Science.gov

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

    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.

  4. 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

  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. 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

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. A Multistrategy Optimization Improved Artificial Bee Colony Algorithm

    PubMed Central

    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 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.

  13. New enhanced artificial bee colony (JA-ABC5) algorithm with application for reactive power optimization.

    PubMed

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

    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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Dynamic artificial bee colony algorithm for multi-parameters optimization of support vector machine-based soft-margin classifier

    NASA Astrophysics Data System (ADS)

    Yan, Yiming; Zhang, Ye; Gao, Fengjiao

    2012-12-01

    This article proposes a `dynamic' artificial bee colony (D-ABC) algorithm for solving optimizing problems. It overcomes the poor performance of artificial bee colony (ABC) algorithm, when applied to multi-parameters optimization. A dynamic `activity' factor is introduced to D-ABC algorithm to speed up convergence and improve the quality of solution. This D-ABC algorithm is employed for multi-parameters optimization of support vector machine (SVM)-based soft-margin classifier. Parameter optimization is significant to improve classification performance of SVM-based classifier. Classification accuracy is defined as the objection function, and the many parameters, including `kernel parameter', `cost factor', etc., form a solution vector to be optimized. Experiments demonstrate that D-ABC algorithm has better performance than traditional methods for this optimizing problem, and better parameters of SVM are obtained which lead to higher classification accuracy.

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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

  4. A spatially informative optic flow model of bee colony with saccadic flight strategy for global optimization.

    PubMed

    Das, Swagatam; Biswas, Subhodip; Panigrahi, Bijaya K; Kundu, Souvik; Basu, Debabrota

    2014-10-01

    This paper presents a novel search metaheuristic inspired from the physical interpretation of the optic flow of information in honeybees about the spatial surroundings that help them orient themselves and navigate through search space while foraging. The interpreted behavior combined with the minimal foraging is simulated by the artificial bee colony algorithm to develop a robust search technique that exhibits elevated performance in multidimensional objective space. Through detailed experimental study and rigorous analysis, we highlight the statistical superiority enjoyed by our algorithm over a wide variety of functions as compared to some highly competitive state-of-the-art methods.

  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.

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

    PubMed Central

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

    2013-01-01

    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

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. Chronic sublethal stress causes bee colony failure.

    PubMed

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

    2013-12-01

    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.

  14. Chronic sublethal stress causes bee colony failure.

    PubMed

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

    2013-12-01

    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. 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

  16. 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...

  17. 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

  18. Predictive markers of honey bee colony collapse.

    PubMed

    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.

  19. 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...

  20. 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.

  1. Pathogen webs in collapsing honey bee colonies.

    PubMed

    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.

  2. 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

  3. 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...

  4. 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.

  5. 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.

  6. 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

  7. 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...

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

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

    PubMed

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

    2013-11-06

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

  14. 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

  15. 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

  16. Genetic diversity in honey bee colonies enhances productivity and fitness.

    PubMed

    Mattila, Heather R; Seeley, Thomas D

    2007-07-20

    Honey bee queens mate with many males, creating numerous patrilines within colonies that are genetically distinct. The effects of genetic diversity on colony productivity and long-term fitness are unknown. We show that swarms from genetically diverse colonies (15 patrilines per colony) founded new colonies faster than swarms from genetically uniform colonies (1 patriline per colony). Accumulated differences in foraging rates, food storage, and population growth led to impressive boosts in the fitness (i.e., drone production and winter survival) of genetically diverse colonies. These results further our understanding of the origins of polyandry in honey bees and its benefits for colony performance.

  17. A quantitative model of honey bee colony population dynamics.

    PubMed

    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

  18. 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

  19. 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

  20. 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

  1. 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

    2016-09-09

    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.

  2. 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

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

    PubMed Central

    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

  4. 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

  5. Varroa-virus interaction in collapsing honey bee colonies.

    PubMed

    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.

  6. 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

  7. 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.

  8. 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

  9. Modelling food and population dynamics in honey bee colonies.

    PubMed

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

    2013-01-01

    Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee population dynamics to explore how food availability and bee death rates interact to determine colony growth and development. Our model uses simple differential equations to represent the transitions of eggs laid by the queen to brood, then hive bees and finally forager bees, and the process of social inhibition that regulates the rate at which hive bees begin to forage. We assume that food availability can influence both the number of brood successfully reared to adulthood and the rate at which bees transition from hive duties to foraging. The model predicts complex interactions between food availability and forager death rates in shaping colony fate. Low death rates and high food availability results in stable bee populations at equilibrium (with population size strongly determined by forager death rate) but consistently increasing food reserves. At higher death rates food stores in a colony settle at a finite equilibrium reflecting the balance of food collection and food use. When forager death rates exceed a critical threshold the colony fails but residual food remains. Our model presents a simple mathematical framework for exploring the interactions of food and forager mortality on colony fate, and provides the mathematical basis for more involved simulation models of hive performance. PMID:23667418

  10. Modelling Food and Population Dynamics in Honey Bee Colonies

    PubMed Central

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

    2013-01-01

    Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee population dynamics to explore how food availability and bee death rates interact to determine colony growth and development. Our model uses simple differential equations to represent the transitions of eggs laid by the queen to brood, then hive bees and finally forager bees, and the process of social inhibition that regulates the rate at which hive bees begin to forage. We assume that food availability can influence both the number of brood successfully reared to adulthood and the rate at which bees transition from hive duties to foraging. The model predicts complex interactions between food availability and forager death rates in shaping colony fate. Low death rates and high food availability results in stable bee populations at equilibrium (with population size strongly determined by forager death rate) but consistently increasing food reserves. At higher death rates food stores in a colony settle at a finite equilibrium reflecting the balance of food collection and food use. When forager death rates exceed a critical threshold the colony fails but residual food remains. Our model presents a simple mathematical framework for exploring the interactions of food and forager mortality on colony fate, and provides the mathematical basis for more involved simulation models of hive performance. PMID:23667418

  11. 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

  12. 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

    2015-06-01

    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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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 ...

  19. Honey bee colonies are group-level adaptive units.

    PubMed

    Seeley, T D

    1997-07-01

    It is not widely recognized that natural selection has produced adaptive units at the level of groups. Multilevel selection theory shows that groups can evolve a high level of functional organization when between-group selection predominates over within-group selection. Strong empirical evidence that natural selection has produced adaptive units at the group level comes from studies of social insects in which we find colonies in certain species functioning as highly integrated units. The functional organization of a social insect colony is best understood for honey bees. Recent experimental analyses of honey bee colonies have revealed striking group-level adaptations that improve the foraging efficiency of colonies, including special systems of communication and feedback control. These findings are reviewed with the aim of showing that evolution has produced adaptively organized entities at the group level.

  20. 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.

  1. 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

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

    PubMed Central

    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

  3. 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.

  4. 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...

  5. 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...

  6. Surplus nectar available for subalpine bumble bee colony growth.

    PubMed

    Elliott, Susan E

    2009-12-01

    Mutualisms may cause coupled population expansion or decline if both partners respond to variation in the other's abundance. Many studies have shown how the abundance of animal mutualists affects plant reproduction, but less is known about how the abundance of plant mutualists affects animal reproduction. Over 2 yr, I compared reproduction of the bumble bee, Bombus appositus, across meadows that varied naturally in flower density, and I compared reproduction between fed colonies and unfed control colonies. Colony reproduction (gyne, worker, and male production) was constant across meadows that varied naturally in flower density. Forager densities per flower did not vary among meadows, and daily nectar depletion was consistently low across meadows, suggesting that bees had ample nectar in all meadows. However, colonies directly fed with supplemental nectar and pollen generally produced over twice as many gynes as control colonies. Feeding did not affect male or worker production. Although colonies may benefit from food supplementation at the nest, it is possible that they may not benefit from additional flowers because they have too few workers to collect extra resources. PMID:20021764

  7. Honey Bee-Infecting Plant Virus with Implications on Honey Bee Colony Health

    PubMed Central

    Flenniken, Michelle L.

    2014-01-01

    ABSTRACT Honey bees are eusocial insects that are commercially managed to provide pollination services for agricultural crops. Recent increased losses of honey bee colonies (averaging 32% annually since 2006) are associated with the incidence and abundance of pathogens. In their study in mBio, J. L. Li et al. [mBio 5(1):e00898-13, 2014, doi:10.1128/mBio.00898-13] share their discovery that a plant virus, tobacco ring spot virus (TRSV), replicates in honey bees and that the prevalence of this virus was high in weak colonies. Their findings increase our understanding of the role of viruses in honey bee colony losses and underscore the importance of surveying for new and/or emerging viruses in honey bees. Furthermore, their findings will pique the interest of virologists and biologists across all disciplines. The discovery that a plant virus (TRSV) replicates, spreads, and negatively affects the health of an insect host will lead to additional studies on the mechanisms of host-specific adaptation and the role of cross-kingdom infections in the transmission of this virus. PMID:24570369

  8. Honey bee-infecting plant virus with implications on honey bee colony health.

    PubMed

    Flenniken, Michelle L

    2014-01-01

    Honey bees are eusocial insects that are commercially managed to provide pollination services for agricultural crops. Recent increased losses of honey bee colonies (averaging 32% annually since 2006) are associated with the incidence and abundance of pathogens. In their study in mBio, J. L. Li et al. [mBio 5(1):e00898-13, 2014, doi:10.1128/mBio.00898-13] share their discovery that a plant virus, tobacco ring spot virus (TRSV), replicates in honey bees and that the prevalence of this virus was high in weak colonies. Their findings increase our understanding of the role of viruses in honey bee colony losses and underscore the importance of surveying for new and/or emerging viruses in honey bees. Furthermore, their findings will pique the interest of virologists and biologists across all disciplines. The discovery that a plant virus (TRSV) replicates, spreads, and negatively affects the health of an insect host will lead to additional studies on the mechanisms of host-specific adaptation and the role of cross-kingdom infections in the transmission of this virus. PMID:24570369

  9. 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

  10. Sudden deaths and colony population decline in Greek honey bee colonies.

    PubMed

    Bacandritsos, N; Granato, A; Budge, G; Papanastasiou, I; Roinioti, E; Caldon, M; Falcaro, C; Gallina, A; Mutinelli, F

    2010-11-01

    During June and July of 2009, sudden deaths, tremulous movements and population declines of adult honey bees were reported by the beekeepers in the region of Peloponnesus (Mt. Mainalo), Greece. A preliminary study was carried out to investigate these unexplained phenomena in this region. In total, 37 bee samples, two brood frames containing honey bee brood of various ages, eight sugar samples and four sugar patties were collected from the affected colonies. The samples were tested for a range of pests, pathogens and pesticides. Symptomatic adult honey bees tested positive for Varroa destructor, Nosema ceranae, Chronic bee paralysis virus (CBPV), Acute paralysis virus (ABPV), Deformed wing virus (DWV), Sacbrood virus (SBV) and Black queen cell virus (BQCV), but negative for Acarapis woodi. American Foulbrood was absent from the brood samples. Chemical analysis revealed that amitraz, thiametoxan, clothianidin and acetamiprid were all absent from symptomatic adult bees, sugar and sugar patty samples. However, some bee samples, were contaminated with imidacloprid in concentrations between 14 ng/g and 39 ng/g tissue. We present: the infection of Greek honey bees by multiple viruses; the presence of N. ceranae in Greek honey bees and the first record of imidacloprid (neonicotonoid) residues in Greek honey bee tissues. The presence of multiple pathogens and pesticides made it difficult to associate a single specific cause to the depopulation phenomena observed in Greece, although we believe that viruses and N. ceranae synergistically played the most important role. A follow-up in-depth survey across all Greek regions is required to provide context to these preliminary findings.

  11. Sudden deaths and colony population decline in Greek honey bee colonies.

    PubMed

    Bacandritsos, N; Granato, A; Budge, G; Papanastasiou, I; Roinioti, E; Caldon, M; Falcaro, C; Gallina, A; Mutinelli, F

    2010-11-01

    During June and July of 2009, sudden deaths, tremulous movements and population declines of adult honey bees were reported by the beekeepers in the region of Peloponnesus (Mt. Mainalo), Greece. A preliminary study was carried out to investigate these unexplained phenomena in this region. In total, 37 bee samples, two brood frames containing honey bee brood of various ages, eight sugar samples and four sugar patties were collected from the affected colonies. The samples were tested for a range of pests, pathogens and pesticides. Symptomatic adult honey bees tested positive for Varroa destructor, Nosema ceranae, Chronic bee paralysis virus (CBPV), Acute paralysis virus (ABPV), Deformed wing virus (DWV), Sacbrood virus (SBV) and Black queen cell virus (BQCV), but negative for Acarapis woodi. American Foulbrood was absent from the brood samples. Chemical analysis revealed that amitraz, thiametoxan, clothianidin and acetamiprid were all absent from symptomatic adult bees, sugar and sugar patty samples. However, some bee samples, were contaminated with imidacloprid in concentrations between 14 ng/g and 39 ng/g tissue. We present: the infection of Greek honey bees by multiple viruses; the presence of N. ceranae in Greek honey bees and the first record of imidacloprid (neonicotonoid) residues in Greek honey bee tissues. The presence of multiple pathogens and pesticides made it difficult to associate a single specific cause to the depopulation phenomena observed in Greece, although we believe that viruses and N. ceranae synergistically played the most important role. A follow-up in-depth survey across all Greek regions is required to provide context to these preliminary findings. PMID:20804765

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. Colony Level Prevalence and Intensity of Nosema ceranae in Honey Bees (Apis mellifera L.)

    PubMed Central

    Lucas, Hannah M.; Webster, Thomas C.; Sagili, Ramesh R.

    2016-01-01

    Nosema ceranae is a widely prevalent microsporidian parasite in the western honey bee. There is considerable uncertainty regarding infection dynamics of this important pathogen in honey bee colonies. Understanding the infection dynamics at the colony level may aid in development of a reliable sampling protocol for N. ceranae diagnosis, and provide insights into efficient treatment strategies. The primary objective of this study was to characterize the prevalence (proportion of the sampled bees found infected) and intensity (number of spores per bee) of N. ceranae infection in bees from various age cohorts in a colony. We examined N. ceranae infection in both overwintered colonies that were naturally infected with N. ceranae and in quadruple cohort nucleus colonies that were established and artificially inoculated with N. ceranae. We also examined and quantified effects of N. ceranae infection on hypopharyngeal gland protein content and gut pH. There was no correlation between the prevalence and intensity of N. ceranae infection in composite samples (pooled bee samples used for analysis). Our results indicated that the prevalence and intensity of N. ceranae infection is significantly influenced by honey bee age. The N. ceranae infection prevalence values from composite samples of background bees (unmarked bees collected from four different locations in a colony) were not significantly different from those pertaining to marked-bee age cohorts specific to each sampling date. The foraging-aged bees had a higher prevalence of N. ceranae infection when compared to nurse-aged bees. N. ceranae did not have a significant effect on hypopharyngeal gland protein content. Further, there was no significant difference in mean gut pH of N. ceranae infected bees and non-infected bees. This study provides comprehensive insights into N. ceranae infection dynamics at the colony level, and also demonstrates the effects of N. ceranae infection on hypopharyngeal gland protein content and

  18. 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.

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

    PubMed

    Cox-Foster, Diana L; Conlan, Sean; Holmes, Edward C; Palacios, Gustavo; Evans, Jay D; Moran, Nancy A; Quan, Phenix-Lan; Briese, Thomas; Hornig, Mady; Geiser, David M; Martinson, Vince; vanEngelsdorp, Dennis; Kalkstein, Abby L; Drysdale, Andrew; Hui, Jeffrey; Zhai, Junhui; Cui, Liwang; Hutchison, Stephen K; Simons, Jan Fredrik; Egholm, Michael; Pettis, Jeffery S; Lipkin, W Ian

    2007-10-12

    In colony collapse disorder (CCD), honey bee colonies inexplicably lose their workers. CCD has resulted in a loss of 50 to 90% of colonies in beekeeping operations across the United States. The observation that irradiated combs from affected colonies can be repopulated with naive bees suggests that infection may contribute to CCD. We used an unbiased metagenomic approach to survey microflora in CCD hives, normal hives, and imported royal jelly. Candidate pathogens were screened for significance of association with CCD by the examination of samples collected from several sites over a period of 3 years. One organism, Israeli acute paralysis virus of bees, was strongly correlated with CCD.

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

    PubMed

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

    2014-07-18

    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.

  1. An artificial bee colony algorithm for uncertain portfolio selection.

    PubMed

    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

  2. An artificial bee colony algorithm for uncertain portfolio selection.

    PubMed

    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.

  3. 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

  4. 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.

  5. 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.

  6. 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...

  7. Dynamics of the Presence of Israeli Acute Paralysis Virus in Honey Bee Colonies with Colony Collapse Disorder

    PubMed Central

    Hou, Chunsheng; Rivkin, Hadassah; Slabezki, Yossi; Chejanovsky, Nor

    2014-01-01

    The determinants of Colony Collapse Disorder (CCD), a particular case of collapse of honey bee colonies, are still unresolved. Viruses including the Israeli acute paralysis virus (IAPV) were associated with CCD. We found an apiary with colonies showing typical CCD characteristics that bore high loads of IAPV, recovered some colonies from collapse and tested the hypothesis if IAPV was actively replicating in them and infectious to healthy bees. We found that IAPV was the dominant pathogen and it replicated actively in the colonies: viral titers decreased from April to September and increased from September to December. IAPV extracted from infected bees was highly infectious to healthy pupae: they showed several-fold amplification of the viral genome and synthesis of the virion protein VP3. The health of recovered colonies was seriously compromised. Interestingly, a rise of IAPV genomic copies in two colonies coincided with their subsequent collapse. Our results do not imply IAPV as the cause of CCD but indicate that once acquired and induced to replication it acts as an infectious factor that affects the health of the colonies and may determine their survival. This is the first follow up outside the US of CCD-colonies bearing IAPV under natural conditions. PMID:24800677

  8. Dynamics of the presence of israeli acute paralysis virus in honey bee colonies with colony collapse disorder.

    PubMed

    Hou, Chunsheng; Rivkin, Hadassah; Slabezki, Yossi; Chejanovsky, Nor

    2014-05-05

    The determinants of Colony Collapse Disorder (CCD), a particular case of collapse of honey bee colonies, are still unresolved. Viruses including the Israeli acute paralysis virus (IAPV) were associated with CCD. We found an apiary with colonies showing typical CCD characteristics that bore high loads of IAPV, recovered some colonies from collapse and tested the hypothesis if IAPV was actively replicating in them and infectious to healthy bees. We found that IAPV was the dominant pathogen and it replicated actively in the colonies: viral titers decreased from April to September and increased from September to December. IAPV extracted from infected bees was highly infectious to healthy pupae: they showed several-fold amplification of the viral genome and synthesis of the virion protein VP3. The health of recovered colonies was seriously compromised. Interestingly, a rise of IAPV genomic copies in two colonies coincided with their subsequent collapse. Our results do not imply IAPV as the cause of CCD but indicate that once acquired and induced to replication it acts as an infectious factor that affects the health of the colonies and may determine their survival. This is the first follow up outside the US of CCD-colonies bearing IAPV under natural conditions.

  9. Heat shielding: A novel method of colonial thermoregulation in honey bees.

    PubMed

    Starks, P T; Gilley, D C

    1999-09-01

    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.

  10. 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."

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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...

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. Protein levels and colony development of Africanized and European honey bees fed natural and artificial diets.

    PubMed

    Morais, M M; Turcatto, A P; Pereira, R A; Francoy, T M; Guidugli-Lazzarini, K R; Gonçalves, L S; de Almeida, J M V; Ellis, J D; De Jong, D

    2013-12-19

    Pollen substitute diets are a valuable resource for maintaining strong and health honey bee colonies. Specific diets may be useful in one region or country and inadequate or economically unviable in others. We compared two artificial protein diets that had been formulated from locally-available ingredients in Brazil with bee bread and a non-protein sucrose diet. Groups of 100 newly-emerged, adult workers of Africanized honey bees in Brazil and European honey bees in the USA were confined in small cages and fed on one of four diets for seven days. The artificial diets included a high protein diet made of soy milk powder and albumin, and a lower protein level diet consisting of soy milk powder, brewer's yeast and rice bran. The initial protein levels in newly emerged bees were approximately 18-21 µg/µL hemolymph. After feeding on the diets for seven days, the protein levels in the hemolymph were similar among the protein diet groups (~37-49 µg/µL after seven days), although Africanized bees acquired higher protein levels, increasing 145 and 100% on diets D1 and D2, respectively, versus 83 and 60% in the European bees. All the protein diets resulted in significantly higher levels of protein than sucrose solution alone. In the field, the two pollen substitute diets were tested during periods of low pollen availability in the field in two regions of Brazil. Food consumption, population development, colony weight, and honey production were evaluated to determine the impact of the diets on colony strength parameters. The colonies fed artificial diets had a significant improvement in all parameters, while control colonies dwindled during the dearth period. We conclude that these two artificial protein diets have good potential as pollen substitutes during dearth periods and that Africanized bees more efficiently utilize artificial protein diets than do European honey bees.

  4. Viral prevalence increases with regional colony abundance in honey bee drones (Apis mellifera L).

    PubMed

    Forfert, Nadège; Natsopoulou, Myrsini E; Paxton, Robert J; Moritz, Robin F A

    2016-10-01

    Transmission among colonies is a central feature for the epidemiology of honey bee pathogens. High colony abundance may promote transmission among colonies independently of apiary layout, making colony abundance a potentially important parameter determining pathogen prevalence in populations of honey bees. To test this idea, we sampled male honey bees (drones) from seven distinct drone congregation areas (DCA), and used their genotypes to estimate colony abundance at each site. A multiplex ligation dependent probe amplification assay (MLPA) was used to assess the prevalence of ten viruses, using five common viral targets, in individual drones. There was a significant positive association between colony abundance and number of viral infections. This result highlights the potential importance of high colony abundance for pathogen prevalence, possibly because high population density facilitates pathogen transmission. Pathogen prevalence in drones collected from DCAs may be a useful means of estimating the disease status of a population of honey bees during the mating season, especially for localities with a large number of wild or feral colonies.

  5. 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...

  6. Viral prevalence increases with regional colony abundance in honey bee drones (Apis mellifera L).

    PubMed

    Forfert, Nadège; Natsopoulou, Myrsini E; Paxton, Robert J; Moritz, Robin F A

    2016-10-01

    Transmission among colonies is a central feature for the epidemiology of honey bee pathogens. High colony abundance may promote transmission among colonies independently of apiary layout, making colony abundance a potentially important parameter determining pathogen prevalence in populations of honey bees. To test this idea, we sampled male honey bees (drones) from seven distinct drone congregation areas (DCA), and used their genotypes to estimate colony abundance at each site. A multiplex ligation dependent probe amplification assay (MLPA) was used to assess the prevalence of ten viruses, using five common viral targets, in individual drones. There was a significant positive association between colony abundance and number of viral infections. This result highlights the potential importance of high colony abundance for pathogen prevalence, possibly because high population density facilitates pathogen transmission. Pathogen prevalence in drones collected from DCAs may be a useful means of estimating the disease status of a population of honey bees during the mating season, especially for localities with a large number of wild or feral colonies. PMID:27444641

  7. 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 ...

  8. 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.

  9. 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

  10. Evaluation of lysozyme-HCl for the treatment of chalkbrood disease in honey bee colonies.

    PubMed

    Van Haga, A; Keddie, B A; Pernal, S F

    2012-12-01

    Chalkbrood, caused by Ascosphaera apis (Maassen and Claussen) Olive and Spiltor, is a cosmopolitan fungal disease of honey bee larvae (Apis mellifera L.) for which there is no chemotherapeutic control. We evaluated the efficacy of lysozyme-HCl, an inexpensive food-grade antimicrobial extracted from hen egg white, for the treatment of chalkbrood disease in honey bee colonies. Our study compared three doses of lysozyme-HCl in sugar syrup (600, 3,000, and 6,000 mg) administered weekly for 3 wk among chalkbrood-inoculated colonies, colonies that were inoculated but remained untreated, and colonies neither inoculated or treated. Lysozyme-HCl at the highest dose evaluated was found to suppress development of chalkbrood disease in inoculated colonies to levels observed in uninoculated, untreated colonies, and did not adversely affect adult bee survival or brood production. Honey production was significantly negatively correlated with increased disease severity but there were no significant differences in winter survival among treatment groups. Based on our results, lysozyme-HCl appears to be a promising, safe therapeutic agent for the control of chalkbrood in honey bee colonies.

  11. A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm

    PubMed Central

    Ju, Chunhua

    2013-01-01

    Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony (ABC) algorithm to overcome the local optimal problem caused by K-means. After that we adopt the modified cosine similarity to compute the similarity between users in the same clusters. Finally, we generate recommendation results for the corresponding target users. Detailed numerical analysis on a benchmark dataset MovieLens and a real-world dataset indicates that our new collaborative filtering approach based on users clustering algorithm outperforms many other recommendation methods. PMID:24381525

  12. 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.

  13. Manipulation of colony environment modulates honey bee aggression and brain gene expression

    PubMed Central

    Rittschof, Clare C.; Robinson, Gene E.

    2013-01-01

    The social environment plays an essential role in shaping behavior for most animals. Social effects on behavior are often linked to changes in brain gene expression (Robinson et al., 2008). In the honey bee (Apis mellifera L.), social modulation of individual aggression allows colonies to adjust the intensity with which they defend their hive in response to predation threat (Alaux & Robinson, 2007, Couvillon et al., 2008, Hunt et al., 2003). Previous research has demonstrated social effects on both aggression and aggression-related brain gene expression in honey bees, caused by alarm pheromone and unknown factors related to colony genotype (Alaux et al., 2009b). For example, some bees from less aggressive genetic stock reared in colonies with genetic predispositions toward increased aggression show both increased aggression and more aggressive-like brain gene expression profiles (Alaux et al., 2009b, Guzmán-Novoa et al., 2004). We tested the hypothesis that exposure to a colony environment influenced by high levels of predation threat results in increased aggression and aggressive-like gene expression patterns in individual bees. We assessed gene expression using four marker genes. Experimentally induced predation threats modified behavior, but the effect was opposite of our predictions: disturbed colonies showed decreased aggression. Disturbed colonies also decreased foraging activity, suggesting that they did not habituate to threats; other explanations for this finding are discussed. Bees in disturbed colonies also showed changes in brain gene expression, some of which paralleled behavioral findings. These results demonstrate that bee aggression, and associated molecular processes, are subject to complex social influences. PMID:24034579

  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.

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

    PubMed

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

    2012-11-01

    Reported widespread declines of wild and managed insect pollinators have serious consequences for global ecosystem services and agricultural production. Bees contribute approximately 80% of insect pollination, so it is important to understand and mitigate the causes of current declines in bee populations . Recent studies have implicated the role of pesticides in these declines, as exposure to these chemicals has been associated with changes in bee behaviour and reductions in colony queen production. However, the key link between changes in individual behaviour and the consequent impact at the colony level has not been shown. Social bee colonies depend on the collective performance of many individual workers. Thus, although field-level pesticide concentrations can have subtle or sublethal effects at the individual level, it is not known whether bee societies can buffer such effects or whether it results in a severe cumulative effect at the colony level. Furthermore, widespread agricultural intensification means that bees are exposed to numerous pesticides when foraging, yet the possible combinatorial effects of pesticide exposure have rarely been investigated. 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 that 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.

  16. 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).

  17. 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.

  18. 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...

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  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. Functional flexibility of the honey bee hypopharyngeal gland in a dequeened colony.

    PubMed

    Ohashi, K; Sasaki, M; Sasagawa, H; Nakamura, J; Natori, S; Kubo, T

    2000-11-01

    The role of the worker honey bee Apis mellifera L. changes depending on age after eclosion (age polyethism): young workers (nurse bees) take care of their brood by synthesizing and secreting brood food (royal jelly), while older workers (foragers) forage for nectar and process it into honey. Previously, we showed that the major proteins synthesized in the hypopharyngeal gland of the worker change from brood food proteins to alpha-glucosidase at the single secretory cell level in parallel with this age polyethism [Kubo et al., J. Biochem. 119, 291-295 (1996); Ohashi et al., Eur. J. Biochem. 249, 797-802 (1997)]. Here, we examined whether the function of the hypopharyngeal gland has flexibility depending on the colony conditions, by creating a dequeened colony in which the older workers were compelled to feed the drone larvae. It was found that most of the older workers in the dequeened colony synthesized brood food proteins as did nurse bees. Furthermore, the percentage of workers that synthesized brood food proteins was maintained at 80-90% of the total workers for at least two months, as in a normal colony. These results indicate that the function of the hypopharyngeal gland cells of the worker has flexibility and can, if necessary, be maintained as that of the nurse bee, depending on the condition of the colony.

  6. 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

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

    PubMed Central

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

    2016-01-01

    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

  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. Changes in learning and foraging behaviour within developing bumble bee (Bombus terrestris) colonies.

    PubMed

    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.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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,...

  20. 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 ...

  1. Artificial Bee Colony Algorithm for Transient Performance Augmentation of Grid Connected Distributed Generation

    NASA Astrophysics Data System (ADS)

    Chatterjee, A.; Ghoshal, S. P.; Mukherjee, V.

    In this paper, a conventional thermal power system equipped with automatic voltage regulator, IEEE type dual input power system stabilizer (PSS) PSS3B and integral controlled automatic generation control loop is considered. A distributed generation (DG) system consisting of aqua electrolyzer, photovoltaic cells, diesel engine generator, and some other energy storage devices like flywheel energy storage system and battery energy storage system is modeled. This hybrid distributed system is connected to the grid. While integrating this DG with the onventional thermal power system, improved transient performance is noticed. Further improvement in the transient performance of this grid connected DG is observed with the usage of superconducting magnetic energy storage device. The different tunable parameters of the proposed hybrid power system model are optimized by artificial bee colony (ABC) algorithm. The optimal solutions offered by the ABC algorithm are compared with those offered by genetic algorithm (GA). It is also revealed that the optimizing performance of the ABC is better than the GA for this specific application.

  2. 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

  3. Distance Between Honey Bee Apis mellifera Colonies Regulates Populations of Varroa destructor at a Landscape Scale

    PubMed Central

    Nolan, Maxcy P.; Delaplane, Keith S.

    2016-01-01

    Inter-colony distance of Apis mellifera significantly affects colony numbers of the parasitic mite Varroa destructor. We set up 15 apiaries, each consisting of two colonies. Each apiary pair was assigned an inter-colony distance of 0, 10, or 100 m. Colonies were rendered nearly mite-free, then one colony in each pair was seeded with 300 female mites (mite-donor colony), while the other remained uninoculated (mite-recipient colony). After four months of monitoring, a whole model analysis showed that apiaries in which colonies were spaced 100 m apart contained lower average mite numbers than 0 m or 10 m apiaries. There were interactions among colony type, distance, and sampling date; however, when there were significant differences mite numbers were always lower in 100 m apiaries than 10 m apiaries. These findings pose the possibility that Varroa populations are resource regulated at a landscape scale: near-neighbor colonies constitute reproductive resource for mites in the form of additional bee brood. PMID:27812228

  4. Molecular identification of chronic bee paralysis virus infection in Apis mellifera colonies in Japan.

    PubMed

    Morimoto, Tomomi; Kojima, Yuriko; Yoshiyama, Mikio; Kimura, Kiyoshi; Yang, Bu; Kadowaki, Tatsuhiko

    2012-07-01

    Chronic bee paralysis virus (CBPV) infection causes chronic paralysis and loss of workers in honey bee colonies around the world. Although CBPV shows a worldwide distribution, it had not been molecularly detected in Japan. Our investigation of Apis mellifera and Apis cerana japonica colonies with RT-PCR has revealed CBPV infection in A. mellifera but not A. c. japonica colonies in Japan. The prevalence of CBPV is low compared with that of other viruses: deformed wing virus (DWV), black queen cell virus (BQCV), Israel acute paralysis virus (IAPV), and sac brood virus (SBV), previously reported in Japan. Because of its low prevalence (5.6%) in A. mellifera colonies, the incidence of colony losses by CBPV infection must be sporadic in Japan. The presence of the (-) strand RNA in dying workers suggests that CBPV infection and replication may contribute to their symptoms. Phylogenetic analysis demonstrates a geographic separation of Japanese isolates from European, Uruguayan, and mainland US isolates. The lack of major exchange of honey bees between Europe/mainland US and Japan for the recent 26 years (1985-2010) may have resulted in the geographic separation of Japanese CBPV isolates. PMID:22852042

  5. Molecular Identification of Chronic Bee Paralysis Virus Infection in Apis mellifera Colonies in Japan

    PubMed Central

    Morimoto, Tomomi; Kojima, Yuriko; Yoshiyama, Mikio; Kimura, Kiyoshi; Yang, Bu; Kadowaki, Tatsuhiko

    2012-01-01

    Chronic bee paralysis virus (CBPV) infection causes chronic paralysis and loss of workers in honey bee colonies around the world. Although CBPV shows a worldwide distribution, it had not been molecularly detected in Japan. Our investigation of Apis mellifera and Apis cerana japonica colonies with RT-PCR has revealed CBPV infection in A. mellifera but not A. c. japonica colonies in Japan. The prevalence of CBPV is low compared with that of other viruses: deformed wing virus (DWV), black queen cell virus (BQCV), Israel acute paralysis virus (IAPV), and sac brood virus (SBV), previously reported in Japan. Because of its low prevalence (5.6%) in A. mellifera colonies, the incidence of colony losses by CBPV infection must be sporadic in Japan. The presence of the (−) strand RNA in dying workers suggests that CBPV infection and replication may contribute to their symptoms. Phylogenetic analysis demonstrates a geographic separation of Japanese isolates from European, Uruguayan, and mainland US isolates. The lack of major exchange of honey bees between Europe/mainland US and Japan for the recent 26 years (1985–2010) may have resulted in the geographic separation of Japanese CBPV isolates. PMID:22852042

  6. 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.

  7. 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

  8. 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

  9. 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...

  10. 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...

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Screening alternative therapies to control Nosemosis type C in honey bee (Apis mellifera iberiensis) colonies.

    PubMed

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

    2013-12-01

    Nosemosis type C caused by the microsporidium Nosema ceranae is one of the most widespread of the adult honey bee diseases, and due to its detrimental effects on both strength and productivity of honey bee colonies, an appropriate control of this disease is advisable. Fumagillin is the only veterinary medicament recommended by the World Organization for Animal Health (OIE) to suppress infections by Nosema, but the use of this antibiotic is prohibited in the European Union and few alternatives are available at present to control the disease. In the present study three therapeutic agents (Nosestat®, Phenyl salicylate and Vitafeed Gold®) have been tested to control N. ceranae infection in honey bee colonies, and have been compared to the use of fumagillin. None of the products tested was effective against Nosema under our experimental conditions. Low consumption of the different doses of treatments may have had a strong influence on the results obtained, highlighting the importance of this issue and emphasizing that this should be evaluated in studies to test therapeutic treatments of honey bee colonies.

  19. 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

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

    PubMed

    Yoder, Jay A; Jajack, Andrew J; Rosselot, Andrew E; Smith, Terrance J; Yerke, Mary Clare; Sammataro, Diana

    2013-01-01

    Fermentation by fungi converts stored pollen into bee bread that is fed to honey bee larvae, Apis mellifera, so the diversity of fungi in bee bread may be related to its food value. To explore the relationship between fungicide exposure and bee bread fungi, samples of bee bread collected from bee colonies pollinating orchards from 7 locations over 2 years were analyzed for fungicide residues and fungus composition. There were detectable levels of fungicides from regions that were sprayed before bloom. An organic orchard had the highest quantity and variety of fungicides, likely due to the presence of treated orchards within bees' flight range. Aspergillus, Penicillium, Rhizopus, and Cladosporium (beneficial fungi) were the primary fungal isolates found, regardless of habitat differences. There was some variation in fungal components amongst colonies, even within the same apiary. The variable components were Absidia, Alternaria, Aureobasidium, Bipolaris, Fusarium, Geotrichum, Mucor, Nigrospora, Paecilomyces, Scopulariopsis, and Trichoderma. The number of fungal isolates was reduced as an effect of fungicide contamination. Aspergillus abundance was particularly affected by increased fungicide levels, as indicated by Simpson's diversity index. Bee bread showing fungicide contamination originated from colonies, many of which showed chalkbrood symptoms.

  1. 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

  2. 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

  3. Exposure to pesticides at sublethal level and their distribution within a honey bee (Apis mellifera) colony.

    PubMed

    Smodis Skerl, Maja Ivana; Kmecl, Veronika; Gregorc, Ales

    2010-08-01

    Honey bee colonies were exposed to pesticides used in agriculture or within bee hives by beekeepers: coumaphos; diazinon; amitraz or fluvalinate. Samples of bee workers, larvae and royal jelly were analysed using Gas Chromatography-Electron Capture Detection (GC-ECD). Amitraz was quantified using High Performance Liquid Chromatography (HPLC), and Gas Chromatography-Tandem Mass Spectrometry (GC/MS/MS) was used for quantification of diazinon. Sixth day after treatment, coumaphos was found in the royal jelly (250 ng/g) secreted by nurse workers and fluvalinate was found in both bee heads (105 ng/g, 8 days after treatment) and in larvae (110 ng/g, 4 days after treatment). Amitraz residues in all sampled material were below the level of detection of 10 ng/g. Diazinon was not detected in any of the analysed samples. The large quantities of fluvalinate found in bee heads and larvae, the coumaphos residues in royal jelly, and additional potential sub-lethal effects on individual honey bees or brood are discussed.

  4. Learning and memory in workers reared by nutritionally stressed honey bee (Apis mellifera L.) colonies.

    PubMed

    Mattila, Heather R; Smith, Brian H

    2008-12-15

    Chronic nutritional stress can have a negative impact on an individual's learning ability and memory. However, in social animals that share food among group members, such as the honey bee (Apis mellifera L.), it is unknown whether group-level nutritional stress is manifested in the learning performance of individuals. Accordingly, we examined learning and memory in honey bee workers reared by colonies exposed to varying degrees of long-term pollen stress. Pollen provides honey bee workers with almost all of the proteins, lipids, vitamins, and minerals that they require as larvae and adults. Colonies were created that were either chronically pollen poor or pollen rich, or were intermediate in pollen supply; treatments altered colonies' pollen stores and brood-rearing capacity. Workers from these colonies were put through a series of olfactory-conditioning assays using proboscis-extension response (PER). PER thresholds were determined, then workers learned in olfactory-conditioning trials to associate two floral odors (one novel and the other presented previously without reward) with stimulation with sucrose and a sucrose reward. The strength of the memory that was formed for the odor/sucrose association was tested after olfactory-conditioning assays ended. Colony-level nutritional status had no effect on worker learning or memory (response threshold of workers to sucrose, acquisition of the odor/sucrose association, occurrence of latent inhibition, or memory retention over 72 h). We conclude that potential effects of chronic, colony-wide nutrient deprivation on learning and memory are not found in workers, probably because colonies use brood-rearing capacity to buffer nutrient stress at the level of the individual.

  5. Weighing risk factors associated with bee colony collapse disorder by classification and regression tree analysis.

    PubMed

    VanEngelsdorp, Dennis; Speybroeck, Niko; Evans, Jay D; Nguyen, Bach Kim; Mullin, Chris; Frazier, Maryann; Frazier, Jim; Cox-Foster, Diana; Chen, Yanping; Tarpy, David R; Haubruge, Eric; Pettis, Jeffrey S; Saegerman, Claude

    2010-10-01

    Colony collapse disorder (CCD), a syndrome whose defining trait is the rapid loss of adult worker honey bees, Apis mellifera L., is thought to be responsible for a minority of the large overwintering losses experienced by U.S. beekeepers since the winter 2006-2007. Using the same data set developed to perform a monofactorial analysis (PloS ONE 4: e6481, 2009), we conducted a classification and regression tree (CART) analysis in an attempt to better understand the relative importance and interrelations among different risk variables in explaining CCD. Fifty-five exploratory variables were used to construct two CART models: one model with and one model without a cost of misclassifying a CCD-diagnosed colony as a non-CCD colony. The resulting model tree that permitted for misclassification had a sensitivity and specificity of 85 and 74%, respectively. Although factors measuring colony stress (e.g., adult bee physiological measures, such as fluctuating asymmetry or mass of head) were important discriminating values, six of the 19 variables having the greatest discriminatory value were pesticide levels in different hive matrices. Notably, coumaphos levels in brood (a miticide commonly used by beekeepers) had the highest discriminatory value and were highest in control (healthy) colonies. Our CART analysis provides evidence that CCD is probably the result of several factors acting in concert, making afflicted colonies more susceptible to disease. This analysis highlights several areas that warrant further attention, including the effect of sublethal pesticide exposure on pathogen prevalence and the role of variability in bee tolerance to pesticides on colony survivorship.

  6. Learning and memory in workers reared by nutritionally stressed honey bee (Apis mellifera L.) colonies.

    PubMed

    Mattila, Heather R; Smith, Brian H

    2008-12-15

    Chronic nutritional stress can have a negative impact on an individual's learning ability and memory. However, in social animals that share food among group members, such as the honey bee (Apis mellifera L.), it is unknown whether group-level nutritional stress is manifested in the learning performance of individuals. Accordingly, we examined learning and memory in honey bee workers reared by colonies exposed to varying degrees of long-term pollen stress. Pollen provides honey bee workers with almost all of the proteins, lipids, vitamins, and minerals that they require as larvae and adults. Colonies were created that were either chronically pollen poor or pollen rich, or were intermediate in pollen supply; treatments altered colonies' pollen stores and brood-rearing capacity. Workers from these colonies were put through a series of olfactory-conditioning assays using proboscis-extension response (PER). PER thresholds were determined, then workers learned in olfactory-conditioning trials to associate two floral odors (one novel and the other presented previously without reward) with stimulation with sucrose and a sucrose reward. The strength of the memory that was formed for the odor/sucrose association was tested after olfactory-conditioning assays ended. Colony-level nutritional status had no effect on worker learning or memory (response threshold of workers to sucrose, acquisition of the odor/sucrose association, occurrence of latent inhibition, or memory retention over 72 h). We conclude that potential effects of chronic, colony-wide nutrient deprivation on learning and memory are not found in workers, probably because colonies use brood-rearing capacity to buffer nutrient stress at the level of the individual. PMID:18761030

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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...

  15. 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 ...

  16. 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

  17. 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

  18. 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.

  19. 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

  20. A Modified Artificial Bee Colony Algorithm for p-Center Problems

    PubMed Central

    Yurtkuran, Alkın

    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

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. The effect of induced queen replacement on Nosema spp. infection in honey bee (Apis mellifera iberiensis) colonies.

    PubMed

    Botías, Cristina; Martín-Hernández, Raquel; Días, Joyce; García-Palencia, Pilar; Matabuena, María; Juarranz, Angeles; Barrios, Laura; Meana, Aránzazu; Nanetti, Antonio; Higes, Mariano

    2012-04-01

    Microsporidiosis of adult honeybees caused by Nosema apis and Nosema ceranae is a common worldwide disease with negative impacts on colony strength and productivity. Few options are available to control the disease at present. The role of the queen in bee population renewal and the replacement of bee losses due to Nosema infection is vital to maintain colony homeostasis. Younger queens have a greater egg laying potential and they produce a greater proportion of uninfected newly eclosed bees to compensate for adult bee losses; hence, a field study was performed to determine the effect of induced queen replacement on Nosema infection in honey bee colonies, focusing on colony strength and honey production. In addition, the impact of long-term Nosema infection of a colony on the ovaries and ventriculus of the queen was evaluated. Queen replacement resulted in a remarkable decrease in the rates of Nosema infection, comparable with that induced by fumagillin treatment. However, detrimental effects on the overall colony state were observed due to the combined effects of stressors such as the queenless condition, lack of brood and high infection rates. The ovaries and ventriculi of queens in infected colonies revealed no signs of Nosema infection and there were no lesions in ovarioles or epithelial ventricular cells.

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Acaricide Treatment Affects Viral Dynamics in Varroa destructor-Infested Honey Bee Colonies via both Host Physiology and Mite Control

    PubMed Central

    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

  16. 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

  17. 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

  18. 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...

  19. 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...

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

    PubMed

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

    2013-04-10

    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.

  1. [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

  2. Clinical signs of deformed wing virus infection are predictive markers for honey bee colony losses.

    PubMed

    Dainat, Benjamin; Neumann, Peter

    2013-03-01

    The ectoparasitic mite Varroa destructor acting as a virus vector constitutes a central mechanism for losses of managed honey bee, Apis mellifera, colonies. This creates demand for an easy, accurate and cheap diagnostic tool to estimate the impact of viruliferous mites in the field. Here we evaluated whether the clinical signs of the ubiquitous and mite-transmitted deformed wing virus (DWV) can be predictive markers of winter losses. In fall and winter 2007/2008, A.m. carnica workers with apparent wing deformities were counted daily in traps installed on 29 queenright colonies. The data show that colonies which later died had a significantly higher proportion of workers with wing deformities than did those which survived. There was a significant positive correlation between V. destructor infestation levels and the number of workers displaying DWV clinical signs, further supporting the mite's impact on virus infections at the colony level. A logistic regression model suggests that colony size, the number of workers with wing deformities and V. destructor infestation levels constitute predictive markers for winter colony losses in this order of importance and ease of evaluation.

  3. [Development of infestation with Varroa jacobsoni O. in bee colonies in Tunisia].

    PubMed

    Ritter, W; Michel, P; Schwendemann, A; Bartoldi, M

    1990-04-01

    The mite Varroa jacobsoni, an ectoparasite of the honey bee, was imported to Tunisia probably in 1976. Afterwards, this parasitosis caused severe losses of colonies for several years. The continued examination of the level of infestation in colonies of a "GTZ" project stated a steady number of mites since 1980. Only in a few colonies, the infestation was above the limit of damage. Though the colonies in North West Tunisia did not receive any treatment since 1986 there was no increase of infestation. In order to investigate the reason for this the mites' ability of reproduction was examined during two following years. The portion of infertile female mites in the worker brood in most of the colonies was with 50% considerably higher than in Europe. In Brazil, the adaptation between host and mite produced similar low reproduction rates. As, however, in Tunisia the portion of infertile females in the drone brood of the individual colonies corresponded to the one in the worker brood climatic conditions are supposed to be responsible.

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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.

  17. A Survey of Honey Bee Colony Losses in the U.S., Fall 2007 to Spring 2008

    PubMed Central

    vanEngelsdorp, Dennis; Hayes, Jerry; Underwood, Robyn M.; Pettis, Jeffery

    2008-01-01

    Background Honey bees are an essential component of modern agriculture. A recently recognized ailment, Colony Collapse Disorder (CCD), devastates colonies, leaving hives with a complete lack of bees, dead or alive. Up to now, estimates of honey bee population decline have not included losses occurring during the wintering period, thus underestimating actual colony mortality. Our survey quantifies the extent of colony losses in the United States over the winter of 2007–2008. Methodology/Principal Findings Surveys were conducted to quantify and identify management factors (e.g. operation size, hive migration) that contribute to high colony losses in general and CCD symptoms in particular. Over 19% of the country's estimated 2.44 million colonies were surveyed. A total loss of 35.8% of colonies was recorded; an increase of 11.4% compared to last year. Operations that pollinated almonds lost, on average, the same number of colonies as those that did not. The 37.9% of operations that reported having at least some of their colonies die with a complete lack of bees had a total loss of 40.8% of colonies compared to the 17.1% loss reported by beekeepers without this symptom. Large operations were more likely to have this symptom suggesting that a contagious condition may be a causal factor. Sixty percent of all colonies that were reported dead in this survey died without dead bees, and thus possibly suffered from CCD. In PA, losses varied with region, indicating that ambient temperature over winter may be an important factor. Conclusions/Significance Of utmost importance to understanding the recent losses and CCD is keeping track of losses over time and on a large geographic scale. Given that our surveys are representative of the losses across all beekeeping operations, between 0.75 and 1.00 million honey bee colonies are estimated to have died in the United States over the winter of 2007–2008. This article is an extensive survey of U.S. beekeepers across the continent

  18. 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.

  19. 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

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

    PubMed

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

    2011-04-01

    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.

  1. Colony-level variation in pollen collection and foraging preferences among wild-caught bumble bees (Hymenoptera: Apidae).

    PubMed

    Saifuddin, Mustafa; Jha, Shalene

    2014-04-01

    Given that many pollinators have exhibited dramatic declines related to habitat destruction, an improved understanding of pollinator resource collection across human-altered landscapes is essential to conservation efforts. Despite the importance of bumble bees (Bombus spp.) as global pollinators, little is known regarding how pollen collection patterns vary between individuals, colonies, and landscapes. In this study, Vosnesensky bumble bees (Bombus vosnesenskii Radoszkowski) were collected from a range of human-altered and natural landscapes in northern California. Extensive vegetation surveys and Geographic Information System (GIS)-based habitat classifications were conducted at each site, bees were genotyped to identify colony mates, and pollen loads were examined to identify visited plants. In contrast to predictions based on strong competitive interactions, pollen load composition was significantly more similar for bees captured in a shared study region compared with bees throughout the research area but was not significantly more similar for colony mates. Preference analyses revealed that pollen loads were not composed of the most abundant plant species per study region. The majority of ranked pollen preference lists were significantly correlated for pairwise comparisons of colony mates and individuals within a study region, whereas the majority of pairwise comparisons of ranked pollen preference lists between individuals located at separate study regions were uncorrelated. Results suggest that pollen load composition and foraging preferences are similar for bees throughout a shared landscape regardless of colony membership. The importance of native plant species in pollen collection is illustrated through preference analyses, and we suggest prioritization of specific rare native plant species for enhanced bumble bee pollen collection.

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. A novel artificial bee colony algorithm based on internal-feedback strategy for image template matching.

    PubMed

    Li, Bai; Gong, Li-Gang; Li, Ya

    2014-01-01

    Image template matching refers to the technique of locating a given reference image over a source image such that they are the most similar. It is a fundamental mission in the field of visual target recognition. In general, there are two critical aspects of a template matching scheme. One is similarity measurement and the other is best-match location search. In this work, we choose the well-known normalized cross correlation model as a similarity criterion. The searching procedure for the best-match location is carried out through an internal-feedback artificial bee colony (IF-ABC) algorithm. IF-ABC algorithm is highlighted by its effort to fight against premature convergence. This purpose is achieved through discarding the conventional roulette selection procedure in the ABC algorithm so as to provide each employed bee an equal chance to be followed by the onlooker bees in the local search phase. Besides that, we also suggest efficiently utilizing the internal convergence states as feedback guidance for searching intensity in the subsequent cycles of iteration. We have investigated four ideal template matching cases as well as four actual cases using different searching algorithms. Our simulation results show that the IF-ABC algorithm is more effective and robust for this template matching mission than the conventional ABC and two state-of-the-art modified ABC algorithms do.

  7. 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

  8. 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

  9. Ant Colony Optimization Algorithm for Continuous Domains Based on Position Distribution Model of Ant Colony Foraging

    PubMed Central

    Liu, Liqiang; Dai, Yuntao

    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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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

  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.

  19. 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

  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.

  1. 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

  2. Aircraft technology portfolio optimization using ant colony optimization

    NASA Astrophysics Data System (ADS)

    Villeneuve, Frederic J.; Mavris, Dimitri N.

    2012-11-01

    Technology portfolio selection is a combinatorial optimization problem often faced with a large number of combinations and technology incompatibilities. The main research question addressed in this article is to determine if Ant Colony Optimization (ACO) is better suited than Genetic Algorithms (GAs) and Simulated Annealing (SA) for technology portfolio optimization when incompatibility constraints between technologies are present. Convergence rate, capability to find optima, and efficiency in handling of incompatibilities are the three criteria of comparison. The application problem consists of finding the best technology portfolio from 29 aircraft technologies. The results show that ACO and GAs converge faster and find optima more easily than SA, and that ACO can optimize portfolios with technology incompatibilities without using penalty functions. This latter finding paves the way for more use of ACO when the number of constraints increases, such as in the technology and concept selection for complex engineering systems.

  3. 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.

  4. 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

  5. Honey bee colonies provided with natural forage have lower pathogen loads and higher overwinter survival than those fed protein supplements

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Symptoms of nutritional stress can manifest in several ways, including higher incidence of disease in stressed individuals. Honey bees experience nutritional stress when there is insufficient forage. During these times, managed colonies are fed protein supplements (PS). Recently, land managers have ...

  6. 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...

  7. 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...

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. Kin discrimination within honey bee (Apis mellifera) colonies: An analysis of the evidence.

    PubMed

    Breed, M D; Welch, C K; Cruz, R

    1994-12-01

    Compelling evolutionary arguments lead to the prediction that honey bee workers should discriminate between supersisters and half-sisters within colonies. We review the theoretical support for discrimination during swarming, queen rearing, feeding, and grooming. A survey of the data that tests whether such discrimination takes place shows that, despite substantial effort in a number of laboratories, there is no conclusive evidence for intracolony discrimination in any of the postulated contexts. The strongest suggestive data is in the critical context of queen rearing, but flaws in experimental design or analysis make the best available tests inconclusive. We present new data that shows that cues exist on which discriminations can be made among adult workers in nestmate recognition interactions and in feeding interactions, but our data does not differentiate between subfamily recognition and recognition associated with color phenotypes. We conclude that while selection may favor discrimination between supersisters and half-sisters, as a practical matter such discriminations play no role, or only a minor role, in the biology of the honey bee.

  13. 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

  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.

  15. 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

  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

    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.

  18. 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…

  19. 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.

  20. 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.

  1. IAPV, a bee-affecting virus associated with Colony Collapse Disorder can be silenced by dsRNA ingestion.

    PubMed

    Maori, E; Paldi, N; Shafir, S; Kalev, H; Tsur, E; Glick, E; Sela, I

    2009-02-01

    Colony Collapse Disorder (CCD) has been associated with Israeli acute paralysis virus (IAPV). CCD poses a serious threat to apiculture and agriculture as a whole, due to the consequent inability to provide the necessary amount of bees for pollination of critical crops. Here we report on RNAi-silencing of IAPV infection by feeding bees with double-stranded RNA, as an efficient and feasible way of controlling this viral disease. The association of CCD with IAPV is discussed, as well as the potential of controlling CCD.

  2. 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...

  3. Treatment with synthetic brood pheromone (SuperBoost) enhances honey production and improves overwintering survival of package honey bee (Hymenoptera: Apidae) colonies.

    PubMed

    Lait, Cameron G; Borden, John H; Kovacs, Ervin; Moeri, Onour E; Campbell, Michael; Machial, Cristina M

    2012-04-01

    We evaluated a year-long treatment regime testing synthetic, 10-component, honey bee, Apis mellifera L. (Hymenoptera: Apidae), brood pheromone (SuperBoost; Contech Enterprises Inc., Delta, BC, Canada) on the productivity and vigor of package bee colonies in the lower Fraser Valley of British Columbia, Canada. Fifty-eight newlyestablished 1.3-kg (3-lb) colonies treated three times with SuperBoost at 5-wk intervals starting 30 April 2009 were compared with 52 untreated control colonies. Treated colonies produced 84.3% more honey than untreated control colonies. By 8 September 2009, SuperBoost-treated colonies had 35.4% more adults than untreated colonies. By 28 September, net survival of treated and control colonies was 72.4 and 67.3%, respectively. On 5 October, treated and control colonies were divided into two additional groups, making up four cohorts: SuperBoost-treated colonies treated again during fall and spring build-up feeding with pollen substitute diet (BeePro, Mann Lake Ltd., Hackensack, MN; TIT); controls that remained untreated throughout the year (CCC); colonies treated with SuperBoost in spring-summer 2009 but not treated thereafter (TCC); and original control colonies treated with SuperBoost during the fall and spring build-up feeding periods (CTT). There was no difference among cohorts in consumption of BeePro during fall feeding, but TTT colonies (including daughter colonies split off from parent colonies) consumed 50.8% more diet than CCC colonies during spring build-up feeding. By 21 April, the normalized percentages of the original number of colonies remaining (dead colonies partially offset by splits) were as follows: CCC, 31.4%; CTT, 43.8%; TCC, 53.59%; and TTT, 80.0%. The net benefit of placing 100 newly established package bee colonies on a year-long six-treatment regime with SuperBoost would be US$6,202 (US$62.02 per colony). We conclude that treatment with SuperBoost enhanced the productivity and survival of package bee colonies and

  4. 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

  5. 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.

  6. 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

  7. Varroa destructor (Mesostigmata: Varroidae) in Costa Rica: population dynamics and its influence on the colony condition of Africanized honey bees (Hymenoptera: Apidae).

    PubMed

    Calderón, Rafael A; van Veen, Johan W

    2008-12-01

    The development of Varroa destructor Anderson & Trueman (Mesostigmata: Varroidae) population dynamics in Africanized honey bees, Apis mellifera L. (Hymenoptera: Apidae) colonies was monitored from February to July 2004 in Atenas, Costa Rica. A correlation between the mite infestation level and the colony condition was evaluated. For each colony, infestation of varroa in adult bees was measured twice a month. Sticky boards were placed on the bottom boards of each colony to collect fallen mites. The condition of the colonies was evaluated by measuring the amount of brood and adult bees. Our results consistently showed that mite infestation on adult bees increased significantly in the experimental colonies, rising to 10.0% by the end of the experiment. In addition, the mean mite fall increased significantly over the course of the study in the treated (R = 0.72, P < 0.05) and untreated colonies (R = 0.74, P < 0.05) to a level of 63.8 and 73.5 mites per day, respectively. The increase in varroa infestation coincided with a decrease in the amount of brood. Furthermore, adult bees with deformed wings or even without wings crawling in front of their hive occurred in highly infested colonies (mite infestation = 10.0% or more).

  8. Fipronil promotes motor and behavioral changes in honey bees (Apis mellifera) and affects the development of colonies exposed to sublethal doses.

    PubMed

    Zaluski, Rodrigo; Kadri, Samir Moura; Alonso, Diego Peres; Martins Ribolla, Paulo Eduardo; de Oliveira Orsi, Ricardo

    2015-05-01

    Bees play a crucial role in pollination and generate honey and other hive products; therefore, their worldwide decline is cause for concern. New broad-spectrum systemic insecticides such as fipronil can harm bees and their use has been discussed as a potential threat to bees' survival. In the present study, the authors evaluate the in vitro toxicity of fipronil and note behavioral and motor activity changes in Africanized adult Apis mellifera that ingest or come into contact with lethal or sublethal doses of fipronil. The effects of sublethal doses on brood viability, population growth, behavior, and the expression of the defensin 1 gene in adult bees were studied in colonies fed with contaminated sugar syrup (8 µg fipronil L(-1) ). Fipronil is highly toxic to bees triggering agitation, seizures, tremors, and paralysis. Bees that are exposed to a lethal or sublethal doses showed reduced motor activity. The number of eggs that hatched, the area occupied by worker eggs, and the number of larvae and pupae that developed were reduced, adult bees showed lethargy, and colonies were abandoned when they were exposed to sublethal doses of fipronil. No change was seen in the bees' expression of defensin 1. The authors conclude that fipronil is highly toxic to honey bees and even sublethal doses may negatively affect the development and maintenance of colonies.

  9. 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

  10. 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.

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

    PubMed

    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.

  12. 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.

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

    PubMed

    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. PMID:23179948

  14. Associations of parameters related to the fall of Varroa destructor (Mesostigmata: Varroidae) in Russian and Italian honey bee (Hymenoptera: Apidae) colonies.

    PubMed

    Rinderer, Thomas E; De Guzman, Lilia I; Frake, Amanda M

    2013-04-01

    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 and Italian honey bees using 29 candidate measurements. Measurements included damaged and nondamaged younger mites, 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. Regression analyses were used to determine the relationships of these candidate measurements to the number of mites in the colonies. The largest positive regressions were found for trapped younger mites (Y) and trapped fresh mites (F). Measurments of Y and F across time could be used to estimate mite population growth for the purposes of selective breeding. The largest negative regressions with colony mites were observed for: trapped older mites/trapped mites (O/T), trapped older mites/trapped younger mites (O/Y), and trapped injured older mites/injured mites (IO/I). O/T and O/Y are significantly higher for Russian honey bee colonies suggesting that they are related to at least some of the mechanisms used by Russian honey bee to resist Varroa population growth. O/T and O/Y have strong negative relationships with colony mites for both Russian honey bee and Italian colonies suggesting that both strains possibly could be selected for reduced colony mites using O/T or O/Y.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

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

    PubMed

    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.

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

    PubMed

    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

  2. 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

  3. 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...

  4. 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.

  5. 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

  6. 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.

  7. Efficacy of strips coated with Metarhizium anisopliae for control of Varroa destructor (Acari: Varroidae) in honey bee colonies in Texas and Florida.

    PubMed

    Kanga, Lambert H B; Jones, Walker A; Gracia, Carlos

    2006-01-01

    Strips coated with conidia of Metarhizium anisopliae (Metschinkoff; Deuteromycetes: Hyphomycetes) to control the parasitic mite, Varroa destructor (Anderson and Trueman) in colonies of honey bees, Apis mellifera (Hymenoptera: Apidae) were compared against the miticide, tau-fluvalinate (Apistan) in field trials in Texas and Florida (USA). Apistan and the fungal treatments resulted in successful control of mite populations in both locations. At the end of the 42-day period of the experiment in Texas, the number of mites per bee was reduced by 69-fold in bee hives treated with Apistan and 25-fold in hives treated with the fungus; however mite infestations increased by 1.3-fold in the control bee hives. Similarly, the number of mites in sealed brood was 13-fold and 3.6-fold higher in the control bee hives than in those treated with Apistan and with the fungus, respectively. Like the miticide Apistan, the fungal treatments provided a significant reduction of mite populations at the end of the experimental period. The data from the broodless colonies treated with the fungus indicated 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. In established colonies in Florida, honey bee colony development did not increase under either Apistan or fungal treatments at the end of the experimental period, suggesting that other factors (queen health, food source, food availability) play some major role in the growth of bee colonies. Overall, microbial control of Varroa mites with fungal pathogens could be a useful component of an integrated pest management program for the honey bee industry.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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...

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. Effects, but no interactions, of ubiquitous pesticide and parasite stressors on honey bee (Apis mellifera) lifespan and behaviour in a colony environment.

    PubMed

    Retschnig, Gina; Williams, Geoffrey R; Odemer, Richard; Boltin, Janina; Di Poto, Cornelia; Mehmann, Marion M; Retschnig, Peter; Winiger, Pius; Rosenkranz, Peter; Neumann, Peter

    2015-11-01

    Interactions between pesticides and parasites are believed to be responsible for increased mortality of honey bee (Apis mellifera) colonies in the northern hemisphere. Previous efforts have employed experimental approaches using small groups under laboratory conditions to investigate influence of these stressors on honey bee physiology and behaviour, although both the colony level and field conditions play a key role for eusocial honey bees. Here, we challenged honey bee workers under in vivo colony conditions with sublethal doses of the neonicotinoid thiacloprid, the miticide tau-fluvalinate and the endoparasite Nosema ceranae, to investigate potential effects on longevity and behaviour using observation hives. In contrast to previous laboratory studies, our results do not suggest interactions among stressors, but rather lone effects of pesticides and the parasite on mortality and behaviour, respectively. These effects appear to be weak due to different outcomes at the two study sites, thereby suggesting that the role of thiacloprid, tau-fluvalinate and N. ceranae and interactions among them may have been overemphasized. In the future, investigations into the effects of honey bee stressors should prioritize the use of colonies maintained under a variety of environmental conditions in order to obtain more biologically relevant data.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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...

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    PubMed

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems. PMID:27652166

  17. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    PubMed

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

  18. Modeling Honey Bee Populations.

    PubMed

    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.

  19. 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

  20. Modeling Honey Bee Populations.

    PubMed

    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

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

    PubMed

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

    2012-01-24

    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.

  2. Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model

    NASA Astrophysics Data System (ADS)

    Deng, Guang-Feng; Lin, Woo-Tsong

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

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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

    2012-10-22

    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.

  12. 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

  13. 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

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. 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

  19. Bee poison

    MedlinePlus

    ... stings contain a substance called venom. Africanized bee colonies are very sensitive to being disturbed. When they ... and blood vessels Severe decrease in blood pressure Collapse * Lungs: Difficulty breathing * Skin Hives * Itching Swelling and ...

  20. How bees tune their dancing according to their colony's nectar influx: re-examining the role of the food-receivers' 'eagerness'.

    PubMed

    De Marco, Rodrigo J

    2006-02-01

    Apis mellifera bees perform dances to communicate the presence of desirable nectar sources. The regulation of these dances does not depend exclusively on properties of the nectar sources, but also upon certain stimuli derived from the foraging status of the colony as a whole; i.e. bees exploiting a source of constant profitability are more likely to dance when the colony's nectar intake rate is low. Based on these stimuli, individual bees tune their dances according to their colony's nectar influx without visiting alternative nectar sources. Division of labour, in addition, is a common feature in honeybees. Upon returning to the nest, successful foragers transfer the content of their crops to food-receivers by means of a common behaviour in social insects called trophallaxis, i.e. the transfer of liquid food by mouth. Martin Lindauer stated that a returned forager may sense the foraging status of its colony on the basis of the food transfer process by computing how quickly and eagerly the food-receivers unload its crop. This study focuses on the forager's experience during the food transfer process, its variability based on the colony's nectar influx, and the separate effects that the 'ease' and the 'eagerness' of the food-unloading have on the tuning of recruitment dances. Results indicate that foragers can rapidly sense variations in the colony's nectar influx, even when they experience no variation in the time interval between their return to the hive and the beginning of the food transfer. To accomplish this task they appear to use stimuli derived from the number of food-receivers, which enable them, in turn, to set their dance thresholds in relation to the nectar influx of their colony. The relevance of these findings is discussed in the context of communication and successful foraging.

  1. 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.

  2. Brood removal influences fall of Varroa destructor (Mesostigmata: Varroidae) in honey bee (Hymenoptera: Apidae) colonies

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The hygienic removal of brood infested with Varroa destructor by Apis mellifera disrupts the reproduction of the infesting mites and exposes the foundress mites to potential removal from the colony by grooming. Using brood deliberately infested with marked Varroa, we investigated the association bet...

  3. 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

  4. 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

  5. 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 ...

  6. Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment.

    PubMed

    Tang, Phooi Wah; Choon, Yee Wen; Mohamad, Mohd Saberi; Deris, Safaai; Napis, Suhaimi

    2015-03-01

    Metabolic engineering is a research field that focuses on the design of models for metabolism, and uses computational procedures to suggest genetic manipulation. It aims to improve the yield of particular chemical or biochemical products. Several traditional metabolic engineering methods are commonly used to increase the production of a desired target, but the products are always far below their theoretical maximums. Using numeral optimisation algorithms to identify gene knockouts may stall at a local minimum in a multivariable function. This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. The dataset used in this work was from the iJO1366 Escherichia coli metabolic network. The experimental results include the production rate, growth rate and a list of knockout genes. From the comparative analysis, ABCMOMA produced better results compared to previous works, showing potential for solving genetic engineering problems.

  7. 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.

  8. Ant system: optimization by a colony of cooperating agents.

    PubMed

    Dorigo, M; Maniezzo, V; Colorni, A

    1996-01-01

    An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. Differences Among Commonly Sprayed Orchard Fungicides in Targeting the Beneficial Fungi Associated with Honey Bee Colony and Bee Bread Provisions (In Vitro)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Our studies evaluated the effects of representative fungicides, boscalid and pyraclostrobin, propiconazole, and chlorothalonil, alone and in combination, on 12 fungi species isolated from bee bread. Chlorothalonil was fungicidal (slowed growth without killing) and was least effective on Aspergillus...

  19. Consumption of tyrosine in royal jelly increases brain levels of dopamine and tyramine and promotes transition from normal to reproductive workers in queenless honey bee colonies.

    PubMed

    Matsuyama, Syuhei; Nagao, Takashi; Sasaki, Ken

    2015-01-15

    Dopamine (DA) and tyramine (TA) have neurohormonal roles in the production of reproductive workers in queenless colonies of honey bees, but the regulation of these biogenic amines in the brain are still largely unclear. Nutrition is an important factor in promoting reproduction and might be involved in the regulation of these biogenic amines in the brain. To test this hypothesis, we examined the effect of oral treatments of tyrosine (Tyr; a common precursor of DA, TA and octopamine, and a component of royal jelly) in queenless workers and quantified the resulting production of biogenic amines. Tyrosine treatments enhanced the levels of DA, TA and their metabolites in the brain. Workers fed royal jelly had significantly larger brain levels of Tyr, DA, TA and the metabolites in the brains compared with those bees fed honey or sucrose (control). Treatment with Tyr also inhibited the behavior of workers outside of the hive and promoted ovarian development. These results suggest that there is a link between nutrition and the regulation of DA and TA in the brain to promote the production of reproductive workers in queenless honey bee colonies. PMID:25448251

  20. Consumption of tyrosine in royal jelly increases brain levels of dopamine and tyramine and promotes transition from normal to reproductive workers in queenless honey bee colonies.

    PubMed

    Matsuyama, Syuhei; Nagao, Takashi; Sasaki, Ken

    2015-01-15

    Dopamine (DA) and tyramine (TA) have neurohormonal roles in the production of reproductive workers in queenless colonies of honey bees, but the regulation of these biogenic amines in the brain are still largely unclear. Nutrition is an important factor in promoting reproduction and might be involved in the regulation of these biogenic amines in the brain. To test this hypothesis, we examined the effect of oral treatments of tyrosine (Tyr; a common precursor of DA, TA and octopamine, and a component of royal jelly) in queenless workers and quantified the resulting production of biogenic amines. Tyrosine treatments enhanced the levels of DA, TA and their metabolites in the brain. Workers fed royal jelly had significantly larger brain levels of Tyr, DA, TA and the metabolites in the brains compared with those bees fed honey or sucrose (control). Treatment with Tyr also inhibited the behavior of workers outside of the hive and promoted ovarian development. These results suggest that there is a link between nutrition and the regulation of DA and TA in the brain to promote the production of reproductive workers in queenless honey bee colonies.

  1. Bees do not use nearest-neighbour rules for optimization of multi-location routes.

    PubMed

    Lihoreau, Mathieu; Chittka, Lars; Le Comber, Steven C; Raine, Nigel E

    2012-02-23

    Animals collecting patchily distributed resources are faced with complex multi-location routing problems. Rather than comparing all possible routes, they often find reasonably short solutions by simply moving to the nearest unvisited resources when foraging. Here, we report the travel optimization performance of bumble-bees (Bombus terrestris) foraging in a flight cage containing six artificial flowers arranged such that movements between nearest-neighbour locations would lead to a long suboptimal route. After extensive training (80 foraging bouts and at least 640 flower visits), bees reduced their flight distances and prioritized shortest possible routes, while almost never following nearest-neighbour solutions. We discuss possible strategies used during the establishment of stable multi-location routes (or traplines), and how these could allow bees and other animals to solve complex routing problems through experience, without necessarily requiring a sophisticated cognitive representation of space.

  2. 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

  3. 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.

  4. 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.

  5. Multitrophic interaction facilitates parasite–host relationship between an invasive beetle and the honey bee

    PubMed Central

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

    2007-01-01

    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

  6. 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

  7. 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...

  8. 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

  9. Monitoring colony phenology using within-day variability in continuous weight and temperature of honey bee hives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Continuous weight and temperature data were collected for honey bee hives in two locations in Arizona, and those data were evaluated with respect to separate measurements of hive phenology to develop methods for monitoring hives non-invasively. Both the weight and temperature data were divided into ...

  10. 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...

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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…

  17. 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

  18. 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

  19. Application of the dynamic ant colony algorithm on the optimal operation of cascade reservoirs

    NASA Astrophysics Data System (ADS)

    Tong, X. X.; Xu, W. S.; Wang, Y. F.; Zhang, Y. W.; Zhang, P. C.

    2016-08-01

    Due to the lack of dynamic adjustments between global searches and local optimization, it is difficult to maintain high diversity and overcome local optimum problems for Ant Colony Algorithms (ACA). Therefore, this paper proposes an improved ACA, Dynamic Ant Colony Algorithm (DACA). DACA applies dynamic adjustments on heuristic factor changes to balance global searches and local optimization in ACA, which decreases cosines. At the same time, by utilizing the randomness and ergodicity of the chaotic search, DACA implements the chaos disturbance on the path found in each ACA iteration to improve the algorithm's ability to jump out of the local optimum and avoid premature convergence. We conducted a case study with DACA for optimal joint operation of the Dadu River cascade reservoirs. The simulation results were compared with the results of the gradual optimization method and the standard ACA, which demonstrated the advantages of DACA in speed and precision.

  20. Effects of western honey bee (Hymenoptera: Apidae) colony, cell type, and larval sex on host acquisition by female Varroa destructor (Acari: Varroidae).

    PubMed

    Calderone, N W; Kuenen, L P

    2001-10-01

    Female mites of the genus Varroa reproduce on the immature stages of Apis cerana F. and A. mellifera L. Mites are found more often in drone brood than worker brood, and while evolutionary explanations for this bias are well supported, the proximate mechanisms are not known. In one experiment, we verified that the proportion of hosts with one or more mites (MPV, mite prevalence value) was significantly greater for drones (0.763 +/- 0.043) (lsmean +/- SE) than for workers (0.253 +/- 0.043) in populations of mites and bees in the United States. Similar results were found for the average number of mites per host. In a second experiment, using a cross-fostering technique in which worker and drone larvae were reared in both worker and drone cells, we found that cell type, larval sex, colony and all interactions affected the level of mites on a host. Mite prevalence values were greatest in drone larvae reared in drone cells (0.907 +/- 0.025), followed by drone larvae reared in worker cells (0.751 +/- 0.025), worker larvae reared in worker cells (0.499 +/- 0.025), and worker larvae reared in drone cells (0.383 +/- 0.025). Similar results were found for the average number of mites per host. Our data show that mite levels are affected by environmental factors (cell type), by factors intrinsic to the host (sex), and by interactions between these factors. In addition, colony-to-colony variation is important to the expression of intrinsic and environmental factors.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. Colony collapse disorder in Europe.

    PubMed

    Dainat, Benjamin; Vanengelsdorp, Dennis; Neumann, Peter

    2012-02-01

    Colony collapse disorder (CCD) is a condition of honey bees, which has contributed in part to the recent major losses of honey bee colonies in the USA. Here we report the first CCD case from outside of the USA. We suggest that more standardization is needed for the case definition to diagnose CCD and to compare data on a global scale.

  7. Detection Of Ventricular Late Potentials Using Wavelet Transform And ANT Colony Optimization

    NASA Astrophysics Data System (ADS)

    Subramanian, A. Sankara; Gurusamy, G.; Selvakumar, G.

    2010-10-01

    Ventricular late Potentials (VLPs) are low-level high frequency signals that are usually found with in the terminal part of the QRS complex from patients after Myocardial Infraction. Patients with VLPs are at risk of developing Ventricular Tachycardia, which is the major cause of death if patients suffering from heart disease. In this paper the Discrete Wavelet Transform was used to detect VLPs and then ANT colony optimization (ACO) was applied to classify subjects with and without VLPs. A set of Discrete Wavelet Transform (DWT) coefficients is selected from the wavelet decomposition. Three standard parameters of VLPs such as QRST, D40 and V40 are also established. After that a novel clustering algorithm based on Ant Colony Optimization is developed for classifying arrhythmia types. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.

  8. 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

  9. 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.

  10. 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.

  11. On optimal decision-making in brains and social insect colonies.

    PubMed

    Marshall, James A R; Bogacz, Rafal; Dornhaus, Anna; Planqué, Robert; Kovacs, Tim; Franks, Nigel R

    2009-11-01

    The problem of how to compromise between speed and accuracy in decision-making faces organisms at many levels of biological complexity. Striking parallels are evident between decision-making in primate brains and collective decision-making in social insect colonies: in both systems, separate populations accumulate evidence for alternative choices; when one population reaches a threshold, a decision is made for the corresponding alternative, and this threshold may be varied to compromise between the speed and the accuracy of decision-making. In primate decision-making, simple models of these processes have been shown, under certain parametrizations, to implement the statistically optimal procedure that minimizes decision time for any given error rate. In this paper, we adapt these same analysis techniques and apply them to new models of collective decision-making in social insect colonies. We show that social insect colonies may also be able to achieve statistically optimal collective decision-making in a very similar way to primate brains, via direct competition between evidence-accumulating populations. This optimality result makes testable predictions for how collective decision-making in social insects should be organized. Our approach also represents the first attempt to identify a common theoretical framework for the study of decision-making in diverse biological systems.

  12. 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.

  13. 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

  14. Importance of Ecological Factors and Colony Handling for Optimizing Health Status of Apiaries in Mediterranean Ecosystems

    PubMed Central

    Asensio, Irene; Muñoz, María Jesús; Fernández-Carrión, Eduardo; Sánchez-Vizcaíno, José Manuel; Carballo, Matilde

    2016-01-01

    We analyzed six apiaries in several natural environments with a Mediterranean ecosystem in Madrid, central Spain, in order to understand how landscape and management characteristics may influence apiary health and bee production in the long term. We focused on five criteria (habitat quality, landscape heterogeneity, climate, management and health), as well as 30 subcriteria, and we used the analytic hierarchy process (AHP) to rank them according to relevance. Habitat quality proved to have the highest relevance, followed by beehive management. Within habitat quality, the following subcriteria proved to be most relevant: orographic diversity, elevation range and important plant species located 1.5 km from the apiary. The most important subcriteria under beehive management were honey production, movement of the apiary to a location with a higher altitude and wax renewal. Temperature was the most important subcriterion under climate, while pathogen and Varroa loads were the most significant under health. Two of the six apiaries showed the best values in the AHP analysis and showed annual honey production of 70 and 28 kg/colony. This high productivity was due primarily to high elevation range and high orographic diversity, which favored high habitat quality. In addition, one of these apiaries showed the best value for beehive management, while the other showed the best value for health, reflected in the low pathogen load and low average number of viruses. These results highlight the importance of environmental factors and good sanitary practices to maximize apiary health and honey productivity. PMID:27727312

  15. [Classification of hyperspectral imagery based on ant colony compositely optimizing SVM in spatial and spectral features].

    PubMed

    Chen, Shan-Jing; Hu, Yi-Hua; Shi, Liang; Wang, Lei; Sun, Du-Juan; Xu, Shi-Long

    2013-08-01

    A novel classification algorithm of hyperspectral imagery based on ant colony compositely optimizing support vector machine in spatial and spectral features was proposed. Two types of virtual ants searched for the bands combination with the maximum class separation distance and heterogeneous samples in spatial and spectral features alternately. The optimal characteristic bands were extracted, and bands redundancy of hyperspectral imagery decreased. The heterogeneous samples were eliminated form the training samples, and the distribution of samples was optimized in feature space. The hyperspectral imagery and training samples which had been optimized were used in classification algorithm of support vector machine, so that the class separation distance was extended and the accuracy of classification was improved. Experimental results demonstrate that the proposed algorithm, which acquires an overall accuracy 95.45% and Kappa coefficient 0.925 2, can obtain greater accuracy than traditional hyperspectral image classification algorithms.

  16. 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

  17. 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 ...

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. 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...

  8. 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...

  9. 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...

  10. 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.

  11. 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 ...

  12. Optimization of Extraction Condition of Bee Pollen Using Response Surface Methodology: Correlation between Anti-Melanogenesis, Antioxidant Activity, and Phenolic Content.

    PubMed

    Kim, Seon Beom; Jo, Yang Hee; Liu, Qing; Ahn, Jong Hoon; Hong, In Pyo; Han, Sang Mi; Hwang, Bang Yeon; Lee, Mi Kyeong

    2015-11-02

    Bee pollen is flower pollen with nectar and salivary substances of bees and rich in essential components. Bee pollen showed antioxidant and tyrosinase inhibitory activity in our assay system. To maximize the antioxidant and tyrosinase inhibitory activity of bee pollen, extraction conditions, such as extraction solvent, extraction time, and extraction temperature, were optimized using response surface methodology. Regression analysis showed a good fit of this model and yielded the second-order polynomial regression for tyrosinase inhibition and antioxidant activity. Among the extraction variables, extraction solvent greatly affected the activity. The optimal condition was determined as EtOAc concentration in MeOH, 69.6%; temperature, 10.0 °C; and extraction time, 24.2 h, and the tyrosinase inhibitory and antioxidant activity under optimal condition were found to be 57.9% and 49.3%, respectively. Further analysis showed the close correlation between activities and phenolic content, which suggested phenolic compounds are active constituents of bee pollen for tyrosinase inhibition and antioxidant activity. Taken together, these results provide useful information about bee pollen as cosmetic therapeutics to reduce oxidative stress and hyperpigmentation.

  13. Use of flax oil to influence honey bee nestmate recognition.

    PubMed

    Breed, Michael D; Lyon, Cecily A; Sutherland, Anna; Buchwald, Robert

    2012-08-01

    Fatty acids, normally found in comb wax, have a strong influence on nestmate recognition in honey bees, Apis mellifera L. Previous work has shown that bees from different colonies, when treated with 16- or 18-carbon fatty acids, such as oleic, linoleic, or linolenic acids, are much less likely to fight than bees from two colonies when only one of the two is treated. Previous work also shows that the influence of comb wax on recognition has practical applications; transfer of empty comb between colonies, before merger of those colonies, reduces fighting among workers within the merged colony. Flax oil contains many of the same fatty acids as beeswax. Here, we tested the hypothesis that treatment of individual bees with flax oil affects nestmate recognition; the results proved to be consistent with this hypothesis and showed that treated bees from different colonies were less likely to fight than untreated bees. These results suggest that flax oil may be useful in facilitating colony mergers.

  14. A Novel Method of Failure Sample Selection for Electrical Systems Using Ant Colony Optimization

    PubMed Central

    Tian, Shulin; Yang, Chenglin; Liu, Cheng

    2016-01-01

    The influence of failure propagation is ignored in failure sample selection based on traditional testability demonstration experiment method. Traditional failure sample selection generally causes the omission of some failures during the selection and this phenomenon could lead to some fearful risks of usage because these failures will lead to serious propagation failures. This paper proposes a new failure sample selection method to solve the problem. First, the method uses a directed graph and ant colony optimization (ACO) to obtain a subsequent failure propagation set (SFPS) based on failure propagation model and then we propose a new failure sample selection method on the basis of the number of SFPS. Compared with traditional sampling plan, this method is able to improve the coverage of testing failure samples, increase the capacity of diagnosis, and decrease the risk of using. PMID:27738424

  15. Optimized In Vitro Antibiotic Susceptibility Testing Method for Small-Colony Variant Staphylococcus aureus.

    PubMed

    Precit, Mimi R; Wolter, Daniel J; Griffith, Adam; Emerson, Julia; Burns, Jane L; Hoffman, Lucas R

    2016-03-01

    Staphylococcus aureus small-colony variants (SCVs) emerge frequently during chronic infections and are often associated with worse disease outcomes. There are no standardized methods for SCV antibiotic susceptibility testing (AST) due to poor growth and reversion to normal-colony (NC) phenotypes on standard media. We sought to identify reproducible methods for AST of S. aureus SCVs and to determine whether SCV susceptibilities can be predicted on the basis of treatment history, SCV biochemical type (auxotrophy), or the susceptibilities of isogenic NC coisolates. We tested the growth and stability of SCV isolates on 11 agar media, selecting for AST 2 media that yielded optimal SCV growth and the lowest rates of reversion to NC phenotypes. We then performed disk diffusion AST on 86 S. aureus SCVs and 28 isogenic NCs and Etest for a subset of 26 SCVs and 24 isogenic NCs. Growth and reversion were optimal on brain heart infusion agar and Mueller-Hinton agar supplemented with compounds for which most clinical SCVs are auxotrophic: hemin, menadione, and thymidine. SCVs were typically nonsusceptible to either trimethoprim-sulfamethoxazole or aminoglycosides, in accordance with the auxotrophy type. In contrast, SCVs were variably nonsusceptible to fluoroquinolones, macrolides, lincosamides, fusidic acid, and rifampin; mecA-positive SCVs were invariably resistant to cefoxitin. All isolates (both SCVs and NCs) were susceptible to quinupristin-dalfopristin, vancomycin, minocycline, linezolid, chloramphenicol, and tigecycline. Analysis of SCV auxotrophy type, isogenic NC antibiograms, and antibiotic treatment history had limited utility in predicting SCV susceptibilities. With clinical correlation, this AST method and these results may prove useful in directing treatment for SCV infections. PMID:26729501

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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 ...

  1. 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

  2. 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.

  3. Male reproductive parasitism: a factor in the africanization of European honey-bee populations.

    PubMed

    Rinderer, T E; Hellmich, R L; Danka, R G; Collins, A M

    1985-05-31

    Africanized drone honey bees (Apis mellifera) migrate into European honey-bee colonies in large numbers, but Africanized colonies only rarely host drones from other colonies. This migration leads to a strong mating advantage for Africanized bees since it both inhibits European drone production and enhances Africanized drone production.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. Special Issue: Honey Bee Viruses.

    PubMed

    Gisder, Sebastian; Genersch, Elke

    2015-10-01

    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.

  12. 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

  13. Special Issue: Honey Bee Viruses.

    PubMed

    Gisder, Sebastian; Genersch, Elke

    2015-10-01

    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

  14. 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

  15. A Multipath Routing Protocol Based on Clustering and Ant Colony Optimization for Wireless Sensor Networks

    PubMed Central

    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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. Liquid chromatography coupled to ion trap-tandem mass spectrometry to evaluate juvenile hormone III levels in bee hemolymph from Nosema spp. infected colonies.

    PubMed

    Ares, A M; Nozal, M J; Bernal, J L; Martín-Hernández, R; M Higes; Bernal, J

    2012-06-15

    It has been described a fast, simple and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to measure juvenile hormone III (JH III), which was used to study of the effects of Nosema spp. infection on JH III levels in bee hemolymph. Honey bee hemolymph was extracted by centrifugation and mixed with a solution of phenylthiourea in methanol. This mixture was then centrifuged and the supernatant removed and evaporated to dryness. The residue was reconstituted in methanol containing the internal standard (methoprene) and injected onto an LC-MS/MS (ion-trap) system coupled to electrospray ionization (ESI) in positive mode. Chromatography was performed on a Synergi Hydro-RP column (4 μm, 30 mm × 4.60 mm i.d.) using a mobile phase of 20 mM ammonium formate and methanol in binary gradient elution mode. The method was fully validated and it was found to be selective, linear from 15 to 14,562 pg/μL, precise and accurate, with %RSD values below 5%. The limits of detection and quantification were: LOD, 6 pg/μL; LOQ, 15 pg/μL. Finally, the proposed LC-MS/MS method was used to analyze JH III levels in the hemolymph of worker honey bees (Apis mellifera iberiensis) experimentally infected with different Nosema spp. (Nosema apis, Spanish and Dutch Nosema ceranae strains). The highest concentrations of JH III were detected in hemolymph from bees infected with Spanish N. ceranae.

  2. 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

  3. 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

  4. 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.

  5. Optimizing outpatient serial sputum colony counting for studies of tuberculosis treatment in resource-poor settings.

    PubMed

    Sloan, Derek J; Corbett, Elizabeth L; Butterworth, Anthony E; Mwandumba, Henry C; Khoo, Saye H; Mdolo, Aaron; Shani, Doris; Kamdolozi, Mercy; Allen, Jenny; Mitchison, Denis A; Coleman, David J; Davies, Geraint R

    2012-07-01

    Serial Sputum Colony Counting (SSCC) is an important technique in clinical trials of new treatments for tuberculosis (TB). Quantitative cultures on selective Middlebrook agar are used to calculate the rate of bacillary elimination from sputum collected from patients at different time points during the first 2 months of therapy. However, the procedure can be complicated by high sample contamination rates. This study, conducted in a resource-poor setting in Malawi, assessed the ability of different antifungal drugs in selective agar to reduce contamination. Overall, 229 samples were studied and 15% to 27% were contaminated. Fungal organisms were particularly implicated, and samples collected later in treatment were at particular risk (P < 0.001). Amphotericin B (AmB) is the standard antifungal drug used on SSCC plates at a concentration of 10 mg/ml. On selective Middlebrook 7H10 plates, AmB at 30 mg/ml reduced sample contamination by 17% compared with AmB at 10 mg/ml. The relative risk of contamination using AmB at 10 mg/ml was 1.79 (95% confidence interval [CI], 1.25 to 3.55). On Middlebrook 7H11 plates, a combination of AmB at 10 mg/ml and carbendazim at 50 mg/ml was associated with 10% less contamination than AmB at 30 mg/ml. The relative risk of contamination with AmB at 30 mg/ml was 1.79 (95% CI, 1.01 to 3.17). Improved antifungal activity was accompanied by a small reduction in bacillary counts, but this did not affect modeling of bacillary elimination. In conclusion, a combination of AmB and carbendazim optimized the antifungal activity of selective media for growth of TB. We recommend this method to reduce contamination rates and improve SSCC studies in African countries where the burden of TB is highest.

  6. 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.

  7. 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.

  8. 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

  9. 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...

  10. Multiyear survey targeting disease incidence in US honey bees

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The US National Honey Bee Disease Survey sampled colony pests and diseases from 2009 to 2014. We verified the absence of Tropilaelaps spp., the Asian honey bee (Apis cerana), and slow bee paralysis virus. Endemic health threats were quantified, including Varroa destructor, Nosema spp., and eight hon...

  11. 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

  12. Parasite Pressures on Feral Honey Bees (Apis mellifera sp.)

    PubMed Central

    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

  13. 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

  14. 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

  15. 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

  16. 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…

  17. 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.

  18. 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

  19. 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.

  20. 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...

  1. 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

  2. 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...

  3. 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...

  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.

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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

  11. Bee Pollen

    MedlinePlus

    ... bee venom, honey, or royal jelly. People take bee pollen for nutrition; as an appetite stimulant; to improve stamina and athletic performance; and for premature aging, premenstrual syndrome (PMS), hay fever (allergic ... Bee pollen is also used for gastrointestinal (GI) problems ...

  12. 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; Zh