63 research outputs found
An Improved Bound for First-Fit on Posets Without Two Long Incomparable Chains
It is known that the First-Fit algorithm for partitioning a poset P into
chains uses relatively few chains when P does not have two incomparable chains
each of size k. In particular, if P has width w then Bosek, Krawczyk, and
Szczypka (SIAM J. Discrete Math., 23(4):1992--1999, 2010) proved an upper bound
of ckw^{2} on the number of chains used by First-Fit for some constant c, while
Joret and Milans (Order, 28(3):455--464, 2011) gave one of ck^{2}w. In this
paper we prove an upper bound of the form ckw. This is best possible up to the
value of c.Comment: v3: referees' comments incorporate
Manhattan orbifolds
We investigate a class of metrics for 2-manifolds in which, except for a
discrete set of singular points, the metric is locally isometric to an L_1 (or
equivalently L_infinity) metric, and show that with certain additional
conditions such metrics are injective. We use this construction to find the
tight span of squaregraphs and related graphs, and we find an injective metric
that approximates the distances in the hyperbolic plane analogously to the way
the rectilinear metrics approximate the Euclidean distance.Comment: 17 pages, 15 figures. Some definitions and proofs have been revised
since the previous version, and a new example has been adde
Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation
We consider two neuronal networks coupled by long-range excitatory
interactions. Oscillations in the gamma frequency band are generated within
each network by local inhibition. When long-range excitation is weak, these
oscillations phase-lock with a phase-shift dependent on the strength of local
inhibition. Increasing the strength of long-range excitation induces a
transition to chaos via period-doubling or quasi-periodic scenarios. In the
chaotic regime oscillatory activity undergoes fast temporal decorrelation. The
generality of these dynamical properties is assessed in firing-rate models as
well as in large networks of conductance-based neurons.Comment: 4 pages, 5 figures. accepted for publication in Physical Review
Letter
Bounds on the Complexity of Halfspace Intersections when the Bounded Faces have Small Dimension
We study the combinatorial complexity of D-dimensional polyhedra defined as
the intersection of n halfspaces, with the property that the highest dimension
of any bounded face is much smaller than D. We show that, if d is the maximum
dimension of a bounded face, then the number of vertices of the polyhedron is
O(n^d) and the total number of bounded faces of the polyhedron is O(n^d^2). For
inputs in general position the number of bounded faces is O(n^d). For any fixed
d, we show how to compute the set of all vertices, how to determine the maximum
dimension of a bounded face of the polyhedron, and how to compute the set of
bounded faces in polynomial time, by solving a polynomial number of linear
programs
Measuring Instantaneous Frequency of Local Field Potential Oscillations using the Kalman Smoother
Rhythmic local field potentials (LFPs) arise from coordinated neural activity. Inference of neural function based on the properties of brain rhythms remains a challenging data analysis problem. Algorithms that characterize non-stationary rhythms with high temporal and spectral resolution may be useful for interpreting LFP activity on the timescales in which they are generated. We propose a Kalman smoother based dynamic autoregressive model for tracking the instantaneous frequency (iFreq) and frequency modulation (FM) of noisy and non-stationary sinusoids such as those found in LFP data. We verify the performance of our algorithm using simulated data with broad spectral content, and demonstrate its application using real data recorded from behavioral learning experiments. In analyses of ripple oscillations (100–250 Hz) recorded from the rodent hippocampus, our algorithm identified novel repetitive, short timescale frequency dynamics. Our results suggest that iFreq and FM may be useful measures for the quantification of small timescale LFP dynamics.National Institutes of Health (U.S.) (NIH/NIMH R01 MH59733)National Institutes of Health (U.S.) (NIH/NIHLB R01 HL084502)Massachusetts Institute of Technology (Henry E. Singleton Presidential Graduate Fellowship Award
Consensus guidelines for the use and interpretation of angiogenesis assays
The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference
Planar Orientations with Low Out-Degree and Compaction of Adjacency Matrices
We consider the problem of orienting the edges of a planar graph in such a way that the out-degree of each vertex is minimized. If, for each vertex v, the out-degree is at most d, then we say that such an orientation is d-bounded. We prove the following results: ffl Each planar graph has a 5-bounded acyclic orientation, which can be constructed in linear time. ffl Each planar graph has a 3-bounded orientation, which can be constructed in linear time. ffl A 6-bounded acyclic orientation, and a 3-bounded orientation, of each planar graph can each be constructed in parallel time O(log n log n) on an EREW PRAM, using O(n= log n log n) processors. As an application of these results, we present a data structure such that each entry in the adjacency matrix of a planar graph can be looked up in constant time. The data structure uses linear storage, and can be constructed in linear time. Department of Mathematics and Computer Science, University of California, Riverside, CA 92521. On..
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