Gene co-citation networks associated with worker sterility in honey bees.

BACKGROUND: The evolution of reproductive self-sacrifice is well understood from kin theory, yet our understanding of how actual genes influence the expression of reproductive altruism is only beginning to take shape. As a model in the molecular study of social behaviour, the honey bee Apis mellifera has yielded hundreds of genes associated in their expression with differences in reproductive status of females, including genes directly associated with sterility, yet there has not been an attempt to link these candidates into functional networks that explain how workers regulate sterility in the presence of queen pheromone. In this study we use available microarray data and a co-citation analysis to describe what gene interactions might regulate a worker\u27s response to ovary suppressing queen pheromone. RESULTS: We reconstructed a total of nine gene networks that vary in size and gene composition, but that are significantly enriched for genes of reproductive function. The networks identify, for the first time, which candidate microarray genes are of functional importance, as evidenced by their degree of connectivity to other genes within each of the inferred networks. Our study identifies single genes of interest related to oogenesis, including eggless, and further implicates pathways related to insulin, ecdysteroid, and dopamine signaling as potentially important to reproductive decision making in honey bees. CONCLUSIONS: The networks derived here appear to be variable in gene composition, hub gene identity, and the overall interactions they describe. One interpretation is that workers use different networks to control personal reproduction via ovary activation, perhaps as a function of age or environmental circumstance. Alternatively, the multiple networks inferred here may represent segments of the larger, single network that remains unknown in its entirety. The networks generated here are provisional but do offer a new multi-gene framework for understanding how honey bees regulate personal reproduction within their highly social breeding system

The effect of aspect ratio on the wake of the Ahmed body

This paper seeks to further elucidate the wake of the Ahmed body by investigating how the time-averaged flow structures vary with frontal aspect ratio. High-resolution particle image velocimetry results are provided for eight different width Ahmed geometries at Re = 3 × 10^4. It is shown that the narrower the body, the greater the downwash over the back slant, meaning the flow remains more attached. At a critical aspect ratio ( AR = 1.9), the flow downstream changes. The separation over the back slant is shown to be affected by the AR, and this in turn has a significant effect on the circulation in the c-pillar vortices

The nature of the vortical structures in the near wake of the Ahmed body

This study presents the results from high-spatial-resolution water-channel velocity-field measurements behind an Ahmed body with 25° rear slant angle. The Ahmed body represents a simplified generic model of a hatchback automobile that has been widely used to study near-wake flow dynamics. The results help clarify the unresolved question of whether the time-mean near-wake flow structure is topologically equivalent to a toroidal vortex or better described by a pair of horizontally aligned horseshoe vortices, with their legs pointing downstream. The velocimetry data presented allows the tracking of the vortical structures throughout the near wake through a set of orthogonal planes, as well as the measurement of their circulation. The spanwise vortices that form as the flow separates from the top and bottom rear edges are shown to tilt downstream at the sides of the body, while no evidence is found of a time-mean attached toroidal vortex, at least for the Reynolds number (based on the square root of the frontal area) of Re~30000 under consideration

Machine Learning Topological Invariants with Neural Networks

In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.Comment: 6 pages, 4 figures and 1 table + 2 pages of supplemental materia

Bivalve Grazing Can Shape Phytoplankton Communities

The ability of bivalve filter feeders to limit phytoplankton biomass in shallow waters is well-documented, but the role of bivalves in shaping phytoplankton communities is not. The coupled effect of bivalve grazing at the sediment-water interface and sinking of phytoplankton cells to that bottom filtration zone could influence the relative biomass of sinking (diatoms) and non-sinking phytoplankton. Simulations with a pseudo-2D numerical model showed that benthic filter feeding can interact with sinking to alter diatom:non-diatom ratios. Cases with the smallest proportion of diatom biomass were those with the fastest sinking speeds and strongest bivalve grazing rates. Hydrodynamics modulated the coupled sinking-grazing influence on phytoplankton communities. For example, in simulations with persistent stratification, the non-sinking forms accumulated in the surface layer away from bottom grazers while the sinking forms dropped out of the surface layer toward bottom grazers. Tidal-scale stratification also influenced vertical gradients of the two groups in opposite ways. The model was applied to Suisun Bay, a low-salinity habitat of the San Francisco Bay system that was transformed by the introduction of the exotic clam Potamocorbula amurensis. Simulation results for this Bay were similar to (but more muted than) those for generic habitats, indicating that P. amurensis grazing could have caused a disproportionate loss of diatoms after its introduction. Our model simulations suggest bivalve grazing affects both phytoplankton biomass and community composition in shallow waters. We view these results as hypotheses to be tested with experiments and more complex modeling approaches

Polygyny without wealth: popularity in gift games predicts polygyny in BaYaka Pygmies.

The occurrence of polygynous marriage in hunter-gatherer societies, which do not accumulate wealth, remains largely unexplored since resource availability is dependent on male hunting capacity and limited by the lack of storage. Hunter-gatherer societies offer the greatest insight in to human evolution since they represent the majority of our species' evolutionary history. In order to elucidate the evolution of hunter-gatherer polygyny, we study marriage patterns of BaYaka Pygmies. We investigate (i) rates of polygyny among BaYaka hunter-gatherers; (ii) whether polygyny confers a fitness benefit to BaYaka men; (iii) in the absence of wealth inequalities, what are the alternative explanations for polygyny among the BaYaka. To understand the latter, we explore differences in phenotypic quality (height and strength), and social capital (popularity in gift games). We find polygynous men have increased reproductive fitness; and that social capital and popularity but not phenotypic quality might have been important mechanisms by which some male hunter-gatherers sustained polygynous marriages before the onset of agriculture and wealth accumulation