Making Self-Stabilizing any Locally Greedy Problem

We propose a way to transform synchronous distributed algorithms solving locally greedy and mendable problems into self-stabilizing algorithms in anonymous networks. Mendable problems are a generalization of greedy problems where any partial solution may be transformed -- instead of completed -- into a global solution: every time we extend the partial solution we are allowed to change the previous partial solution up to a given distance. Locally here means that to extend a solution for a node, we need to look at a constant distance from it. In order to do this, we propose the first explicit self-stabilizing algorithm computing a $(k,k-1)$-ruling set (i.e. a "maximal independent set at distance $k$"). By combining multiple time this technique, we compute a distance-$K$ coloring of the graph. With this coloring we can finally simulate \local~model algorithms running in a constant number of rounds, using the colors as unique identifiers. Our algorithms work under the Gouda daemon, which is similar to the probabilistic daemon: if an event should eventually happen, it will occur under this daemon

In vivo expression of natural killer cell inhibitory receptors by human melanoma-specific cytolytic T lymphocytes.

Natural killer (NK) receptor signaling can lead to reduced cytotoxicity by NK cells and cytolytic T lymphocytes (CTLs) in vitro. Whether T cells are inhibited in vivo remains unknown, since peptide antigen-specific CD8(+) T cells have so far not been found to express NK receptors in vivo. Here we demonstrate that melanoma patients may bear tumor-specific CTLs expressing NK receptors. The lysis of melanoma cells by patient-derived CTLs was inhibited by the NK receptor CD94/NKG2A. Thus, tumor-specific CTL activity may be decreased through NK receptor triggering in vivo

Making Self-Stabilizing Algorithms for Any Locally Greedy Problem

Self-stabilizing algorithms are a way to deal with network dynamicity, as it will update itself after a network change (addition or removal of nodes or edges), as long as changes are not frequent. We propose an automatic transformation of synchronous distributed algorithms that solve locally greedy and mendable problems into self-stabilizing algorithms in anonymous networks. Mendable problems are a generalization of greedy problems where any partial solution may be transformed -instead of completed- into a global solution: every time we extend the partial solution, we are allowed to change the previous partial solution up to a given distance. Locally here means that to extend a solution for a node, we need to look at a constant distance from it. In order to do this, we propose the first explicit self-stabilizing algorithm computing a (k,k-1)-ruling set (i.e. a "maximal independent set at distance k"). By combining this technique multiple times, we compute a distance-K coloring of the graph. With this coloring we can finally simulate Local model algorithms running in a constant number of rounds, using the colors as unique identifiers. Our algorithms work under the Gouda daemon, similar to the probabilistic daemon: if an event should eventually happen, it will occur

Le problème du voyageur canadien dans les graphes temporels

This paper formalises the Canadian Traveller problem as a positional two-player game on graphs. We consider two variants depending on whether an edge is blocked. In the locally-informed variant, the traveller learns if an edge is blocked upon reaching one of its endpoints, while in the uninformed variant, they discover this only when the edge is supposed to appear. We provide a polynomial algorithm for each shortest path variant in the uninformed case. This algorithm also solves the case of directed acyclic non-temporal graphs. In the locally-informed case, we prove that finding a winning strategy is PSPACE-complete. Moreover, we establish that the problem is polynomial-time solvable when $k=1$ but NP-hard for $k\geq 2$. Additionally, we show that the standard (non-temporal) Canadian Traveller Problem is NP-hard when there are $k\geq 4$ blocked edges, which is, to the best of our knowledge, the first hardness result for CTP for a constant number of blocked edges

How to switch disease-modifying treatments in multiple sclerosis: Guidelines from the French Multiple Sclerosis Society (SFSEP)

BACKGROUND: Today, there are no recommendations on switching disease-modifying treatments (DMTs) in multiple sclerosis (MS). OBJECTIVES: To establish guidelines on switching DMTs MS. METHODS: A Steering Committee composed of seven MS experts from the French Group for Recommendations in Multiple Sclerosis (France4MS) defined 15 proposals. These proposals were then submitted to a Rating Group, composed of 48 French MS experts, for evaluation. The proposals were classified as 'appropriate', 'inappropriate' or 'uncertain'. RESULTS: Switching from a first-line therapy to another first-line therapy or a second-line therapy could be done without a washout period. Switching from a second-line therapy to a first-line therapy could be done without a washout period with fingolimod or natalizumab, after 3 months with ocrelizumab or mitoxantrone, and, if disease activity occurs with alemtuzumab or cladribine. The switch from a second-line therapy to another second-line therapy could be done after a washout period of 1 month with fingolimod or natalizumab, after 3 months with ocrelizumab, after 6 months with mitoxantrone, and, if disease activity occurs, with alemtuzumab or cladribine. CONCLUSION: This expert consensus approach provides physicians with some guidelines on optimizing the benefit/risk ratio when switching DMTs in patients with MS