Observed Evidence of a Stable Atlantic Meridional Overturning Circulation since the 1990s

<p>The Atlantic Meridional Overturning Circulation (AMOC) is crucially important in the global climate system due to its role in the meridional heat and freshwater distribution. Model simulations and constructed AMOC indices suggest that the AMOC may have been weakening for decades. However, direct AMOC observations, introduced in 2004 in the subtropics (the RAPID program) and in 2014 in the subpolar North Atlantic (the OSNAP program), are not sufficiently long to capture changes dating back to previous periods. Here we use repeated hydrographic sections in the subtropical and subpolar North Atlantic through the early 1990s to the mid-2010s, combined with a box inverse model that is constrained using satellite altimetry, to analyze hydrographic changes and the AMOC. In combination with a state-of-the-art ocean state estimate, GECCO2, we show that despite dramatic hydrographic changes in the subtropical and subpolar North Atlantic over the past two and half decades, the AMOC has not significantly weakened over the same period. Our hydrography-based estimates also illustrate a remarkably stable partition of the subpolar overturning between the Labrador basin and the eastern subpolar basins on decadal timescales since the 1990s.</p>

A Coalition Formation Game Approach for Efficient Cooperative Multi-UAV Deployment

Unmanned aerial vehicle (UAV) cooperative control has been an important issue in UAV-assisted sensor networks, thanks to the considerable benefit obtained from the cooperative mechanism of UAVs being applied as a flying base station. In a coverage scenarios, the trade-off between coverage and transmission performance often makes deployment of UAVs fall into a dilemma, since both indexes are related to the distance between UAVs. To address this issue, UAV coverage and data transmission mechanism is analyzed in this paper; then, an efficient multi-UAV cooperative deployment model is proposed. The problem is modeled as a coalition formation game (CFG). The CFG with Pareto order is proved to have a stable partition. Then, an effective approach consisting of coverage deployment and coalition selection is designed, wherein UAVs can decide strategies cooperatively to achieve better coverage performance. Combining analysis of game approach, coalition selection and the position deployment algorithm based on Pareto order (CSPDA-PO) is designed to execute coverage deployment and coalition selection. Finally, simulation results are shown to validate the proposed approach based on an efficient multi-UAV cooperative deployment model.

A Coalition Formation Game Approach for Efficient Cooperative Multi-UAV Deployment

UAV cooperative control has been an important issue in UAV-assisted sensor network, thanks to the considerable benefit obtained from cooperative mechanism of UAVs being applied as a flying base station. In coverage scenario, the tradeoff between coverage performance and transmission performance often makes deployment of UAVs fall into a dilemma, since both indexes are related to the distance between UAVs. To address this issue, UAV coverage and data transmission mechanism is analyzed in this paper, then an efficient multi-UAV cooperative deployment model is proposed. The problem is also modeled as a coalition formation game (CFG). The CFG with Pareto order is proved to have a stable partition. Then, an effective approach consisting of coverage deployment and coalition selection is designed, wherein UAVs can decide strategies cooperatively to achieve better coverage performance. Combining analysis of game approach, a coalition selection and position deployment algorithm based on Pareto order (CSPDA-PO) is designed to execute coverage deployment and coalition selection. Finally, simulation results are shown to validate the proposed approach based on efficient multi-UAV cooperative deployment model.

A GENERIC APPROACH TO COALITION FORMATION

We propose an abstract approach to coalition formation that focuses on simple merge and split rules transforming partitions of a group of players. We identify conditions under which every iteration of these rules yields a unique partition. The main conceptual tool is a specific notion of a stable partition. The results are parametrized by a preference relation between partitions of a group of players and naturally apply to coalitional TU-games, hedonic games and exchange economy games.

Partitioned Transient Analysis Procedures for Coupled-Field Problems: Accuracy Analysis

Partitioned solution procedures for direct time integration of second-order coupled-field systems are studied from the standpoint of accuracy. These procedures are derived by three formulation steps: implicit integration of coupled governing equations, partitioning of resulting algebraic systems and extrapolation on the right-hand partition. It is shown that the combined effect of partition, extrapolation, and computational paths governs the choice of stable extrapolators and preservation of rigid-body motions. Stable extrapolators for various computational paths are derived and implementation-extrapolator combinations which preserve constant-velocity and constant-acceleration rigid-body motions are identified. A spectral analysis shows that the primary error source introduced by a stable partition is frequency distortion. Finally, as a guide to practical applications, the advantages and shortcomings of five specific partitions are discussed.

Dynamic clustering and strong patterns recognition: new tools in automatic classification

The dynamic clustering method (D.C.M.) developed by Diday is a nonhierarchical classification procedure which can help the geologist who is faced with the problem of forming groups among a multidimensional population of chemical analyses. Instead of computing the similarity between every possible pair of elements of a population, the D.C.M. suggests the use of a set of nuclei which will act as a template in the process of grouping elements together to form a partition of the population. By using the concept of similarity between an element and a group of elements, called a nucleus, the D.C.M. will assign a group number to every individual of the original population.When the first partition has been completed, the more representative elements of the groups are chosen and combined into an improved set of nuclei. This set will then be used to perform a second grouping and the whole process will be repeated over and over until no improvement can be achieved by an other iteration. The result is a local optimum, i.e. a stable partition into a given number of groups. The D.C.M. can be applied several times to the same set of data to generate different local optima (the starting set of nuclei being different). By grouping the elements which were classified together for every local optimum, a partition into an equal or greater number of groups can result. This is the concept of strong patterns.Three hundred and thirty-three rocks of the Monteregian Hills petrogenetic suite were classified on the basis of their content in ten major elements. Five major groups, corresponding to five different rock types could be easily recognized and discriminated without any a priori assumptions. It is suggested that the algorithms presented here could be used to achieve more subtle partitioning problems, efficiently and economically, on larger sets of data.