On commutativity based edge lean search

Exploring a graph through search is one of the most basic building blocks of various applications. In a setting with a huge state space, such as in testing and verification, optimizing the search may be crucial. We consider the problem of visiting all states in a graph where edges are generated by actions and the (reachable) states are not known in advance. Some of the actions may commute, i.e., they result in the same state for every order in which they are taken (this is the case when the actions are performed independently by different processes). We show how to use commutativity to achieve full coverage of the states while traversing considerably fewer edges

Computing the Similarity Between Moving Curves

In this paper we study similarity measures for moving curves which can, for example, model changing coastlines or retreating glacier termini. Points on a moving curve have two parameters, namely the position along the curve as well as time. We therefore focus on similarity measures for surfaces, specifically the Fr\'echet distance between surfaces. While the Fr\'echet distance between surfaces is not even known to be computable, we show for variants arising in the context of moving curves that they are polynomial-time solvable or NP-complete depending on the restrictions imposed on how the moving curves are matched. We achieve the polynomial-time solutions by a novel approach for computing a surface in the so-called free-space diagram based on max-flow min-cut duality

Parvalbumin interneuron dysfunction in a thalamo-prefrontal cortical circuit in Disc1 locus impairment mice

Altered cortical excitation-inhibition (E-I) balance resulting from abnormal parvalbumin interneuron (PV IN) function is a proposed pathophysiological mechanism of schizophrenia (SZ) and other major psychiatric disorders. Preclinical studies have indicated that disrupted-in-schizophrenia-1 (DISC1) is a useful molecular lead to address the biology of prefrontal cortex dependent cognition and PV IN function. To date, prefrontal cortical inhibitory circuit function has not been investigated in depth in Disc1 locus impairment (LI) mouse models. Therefore, we used a Disc1 LI mouse model to investigate E-I balance in medial prefrontal cortical (mPFC) circuits. We found that inhibition onto layer 3 excitatory pyramidal neurons in the mPFC was significantly reduced in Disc1 LI mice. This reduced inhibition was accompanied by decreased GABA release from local PV, but not somatostatin (SOM) interneurons, and by impaired feedforward inhibition in the mediodorsal thalamus (MD) to mPFC circuit. Our mechanistic findings of abnormal PV IN function in a Disc1 LI model provide insight into biology that may be relevant to neuropsychiatric disorders including schizophrenia.SIGNIFICANCE STATEMENT A popular theory suggests that dysregulation of fast-spiking parvalbumin interneurons (PV INs) and elevated excitation-inhibition (E-I) balance contribute to the pathophysiology of various psychiatric disorders. Previous studies suggest that genetic perturbations of the disrupted-in-schizophrenia-1 (Disc1) gene affect prefrontal cortex-dependent cognition and PV IN function, but synaptic and circuit physiology data are lacking. Here, we provide evidence that the presynaptic function of PV INs in the medial prefrontal cortex is altered in Disc1 LI mice and that E-I balance is elevated within a thalamofrontal circuit known to be important for cognition. These findings may contribute to our understanding of the biology that gives rise to cognitive symptoms in a range of neuropsychiatric disorders

Abstract Interpretation with Unfoldings

We present and evaluate a technique for computing path-sensitive interference conditions during abstract interpretation of concurrent programs. In lieu of fixed point computation, we use prime event structures to compactly represent causal dependence and interference between sequences of transformers. Our main contribution is an unfolding algorithm that uses a new notion of independence to avoid redundant transformer application, thread-local fixed points to reduce the size of the unfolding, and a novel cutoff criterion based on subsumption to guarantee termination of the analysis. Our experiments show that the abstract unfolding produces an order of magnitude fewer false alarms than a mature abstract interpreter, while being several orders of magnitude faster than solver-based tools that have the same precision.Comment: Extended version of the paper (with the same title and authors) to appear at CAV 201

Fluctuating Hall resistance defeats the quantized Hall insulator

Using the Chalker-Coddington network model as a drastically simplified, but universal model of integer quantum Hall physics, we investigate the plateau-to-insulator transition at strong magnetic field by means of a real-space renormalization approach. Our results suggest that for a fully quantum coherent situation, the quantized Hall insulator with R_H approx. h/e^2 is observed up to R_L ~25 h/e^2 when studying the most probable value of the distribution function P(R_H). Upon further increasing R_L ->\infty the Hall insulator with diverging Hall resistance R_H \propto R_L^kappa is seen. The crossover between these two regimes depends on the precise nature of the averaging procedure.Comment: major revision, discussion of averaging improved; 8 pages, 7 figures; accepted for publication in EP

Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

The quantized Hall effect in the presence of resistance fluctuations

We present an experimental study of mesoscopic, two-dimensional electronic systems at high magnetic fields. Our samples, prepared from a low-mobility InGaAs/InAlAs wafer, exhibit reproducible, sample specific, resistance fluctuations. Focusing on the lowest Landau level we find that, while the diagonal resistivity displays strong fluctuations, the Hall resistivity is free of fluctuations and remains quantized at its $\nu=1$ value, $h/e^{2}$. This is true also in the insulating phase that terminates the quantum Hall series. These results extend the validity of the semicircle law of conductivity in the quantum Hall effect to the mesoscopic regime.Comment: Includes more data, changed discussio

A well-separated pairs decomposition algorithm for k-d trees implemented on multi-core architectures

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.Variations of k-d trees represent a fundamental data structure used in Computational Geometry with numerous applications in science. For example particle track tting in the software of the LHC experiments, and in simulations of N-body systems in the study of dynamics of interacting galaxies, particle beam physics, and molecular dynamics in biochemistry. The many-body tree methods devised by Barnes and Hutt in the 1980s and the Fast Multipole Method introduced in 1987 by Greengard and Rokhlin use variants of k-d trees to reduce the computation time upper bounds to O(n log n) and even O(n) from O(n2). We present an algorithm that uses the principle of well-separated pairs decomposition to always produce compressed trees in O(n log n) work. We present and evaluate parallel implementations for the algorithm that can take advantage of multi-core architectures.The Science and Technology Facilities Council, UK

Thermal and mechanical properties of hemp fabric-reinforced nanoclay-cement nano-composites

The influence of nanoclay on thermal and mechanical properties of hemp fabric-reinforced cement composite is presented in this paper. Results indicate that these properties are improved as a result of nanoclay addition. An optimum replacement of ordinary Portland cement with 1 wt% nanoclay is observed through improved thermal stability, reduced porosity and water absorption as well as increased density, flexural strength, fracture toughness and impact strength of hemp fabric-reinforced nanocomposite. The microstructural analyses indicate that the nanoclay behaves not only as a filler to improve the microstructure but also as an activator to promote the pozzolanic reaction and thus improve the adhesion between hemp fabric and nanomatrix

Range Quantile Queries: Another Virtue of Wavelet Trees

We show how to use a balanced wavelet tree as a data structure that stores a list of numbers and supports efficient {\em range quantile queries}. A range quantile query takes a rank and the endpoints of a sublist and returns the number with that rank in that sublist. For example, if the rank is half the sublist's length, then the query returns the sublist's median. We also show how these queries can be used to support space-efficient {\em coloured range reporting} and {\em document listing}.Comment: Added note about generalization to any constant number of dimensions