36 research outputs found

    Odour-mediated orientation of beetles is influenced by age, sex and morph

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    The behaviour of insects is dictated by a combination of factors and may vary considerably between individuals, but small insects are often considered en masse and thus these differences can be overlooked. For example, the cowpea bruchid Callosobruchus maculatus F. exists naturally in two adult forms: the active (flight) form for dispersal, and the inactive (flightless), more fecund but shorter-lived form. Given that these morphs show dissimilar biology, it is possible that they differ in odour-mediated orientation and yet studies of this species frequently neglect to distinguish morph type, or are carried out only on the inactive morph. Along with sex and age of individual, adult morph could be an important variable determining the biology of this and similar species, informing studies on evolution, ecology and pest management. We used an olfactometer with motion-tracking to investigate whether the olfactory behaviour and orientation of C. maculatus towards infested and uninfested cowpeas and a plant-derived repellent compound, methyl salicylate, differed between morphs or sexes. We found significant differences between the behaviour of male and female beetles and beetles of different ages, as well as interactive effects of sex, morph and age, in response to both host and repellent odours. This study demonstrates that behavioural experiments on insects should control for sex and age, while also considering differences between adult morphs where present in insect species. This finding has broad implications for fundamental entomological research, particularly when exploring the relationships between physiology, behaviour and evolutionary biology, and the application of crop protection strategies

    A Resource and policy aware VM scheduler for medium-scale clouds

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    Medium-scale private clouds are being widely used in enterprises and universities. While, these clouds have a relatively small pool of resources, diversity of those resources, users, and their needs are still comparable with public clouds. We present a resource and policy aware Virtual Machine (VM) scheduling solution for such medium-scale clouds. The proposed scheduler enables the deployment of VMs based on a predefined set of policies and user priorities, while being aware of the resource utilization of the cloud. This is achieved by periodically polling resource statistics from the cloud nodes, enforcing a set of predefined policies, taking into account the priority levels of users and VM requests, and then scaling, migrating, and preempting VMs based on available resources and policies. Such resource and policy aware scheduling improves resource request acceptance rate and increases the utilization of cloud resources. A proof of concept solution is implemented using Apache CloudStack and validated against a carefully crafted set of resource requests
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