Modulation of fatty acid elongation generates sexually dimorphic hydrocarbons and female attractiveness in Blattella germanica (L.)

Insect cuticular compounds serve multiple functions. As important intersexual signaling chemicals, they show variation between the sexes, but little is known about the underlying molecular mechanisms. Here, we report that sexually dimorphic hydrocarbons (SDHCs) are generated by a fatty acid elongase gene that is regulated by sex-differentiation genes in the German cockroach, Blattella germanica. Sexually mature females possess more C29 cuticular hydrocarbons (CHCs), especially the contact sex pheromone precursor 3,11-DimeC29. An RNAi screen and heterologous expression revealed that BgElo12 and BgElo24 were involved in HC production, but only BgElo12 was responsible for SDHCs. Repressing female-enriched BgElo12 masculinized the female CHC profile, decreased contact sex pheromone level, and reduced the female sexual attractiveness. Moreover, RNAi of the sex-differentiation genes BgTra or BgDsx modulated both BgElo12 transcripts and CHC profiles in females and males. The SDHCs are shaped by sexual selection, as females use them to keep high levels of sex pheromone.

Source Location Privacy Using Ant Colony Optimization in Wireless Sensor Networks

One of the important application domain of sensor network is monitoring a region and/or tracking a target. In such type of applications, the location of the source node tracking that target is very important. At the same time, if the location of the node currently tracking the target is captured by an adversary then that target may fall into a difficult situation. In this chapter, a solution to source location privacy with the help of Ant Colony Optimization is proposed. The idea of pheromone level is normally used to find out the shortest path between the source node and the base station that to minimize the energy consumption of the networks. The pheromone level of the ants is used here to guide the ants to follow different paths to hide the source location from adversaries who uses traffic analysis to capture the source node.

Source Location Privacy Using Ant Colony Optimization in Wireless Sensor Networks

One of the important application domain of sensor network is monitoring a region and/or tracking a target. In such type of applications, the location of the source node tracking that target is very important. At the same time, if the location of the node currently tracking the target is captured by an adversary then that target may fall into a difficult situation. In this chapter, a solution to source location privacy with the help of Ant Colony Optimization is proposed. The idea of pheromone level is normally used to find out the shortest path between the source node and the base station that to minimize the energy consumption of the networks. The pheromone level of the ants is used here to guide the ants to follow different paths to hide the source location from adversaries who uses traffic analysis to capture the source node.

DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM

In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots) with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we develop a new police patrolling strategy based on Bayesian method and ant colony algorithm. In this strategy, virtual marker (pheromone) is laid to mark the visiting history of each crime hotspot, and patrollers continuously decide which hotspot to patrol next based on pheromone level and other variables. Simulation results using real data testifies the effective, scalable, unpredictable and extensible nature of this strategy.