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Notes from Research Data Alliance Plenary Meeting in Dublin, Ireland
Get PDFNotes from the Third Plenary for the Research Data Alliance in Dublin, Ireland on March 26 to 28, 2014 with focus on starting an institutional research data repository
Markov decision processes with multiple long-run average objectives
No full textWe study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with κ limit-average functions, in the expectation objective the goal is to maximize the expected limit-average value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector. We show that under the expectation objective, in contrast to the case of one limit-average function, both randomization and memory are necessary for strategies even for ε-approximation, and that finite-memory randomized strategies are sufficient for achieving Pareto optimal values. Under the satisfaction objective, in contrast to the case of one limit-average function, infinite memory is necessary for strategies achieving a specific value (i.e. randomized finite-memory strategies are not sufficient), whereas memoryless randomized strategies are sufficient for ε-approximation, for all ε > 0. We further prove that the decision problems for both expectation and satisfaction objectives can be solved in polynomial time and the trade-off curve (Pareto curve) can be ε-approximated in time polynomial in the size of the MDP and 1/ε, and exponential in the number of limit-average functions, for all ε > 0. Our analysis also reveals flaws in previous work for MDPs with multiple mean-payoff functions under the expectation objective, corrects the flaws, and allows us to obtain improved results
Active elastic thin shell theory for cellular deformations
No full textWe derive the equations for a thin, axisymmetric elastic shell subjected to an internal active stress giving rise to active tension and moments within the shell. We discuss the stability of a cylindrical elastic shell and its response to a localized change in internal active stress. This description is relevant to describe the cellular actomyosin cortex, a thin shell at the cell surface behaving elastically at a short timescale and subjected to active internal forces arising from myosin molecular motor activity. We show that the recent observations of cell deformation following detachment of adherent cells (Maître J-L et al 2012 Science 338 253-6) are well accounted for by this mechanical description. The actin cortex elastic and bending moduli can be obtained from a quantitative analysis of cell shapes observed in these experiments. Our approach thus provides a non-invasive, imaging-based method for the extraction of cellular physical parameters
Searching for collective behavior in a large network of sensory neurons
No full textMaximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such “K-pairwise” models—being systematic extensions of the previously used pairwise Ising models—provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population's capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction
Blending liquids
Get PDFWe present a method for smoothly blending between existing liquid animations. We introduce a semi-automatic method for matching two existing liquid animations, which we use to create new fluid motion that plausibly interpolates the input. Our contributions include a new space-time non-rigid iterative closest point algorithm that incorporates user guidance, a subsampling technique for efficient registration of meshes with millions of vertices, and a fast surface extraction algorithm that produces 3D triangle meshes from a 4D space-time surface. Our technique can be used to instantly create hundreds of new simulations, or to interactively explore complex parameter spaces. Our method is guaranteed to produce output that does not deviate from the input animations, and it generalizes to multiple dimensions. Because our method runs at interactive rates after the initial precomputation step, it has potential applications in games and training simulations
Exact and approximate determinization of discounted-sum automata
No full textA discounted-sum automaton (NDA) is a nondeterministic finite automaton with edge weights, valuing a run by the discounted sum of visited edge weights. More precisely, the weight in the i-th position of the run is divided by λi, where the discount factor λ is a fixed rational number greater than 1. The value of a word is the minimal value of the automaton runs on it. Discounted summation is a common and useful measuring scheme, especially for infinite sequences, reflecting the assumption that earlier weights are more important than later weights. Unfortunately, determinization of NDAs, which is often essential in formal verification, is, in general, not possible. We provide positive news, showing that every NDA with an integral discount factor is determinizable. We complete the picture by proving that the integers characterize exactly the discount factors that guarantee determinizability: for every nonintegral rational discount factor λ, there is a nondeterminizable λ-NDA. We also prove that the class of NDAs with integral discount factors enjoys closure under the algebraic operations min, max, addition, and subtraction, which is not the case for general NDAs nor for deterministic NDAs. For general NDAs, we look into approximate determinization, which is always possible as the influence of a word's suffix decays. We show that the naive approach, of unfolding the automaton computations up to a sufficient level, is doubly exponential in the discount factor. We provide an alternative construction for approximate determinization, which is singly exponential in the discount factor, in the precision, and in the number of states. We also prove matching lower bounds, showing that the exponential dependency on each of these three parameters cannot be avoided. All our results hold equally for automata over finite words and for automata over infinite words
Improved algorithms for reachability and shortest path on low tree-width graphs
Get PDFWe consider the reachability and shortest path problems on low tree-width graphs, with n nodes, m edges, and tree-width t, on a standard RAM with wordsize . We use \widetilde{O} to hide polynomial factors of the inverse of the Ackermann function.
Our main contributions are three fold:
1. For reachability, we present an algorithm that requires O(n\cdot t^2 \cdot \log(n/t)) preprocessing time, O(n\cdot (t \cdot \log(n/t))/W) space, and O(t/W) time for pair queries and O((n\cdot t)/W) time for single-source queries. Note that for constant t our algorithm uses O(n\cdot \log n) time for preprocessing; and O(n/W) time for single-source queries, which is faster than depth first search/breath first search (after the preprocessing).
2. We present an algorithm for shortest path that requires O(n\cdot t^2) preprocessing time, O(n\cdot t) space, and \widetilde{O}(t^2) time for pair queries and O(n\cdot t) time single-source queries.
3. We give a space versus query time trade-off algorithm for shortest path that, given constant \epsilon>0, requires O(n \cdot t^2) preprocessing time, O(n^{\epsilon} \cdot t^2) space, and \widetilde{O}(n^{1-\epsilon}\cdot t^2) time for pair queries.
Our algorithms improve all existing results, and use very simple data structures
A Framework for Automated Competitive Analysis of On-line Scheduling of Firm-Deadline Tasks
Get PDFWe present a flexible framework for the automated competitive analysis of on-line scheduling algorithms for firm- deadline real-time tasks based on multi-objective graphs: Given a taskset and an on-line scheduling algorithm specified as a labeled transition system, along with some optional safety, liveness, and/or limit-average constraints for the adversary, we automatically compute the competitive ratio of the algorithm w.r.t. a clairvoyant scheduler. We demonstrate the flexibility and power of our approach by comparing the competitive ratio of several on-line algorithms, including D(over), that have been proposed in the past, for various tasksets. Our experimental results reveal that none of these algorithms is universally optimal, in the sense that there are tasksets where other schedulers provide better performance. Our framework is hence a very useful design tool for selecting optimal algorithms for a given application
Blood vessels pattern heparan sulfate gradients between their apical and basolateral aspects
No full textA hallmark of immune cell trafficking is directional guidance via gradients of soluble or surface bound chemokines. Vascular endothelial cells produce, transport and deposit either their own chemokines or chemokines produced by the underlying stroma. Endothelial heparan sulfate (HS) was suggested to be a critical scaffold for these chemokine pools, but it is unclear how steep chemokine gradients are sustained between the lumenal and ablumenal aspects of blood vessels. Addressing this question by semi-quantitative immunostaining of HS moieties around blood vessels with a pan anti-HS IgM mAb, we found a striking HS enrichment in the basal lamina of resting and inflamed post capillary skin venules, as well as in high endothelial venules (HEVs) of lymph nodes. Staining of skin vessels with a glycocalyx probe further suggested that their lumenal glycocalyx contains much lower HS density than their basolateral extracellular matrix (ECM). This polarized HS pattern was observed also in isolated resting and inflamed microvascular dermal cells. Notably, progressive skin inflammation resulted in massive ECM deposition and in further HS enrichment around skin post capillary venules and their associated pericytes. Inflammation-dependent HS enrichment was not compromised in mice deficient in the main HS degrading enzyme, heparanase. Our results suggest that the blood vasculature patterns steep gradients of HS scaffolds between their lumenal and basolateral endothelial aspects, and that inflammatory processes can further enrich the HS content nearby inflamed vessels. We propose that chemokine gradients between the lumenal and ablumenal sides of vessels could be favored by these sharp HS scaffold gradients