The Potential of Restarts for ProbSAT

This work analyses the potential of restarts for probSAT, a quite successful algorithm for k-SAT, by estimating its runtime distributions on random 3-SAT instances that are close to the phase transition. We estimate an optimal restart time from empirical data, reaching a potential speedup factor of 1.39. Calculating restart times from fitted probability distributions reduces this factor to a maximum of 1.30. A spin-off result is that the Weibull distribution approximates the runtime distribution for over 93% of the used instances well. A machine learning pipeline is presented to compute a restart time for a fixed-cutoff strategy to exploit this potential. The main components of the pipeline are a random forest for determining the distribution type and a neural network for the distribution's parameters. ProbSAT performs statistically significantly better than Luby's restart strategy and the policy without restarts when using the presented approach. The structure is particularly advantageous on hard problems.Comment: Eurocast 201

Beeping a Maximal Independent Set

We consider the problem of computing a maximal independent set (MIS) in an extremely harsh broadcast model that relies only on carrier sensing. The model consists of an anonymous broadcast network in which nodes have no knowledge about the topology of the network or even an upper bound on its size. Furthermore, it is assumed that an adversary chooses at which time slot each node wakes up. At each time slot a node can either beep, that is, emit a signal, or be silent. At a particular time slot, beeping nodes receive no feedback, while silent nodes can only differentiate between none of its neighbors beeping, or at least one of its neighbors beeping. We start by proving a lower bound that shows that in this model, it is not possible to locally converge to an MIS in sub-polynomial time. We then study four different relaxations of the model which allow us to circumvent the lower bound and find an MIS in polylogarithmic time. First, we show that if a polynomial upper bound on the network size is known, it is possible to find an MIS in O(log^3 n) time. Second, if we assume sleeping nodes are awoken by neighboring beeps, then we can also find an MIS in O(log^3 n) time. Third, if in addition to this wakeup assumption we allow sender-side collision detection, that is, beeping nodes can distinguish whether at least one neighboring node is beeping concurrently or not, we can find an MIS in O(log^2 n) time. Finally, if instead we endow nodes with synchronous clocks, it is also possible to find an MIS in O(log^2 n) time.Comment: arXiv admin note: substantial text overlap with arXiv:1108.192

Computing in Additive Networks with Bounded-Information Codes

This paper studies the theory of the additive wireless network model, in which the received signal is abstracted as an addition of the transmitted signals. Our central observation is that the crucial challenge for computing in this model is not high contention, as assumed previously, but rather guaranteeing a bounded amount of \emph{information} in each neighborhood per round, a property that we show is achievable using a new random coding technique. Technically, we provide efficient algorithms for fundamental distributed tasks in additive networks, such as solving various symmetry breaking problems, approximating network parameters, and solving an \emph{asymmetry revealing} problem such as computing a maximal input. The key method used is a novel random coding technique that allows a node to successfully decode the received information, as long as it does not contain too many distinct values. We then design our algorithms to produce a limited amount of information in each neighborhood in order to leverage our enriched toolbox for computing in additive networks

Walks of molecular motors in two and three dimensions

Molecular motors interacting with cytoskeletal filaments undergo peculiar random walks consisting of alternating sequences of directed movements along the filaments and diffusive motion in the surrounding solution. An ensemble of motors is studied which interacts with a single filament in two and three dimensions. The time evolution of the probability distribution for the bound and unbound motors is determined analytically. The diffusion of the motors is strongly enhanced parallel to the filament. The analytical expressions are in excellent agreement with the results of Monte Carlo simulations.Comment: 7 pages, 2 figures, to be published in Europhys. Let

Preschool sleep and depression interact to predict gray matter volume trajectories across late childhood to adolescence

There is a close relationship between sleep and depression, and certain maladaptive outcomes of sleep problems may only be apparent in individuals with heightened levels of depression. In a sample enriched for preschool depression, we examined how sleep and depression in early childhood interact to predict later trajectories of gray matter volume. Participants (N = 161) were recruited and assessed during preschool (ages 3-6 years) and were later assessed with five waves of structural brain imaging, spanning from late childhood to adolescence. Sleep and depression were assessed using a semi-structured parent interview when the children were preschool-aged, and total gray matter volume was calculated at each scan wave. Although sleep disturbances alone did not predict gray matter volume/trajectories, preschool sleep and depression symptoms interacted to predict later total gray matter volume and the trajectory of decline in total gray matter volume. Sleep disturbances in the form of longer sleep onset latencies, increased irregularity in the child\u27s sleep schedule, and higher levels of daytime sleepiness in early childhood were all found to interact with early childhood depression severity to predict later trajectories of cortical gray matter volume. Findings provide evidence of the interactive effects of preschool sleep and depression symptoms on later neurodevelopment

Self-adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Abstract. Based on the premise that preconditioners needed for scien-tific computing are not only required to be robust in the numerical sense, but also scalable for up to thousands of light-weight cores, we argue that this two-fold goal is achieved for the recently developed self-adaptive multi-elimination preconditioner. For this purpose, we revise the under-lying idea and analyze the performance of implementations realized in the PARALUTION and MAGMA open-source software libraries on GPU architectures (using either CUDA or OpenCL), Intel’s Many Integrated Core Architecture, and Intel’s Sandy Bridge processor. The comparison with other well-established preconditioners like multi-coloured Gauss-Seidel, ILU(0) and multi-colored ILU(0), shows that the twofold goal of a numerically stable cross-platform performant algorithm is achieved.

Excitability and irritability in preschoolers predicts later psychopathology: The importance of positive and negative emotion dysregulation

Emotion dysregulation is a risk factor for the development of a variety of psychopathologic outcomes. In children, irritability, or dysregulated negative affect, has been the primary focus, as it predicts later negative outcomes even in very young children. However, dysregulation of positive emotion is increasingly recognized as a contributor to psychopathology. Here we used an exploratory factor analysis and defined four factors of emotion dysregulation: irritability, excitability, sadness, and anhedonia, in the preschool-age psychiatric assessment collected in a sample of 302 children ages 3-5 years enriched for early onset depression. The irritability and excitability factor scores defined in preschoolers predicted later diagnosis of mood and externalizing disorders when controlling for other factor scores, social adversity, maternal history of mood disorders, and externalizing diagnoses at baseline. The preschool excitability factor score predicted emotion lability in late childhood and early adolescence when controlling for other factor scores, social adversity, and maternal history. Both excitability and irritability factor scores in preschoolers predicted global functioning into the teen years and early adolescence, respectively. These findings underscore the importance of positive, as well as negative, affect dysregulation as early as the preschool years in predicting later psychopathology, which deserves both further study and clinical consideration

The cytoplasm of living cells: A functional mixture of thousands of components

Inside every living cell is the cytoplasm: a fluid mixture of thousands of different macromolecules, predominantly proteins. This mixture is where most of the biochemistry occurs that enables living cells to function, and it is perhaps the most complex liquid on earth. Here we take an inventory of what is actually in this mixture. Recent genome-sequencing work has given us for the first time at least some information on all of these thousands of components. Having done so we consider two physical phenomena in the cytoplasm: diffusion and possible phase separation. Diffusion is slower in the highly crowded cytoplasm than in dilute solution. Reasonable estimates of this slowdown can be obtained and their consequences explored, for example, monomer-dimer equilibria are established approximately twenty times slower than in a dilute solution. Phase separation in all except exceptional cells appears not to be a problem, despite the high density and so strong protein-protein interactions present. We suggest that this may be partially a byproduct of the evolution of other properties, and partially a result of the huge number of components present.Comment: 11 pages, 1 figure, 1 tabl

Finite size effects and error-free communication in Gaussian channels

The efficacy of a specially constructed Gallager-type error-correcting code to communication in a Gaussian channel is being examined. The construction is based on the introduction of complex matrices, used in both encoding and decoding, which comprise sub-matrices of cascading connection values. The finite size effects are estimated for comparing the results to the bounds set by Shannon. The critical noise level achieved for certain code-rates and infinitely large systems nearly saturates the bounds set by Shannon even when the connectivity used is low