752 research outputs found

    Edit Distance for Pushdown Automata

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    The edit distance between two words w1 , w2 is the minimal number of word operations (letter insertions, deletions, and substitutions) necessary to transform w1 to w2 . The edit distance generalizes to languages L1 , L2 , where the edit distance is the minimal number k such that for every word from L1 there exists a word in L2 with edit distance at most k. We study the edit distance computation problem between pushdown automata and their subclasses. The problem of computing edit distance to a pushdown automaton is undecidable, and in practice, the interesting question is to compute the edit distance from a pushdown automaton (the implementation, a standard model for programs with recursion) to a regular language (the specification). In this work, we present a complete picture of decidability and complexity for deciding whether, for a given threshold k, the edit distance from a pushdown automaton to a finite automaton is at most k

    The yeast Arf-GAP Glo3p is required for the endocytic recycling of cell surface proteins

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    Small GTP-binding proteins of the Ras superfamily play diverse roles in intracellular trafficking. Among them, the Rab, Arf, and Rho families function in successive steps of vesicle transport, in forming vesicles from donor membranes, directing vesicle trafficking toward target membranes and docking vesicles onto target membranes. These proteins act as molecular switches that are controlled by a cycle of GTP binding and hydrolysis regulated by guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs). In this study we explored the role of GAPs in the regulation of the endocytic pathway using fluorescently labeled yeast mating pheromone α-factor. Among 25 non-essential GAP mutants, we found that deletion of the GLO3 gene, encoding Arf-GAP protein, caused defective internalization of fluorescently labeled α-factor. Quantitative analysis revealed that glo3Δ cells show defective α-factor binding to the cell surface. Interestingly, Ste2p, the α-factor receptor, was mis-localized from the plasma membrane to the vacuole in glo3Δ cells. Domain deletion mutants of Glo3p revealed that a GAP-independent function, as well as the GAP activity, of Glo3p is important for both α-factor binding and Ste2p localization at the cell surface. Additionally, we found that deletion of the GLO3 gene affects the size and number of Arf1p-residing Golgi compartments and causes a defect in transport from the TGN to the plasma membrane. Furthermore, we demonstrated that glo3Δ cells were defective in the late endosome-to-TGN transport pathway, but not in the early endosome-to-TGN transport pathway. These findings suggest novel roles for Arf-GAP Glo3p in endocytic recycling of cell surface proteins

    The chain rule for HILL pseudoentropy, revisited

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    Computational notions of entropy (a.k.a. pseudoentropy) have found many applications, including leakage-resilient cryptography, deterministic encryption or memory delegation. The most important tools to argue about pseudoentropy are chain rules, which quantify by how much (in terms of quantity and quality) the pseudoentropy of a given random variable X decreases when conditioned on some other variable Z (think for example of X as a secret key and Z as information leaked by a side-channel). In this paper we give a very simple and modular proof of the chain rule for HILL pseudoentropy, improving best known parameters. Our version allows for increasing the acceptable length of leakage in applications up to a constant factor compared to the best previous bounds. As a contribution of independent interest, we provide a comprehensive study of all known versions of the chain rule, comparing their worst-case strength and limitations

    Efficient zero-knowledge proofs for commitments from learning with errors over rings

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    We extend a commitment scheme based on the learning with errors over rings (RLWE) problem, and present efficient companion zeroknowledge proofs of knowledge. Our scheme maps elements from the ring (or equivalently, n elements fro

    A Symbolic SAT-based Algorithm for Almost-sure Reachability with Small Strategies in POMDPs

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    POMDPs are standard models for probabilistic planning problems, where an agent interacts with an uncertain environment. We study the problem of almost-sure reachability, where given a set of target states, the question is to decide whether there is a policy to ensure that the target set is reached with probability 1 (almost-surely). While in general the problem is EXPTIME-complete, in many practical cases policies with a small amount of memory suffice. Moreover, the existing solution to the problem is explicit, which first requires to construct explicitly an exponential reduction to a belief-support MDP. In this work, we first study the existence of observation-stationary strategies, which is NP-complete, and then small-memory strategies. We present a symbolic algorithm by an efficient encoding to SAT and using a SAT solver for the problem. We report experimental results demonstrating the scalability of our symbolic (SAT-based) approach

    Navigating in tissue mazes: Chemoattractant interpretation in complex environments

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    Guided cell movement is essential for development and integrity of animals and crucially involved in cellular immune responses. Leukocytes are professional migratory cells that can navigate through most types of tissues and sense a wide range of directional cues. The responses of these cells to attractants have been mainly explored in tissue culture settings. How leukocytes make directional decisions in situ, within the challenging environment of a tissue maze, is less understood. Here we review recent advances in how leukocytes sense chemical cues in complex tissue settings and make links with paradigms of directed migration in development and Dictyostelium discoideum amoebae

    A sting in the spit: Widespread cross-infection of multiple RNA viruses across wild and managed bees

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    Summary: Declining populations of bee pollinators are a cause of concern, with major repercussions for biodiversity loss and food security. RNA viruses associated with honeybees represent a potential threat to other insect pollinators, but the extent of this threat is poorly understood. This study aims to attain a detailed understanding of the current and ongoing risk of emerging infectious disease (EID) transmission between managed and wild pollinator species across a wide range of RNA viruses. Within a structured large-scale national survey across 26 independent sites, we quantify the prevalence and pathogen loads of multiple RNA viruses in co-occurring managed honeybee (Apis mellifera) and wild bumblebee (Bombus spp.) populations. We then construct models that compare virus prevalence between wild and managed pollinators. Multiple RNA viruses associated with honeybees are widespread in sympatric wild bumblebee populations. Virus prevalence in honeybees is a significant predictor of virus prevalence in bumblebees, but we remain cautious in speculating over the principle direction of pathogen transmission. We demonstrate species-specific differences in prevalence, indicating significant variation in disease susceptibility or tolerance. Pathogen loads within individual bumblebees may be high and in the case of at least one RNA virus, prevalence is higher in wild bumblebees than in managed honeybee populations. Our findings indicate widespread transmission of RNA viruses between managed and wild bee pollinators, pointing to an interconnected network of potential disease pressures within and among pollinator species. In the context of the biodiversity crisis, our study emphasizes the importance of targeting a wide range of pathogens and defining host associations when considering potential drivers of population decline

    Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene

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    The Auxin Binding Protein1 (ABP1) has been identified based on its ability to bind auxin with high affinity and studied for a long time as a prime candidate for the extracellular auxin receptor responsible for mediating in particular the fast non-transcriptional auxin responses. However, the contradiction between the embryo-lethal phenotypes of the originally described Arabidopsis T-DNA insertional knock-out alleles (abp1-1 and abp1-1s) and the wild type-like phenotypes of other recently described loss-of-function alleles (abp1-c1 and abp1-TD1) questions the biological importance of ABP1 and relevance of the previous genetic studies. Here we show that there is no hidden copy of the ABP1 gene in the Arabidopsis genome but the embryo-lethal phenotypes of abp1-1 and abp1-1s alleles are very similar to the knock-out phenotypes of the neighboring gene, BELAYA SMERT (BSM). Furthermore, the allelic complementation test between bsm and abp1 alleles shows that the embryo-lethality in the abp1-1 and abp1-1s alleles is caused by the off-target disruption of the BSM locus by the T-DNA insertions. This clarifies the controversy of different phenotypes among published abp1 knock-out alleles and asks for reflections on the developmental role of ABP1

    The Complexity of Evolutionary Games on Graphs

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    Evolution occurs in populations of reproducing individuals. The structure of the population affects the outcome of the evolutionary process. Evolutionary graph theory is a powerful approach to study this phenomenon. There are two graphs. The interaction graph specifies who interacts with whom in the context of evolution.The replacement graph specifies who competes with whom for reproduction. The vertices of the two graphs are the same, and each vertex corresponds to an individual of the population. A key quantity is the fixation probability of a new mutant. It is defined as the probability that a newly introduced mutant (on a single vertex) generates a lineage of offspring which eventually takes over the entire population of resident individuals. The basic computational questions are as follows: (i) the qualitative question asks whether the fixation probability is positive; and (ii) the quantitative approximation question asks for an approximation of the fixation probability. Our main results are: (1) We show that the qualitative question is NP-complete and the quantitative approximation question is #P-hard in the special case when the interaction and the replacement graphs coincide and even with the restriction that the resident individuals do not reproduce (which corresponds to an invading population taking over an empty structure). (2) We show that in general the qualitative question is PSPACE-complete and the quantitative approximation question is PSPACE-hard and can be solved in exponential time

    Fungal disease dynamics in insect societies: optimal killing rates and the ambivalent effect of high social interaction rates

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    Entomopathogenic fungi are potent biocontrol agents that are widely used against insect pests, many of which are social insects. Nevertheless, theoretical investigations of their particular life history are scarce. We develop a model that takes into account the main distinguishing features between traditionally studied diseases and obligate killing pathogens, like the (biocontrol-relevant) insect-pathogenic fungi Metarhizium and Beauveria. First, obligate killing entomopathogenic fungi produce new infectious particles (conidiospores) only after host death and not yet on the living host. Second, the killing rates of entomopathogenic fungi depend strongly on the initial exposure dosage, thus we explicitly consider the pathogen load of individual hosts. Further, we make the model applicable not only to solitary host species, but also to group living species by incorporating social interactions between hosts, like the collective disease defences of insect societies. Our results identify the optimal killing rate for the pathogen that minimizes its invasion threshold. Furthermore, we find that the rate of contact between hosts has an ambivalent effect: Dense interaction networks between individuals are considered to facilitate disease outbreaks because of increased pathogen transmission. In social insects, this is compensated by their collective disease defences, i.e., social immunity. For the type of pathogens considered here, we show that even without social immunity, high contact rates between live individuals dilute the pathogen in the host colony and hence can reduce individual pathogen loads below disease-causing levels

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