On dynamical bit sequences

Let X^{(k)}(t) = (X_1(t), ..., X_k(t)) denote a k-vector of i.i.d. random variables, each taking the values 1 or 0 with respective probabilities p and 1-p. As a process indexed by non-negative t, $X^{(k)}(t)$ is constructed--following Benjamini, Haggstrom, Peres, and Steif (2003)--so that it is strong Markov with invariant measure ((1-p)\delta_0+p\delta_1)^k. We derive sharp estimates for the probability that ``X_1(t)+...+X_k(t)=k-\ell for some t in F,'' where F \subset [0,1] is nonrandom and compact. We do this in two very different settings: (i) Where \ell is a constant; and (ii) Where \ell=k/2, k is even, and p=q=1/2. We prove that the probability is described by the Kolmogorov capacitance of F for case (i) and Howroyd's 1/2-dimensional box-dimension profiles for case (ii). We also present sample-path consequences, and a connection to capacities that answers a question of Benjamini et. al. (2003)Comment: 25 pages. This a substantial revision of an earlier paper. The material has been reorganized, and Theorem 1.3 is ne

Blind Normalization of Speech From Different Channels

We show how to construct a channel-independent representation of speech that has propagated through a noisy reverberant channel. This is done by blindly rescaling the cepstral time series by a non-linear function, with the form of this scale function being determined by previously encountered cepstra from that channel. The rescaled form of the time series is an invariant property of it in the following sense: it is unaffected if the time series is transformed by any time-independent invertible distortion. Because a linear channel with stationary noise and impulse response transforms cepstra in this way, the new technique can be used to remove the channel dependence of a cepstral time series. In experiments, the method achieved greater channel-independence than cepstral mean normalization, and it was comparable to the combination of cepstral mean normalization and spectral subtraction, despite the fact that no measurements of channel noise or reverberations were required (unlike spectral subtraction).Comment: 25 pages, 7 figure

Macroeconometric equivalence, microeconomic dissonance, and the design of monetary policy

Many recent studies in macroeconomics have focused on the estimation of DSGE models using a system of loglinear approximations to the models' nonlinear equilibrium conditions. The term macroeconometric equivalence encapsulates the idea that estimates using aggregate data based on first-order approximations to the equilibrium conditions of a DSGE model will not be able to distinguish between alternative underlying preferences and technologies. The concept of microeconomic dissonance refers to the fact that the underlying microeconomic differences become important when optimal monetary policy is analyzed in a nonlinear setting. The relevance of these concepts is established by analysis of optimal steady-state inflation and optimal policy in the stochastic economy using a small-scale New Keynesian model. Microeconomic and financial datasets are promising tools with which to overcome the equivalence problem.Monetary policy ; Macroeconomics ; Microeconomics

Morphological stability of a heterophase interface under electromigration conditions

The evolution of the interface between two mutually insoluble metallic phases, under the influence of a strong electric field is examined. A slight perturbation of the interface away from a plane y=h(x) leads to a component of the electric field along the interface. This creates a diffusion flux of the individual atoms along the interface which, in turn, leads to an increase in the amplitude of the initial perturbation and thus to an interfacial profile instability. The processes is expected to be controlled by interface diffusion in response to three distinct driving forces: the electric field, internal stresses (which arise due to the accumulation or depletion of matter at the interface), and the interfacial curvature. The stress distribution along the interface was found from a self‐consistent solution of the elastic problem. For the instability to occur, differences in effective atomic charges, elastic moduli and/or atomic mobilities of the two constituent metals are required. Small sinusoidal corrugations are shown to grow with time for a range of wavelengths. The corrugations can grow monotonically or vary in oscillatory manner, depending on their wavelength. © 1996 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69819/2/JAPIAU-79-9-6834-1.pd

Dissecting interferon-induced transcriptional programs in human peripheral blood cells

Interferons are key modulators of the immune system, and are central to the control of many diseases. The response of immune cells to stimuli in complex populations is the product of direct and indirect effects, and of homotypic and heterotypic cell interactions. Dissecting the global transcriptional profiles of immune cell populations may provide insights into this regulatory interplay. The host transcriptional response may also be useful in discriminating between disease states, and in understanding pathophysiology. The transcriptional programs of cell populations in health therefore provide a paradigm for deconvoluting disease-associated gene expression profiles.We used human cDNA microarrays to (1) compare the gene expression programs in human peripheral blood mononuclear cells (PBMCs) elicited by 6 major mediators of the immune response: interferons alpha, beta, omega and gamma, IL12 and TNFalpha; and (2) characterize the transcriptional responses of purified immune cell populations (CD4+ and CD8+ T cells, B cells, NK cells and monocytes) to IFNgamma stimulation. We defined a highly stereotyped response to type I interferons, while responses to IFNgamma and IL12 were largely restricted to a subset of type I interferon-inducible genes. TNFalpha stimulation resulted in a distinct pattern of gene expression. Cell type-specific transcriptional programs were identified, highlighting the pronounced response of monocytes to IFNgamma, and emergent properties associated with IFN-mediated activation of mixed cell populations. This information provides a detailed view of cellular activation by immune mediators, and contributes an interpretive framework for the definition of host immune responses in a variety of disease settings

Returning to Learning: Adults' Success in College Is Key to America's Future

Provides an overview of research on adult learners' characteristics, risk factors, and needs at four-year institutions and in for-credit and non-credit courses, and what changes institutions and governments can implement to help adult students succeed

Using state space differential geometry for nonlinear blind source separation

Given a time series of multicomponent measurements of an evolving stimulus, nonlinear blind source separation (BSS) seeks to find a "source" time series, comprised of statistically independent combinations of the measured components. In this paper, we seek a source time series with local velocity cross correlations that vanish everywhere in stimulus state space. However, in an earlier paper the local velocity correlation matrix was shown to constitute a metric on state space. Therefore, nonlinear BSS maps onto a problem of differential geometry: given the metric observed in the measurement coordinate system, find another coordinate system in which the metric is diagonal everywhere. We show how to determine if the observed data are separable in this way, and, if they are, we show how to construct the required transformation to the source coordinate system, which is essentially unique except for an unknown rotation that can be found by applying the methods of linear BSS. Thus, the proposed technique solves nonlinear BSS in many situations or, at least, reduces it to linear BSS, without the use of probabilistic, parametric, or iterative procedures. This paper also describes a generalization of this methodology that performs nonlinear independent subspace separation. In every case, the resulting decomposition of the observed data is an intrinsic property of the stimulus' evolution in the sense that it does not depend on the way the observer chooses to view it (e.g., the choice of the observing machine's sensors). In other words, the decomposition is a property of the evolution of the "real" stimulus that is "out there" broadcasting energy to the observer. The technique is illustrated with analytic and numerical examples.Comment: Contains 14 pages and 3 figures. For related papers, see http://www.geocities.com/dlevin2001/ . New version is identical to original version except for URL in the bylin