First Report of Diaporthe eres Causing Stem Canker on Peach (Prunus persica) in Italy

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Asynchronous Silent Programmable Matter Achieves Leader Election and Compaction

We study models and algorithms for Programmable Matter (PM), that is matter with the ability to change its physical properties (e.g., shape or optical properties) in a programmable fashion. PM can be implemented by assembling a system of weak self-organizing computational elements, called particles, that can be programmed via distributed algorithms to collectively achieve some global task. Recent advances in the production of nanotechnologies have rendered such systems increasingly possible in practice, thus triggering research interests from many areas of computer science. The most established models for PM assume that particles: are modeled as finite state automata; are all identical, executing the same algorithm based on local observation of the surroundings; live and operate in the cells of a hexagonal grid; can move from one cell to another by repeatedly alternating between a contracted state (a particle occupies one cell) and an expanded state (a particle occupies two neighboring cells). Given these elementary features, it is rather hard to design distributed algorithms even for basic tasks and, in fact, all existing solutions to solve fundamental problems via PM have resorted to endowing PM systems with various capabilities to overcome such hardness, thus assuming quite unrealistic features. In this paper, we move toward more realistic computational models for PM. Specifically, we first introduce, a new modeling approach that relaxes several assumptions used in previous ones. Second, we present a distributed algorithm to solve, in the model, a foundational primitive for PM, namely Leader Election. This algorithm works in O(n) rounds for all initial configurations of n particles that are both connected (i.e. particles induce a connected graph) and compact (i.e. without holes, that is no empty cells surrounded by particles occur). As usual in asynchronous contexts, a round is intended as the time within which all particles have been activated at least once. Third, we show that, if the initial configuration admits holes, it is impossible to achieve leader election while preserving connectivity. Finally, by slightly empowering the robots, we design an algorithm to handle initial configurations admitting holes that in O(n2) rounds solves the leader election problem while obtaining also compaction

Forming Sequences of Patterns with Luminous Robots

The extensive studies on computing by a team of identical mobile robots operating in the plane in Look-Compute-Move cycles have been carried out mainly in the traditional {mathcal{ OBLOT}} model, where the robots are silent (have no communication capabilities) and oblivious (in a cycle, they have no memory previous cycles). To partially overcome the limits of obliviousness and silence while maintaining some of their advantages, the stronger model of luminous robots, {mathcal{ LUMI}} , has been introduced where the robots, otherwise oblivious and silent, carry a visible light that can take a number of different colors; a color can be seen by observing robots, and persists from a cycle to the next. In the study of the computational impact of lights, an immediate concern has been to understand and determine the additional computational strength of {mathcal{ LUMI}} over {mathcal{ OBLOT}}. Within this line of investigation, we examine the problem of forming a sequence of geometric patterns, PatternSequenceFormation. A complete characterization of the sequences of patterns formable from a given starting configuration has been determined in the {mathcal{ OBLOT}} model. In this paper, we study the formation of sequences of patterns in the {mathcal{ LUMI}} model and provide a complete characterization. The characterization is constructive: our universal protocol forms all formable sequences, and it does so asynchronously and without rigidity. This characterization explicitly and clearly identifies the computational strength of {mathcal{ LUMI}} over {mathcal{ OBLOT}} with respect to the Pattern Sequence Formation problem

Gathering Anonymous, Oblivious Robots on a Grid

We consider a swarm of $n$ autonomous mobile robots, distributed on a 2-dimensional grid. A basic task for such a swarm is the gathering process: All robots have to gather at one (not predefined) place. A common local model for extremely simple robots is the following: The robots do not have a common compass, only have a constant viewing radius, are autonomous and indistinguishable, can move at most a constant distance in each step, cannot communicate, are oblivious and do not have flags or states. The only gathering algorithm under this robot model, with known runtime bounds, needs $\mathcal{O}(n^2)$ rounds and works in the Euclidean plane. The underlying time model for the algorithm is the fully synchronous $\mathcal{FSYNC}$ model. On the other side, in the case of the 2-dimensional grid, the only known gathering algorithms for the same time and a similar local model additionally require a constant memory, states and "flags" to communicate these states to neighbors in viewing range. They gather in time $\mathcal{O}(n)$. In this paper we contribute the (to the best of our knowledge) first gathering algorithm on the grid that works under the same simple local model as the above mentioned Euclidean plane strategy, i.e., without memory (oblivious), "flags" and states. We prove its correctness and an $\mathcal{O}(n^2)$ time bound in the fully synchronous $\mathcal{FSYNC}$ time model. This time bound matches the time bound of the best known algorithm for the Euclidean plane mentioned above. We say gathering is done if all robots are located within a $2\times 2$ square, because in $\mathcal{FSYNC}$ such configurations cannot be solved

Complement system network in cell physiology and in human diseases

The complement system is a multi-functional system representing the first line host defense against pathogens in innate immune response, through three different pathways. Impairment of its function, consisting in deficiency or excessive deregulated activation, may lead to severe systemic infections or autoimmune disorders. These diseases may be inherited or acquired. Despite many diagnostic tools are currently available, ranging from traditional, such as hemolytic or ELISA based assays, to innovative ones, like next generation sequencing techniques, these diseases are often not recognized. As for therapeutic aspects, strategies based on the use of targeted drugs are now widespread. The aim of this review is to present an updated overview of complement system pathophysiology, clinical implications of its dysfunction and to summarize diagnostic and therapeutic approaches

Parallel Search with no Coordination

We consider a parallel version of a classical Bayesian search problem. $k$ agents are looking for a treasure that is placed in one of the boxes indexed by $\mathbb{N}^+$ according to a known distribution $p$. The aim is to minimize the expected time until the first agent finds it. Searchers run in parallel where at each time step each searcher can "peek" into a box. A basic family of algorithms which are inherently robust is \emph{non-coordinating} algorithms. Such algorithms act independently at each searcher, differing only by their probabilistic choices. We are interested in the price incurred by employing such algorithms when compared with the case of full coordination. We first show that there exists a non-coordination algorithm, that knowing only the relative likelihood of boxes according to $p$, has expected running time of at most $10+4(1+\frac{1}{k})^2 T$, where $T$ is the expected running time of the best fully coordinated algorithm. This result is obtained by applying a refined version of the main algorithm suggested by Fraigniaud, Korman and Rodeh in STOC'16, which was designed for the context of linear parallel search.We then describe an optimal non-coordinating algorithm for the case where the distribution $p$ is known. The running time of this algorithm is difficult to analyse in general, but we calculate it for several examples. In the case where $p$ is uniform over a finite set of boxes, then the algorithm just checks boxes uniformly at random among all non-checked boxes and is essentially $2$ times worse than the coordinating algorithm.We also show simple algorithms for Pareto distributions over $M$ boxes. That is, in the case where $p(x) \sim 1/x^b$ for $0< b < 1$, we suggest the following algorithm: at step $t$ choose uniformly from the boxes unchecked in ${1, . . . ,min(M, \lfloor t/\sigma\rfloor)}$, where $\sigma = b/(b + k - 1)$. It turns out this algorithm is asymptotically optimal, and runs about $2+b$ times worse than the case of full coordination

Neutralization of IFN-γ reverts clinical and laboratory features in a mouse model of macrophage activation syndrome.

BACKGROUND: The pathogenesis of macrophage activation syndrome (MAS) is not clearly understood: a large body of evidence supports the involvement of mechanisms similar to those implicated in the setting of primary hemophagocytic lymphohistiocytosis. OBJECTIVE: We sought to investigate the pathogenic role of IFN-γ and the therapeutic efficacy of IFN-γ neutralization in an animal model of MAS. METHODS: We used an MAS model established in mice transgenic for human IL-6 (IL-6TG mice) challenged with LPS (MAS mice). Levels of IFN-γ and IFN-γ-inducible chemokines were evaluated by using real-time PCR in the liver and spleen and by means of ELISA in plasma. IFN-γ neutralization was achieved by using the anti-IFN-γ antibody XMG1.2 in vivo. RESULTS: Mice with MAS showed a significant upregulation of the IFN-γ pathway, as demonstrated by increased mRNA levels of Ifng and higher levels of phospho-signal transducer and activator of transcription 1 in the liver and spleen and increased expression of the IFN-γ-inducible chemokines Cxcl9 and Cxcl10 in the liver and spleen, as well as in plasma. A marked increase in Il12a and Il12b expression was also found in livers and spleens of mice with MAS. In addition, mice with MAS had a significant increase in numbers of liver CD68+ macrophages. Mice with MAS treated with an anti-IFN-γ antibody showed a significant improvement in survival and body weight recovery associated with a significant amelioration of ferritin, fibrinogen, and alanine aminotransferase levels. In mice with MAS, treatment with the anti-IFN-γ antibody significantly decreased circulating levels of CXCL9, CXCL10, and downstream proinflammatory cytokines. The decrease in CXCL9 and CXCL10 levels paralleled the decrease in serum levels of proinflammatory cytokines and ferritin. CONCLUSION: These results provide evidence for a pathogenic role of IFN-γ in the setting of MAS