Honeybees Learn Odour Mixtures via a Selection of Key Odorants

BACKGROUND The honeybee has to detect, process and learn numerous complex odours from her natural environment on a daily basis. Most of these odours are floral scents, which are mixtures of dozens of different odorants. To date, it is still unclear how the bee brain unravels the complex information contained in scent mixtures. METHODOLOGY/PRINCIPAL FINDINGS This study investigates learning of complex odour mixtures in honeybees using a simple olfactory conditioning procedure, the Proboscis-Extension-Reflex (PER) paradigm. Restrained honeybees were trained to three scent mixtures composed of 14 floral odorants each, and then tested with the individual odorants of each mixture. Bees did not respond to all odorants of a mixture equally: They responded well to a selection of key odorants, which were unique for each of the three scent mixtures. Bees showed less or very little response to the other odorants of the mixtures. The bees' response to mixtures composed of only the key odorants was as good as to the original mixtures of 14 odorants. A mixture composed of the other, non-key-odorants elicited a significantly lower response. Neither an odorant's volatility or molecular structure, nor learning efficiencies for individual odorants affected whether an odorant became a key odorant for a particular mixture. Odorant concentration had a positive effect, with odorants at high concentration likely to become key odorants. CONCLUSIONS/SIGNIFICANCE Our study suggests that the brain processes complex scent mixtures by predominantly learning information from selected key odorants. Our observations on key odorant learning lend significant support to previous work on olfactory learning and mixture processing in honeybees.This work was supported by a grant from the Commonwealth Scientific and Industrial Research Organisation Food Futures Flagship Collaborative Research Fund (CBR3_45865_9 W2003, http://www.csiro.au/org/FoodFuturesFlagship.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Strategies for pre-emptive mid-air collision avoidance in Budgerigars

We have investigated how birds avoid mid-air collisions during head-on encounters. Trajectories of birds flying towards each other in a tunnel were recorded using high speed video cameras. Analysis and modelling of the data suggest two simple strategies for collision avoidance: (a) each bird veers to its right and (b) each bird changes its altitude relative to the other bird according to a preset preference. Both strategies suggest simple rules by which collisions can be avoided in head-on encounters by two agents, be they animals or machines. The findings are potentially applicable to the design of guidance algorithms for automated collision avoidance on aircraft

How lost "passenger" ants find their way home

Summary: Animal navigation has fascinated biologists and engineers for centuries, and some of the most illuminating discoveries have come from the study of creatures with a brain no larger than a sesame seed. In an elegant recent study, Pfeiffer and Wittlinger (Science, 353, 1155–1157, 2016) have shown the means by which desert ants, carried from one nest to another by a relative, find their own way back home if they are accidentally dropped en route

On pseudo-conservation laws for the cyclic server system with compound Poisson arrivals

Boxma and Groenendijk obtain the pseudo-conservation laws for cyclic server systems, for both the continuous-time system with simple Poisson arrivals, and for the discrete-time system. We extend these laws to the continuous-time cyclic server system with compound Poisson arrivals. In the process we identify an error in Boxma and Groenendijk's analysis of the semi-exhaustive service strategy in the discrete-time cyclic server system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29064/1/0000097.pd

UAS stealth: target pursuit at constant distance using a bio-inspired motion camouflage guidance law

The aim of this study is to derive a guidance law by which an Unmanned Aerial System(s) (UAS) can pursue a moving target at a constant distance, while concealing its own motion. We derive a closed-form solution for the trajectory of the UAS by imposing two key constraints:
 (1) the shadower moves in such a way as to be perceived as a stationary object by the shadowee, and (2) the distance between the shadower and shadowee is kept constant. Additionally, the theory presented in this paper considers constraints on the maximum achievable speed and acceleration of the shadower. Our theory is tested through Matlab simulations, which validate the camouflage strategy for both 2D and 3D conditions. Furthermore, experiments using a realistic vision-based implementation are conducted in a virtual environment, where the results demonstrate that even with noisy state information it is possible to remain well camouflaged using the Constant Distance Motion Camouflage (CDMC) technique

Visual regulation of ground speed and headwind compensation in freely flying honey bees (Apis mellifera L.)

There is now increasing evidence that honey bees regulate their ground speed in flight by holding constant the speed at which the image of the environment moves across the eye (optic flow). We have investigated the extent to which ground speed is affected by headwinds. Honey bees were trained to enter a tunnel to forage at a sucrose feeder placed at its far end. Ground speeds in the tunnel were recorded while systematically varying the visual texture of the tunnel, and the strength of headwinds experienced by the flying bees. We found that in a flight tunnel bees used visual cues to maintain their ground speed, and adjusted their air speed to maintain a constant rate of optic How, even against headwinds which were, at their strongest, 50% of a bee's maximum recorded forward velocity. Manipulation of the visual texture revealed that headwind is compensated almost fully even when the optic flow cues are very sparse and subtle, demonstrating the robustness of this visual flight control system. We discuss these findings in the context of field observations of flying bees

Tandem AGV systems: A partitioning algorithm and performance comparison with conventional AGV systems

In an earlier paper, Bozer and Srinivasan introduced the tandem concept for automated guided vehicle (AGV) systems and presented an analytical model to evaluate the throughput performance of a basic component of the system; namely, a single vehicle serving a set of workstations under the First-Encountered-First-Served rule. In this study, using the above analytical model and certain column generation techniques, we present a heuristic partitioning scheme to configure tandem AGV systems. The partitioning scheme is based on a variation of the well-known set partitioning problem. It is aimed at evenly distributing the workload among all the AGVs in the system. We demonstrate the procedure with two numerical examples. Using simulation, the performance of the tandem configuration obtained for each example is compared to that of the corresponding conventional AGV system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29686/1/0000013.pd

NetMod: A Design Tool for Large-Scale Heterogeneous Campus Networks

The Network Modeling Tool (NetMod) uses simple analytical models to provide the designers of large interconnected local area networks with an in-depth analysis of the potential performance of these systems. This tool can be used in either a university, industrial, or governmental campus networking environment consisting of thousands of computer sites. NetMod is implemented with a combination of the easy-to-use Macintosh software packages HyperCard and Excel. The objectives of NetMod, the analytical models, and the user interface are described in detail along with its application to an actual campus-wide network.http://deepblue.lib.umich.edu/bitstream/2027.42/107971/1/citi-tr-90-1.pd