3,838 research outputs found

    Neural Correlates of Social Behavior in Mushroom Body Extrinsic Neurons of the Honeybee Apis mellifera

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    The social behavior of honeybees (Apis mellifera) has been extensively investigated, but little is known about its neuronal correlates. We developed a method that allowed us to record extracellularly from mushroom body extrinsic neurons (MB ENs) in a freely moving bee within a small but functioning mini colony of approximately 1,000 bees. This study aimed to correlate the neuronal activity of multimodal high-order MB ENs with social behavior in a close to natural setting. The behavior of all bees in the colony was video recorded. The behavior of the recorded animal was compared with other hive mates and no significant differences were found. Changes in the spike rate appeared before, during or after social interactions. The time window of the strongest effect on spike rate changes ranged from 1 s to 2 s before and after the interaction, depending on the individual animal and recorded neuron. The highest spike rates occurred when the experimental animal was situated close to a hive mate. The variance of the spike rates was analyzed as a proxy for high order multi-unit processing. Comparing randomly selected time windows with those in which the recorded animal performed social interactions showed a significantly increased spike rate variance during social interactions. The experimental set-up employed for this study offers a powerful opportunity to correlate neuronal activity with intrinsically motivated behavior of socially interacting animals. We conclude that the recorded MB ENs are potentially involved in initiating and controlling social interactions in honeybees

    A Community-based Cloud Computing Caching Service

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    Caching has become an important technology in the development of cloud computing-based high-performance web services. Caches reduce the request to response latency experienced by users, and reduce workload on backend databases. They need a high cache-hit rate to be fit for purpose, and this rate is dependent on the cache management policy used. Existing cache management policies are not designed to prevent cache pollution or cache monopoly problems, which impacts negatively on the cache-hit rate. This paper proposes a community-based caching approach (CC) to address these two problems. CC was evaluated for performance against thirteen commercially available cache management policies, and results demonstrate that the cache-hit rate achieved by CC was between 0.7% and 55% better than the alternate cache management policies

    Living IoT: A Flying Wireless Platform on Live Insects

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    Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201

    Applications of Bee Colony Optimization

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    Many computationally difficult problems are attacked using non-exact algorithms, such as approximation algorithms and heuristics. This thesis investigates an ex- ample of the latter, Bee Colony Optimization, on both an established optimization problem in the form of the Quadratic Assignment Problem and the FireFighting problem, which has not been studied before as an optimization problem. Bee Colony Optimization is a swarm intelligence algorithm, a paradigm that has increased in popularity in recent years, and many of these algorithms are based on natural pro- cesses. We tested the Bee Colony Optimization algorithm on the QAPLIB library of Quadratic Assignment Problem instances, which have either optimal or best known solutions readily available, and enabled us to compare the quality of solutions found by the algorithm. In addition, we implemented a couple of other well known algorithms for the Quadratic Assignment Problem and consequently we could analyse the runtime of our algorithm. We introduce the Bee Colony Optimization algorithm for the FireFighting problem. We also implement some greedy algorithms and an Ant Colony Optimization al- gorithm for the FireFighting problem, and compare the results obtained on some randomly generated instances. We conclude that Bee Colony Optimization finds good solutions for the Quadratic Assignment Problem, however further investigation on speedup methods is needed to improve its performance to that of other algorithms. In addition, Bee Colony Optimization is effective on small instances of the FireFighting problem, however as instance size increases the results worsen in comparison to the greedy algorithms, and more work is needed to improve the decisions made on these instances

    Integrated Honey Bee Education and Research Aids for Promoting Pollinator Conservation

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    Extension and outreach programs combine University instruction and research, with off-campus outreach and service to the community. Successful public education requires training in which colleges and their education services provide programs relevant to today’s needs. To better engage with the public, institutions and Extension professionals often partner with private and not-for-profit organizations to provide training opportunities. The following thesis reviews one such partnership with the University of Nebraska-Lincoln and Kimmel Orchard & Vineyard that provides science-focused, on-farm experiences and agriculture production training programming. Chapter 1 reviews their partnership since it began in 2005 and highlights examples of current farm-to-table education and conservation programs emphasizing the roles beneficial insects play in agroecosystems. Given the popularity of beekeeping, the reasons for keeping bees and demographics of beekeepers have greatly diversified over the past decade. With the evolving needs in beekeeping, innovations are necessary to provide scientifically vetted, evidence-based, and time-tested tools for beekeepers. Chapter 2 provides an evaluation of alternative honey bee hive structures comparing productivity and colony performance across three hive types to assess advantages and disadvantages for each. Results indicate minor differences in overall colony productivity, including some differences in brood and adult population, wax, pollen and nectar production levels between colonies managed in smaller boxes (Supers) compared to the other two hive types, but with no significant differences in overall honey yield, mite counts nor survivability. Data suggests that using alternative hive structures that require less physical labor such as smaller boxes (Supers) or hives that expand horizontally (Brummels) will be comparable to using the standard Langstroth hive structures (Deeps) and will not impact colony performance measures. The results of this study identify alternative options for managing bee colonies without the heavy lifting requirements of the standard Langstroth method and promotes local engagement regarding the importance of pollinator-friendly landscapes and practices that support healthy landscapes for managed and wild bees. Advisor: Judy Wu-Smar

    Navigation and dance communication in honeybees: a cognitive perspective

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    Flying insects like the honeybee experience the world as a metric layout embedded in a compass, the time-compensated sun compass. The focus of the review lies on the properties of the landscape memory as accessible by data from radar tracking and analyses of waggle dance following. The memory formed during exploration and foraging is thought to be composed of multiple elements, the aerial pictures that associate the multitude of sensory inputs with compass directions. Arguments are presented that support retrieval and use of landscape memory not only during navigation but also during waggle dance communication. I argue that bees expect landscape features that they have learned and that are retrieved during dance communication. An intuitive model of the bee’s navigation memory is presented that assumes the picture memories form a network of geographically defined locations, nodes. The intrinsic components of the nodes, particularly their generalization process leads to binding structures, the edges. In my view, the cognitive faculties of landscape memory uncovered by these experiments are best captured by the term cognitive map

    HoneybeeZZZ [1st grade]

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    First grade students will engage in a research unit about honey bees, learning about colony demographics, habitats, pollination patterns and preferences, and their importance within the agriculture world. The goal is for students to understand the importance of honeybees and their impact on our global and local ecological systems
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