Extending Hamiltonian Operators to Get Bi-Hamiltonian Coupled KdV Systems

An analysis of extension of Hamiltonian operators from lower order to higher order of matrix paves a way for constructing Hamiltonian pairs which may result in hereditary operators. Based on a specific choice of Hamiltonian operators of lower order, new local bi-Hamiltonian coupled KdV systems are proposed. As a consequence of bi-Hamiltonian structure, they all possess infinitely many symmetries and infinitely many conserved densities.Comment: 13 pages, late

Myogenic transcription factors regulate pro-metastatic miR-182

Approximately thirty percent of patients with soft-tissue sarcoma die from pulmonary metastases. The mechanisms that drive sarcoma metastasis are not well understood. Recently, we identified miR-182 as a driver of sarcoma metastasis in a primary mouse model of soft-tissue sarcoma. We also observed elevated miR-182 in a subset of primary human sarcomas that metastasized to the lungs. Here, we show that myogenic differentiation factors regulate miR-182 levels to contribute to metastasis in mouse models. We find that MyoD directly binds the miR-182 promoter to increase miR-182 expression. Furthermore, mechanistic studies revealed that Pax7 can promote sarcoma metastasis in vivo through MyoD-dependent regulation of pro-metastatic miR-182. Taken together, these results suggest that sarcoma metastasis can be partially controlled through Pax7/MyoD-dependent activation of miR-182 and provide insight into the role that myogenic transcription factors play in sarcoma progression

Coupled KdV equations of Hirota-Satsuma type

It is shown that the system of two coupled Korteweg-de Vries equations passes the Painlev\'e test for integrability in nine distinct cases of its coefficients. The integrability of eight cases is verified by direct construction of Lax pairs, whereas for one case it remains unknown

Robot Mapping and Localisation for Feature Sparse Water Pipes Using Voids as Landmarks

Robotic systems for water pipe inspection do not generally include navigation components for mapping the pipe network and locating damage. Such navigation systems would be highly advantageous for water companies because it would allow them to more effectively target maintenance and reduce costs. In water pipes, a major challenge for robot navigation is feature sparsity. In order to address this problem, a novel approach for robot navigation in water pipes is developed here, which uses a new type of landmark feature - voids outside the pipe wall, sensed by ultrasonic scanning. The method was successfully demonstrated in a laboratory environment and showed for the first time the potential of using voids for robot navigation in water pipes

Integrable KdV Systems: Recursion Operators of Degree Four

The recursion operator and bi-Hamiltonian formulation of the Drinfeld- Sokolov system are givenComment: Latex File, to be published in Physucs Letters

Robot mapping and localisation in metal water pipes using hydrophone induced vibration and map alignment by dynamic time warping

Water is a highly valuable resource so asset management of associated infrastructure is of critical importance. Water distribution pipe networks are usually buried, and so are difficult to access. Robots are therefore appealing for performing inspection and detecting damage to target repairs. However, robot mapping and localisation of buried water pipes has not been widely investigated to date, and is challenging because pipes tend to be relatively featureless. In this paper we propose a mapping and localisation algorithm for metal water pipes with two key novelties: the development of a new type of map based on hydrophone induced vibration signals of metal pipes, and a mapping algorithm based on spatial warping and averaging of dead reckoning signals used to calibrate the map (using dynamic time warping). Localisation is performed using both terrain-based extended Kalman filtering and also particle filtering. We successfully demonstrate and evaluate the approach on a combination of experimental and simulation data, showing improved localisation compared to dead reckoning

PipeSLAM: Simultaneous Localisation and Mapping in Feature Sparse Water Pipes using the Rao-Blackwellised Particle Filter

Water, a valuable resource, is usually distributed through urban environments by buried pipes. These pipes are difficult to access for inspection, maintenance and repair. This makes in-pipe robots an appealing technology for inspecting water pipes and localising damage prior to repair from above ground. Accurate localisation of damage is of critical importance because of the costs associated with excavating roads, disrupting traffic and disrupting the water supply. The problem is that pipes tend to be relatively featureless making robot localisation a challenging problem. In this paper we propose a novel simultaneous localisation and mapping (SLAM) algorithm for metal water pipes. The approach we take is to excite pipe vibration with a hydrophone (sound induced vibration), which leads to a map of pipe vibration amplitude over space. We then develop a SLAM algorithm that makes use of this new type of map, where the estimation method is based on the Rao-Blackwellised particle filter (RBPF), termed PipeSLAM. The approach is also suited to SLAM in plastic water pipes using a similar type of map derived from ultrasonic sensing. We successfully demonstrate the feasibility of the approach using a combination of experimental and simulation data

Non-Markovian Dynamics of Spin Squeezing

We evaluate the spin squeezing dynamics of N independent spin-1/2 particles with exchange symmetry. Each spin interacts with its own reservoir, and the reservoirs are independently and identical. The spin squeezing parameter is analytically calculated with different kinds of decoherence. The spin squeezing property vanishes with evolution time under the Markovian decoherence. Whereas coupled to the non-Markovian decoherence channels, the spin squeezing property collapses and revives with time. As spin squeezing can be regarded as a witness of multipartite entanglement, thus our scheme shows the collapse and revival of multipartite entanglement under non-Markovian decoherence.Comment: 13 pages, 7 figure