Motility fractionation of bacteria by centrifugation

Centrifugation is a widespread laboratory technique used to separate mixtures into fractions characterized by a specific size, weight or density. We demonstrate that centrifugation can be also used to separate swimming cells having different motility. To do this we study self-propelled bacteria under the influence of an external centrifugal field. Using dynamic image correlation spectroscopy we measure the spatially resolved motility of bacteria after centrifugation. A significant gradient in swimming-speeds is observed for increasing centrifugal speeds. Our results can be reproduced by a model that treats bacteria as "hot" colloidal particles having a diffusion coefficient that depends on the swimming speed.Comment: 7 pages, 5 figures (in press

Model Predictive Sample-based Motion Planning for Unmanned Aircraft Systems

This paper presents an innovative kinodynamic motion planning algorithm for Unmanned Aircraft Systems, called MP-RRT#. MP-RRT# leverages the idea of RRT# and the Model Predictive Control strategy to solve a motion planning problem under differential constraints. Similar to RRT#, the algorithm explores the map by constructing an asymptotically optimal graph. Each time the graph is extended with a new vertex, a forward simulation is performed with a Model Predictive Control to evaluate the motion between two adjacent vertices and compute the trajectory in the state space and the control space. As result, the MP-RRT# algorithm generates a feasible trajectory for the UAS satisfying dynamic constraints. Preliminary simulation results corroborate the proposed approach, in which the computed trajectory is executed by a simulated drone controlled with the PX4 autopilot

Exploring the interplay between urban governance and smart services codesign

The large spreading of e-democracy and e-participatory tools and environments showed, and is still showing, that technologies offer new direction for dealing with the challenge of scaling the deliberative democracy perspective up to the urban governance scale. The recent growth of Urban Living Labs and Human Smart City initiatives is disclosing a promising bridge between the micro-scale of decision and the mechanisms of urban governance. In coherence with these perspectives, the article reports on the interplay between urban governance and the co-design of smart services in urban transformation as it has been observed and analysed in the two European research projects Periphèria and MyNeinghbourhood. The article also discusses the value of service codesign as a strategic practice to experiment new participatory governance in smart cities

Auction-Based Task Allocation and Motion Planning for Multi-Robot Systems with Human Supervision

This paper presents a task allocation strategy for a multi-robot system with a human supervisor. The multi-robot system consists of a team of heterogeneous robots with different capabilities that operate in a dynamic scenario that can change in the robots’ capabilities or in the operational requirements. The human supervisor can intervene in the operation scenario by approving the final plan before its execution or forcing a robot to execute a specific task. The proposed task allocation strategy leverages an auction-based method in combination with a sampling-based multi-goal motion planning. The latter is used to evaluate the costs of execution of tasks based on realistic features of paths. The proposed architecture enables the allocation of tasks accounting for priorities and precedence constraints, as well as the quick re-allocation of tasks after a dynamic perturbation occurs –a crucial feature when the human supervisor preempts the outcome of the algorithm and makes manual adjustments. An extensive simulation campaign in a rescue scenario validates our approach in dynamic scenarios comprising a sensor failure of a robot, a total failure of a robot, and a human-driven re-allocation. We highlight the benefits of the proposed multi-goal strategy by comparing it with single-goal motion planning strategies at the state of the art. Finally, we provide evidence for the system efficiency by demonstrating the powerful synergistic combination of the auction-based allocation and the multi-goal motion planning approach

The impact of deniers on epidemics: A temporal network model

We propose a novel network epidemic model to elucidate the impact of deniers on the spread of epidemic diseases. Specifically, we study the spread of a recurrent epidemic disease, whose progression is captured by a susceptible–infected–susceptible model, in a population partitioned into two groups: cautious individuals and deniers. Cautious individuals may adopt self-protective behaviors, possibly incentivized by information campaigns implemented by public authorities; on the contrary, deniers reject their adoption. Through a mean-field approach, we analytically derive the epidemic threshold for large-scale homogeneous networks, shedding light onto the role of deniers in shaping the course of an epidemic outbreak. Specifically, our analytical insight suggests that even a small minority of deniers may jeopardize the effort of public health authorities when the population is highly polarized. Numerical results extend our analytical findings to heterogeneous networks