Bilevel shared control for teleoperators

A shared system is disclosed for robot control including integration of the human and autonomous input modalities for an improved control. Autonomously planned motion trajectories are modified by a teleoperator to track unmodelled target motions, while nominal teleoperator motions are modified through compliance to accommodate geometric errors autonomously in the latter. A hierarchical shared system intelligently shares control over a remote robot between the autonomous and teleoperative portions of an overall control system. Architecture is hierarchical, and consists of two levels. The top level represents the task level, while the bottom, the execution level. In space applications, the performance of pure teleoperation systems depend significantly on the communication time delays between the local and the remote sites. Selection/mixing matrices are provided with entries which reflect how each input's signals modality is weighted. The shared control minimizes the detrimental effects caused by these time delays between earth and space

A parallel and adaptive multigrid solver for the solutions of the optimal control of geometric evolution laws in two and three dimensions

We present a problem concerning the optimal control of geometric evolution laws. This is a minimisation problem that aims to find a control η which minimises the objective functional J subject to some imposed constraints. We apply this methodology to an application of whole cell tracking. Given two sets of data of cell morphologies, we may solve the optimal control problem to dynamically reconstruct the cell movements between the time frame of these two sets of data. This problem is solved in two and three space dimensions, using a state-of-the-art numerical method, namely multigrid, with adaptivity and parallelism

Spoilage of mackerels preserved in oil

While studying the preservation of mackerels in oil, we came across a type of spoilage similar to "sulfide stinker". Evolution of a stream of bubbles was noticed in less than 48 hours and within a week the fish disintegrated into a pulpy mass

An optimal control approach to cell tracking

Cell tracking is of vital importance in many biological studies, hence robust cell tracking algorithms are needed for inference of dynamic features from (static) in vivo and in vitro experimental imaging data of cells migrating. In recent years much attention has been focused on the modelling of cell motility from physical principles and the development of state-of-the art numerical methods for the simulation of the model equations. Despite this, the vast majority of cell tracking algorithms proposed to date focus solely on the imaging data itself and do not attempt to incorporate any physical knowledge on cell migration into the tracking procedure. In this study, we present a mathematical approach for cell tracking, in which we formulate the cell tracking problem as an inverse problem for fitting a mathematical model for cell motility to experimental imaging data. The novelty of this approach is that the physics underlying the model for cell migration is encoded in the tracking algorithm. To illustrate this we focus on an example of Zebrafish (Danio rerio's larvae) Neutrophil migration and contrast an ad-hoc approach to cell tracking based on interpolation with the model fitting approach we propose in this study

Mussel pollution at Korapuzha estuary (Malabar), with an account of certain coliform types

Oysters, mussels and other shell-fish are highly nutritious foods, which, apart from their usual proximate principles, contain fairly high amounts of minerals like iodine, copper, iron, etc., and vitamins. In the shallow rocky areas of Malabar Coast there are numerous green mussel (Mytilus edulis) beds from which large quantities of mussels are taken out almost throughout the year, which form an important item of food for people of low incomes. As the mussels grow in shallow areas subject to the influence of land drainage, sewage and river systems, these beds constitute a potential hazard to public health on account of possible epidemic infections being carried by the shell-fish

Kin recognition in a semi-natural context: behaviour towards foreign conspecifics in the social wasp Ropalidia marginata (Lep.) (Hymenoptera: Vespidae)

Female wasps of the tropical primitively eusocial species Ropalidia marginata are known to discriminate unfamiliar nestmates from unfamiliar non-nestmates outside the context of their nests. Here, we show that when foreign conspecifics are introduced in the context of a nest in laboratory cages, genetic relatives among them are treated by nest inhabitants more tolerantly than non-relatives, but that no foreign conspecifics are accepted into the nests. However, some wasps may leave their nest and join the foreign relatives and non-relatives to found new colonies cooperatively. Very few of the introduced animals are severely attacked or killed; most are allowed to remain in parts of the cage away from the nest. These results suggest that factors other than genetic relatedness may be involved in regulating tolerance and acceptance of foreign conspecifics on a nest and its vicinity. Our results are different from those of similar experiments with ants, which have demonstrated that former nestmates that are removed as pupae and later introduced as adults are either accepted into the nest or attacked and killed. We attribute this difference to the fact that in a primitively eusocial species such as R. marginata, the rules governing tolerance and acceptance of foreign conspecifics must be quite different from those in highly eusocial species. We also attempt to test some predictions of the conspecific acceptance threshold models of Reeve (Am. Nat. 133:407-435, 1989). Our results uphold the predictions of his fitness consequence submodel but do not support those of his "interaction frequency sub-model"

Implicit-explicit timestepping with finite element approximation of reaction-diffusion systems on evolving domains

We present and analyse an implicit-explicit timestepping procedure with finite element spatial approximation for a semilinear reaction-diffusion systems on evolving domains arising from biological models, such as Schnakenberg's (1979). We employ a Lagrangian formulation of the model equations which permits the error analysis for parabolic equations on a fixed domain but introduces technical difficulties, foremost the space-time dependent conductivity and diffusion. We prove optimal-order error estimates in the \Lp{\infty}(0,T;\Lp{2}(\W)) and \Lp{2}(0,T;\Hil{1}(\W)) norms, and a pointwise stability result. We remark that these apply to Eulerian solutions. Details on the implementation of the Lagrangian and the Eulerian scheme are provided. We also report on a numerical experiment for an application to pattern formation on an evolving domain