobacillus, were present in every bee, though their frequencies varied. The same typical bacterial phylotypes were present in all colonies and at both sites. Community profiles differed significantly among colonies and between sites, mostly due to the presence in some Arizona colonies of two species of Enterobacteriaceae not retrieved previously from bees. Analysis of Sanger sequences of rRNA of the Snodgrassella and Gilliamella phylotypes revealed that single bees contain numerous distinct strains of each phylotype. Strains showed some differentiation between localities, especially for the Snodgrassella phylotype. PMID:22558460

  16. Robust boundary detection and tracking of left ventricles on ultrasound images using active shape model and ant colony optimization.

    PubMed

    Zhang, Yaonan; Gao, Yuan; Jiao, Jinling; Li, Xian; Li, Sai; Yang, Jun

    2014-01-01

    Information regarding the motion, strain and synchronization are important for cardiac diagnosis and therapy. Extraction of such information from ultrasound images remains an open problem till today. In this paper, a novel method is proposed to extract the boundaries of left ventricles and track these boundaries in ultrasound image sequences. The initial detection of boundaries was performed by an active shape model scheme. Subsequent refinement of the boundaries was done by using local variance information of the images. The main objective of this paper is the formulation of a new boundary tracking algorithm using ant colony optimization technique. The experiments conducted on the simulated image sequences and the real cardiac ultrasound image sequences shows a positive and promising result. PMID:25226995

  17. Performance evaluation of ant colony optimization-based solution strategies on the mixed-model assembly line balancing problem

    NASA Astrophysics Data System (ADS)

    Akpinar, Sener; Mirac Bayhan, G.

    2014-06-01

    The aim of this article is to compare the performances of iterative ant colony optimization (ACO)-based solution strategies on a mixed-model assembly line balancing problem of type II (MMALBP-II) by addressing some particular features of real-world assembly line balancing problems such as parallel workstations and zoning constraints. To solve the problem, where the objective is to minimize the cycle time (i.e. maximize the production rate) for a predefined number of workstations in an existing assembly line, two ACO-based approaches which differ in the mission assigned to artificial ants are used. Furthermore, each ACO-based approach is conducted with two different pheromone release strategies: global and local pheromone updating rules. The four ACO-based approaches are used for solving 20 representative MMALBP-II to compare their performance in terms of computational time and solution quality. Detailed comparison results are presented.

  18. A temporal ant colony optimization approach to the shortest path problem in dynamic scale-free networks

    NASA Astrophysics Data System (ADS)

    Yu, Feng; Li, Yanjun; Wu, Tie-Jun

    2010-02-01

    A large number of networks in the real world have a scale-free structure, and the parameters of the networks change stochastically with time. Searching for the shortest paths in a scale-free dynamic and stochastic network is not only necessary for the estimation of the statistical characteristics such as the average shortest path length of the network, but also challenges the traditional concepts related to the “shortest path” of a network and the design of path searching strategies. In this paper, the concept of shortest path is defined on the basis of a scale-free dynamic and stochastic network model, and a temporal ant colony optimization (TACO) algorithm is proposed for searching for the shortest paths in the network. The convergence and the setup for some important parameters of the TACO algorithm are discussed through theoretical analysis and computer simulations, validating the effectiveness of the proposed algorithm.

  19. A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

    PubMed

    Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

    2016-06-01

    This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. PMID:27154739

  20. Identification of gene knockout strategies using a hybrid of an ant colony optimization algorithm and flux balance analysis to optimize microbial strains.

    PubMed

    Lu, Shi Jing; Salleh, Abdul Hakim Mohamed; Mohamad, Mohd Saberi; Deris, Safaai; Omatu, Sigeru; Yoshioka, Michifumi

    2014-09-28

    Reconstructions of genome-scale metabolic networks from different organisms have become popular in recent years. Metabolic engineering can simulate the reconstruction process to obtain desirable phenotypes. In previous studies, optimization algorithms have been implemented to identify the near-optimal sets of knockout genes for improving metabolite production. However, previous works contained premature convergence and the stop criteria were not clear for each case. Therefore, this study proposes an algorithm that is a hybrid of the ant colony optimization algorithm and flux balance analysis (ACOFBA) to predict near optimal sets of gene knockouts in an effort to maximize growth rates and the production of certain metabolites. Here, we present a case study that uses Baker's yeast, also known as Saccharomyces cerevisiae, as the model organism and target the rate of vanillin production for optimization. The results of this study are the growth rate of the model organism after gene deletion and a list of knockout genes. The ACOFBA algorithm was found to improve the yield of vanillin in terms of growth rate and production compared with the previous algorithms. PMID:25462325

  1. The Status of Honey Bee Health in Italy: Results from the Nationwide Bee Monitoring Network.

    PubMed

    Porrini, Claudio; Mutinelli, Franco; Bortolotti, Laura; Granato, Anna; Laurenson, Lynn; Roberts, Katherine; Gallina, Albino; Silvester, Nicholas; Medrzycki, Piotr; Renzi, Teresa; Sgolastra, Fabio; Lodesani, Marco

    2016-01-01

    In Italy a nation-wide monitoring network was established in 2009 in response to significant honey bee colony mortality reported during 2008. The network comprised of approximately 100 apiaries located across Italy. Colonies were sampled four times per year, in order to assess the health status and to collect samples for pathogen, chemical and pollen analyses. The prevalence of Nosema ceranae ranged, on average, from 47-69% in 2009 and from 30-60% in 2010, with strong seasonal variation. Virus prevalence was higher in 2010 than in 2009. The most widespread viruses were BQCV, DWV and SBV. The most frequent pesticides in all hive contents were organophosphates and pyrethroids such as coumaphos and tau-fluvalinate. Beeswax was the most frequently contaminated hive product, with 40% of samples positive and 13% having multiple residues, while 27% of bee-bread and 12% of honey bee samples were contaminated. Colony losses in 2009/10 were on average 19%, with no major differences between regions of Italy. In 2009, the presence of DWV in autumn was positively correlated with colony losses. Similarly, hive mortality was higher in BQCV infected colonies in the first and second visits of the year. In 2010, colony losses were significantly related to the presence of pesticides in honey bees during the second sampling period. Honey bee exposure to poisons in spring could have a negative impact at the colony level, contributing to increase colony mortality during the beekeeping season. In both 2009 and 2010, colony mortality rates were positively related to the percentage of agricultural land surrounding apiaries, supporting the importance of land use for honey bee health. PMID:27182604

  2. The Status of Honey Bee Health in Italy: Results from the Nationwide Bee Monitoring Network

    PubMed Central

    Bortolotti, Laura; Granato, Anna; Laurenson, Lynn; Roberts, Katherine; Gallina, Albino; Silvester, Nicholas; Medrzycki, Piotr; Renzi, Teresa; Sgolastra, Fabio; Lodesani, Marco

    2016-01-01

    In Italy a nation-wide monitoring network was established in 2009 in response to significant honey bee colony mortality reported during 2008. The network comprised of approximately 100 apiaries located across Italy. Colonies were sampled four times per year, in order to assess the health status and to collect samples for pathogen, chemical and pollen analyses. The prevalence of Nosema ceranae ranged, on average, from 47–69% in 2009 and from 30–60% in 2010, with strong seasonal variation. Virus prevalence was higher in 2010 than in 2009. The most widespread viruses were BQCV, DWV and SBV. The most frequent pesticides in all hive contents were organophosphates and pyrethroids such as coumaphos and tau-fluvalinate. Beeswax was the most frequently contaminated hive product, with 40% of samples positive and 13% having multiple residues, while 27% of bee-bread and 12% of honey bee samples were contaminated. Colony losses in 2009/10 were on average 19%, with no major differences between regions of Italy. In 2009, the presence of DWV in autumn was positively correlated with colony losses. Similarly, hive mortality was higher in BQCV infected colonies in the first and second visits of the year. In 2010, colony losses were significantly related to the presence of pesticides in honey bees during the second sampling period. Honey bee exposure to poisons in spring could have a negative impact at the colony level, contributing to increase colony mortality during the beekeeping season. In both 2009 and 2010, colony mortality rates were positively related to the percentage of agricultural land surrounding apiaries, supporting the importance of land use for honey bee health. PMID:27182604

  3. Combining support vector regression and ant colony optimization to reduce NOx emissions in coal-fired utility boilers

    SciTech Connect

    Ligang Zheng; Hao Zhou; Chunlin Wang; Kefa Cen

    2008-03-15

    Combustion optimization has recently demonstrated its potential to reduce NOx emissions in high capacity coal-fired utility boilers. In the present study, support vector regression (SVR), as well as artificial neural networks (ANN), was proposed to model the relationship between NOx emissions and operating parameters of a 300 MW coal-fired utility boiler. The predicted NOx emissions from the SVR model, by comparing with that of the ANN-based model, showed better agreement with the values obtained in the experimental tests on this boiler operated at different loads and various other operating parameters. The mean modeling error and the correlation factor were 1.58% and 0.94, respectively. Then, the combination of the SVR model with ant colony optimization (ACO) to reduce NOx emissions was presented in detail. The experimental results showed that the proposed approach can effectively reduce NOx emissions from the coal-fired utility boiler by about 18.69% (65 ppm). A time period of less than 6 min was required for NOx emissions modeling, and 2 min was required for a run of optimization under a PC system. The computing times are suitable for the online application of the proposed method to actual power plants. 37 refs., 8 figs., 3 tabs.

  4. Impact of electric fields on honey bees

    SciTech Connect

    Bindokas, V.P.

    1985-01-01

    Biological effects in honey bee colonies under a 765-kV, 60-Hz transmission line (electric (E) field = 7 kV/m) were confirmed using controlled dosimetry and treatment reversal to replicate findings within the same season. Hives in the same environment but shielded from E field are normal, suggesting effects are caused by interaction of E field with the hive. Bees flying through the ambient E field are not demonstrably affected. Different thresholds and severity of effects were found in colonies exposed to 7, 5.5, 4.1, 1.8, and 0.65 to 0.85 kV/m at incremental distances from the line. Most colonies exposed at 7 kV/m failed in 8 weeks and failed to overwinter at greater than or equal to4.1 kV/m. Data suggest the limit of a biological effects corridor lies between 15 and 27 m (4.1 and 1.8 kV/m) beyond the outer phase of the transmission line. Mechanisms to explain colony disturbance fall into two categories, direct perception of enhanced in-hive E fields, and perception of shock from induced currents. The same effects induced in colonies with total-hive E-field exposure can be reproduced with shock or E-field exposure of worker bees in extended hive entranceways (= porches). Full-scale experiments demonstrate bee exposure to E fields including 100 kV/m under moisture-free conditions within a non-conductive porch causes no detectable effect on colony behavior. Exposure of bees on a conductive (e.g. wet) substrate produces been disturbance, increased mortality, abnormal propolization, and possible impairment of colony growth. Thresholds for effects caused by step-potential-induced currents are: 275-350 nA - disturbance of single bees; 600 nA - onset of abnormal propolization; and 900 nA - sting.

  5. The plight of the bees

    USGS Publications Warehouse

    Spivak, M.; Mader, E.; Vaughan, M.; Euliss, N.H.

    2011-01-01

    The loss of biodiversity is a trend that is garnering much concern. As organisms have evolved mutualistic and synergistic relationships, the loss of one or a few species can have a much wider environmental impact. Since much pollination is facilitated by bees, the reported colony collapse disorder has many worried of widespread agricultural fallout and thus deleterious impact on human foodstocks. In this Feature, Spivak et al. review what is known of the present state of bee populations and provide information on how to mitigate and reverse the trend. ?? 2010 American Chemical Society.

  6. Pollen foraging in colonies of Melipona bicolor (Apidae, Meliponini): effects of season, colony size and queen number.

    PubMed

    Hilário, S D; Imperatriz-Fonseca, V L

    2009-01-01

    We evaluated the ratio between the number of pollen foragers and the total number of bees entering colonies of Melipona bicolor, a facultative polygynous species of stingless bees. The variables considered in our analysis were: seasonality, colony size and the number of physogastric queens in each colony. The pollen forager ratios varied significantly between seasons; the ratio was higher in winter than in summer. However, colony size and number of queens per colony had no significant effect. We conclude that seasonal differences in pollen harvest are related to the production of sexuals and to the number of individuals and their body size. PMID:19554765

  7. Nosema ceranae in age cohorts of the western honey bee (Apis mellifera).

    PubMed

    Smart, Matthew D; Sheppard, Walter S

    2012-01-01

    Nosemaceranae intensity (mean spores per bee) and prevalence (proportion of bees infected in a sample) were analyzed in honey bees of known ages. Sealed brood combs from five colonies were removed, emerging bees were marked with paint, released back into their colonies of origin, and collected as recently emerged (0-3 days old), as house bees (8-11 days old), and as foragers (22-25 days old). Fifty bees from each of the five colonies were processed individually at each collection date for the intensity and prevalence of N. ceranae infection. Using PCR and specific primers to differentiate Nosema species, N. ceranae was found to be the only species present during the experiment. At each collection age (recent emergence, house, forager) an additional sample from the inner hive cover (background bees=BG) of each colony was collected to compare the N. ceranae results of this sampling method, commonly used for Nosema spore quantification, to the samples comprised of marked bees of known ages. No recently emerged bees exhibited infection with N. ceranae. One house bee out of the 250 individuals analyzed (prevalence=0.4%) tested positive for N. ceranae, at an infection level of 3.35×10(6) spores. Infection levels were not statistically different between the recently emerged (mean=0 spores/bee) and house bees (mean=1.34×10(4) spores/bee) (P=0.99). Foragers exhibited the highest prevalence (8.3%) and infection intensity (mean=2.38×10(6) spores/bee), with a range of 0-8.72×10(7) spores in individual bees. The average infection level across all foragers was significantly higher than that of recently emerged bees (P=0.01) and house bees (P=0.01). Finally, the prevalence of Nosema in infected bees was found to be positively correlated with the infection intensity in the sample. PMID:22001631

  8. Neonicotinoid pesticides severely affect honey bee queens

    PubMed Central

    Williams, Geoffrey R.; Troxler, Aline; Retschnig, Gina; Roth, Kaspar; Yañez, Orlando; Shutler, Dave; Neumann, Peter; Gauthier, Laurent

    2015-01-01

    Queen health is crucial to colony survival of social bees. Recently, queen failure has been proposed to be a major driver of managed honey bee colony losses, yet few data exist concerning effects of environmental stressors on queens. Here we demonstrate for the first time that exposure to field-realistic concentrations of neonicotinoid pesticides during development can severely affect queens of western honey bees (Apis mellifera). In pesticide-exposed queens, reproductive anatomy (ovaries) and physiology (spermathecal-stored sperm quality and quantity), rather than flight behaviour, were compromised and likely corresponded to reduced queen success (alive and producing worker offspring). This study highlights the detriments of neonicotinoids to queens of environmentally and economically important social bees, and further strengthens the need for stringent risk assessments to safeguard biodiversity and ecosystem services that are vulnerable to these substances. PMID:26459072

  9. Neonicotinoid pesticides severely affect honey bee queens.

    PubMed

    Williams, Geoffrey R; Troxler, Aline; Retschnig, Gina; Roth, Kaspar; Yañez, Orlando; Shutler, Dave; Neumann, Peter; Gauthier, Laurent

    2015-01-01

    Queen health is crucial to colony survival of social bees. Recently, queen failure has been proposed to be a major driver of managed honey bee colony losses, yet few data exist concerning effects of environmental stressors on queens. Here we demonstrate for the first time that exposure to field-realistic concentrations of neonicotinoid pesticides during development can severely affect queens of western honey bees (Apis mellifera). In pesticide-exposed queens, reproductive anatomy (ovaries) and physiology (spermathecal-stored sperm quality and quantity), rather than flight behaviour, were compromised and likely corresponded to reduced queen success (alive and producing worker offspring). This study highlights the detriments of neonicotinoids to queens of environmentally and economically important social bees, and further strengthens the need for stringent risk assessments to safeguard biodiversity and ecosystem services that are vulnerable to these substances. PMID:26459072

  10. Effects of Infection on Honey Bee Population Dynamics: A Model

    PubMed Central

    Betti, Matt I.; Wahl, Lindi M.; Zamir, Mair

    2014-01-01

    We propose a model that combines the dynamics of the spread of disease within a bee colony with the underlying demographic dynamics of the colony to determine the ultimate fate of the colony under different scenarios. The model suggests that key factors in the survival or collapse of a honey bee colony in the face of an infection are the rate of transmission of the infection and the disease-induced death rate. An increase in the disease-induced death rate, which can be thought of as an increase in the severity of the disease, may actually help the colony overcome the disease and survive through winter. By contrast, an increase in the transmission rate, which means that bees are being infected at an earlier age, has a drastic deleterious effect. Another important finding relates to the timing of infection in relation to the onset of winter, indicating that in a time interval of approximately 20 days before the onset of winter the colony is most affected by the onset of infection. The results suggest further that the age of recruitment of hive bees to foraging duties is a good early marker for the survival or collapse of a honey bee colony in the face of infection, which is consistent with experimental evidence but the model provides insight into the underlying mechanisms. The most important result of the study is a clear distinction between an exposure of the honey bee colony to an environmental hazard such as pesticides or insecticides, or an exposure to an infectious disease. The results indicate unequivocally that in the scenarios that we have examined, and perhaps more generally, an infectious disease is far more hazardous to the survival of a bee colony than an environmental hazard that causes an equal death rate in foraging bees. PMID:25329468

  11. Pesticide exposure in honey bees results in increased levels of the gut pathogen Nosema

    NASA Astrophysics Data System (ADS)

    Pettis, Jeffery S.; Vanengelsdorp, Dennis; Johnson, Josephine; Dively, Galen

    2012-02-01

    Global pollinator declines have been attributed to habitat destruction, pesticide use, and climate change or some combination of these factors, and managed honey bees, Apis mellifera, are part of worldwide pollinator declines. Here we exposed honey bee colonies during three brood generations to sub-lethal doses of a widely used pesticide, imidacloprid, and then subsequently challenged newly emerged bees with the gut parasite, Nosema spp. The pesticide dosages used were below levels demonstrated to cause effects on longevity or foraging in adult honey bees. Nosema infections increased significantly in the bees from pesticide-treated hives when compared to bees from control hives demonstrating an indirect effect of pesticides on pathogen growth in honey bees. We clearly demonstrate an increase in pathogen growth within individual bees reared in colonies exposed to one of the most widely used pesticides worldwide, imidacloprid, at below levels considered harmful to bees. The finding that individual bees with undetectable levels of the target pesticide, after being reared in a sub-lethal pesticide environment within the colony, had higher Nosema is significant. Interactions between pesticides and pathogens could be a major contributor to increased mortality of honey bee colonies, including colony collapse disorder, and other pollinator declines worldwide.

  12. 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.

  13. Measurement of total anthocyanins content in flowering tea using near infrared spectroscopy combined with ant colony optimization models.

    PubMed

    Xiaowei, Huang; Xiaobo, Zou; Jiewen, Zhao; Jiyong, Shi; Xiaolei, Zhang; Holmes, Mel

    2014-12-01

    Flowering tea has become a popular beverage consumed across the world. Anthocyanins content is considered as an important quality index of flowering tea. The feasibility of using near infrared (NIR) spectra at the wavelength range of 10,000-4000 cm(-1) for rapid and nondestructive determination of total anthocyanins content in flowering tea was investigated. Ant colony optimization interval partial least squares (ACO-iPLS) and Genetic algorithm interval partial least squares (GA-iPLS) were used to develop calibration models for total anthocyanins content. Two characteristic wavelength regions (4590-4783, 5770-5,963 cm(-1)), which corresponding to the ultraviolet/visible absorption bands of anthocyanins, were selected by ACO-iPLS. The optimal ACO-iPLS model for total anthocyanins content (R=0.9856, RMSECV=0.1,198 mg/g) had better performance than full-spectrum PLS, iPLS, and GA-iPLS models. It could be concluded that NIR spectroscopy has significant potential in the nondestructive determination of total anthocyanins content in flowering tea. PMID:24996367

  14. Application of ant colony optimization to image classification using a Markov model with non-stationary neighborhoods

    NASA Astrophysics Data System (ADS)

    Le Hégarat-Mascle, S.; Kallel, A.; Descombes, X.

    2005-10-01

    In global classifications using Markov Random Field (MRF) modelling, the neighbourhood form is generally considered as independent of its location in the image. Such an approach may lead to classification errors for pixels located at the segment borders. The solution proposed here consists in relaxing the assumption of fixed-form neighbourhood. However this non-stationary neighbourhood modelling is useful only if an efficient heuristic can be defined to perform the optimization. Ant colony optimization (ACO) is currently a popular algorithm. It models upon the behavior of social insects for computing strategies: the information gathered by simple autonomous mobile agents, called ants, is shared and exploited for problem solving. Here we propose to use the ACO and to exploit its ability of self-organization. The ants collect information through the image, from one pixel to the others. The choice of the path is a function of the pixel label, favouring paths within a same image segment. We show that this corresponds to an automatic adaptation of the neighbourhood to the segment form. Performance of this new approach is illustrated on a simulated image and on actual remote sensing images, SPOT4/HRV, representing agricultural areas. In the studied examples, we found that it outperforms the fixed-form neighbourhood used in classical MRF classifications. The advantage of having a neighborhood shape that automatically adapts to the image segment clearly appears in these cases of images containing fine elements, lanes or thin fields, but also complex natural landscape structures.

  15. Preliminary results on the evaluation of honey bee stocks for susceptibility to deformed wing virus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We assessed the susceptibility of honey bee stocks to Deformed Wing Virus (DWV) infection. Three stocks (n = 4 colonies per stock) were evaluated: Italian (IHB), Pol-line (POL, hybrid Varroa Sensitive Hygienic bees) and Russian honey bees (RHB). Each queen was caged to obtain uniformly-aged larvae....

  16. Genes Related to Immunity as Expressed in the Alfalfa Leafcutting Bee, Megachile rotundata During Pathogen Challenge

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bees are a large, diverse group of insects that collect pollen and nectar from plants to feed to their young, and as a result, play an important ecological role as pollinators. Honey bees, which form large colonies with a complex social structure, are probably the most well known bee, but the majori...

  17. Intraspecific queen parasitism in a highly eusocial bee

    PubMed Central

    Wenseleers, Tom; Alves, Denise A.; Francoy, Tiago M.; Billen, Johan; Imperatriz-Fonseca, Vera L.

    2011-01-01

    Insect societies are well-known for their advanced cooperation, but their colonies are also vulnerable to reproductive parasitism. Here, we present a novel example of an intraspecific social parasitism in a highly eusocial bee, the stingless bee Melipona scutellaris. In particular, we provide genetic evidence which shows that, upon loss of the mother queen, many colonies are invaded by unrelated queens that fly in from unrelated hives nearby. The reasons for the occurrence of this surprising form of social parasitism may be linked to the fact that unlike honeybees, Melipona bees produce new queens in great excess of colony needs, and that this exerts much greater selection on queens to seek alternative reproductive options, such as by taking over other nests. Overall, our results are the first to demonstrate that queens in highly eusocial bees can found colonies not only via supersedure or swarming, but also by infiltrating and taking over other unrelated nests. PMID:20961883

  18. Managing honey bees (Hymenoptera: Apidae) for greenhouse tomato pollination.

    PubMed

    Sabara, Holly A; Winston, Mark L

    2003-06-01

    Although commercially reared colonies of bumble bees (Bombus sp.) are the primary pollinator world-wide for greenhouse tomatoes (Lycopersicon esculentum Mill.) previous research indicates that honey bees (Apis mellifera L.) might be a feasible alternative or supplement to bumble bee pollination. However, management methods for honey bee greenhouse tomato pollination scarcely have been explored. We 1) tested the effect of initial amounts of brood on colony population size and flight activity in screened greenhouses during the winter, and 2) compared foraging from colonies with brood used within screened and unscreened greenhouses during the summer. Brood rearing was maintained at low levels in both brood and no-brood colonies after 21 d during the winter, and emerging honey bees from both treatments had significantly lower weights than bees from outdoor colonies. Honey bee flight activity throughout the day and over the 21 d in the greenhouse was not influenced by initial brood level. In our summer experiment, brood production in screened greenhouses neared zero after 21 d but higher levels of brood were reared in unscreened greenhouses with access to outside forage. Flower visitation measured throughout the day and over the 21 d the colonies were in the greenhouse was not influenced by screening treatment. An economic analysis indicated that managing honey bees for greenhouse tomato pollination would be financially viable for both beekeepers and growers. We conclude that honey bees can be successfully managed for greenhouse tomato pollination in both screened and unscreened greenhouses if the foraging force is maintained by replacing colonies every 3 wk. PMID:12852587

  19. Mapping Sleeping Bees within Their Nest: Spatial and Temporal Analysis of Worker Honey Bee Sleep

    PubMed Central

    Klein, Barrett Anthony; Stiegler, Martin; Klein, Arno; Tautz, Jürgen

    2014-01-01

    Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony's nest that may impact their sleep. We mapped sleep behavior and temperature of worker bees and produced maps of their nest's comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns. PMID:25029445

  20. BeeDoctor, a versatile MLPA-based diagnostic tool for screening bee viruses.

    PubMed

    De Smet, Lina; Ravoet, Jorgen; de Miranda, Joachim R; Wenseleers, Tom; Mueller, Matthias Y; Moritz, Robin F A; de Graaf, Dirk C

    2012-01-01

    The long-term decline of managed honeybee hives in the world has drawn significant attention to the scientific community and bee-keeping industry. A high pathogen load is believed to play a crucial role in this phenomenon, with the bee viruses being key players. Most of the currently characterized honeybee viruses (around twenty) are positive stranded RNA viruses. Techniques based on RNA signatures are widely used to determine the viral load in honeybee colonies. High throughput screening for viral loads necessitates the development of a multiplex polymerase chain reaction approach in which different viruses can be targeted simultaneously. A new multiparameter assay, called "BeeDoctor", was developed based on multiplex-ligation probe dependent amplification (MLPA) technology. This assay detects 10 honeybee viruses in one reaction. "BeeDoctor" is also able to screen selectively for either the positive strand of the targeted RNA bee viruses or the negative strand, which is indicative for active viral replication. Due to its sensitivity and specificity, the MLPA assay is a useful tool for rapid diagnosis, pathogen characterization, and epidemiology of viruses in honeybee populations. "BeeDoctor" was used for screening 363 samples from apiaries located throughout Flanders; the northern half of Belgium. Using the "BeeDoctor", virus infections were detected in almost eighty percent of the colonies, with deformed wing virus by far the most frequently detected virus and multiple virus infections were found in 26 percent of the colonies. PMID:23144717

  1. BeeDoctor, a Versatile MLPA-Based Diagnostic Tool for Screening Bee Viruses

    PubMed Central

    De Smet, Lina; Ravoet, Jorgen; de Miranda, Joachim R.; Wenseleers, Tom; Mueller, Matthias Y.; Moritz, Robin F. A.; de Graaf, Dirk C.

    2012-01-01

    The long-term decline of managed honeybee hives in the world has drawn significant attention to the scientific community and bee-keeping industry. A high pathogen load is believed to play a crucial role in this phenomenon, with the bee viruses being key players. Most of the currently characterized honeybee viruses (around twenty) are positive stranded RNA viruses. Techniques based on RNA signatures are widely used to determine the viral load in honeybee colonies. High throughput screening for viral loads necessitates the development of a multiplex polymerase chain reaction approach in which different viruses can be targeted simultaneously. A new multiparameter assay, called “BeeDoctor”, was developed based on multiplex-ligation probe dependent amplification (MLPA) technology. This assay detects 10 honeybee viruses in one reaction. “BeeDoctor” is also able to screen selectively for either the positive strand of the targeted RNA bee viruses or the negative strand, which is indicative for active viral replication. Due to its sensitivity and specificity, the MLPA assay is a useful tool for rapid diagnosis, pathogen characterization, and epidemiology of viruses in honeybee populations. “BeeDoctor” was used for screening 363 samples from apiaries located throughout Flanders; the northern half of Belgium. Using the “BeeDoctor”, virus infections were detected in almost eighty percent of the colonies, with deformed wing virus by far the most frequently detected virus and multiple virus infections were found in 26 percent of the colonies. PMID:23144717

  2. Mapping sleeping bees within their nest: spatial and temporal analysis of worker honey bee sleep.

    PubMed

    Klein, Barrett Anthony; Stiegler, Martin; Klein, Arno; Tautz, Jürgen

    2014-01-01

    Patterns of behavior within societies have long been visualized and interpreted using maps. Mapping the occurrence of sleep across individuals within a society could offer clues as to functional aspects of sleep. In spite of this, a detailed spatial analysis of sleep has never been conducted on an invertebrate society. We introduce the concept of mapping sleep across an insect society, and provide an empirical example, mapping sleep patterns within colonies of European honey bees (Apis mellifera L.). Honey bees face variables such as temperature and position of resources within their colony's nest that may impact their sleep. We mapped sleep behavior and temperature of worker bees and produced maps of their nest's comb contents as the colony grew and contents changed. By following marked bees, we discovered that individuals slept in many locations, but bees of different worker castes slept in different areas of the nest relative to position of the brood and surrounding temperature. Older worker bees generally slept outside cells, closer to the perimeter of the nest, in colder regions, and away from uncapped brood. Younger worker bees generally slept inside cells and closer to the center of the nest, and spent more time asleep than awake when surrounded by uncapped brood. The average surface temperature of sleeping foragers was lower than the surface temperature of their surroundings, offering a possible indicator of sleep for this caste. We propose mechanisms that could generate caste-dependent sleep patterns and discuss functional significance of these patterns. PMID:25029445

  3. Genetic component in learning ability in bees.

    PubMed

    Kerr, W E; Moura Duarte, F A; Oliveira, R S

    1975-10-01

    Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival. PMID:1191157

  4. Honey Bee Infecting Lake Sinai Viruses

    PubMed Central

    Daughenbaugh, Katie F.; Martin, Madison; Brutscher, Laura M.; Cavigli, Ian; Garcia, Emma; Lavin, Matt; Flenniken, Michelle L.

    2015-01-01

    Honey bees are critical pollinators of important agricultural crops. Recently, high annual losses of honey bee colonies have prompted further investigation of honey bee infecting viruses. To better characterize the recently discovered and very prevalent Lake Sinai virus (LSV) group, we sequenced currently circulating LSVs, performed phylogenetic analysis, and obtained images of LSV2. Sequence analysis resulted in extension of the LSV1 and LSV2 genomes, the first detection of LSV4 in the US, and the discovery of LSV6 and LSV7. We detected LSV1 and LSV2 in the Varroa destructor mite, and determined that a large proportion of LSV2 is found in the honey bee gut, suggesting that vector-mediated, food-associated, and/or fecal-oral routes may be important for LSV dissemination. Pathogen-specific quantitative PCR data, obtained from samples collected during a small-scale monitoring project, revealed that LSV2, LSV1, Black queen cell virus (BQCV), and Nosema ceranae were more abundant in weak colonies than strong colonies within this sample cohort. Together, these results enhance our current understanding of LSVs and illustrate the importance of future studies aimed at investigating the role of LSVs and other pathogens on honey bee health at both the individual and colony levels. PMID:26110586

  5. Honey Bee Infecting Lake Sinai Viruses.

    PubMed

    Daughenbaugh, Katie F; Martin, Madison; Brutscher, Laura M; Cavigli, Ian; Garcia, Emma; Lavin, Matt; Flenniken, Michelle L

    2015-06-01

    Honey bees are critical pollinators of important agricultural crops. Recently, high annual losses of honey bee colonies have prompted further investigation of honey bee infecting viruses. To better characterize the recently discovered and very prevalent Lake Sinai virus (LSV) group, we sequenced currently circulating LSVs, performed phylogenetic analysis, and obtained images of LSV2. Sequence analysis resulted in extension of the LSV1 and LSV2 genomes, the first detection of LSV4 in the US, and the discovery of LSV6 and LSV7. We detected LSV1 and LSV2 in the Varroa destructor mite, and determined that a large proportion of LSV2 is found in the honey bee gut, suggesting that vector-mediated, food-associated, and/or fecal-oral routes may be important for LSV dissemination. Pathogen-specific quantitative PCR data, obtained from samples collected during a small-scale monitoring project, revealed that LSV2, LSV1, Black queen cell virus (BQCV), and Nosema ceranae were more abundant in weak colonies than strong colonies within this sample cohort. Together, these results enhance our current understanding of LSVs and illustrate the importance of future studies aimed at investigating the role of LSVs and other pathogens on honey bee health at both the individual and colony levels. PMID:26110586

  6. Nutrition, immunity and viral infections in honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Honey bees can be infected with viruses that can spread rapidly in colonies. Here we discuss how honey bees decrease the risk of disease outbreaks by a combination of behaviors (social immunity) and individual immunity. The effectiveness of both social and individual immunity relies on nutrition. Ho...

  7. Deformed wing virus is not related to honey bees' aggressiveness

    PubMed Central

    Rortais, Agnès; Tentcheva, Diana; Papachristoforou, Alexandros; Gauthier, Laurent; Arnold, Gérard; Colin, Marc Edouard; Bergoin, Max

    2006-01-01

    Guards of Cyprian honey bee colonies, Apis mellifera cypria, display a great defensive behaviour against hornets' attacks. The deformed wing virus (DWV) and the kakugo virus (KV) genomes are very similar, but unlike KV, the presence of DWV is not related to honey bees' aggressiveness. This discrepancy is further discussed. PMID:16942620

  8. Antioxidants in wax cappings of honey bee brood

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This is the first time that non-food items from honey bee colonies were assessed for antioxidant activity as it related to Varroa-infestation. Antioxidant activity may be an indication of bee health and while antioxidants are present in honey, propolis, pollen and royal jelly, little work has been...

  9. RNAi and Antiviral Defense in the Honey Bee

    PubMed Central

    Brutscher, Laura M.; Flenniken, Michelle L.

    2015-01-01

    Honey bees play an important agricultural and ecological role as pollinators of numerous agricultural crops and other plant species. Therefore, investigating the factors associated with high annual losses of honey bee colonies in the US is an important and active area of research. Pathogen incidence and abundance correlate with Colony Collapse Disorder- (CCD-) affected colonies in the US and colony losses in the US and in some European countries. Honey bees are readily infected by single-stranded positive sense RNA viruses. Largely dependent on the host immune response, virus infections can either remain asymptomatic or result in deformities, paralysis, or death of adults or larvae. RNA interference (RNAi) is an important antiviral defense mechanism in insects, including honey bees. Herein, we review the role of RNAi in honey bee antiviral defense and highlight some parallels between insect and mammalian immune systems. A more thorough understanding of the role of pathogens on honey bee health and the immune mechanisms bees utilize to combat infectious agents may lead to the development of strategies that enhance honey bee health and result in the discovery of additional mechanisms of immunity in metazoans. PMID:26798663

  10. Patriline variation of Nosema ceranae levels in Russian and Italian honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The microsporidian Nosema ceranae has invaded managed honey bee colonies throughout the world. While the presence of N. ceranae is common, infection levels are highly variable, even among bees within a single colony. The underlying mechanisms driving this variation are not well-understood. The high ...

  11. How Varroa parasitism affects the immunological and nutritional status of the honey bee, Apis mellifera

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We investigated the effect of the parasitic mite Varroa destructor on the immunological and nutritional condition of honey bees, Apis mellifera, from the perspective of the individual bee and the colony. Pupae, newly-emerged adults and foraging adults were sampled from up to 10 colonies at one site ...

  12. An optimized colony forming assay for low-dose-radiation cell survival measurement

    SciTech Connect

    Zhu J.; Sutherland B.; Hu W.; Ding N.; Ye C.; Usikalu M.; Li S.; Hu B.; Zhou G.

    2011-11-01

    The aim of this study is to develop a simple and reliable method to quantify the cell survival of low-dose irradiations. Two crucial factors were considered, the same number of cells plated in each flask and an appropriate interval between cell plating and irradiation. For the former, we optimized cell harvest with trypsin, diluted cells in one container, and directly seeded cells on the bottom of flasks in a low density before irradiation. Reproducible plating efficiency was obtained. For the latter, we plated cells on the bottom of flasks and then monitored the processing of attachment, cell cycle variations, and the plating efficiency after exposure to 20 cGy of X-rays. The results showed that a period of 4.5 h to 7.5 h after plating was suitable for further treatment. In order to confirm the reliability and feasibility of our method, we also measured the survival curves of these M059K and M059J glioma cell lines by following the optimized protocol and obtained consistent results reported by others with cell sorting system. In conclusion, we successfully developed a reliable and simple way to measure the survival fractions of human cells exposed to low dose irradiation, which might be helpful for the studies on low-dose radiation biology.

  13. 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.

  14. Building optimal regression tree by ant colony system-genetic algorithm: application to modeling of melting points.

    PubMed

    Hemmateenejad, Bahram; Shamsipur, Mojtaba; Zare-Shahabadi, Vali; Akhond, Morteza

    2011-10-17

    The classification and regression trees (CART) possess the advantage of being able to handle large data sets and yield readily interpretable models. A conventional method of building a regression tree is recursive partitioning, which results in a good but not optimal tree. Ant colony system (ACS), which is a meta-heuristic algorithm and derived from the observation of real ants, can be used to overcome this problem. The purpose of this study was to explore the use of CART and its combination with ACS for modeling of melting points of a large variety of chemical compounds. Genetic algorithm (GA) operators (e.g., cross averring and mutation operators) were combined with ACS algorithm to select the best solution model. In addition, at each terminal node of the resulted tree, variable selection was done by ACS-GA algorithm to build an appropriate partial least squares (PLS) model. To test the ability of the resulted tree, a set of approximately 4173 structures and their melting points were used (3000 compounds as training set and 1173 as validation set). Further, an external test set containing of 277 drugs was used to validate the prediction ability of the tree. Comparison of the results obtained from both trees showed that the tree constructed by ACS-GA algorithm performs better than that produced by recursive partitioning procedure. PMID:21907021

  15. Estimate of FDG excretion by means of compartmental analysis and ant colony optimization of nuclear medicine data.

    PubMed

    Garbarino, Sara; Caviglia, Giacomo; Brignone, Massimo; Massollo, Michela; Sambuceti, Gianmario; Piana, Michele

    2013-01-01

    [(18)F]fluoro-2-deoxy-D-glucose (FDG) is one of the most utilized tracers for positron emission tomography (PET) applications in oncology. FDG-PET relies on higher glycolytic activity in tumors compared to normal structures as the basis of image contrast. As a glucose analog, FDG is transported into malignant cells which typically exhibit an increased radioactivity. However, different from glucose, FDG is not reabsorbed by the renal system and is excreted to the bladder. The present paper describes a novel computational method for the quantitative assessment of this excretion process. The method is based on a compartmental analysis of FDG-PET data in which the excretion process is explicitly accounted for by the bladder compartment and on the application of an ant colony optimization (ACO) algorithm for the determination of the tracer coefficients describing the FDG transport effectiveness. The validation of this approach is performed by means of both synthetic data and real measurements acquired by a PET device for small animals (micro-PET). Possible oncological applications of the results are discussed in the final section. PMID:24191175

  16. 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.

  17. The alternative Pharaoh approach: stingless bees mummify beetle parasites alive.

    PubMed

    Greco, Mark K; Hoffmann, Dorothee; Dollin, Anne; Duncan, Michael; Spooner-Hart, Robert; Neumann, Peter

    2010-03-01

    Workers from social insect colonies use different defence strategies to combat invaders. Nevertheless, some parasitic species are able to bypass colony defences. In particular, some beetle nest invaders cannot be killed or removed by workers of social bees, thus creating the need for alternative social defence strategies to ensure colony survival. Here we show, using diagnostic radioentomology, that stingless bee workers (Trigona carbonaria) immediately mummify invading adult small hive beetles (Aethina tumida) alive by coating them with a mixture of resin, wax and mud, thereby preventing severe damage to the colony. In sharp contrast to the responses of honeybee and bumblebee colonies, the rapid live mummification strategy of T. carbonaria effectively prevents beetle advancements and removes their ability to reproduce. The convergent evolution of mummification in stingless bees and encapsulation in honeybees is another striking example of co-evolution between insect societies and their parasites. PMID:19997899

  18. The alternative Pharaoh approach: stingless bees mummify beetle parasites alive

    NASA Astrophysics Data System (ADS)

    Greco, Mark K.; Hoffmann, Dorothee; Dollin, Anne; Duncan, Michael; Spooner-Hart, Robert; Neumann, Peter

    2010-03-01

    Workers from social insect colonies use different defence strategies to combat invaders. Nevertheless, some parasitic species are able to bypass colony defences. In particular, some beetle nest invaders cannot be killed or removed by workers of social bees, thus creating the need for alternative social defence strategies to ensure colony survival. Here we show, using diagnostic radioentomology, that stingless bee workers ( Trigona carbonaria) immediately mummify invading adult small hive beetles ( Aethina tumida) alive by coating them with a mixture of resin, wax and mud, thereby preventing severe damage to the colony. In sharp contrast to the responses of honeybee and bumblebee colonies, the rapid live mummification strategy of T. carbonaria effectively prevents beetle advancements and removes their ability to reproduce. The convergent evolution of mummification in stingless bees and encapsulation in honeybees is another striking example of co-evolution between insect societies and their parasites.

  19. Improved Production and Characterization of Recombinant Human Granulocyte Colony Stimulating Factor from E. coli under Optimized Downstream Processes.

    PubMed

    Vemula, Sandeep; Thunuguntla, Rahul; Dedaniya, Akshay; Kokkiligadda, Sujana; Palle, Chaitanya; Ronda, Srinivasa Reddy

    2015-04-01

    This work reports the upstream and downstream process of recombinant human granulocyte colony stimulating factor (rhG-CSF) expressed in Escherichia coli BL21 (DE3)pLysS. The fed batch mode was selected for the maximum output of biomass (6.4g/L) and purified rhG-CSF (136mg/L) under suitable physicochemical environment. The downstream processing steps viz., recovery, solubilization, refolding and concentration were optimized in this study. The maximum rhG-CSF inclusion bodies recovery yield (97%) was accomplished with frequent homogenization and sonication procedure. An efficient solubilization (96%) of rhG-CSF inclusion bodies were observed with 8M urea at pH 9.5. Refolding efficiency studies showed maximum refolding ⩾86% and ⩾84% at 20°C and pH 9 respectively. The renatured protein solution was concentrated, clarified and partially purified (⩾95%) by the cross flow filtration technique. The concentrated protein was further purified by a single step size exclusion chromatography with ⩾98% purity. The characterization of purified rhG-CSF molecular mass as evidenced by SDS-PAGE, western blot and LC/MS analysis was shown to be 18.8kDa. The secondary structure of rhG-CSF was evaluated by the CD spectroscopic technique based on the helical structural components. The biological activity of the purified rhG-CSF showed a similar activity of cell proliferation with the standard rhG-CSF. Overall, the results demonstrate an optimized downstream process for obtaining high yields of biologically active rhG-CSF. PMID:25659501

  20. Impacts of Austrian Climate Variability on Honey Bee Mortality

    NASA Astrophysics Data System (ADS)

    Switanek, Matt; Brodschneider, Robert; Crailsheim, Karl; Truhetz, Heimo

    2015-04-01

    Global food production, as it is today, is not possible without pollinators such as the honey bee. It is therefore alarming that honey bee populations across the world have seen increased mortality rates in the last few decades. The challenges facing the honey bee calls into question the future of our food supply. Beside various infectious diseases, Varroa destructor is one of the main culprits leading to increased rates of honey bee mortality. Varroa destructor is a parasitic mite which strongly depends on honey bee brood for reproduction and can wipe out entire colonies. However, climate variability may also importantly influence honey bee breeding cycles and bee mortality rates. Persistent weather events affects vegetation and hence foraging possibilities for honey bees. This study first defines critical statistical relationships between key climate indicators (e.g., precipitation and temperature) and bee mortality rates across Austria, using 6 consecutive years of data. Next, these leading indicators, as they vary in space and time, are used to build a statistical model to predict bee mortality rates and the respective number of colonies affected. Using leave-one-out cross validation, the model reduces the Root Mean Square Error (RMSE) by 21% with respect to predictions made with the mean mortality rate and the number of colonies. Furthermore, a Monte Carlo test is used to establish that the model's predictions are statistically significant at the 99.9% confidence level. These results highlight the influence of climate variables on honey bee populations, although variability in climate, by itself, cannot fully explain colony losses. This study was funded by the Austrian project 'Zukunft Biene'.