Honey bee foraging distance depends on month and forage type

To investigate the distances at which honey bee foragers collect nectar and pollen, we analysed 5,484 decoded waggle dances made to natural forage sites to determine monthly foraging distance for each forage type. Firstly, we found significantly fewer overall dances made for pollen (16.8 %) than for non-pollen, presumably nectar (83.2 %; P < 2.2 × 10−23). When we analysed distance against month and forage type, there was a significant interaction between the two factors, which demonstrates that in some months, one forage type is collected at farther distances, but this would reverse in other months. Overall, these data suggest that distance, as a proxy for forage availability, is not significantly and consistently driven by need for one type of forage over the other

Two-Dimensional Copolymers and Exact Conformal Multifractality

We consider in two dimensions the most general star-shaped copolymer, mixing random (RW) or self-avoiding walks (SAW) with specific interactions thereof. Its exact bulk or boundary conformal scaling dimensions in the plane are all derived from an algebraic structure existing on a random lattice (2D quantum gravity). The multifractal dimensions of the harmonic measure of a 2D RW or SAW are conformal dimensions of certain star copolymers, here calculated exactly as non rational algebraic numbers. The associated multifractal function f(alpha) are found to be identical for a random walk or a SAW in 2D. These are the first examples of exact conformal multifractality in two dimensions.Comment: 4 pages, 2 figures, revtex, to appear in Phys. Rev. Lett., January 199

Model of the best-of-N nest-site selection process in honeybees

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony’s fitness. To date, the nest-site selection process has mostly been modelled and theoretically analysed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision process dynamics qualitatively change. In this work, we extend previous analyses of a valuesensitive decision-making mechanism to a decision process among N nests. First, we present the decisionmaking dynamics in the symmetric case of N equal-quality nests. Then, we generalise our findings to a best-of-N decision scenario with one superior nest and N – 1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signalling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signalling behaviours. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signalling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signalling ratio

Fluctuations in the Irreversible Decay of Turbulent Energy

A fluctuation law of the energy in freely-decaying, homogeneous and isotropic turbulence is derived within standard closure hypotheses for 3D incompressible flow. In particular, a fluctuation-dissipation relation is derived which relates the strength of a stochastic backscatter term in the energy decay equation to the mean of the energy dissipation rate. The theory is based on the so-called ``effective action'' of the energy history and illustrates a Rayleigh-Ritz method recently developed to evaluate the effective action approximately within probability density-function (PDF) closures. These effective actions generalize the Onsager-Machlup action of nonequilibrium statistical mechanics to turbulent flow. They yield detailed, concrete predictions for fluctuations, such as multi-time correlation functions of arbitrary order, which cannot be obtained by direct PDF methods. They also characterize the mean histories by a variational principle.Comment: 26 pages, Latex Version 2.09, plus seceq.sty, a stylefile for sequential numbering of equations by section. This version includes new discussion of the physical interpretation of the formal Rayleigh-Ritz approximation. The title is also change

A Multi-Objective Optimization for Supply Chain Network Using the Bees Algorithm

A supply chain is a complex network which involves the products, services and information flows between suppliers and customers. A typical supply chain is composed of different levels, hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between the multi-objectives such as cost minimization and lead-time minimization. There are several multi-objective optimization methods which have been applied to find the optimum solutions set based on the Pareto front line. In this study, a swarm-based optimization method, namely, the bees algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature and several experiments have been conducted in order to show the performance of the proposed model; in addition, the results have been compared to those achieved by the ant colony optimization method. The results show that the proposed bees algorithm is able to achieve better Pareto solutions for the supply chain problem

The Emerging Scholarly Brain

It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.Comment: to appear in Future Professional Communication in Astronomy-II (FPCA-II) editors A. Heck and A. Accomazz

Magnetic fluctuations in the classical XY model: the origin of an exponential tail in a complex system

We study the probability density function for the fluctuations of the magnetic order parameter in the low temperature phase of the XY model of finite size. In two-dimensions this system is critical over the whole of the low temperature phase. It is shown analytically and without recourse to the scaling hypothesis that, in this case, the distribution is non-Gaussian and of universal form, independent of both system size and critical exponent $\eta$. An exact expression for the generating function of the distribution is obtained, which is transformed and compared with numerical data from high resolution molecular dynamics and Monte Carlo simulations. The calculation is extended to general dimension and an exponential tail is found in all dimensions less than four, despite the fact that critical fluctuations are limited to D=2. These results are discussed in the light of similar behaviour observed in models of interface growth and for dissipative systems driven into a non-equilibrium steady state.Comment: 32 pages, 13 figures, 1 table. Few changes. To appear in Phys. Rev.

Aversive Learning in Honeybees Revealed by the Olfactory Conditioning of the Sting Extension Reflex

Invertebrates have contributed greatly to our understanding of associative learning because they allow learning protocols to be combined with experimental access to the nervous system. The honeybee Apis mellifera constitutes a standard model for the study of appetitive learning and memory since it was shown, almost a century ago, that bees learn to associate different sensory cues with a reward of sugar solution. However, up to now, no study has explored aversive learning in bees in such a way that simultaneous access to its neural bases is granted. Using odorants paired with electric shocks, we conditioned the sting extension reflex, which is exhibited by harnessed bees when subjected to a noxious stimulation. We show that this response can be conditioned so that bees learn to extend their sting in response to the odorant previously punished. Bees also learn to extend the proboscis to one odorant paired with sugar solution and the sting to a different odorant paired with electric shock, thus showing that they can master both appetitive and aversive associations simultaneously. Responding to the appropriate odorant with the appropriate response is possible because two different biogenic amines, octopamine and dopamine subserve appetitive and aversive reinforcement, respectively. While octopamine has been previously shown to substitute for appetitive reinforcement, we demonstrate that blocking of dopaminergic, but not octopaminergic, receptors suppresses aversive learning. Therefore, aversive learning in honeybees can now be accessed both at the behavioral and neural levels, thus opening new research avenues for understanding basic mechanisms of learning and memory

Challenging fear: Chemical alarm signals are not causing morphology changes in crucian carp (Carassius carassius)

Crucian carp develops a deep body in the presence of chemical cues from predators, which makes the fish less vulnerable to gape-limited predators. The active components originate in conspecifics eaten by predators, and are found in the filtrate of homogenised conspecific skin. Chemical alarm signals, causing fright reactions, have been the suspected inducers of such morphological changes. We improved the extraction procedure of alarm signals by collecting the supernatant after centrifugation of skin homogenates. This removes the minute particles that normally make a filtered sample get turbid. Supernatants were subsequently diluted and frozen into ice-cubes. Presence of alarm signals was confirmed by presenting thawed ice-cubes to crucian carp in behaviour tests at start of laboratory growth experiments. Frozen extracts were added further on three times a week. Altogether, we tested potential body-depth-promoting properties of alarm signals twice in the laboratory and once in the field. Each experiment lasted for a minimum of 50&nbsp;days. Despite growth of crucian carp in all experiments, no morphology changes were obtained. Accordingly, we conclude that the classical alarm signals that are releasing instant fright reactions are not inducing morphological changes in this species. The chemical signals inducing a body-depth increase are suspected to be present in the particles removed during centrifugation (i.e., in the precipitate). Tissue particles may be metabolized by bacteria in the intestine of predators, resulting in water-soluble cues. Such latent chemical signals have been found in other aquatic organisms, but hitherto not reported in fishe