1,676 research outputs found

    A Turner syndrome neurocognitive phenotype maps to Xp22.3

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    BACKGROUND: Turner syndrome (TS) is associated with a neurocognitive phenotype that includes selective nonverbal deficits, e.g., impaired visual-spatial abilities. We previously reported evidence that this phenotype results from haploinsufficiency of one or more genes on distal Xp. This inference was based on genotype/phenotype comparisons of individual girls and women with partial Xp deletions, with the neurocognitive phenotype considered a dichotomous trait. We sought to confirm our findings in a large cohort (n = 47) of adult women with partial deletions of Xp or Xq, enriched for subjects with distal Xp deletions. METHODS: Subjects were recruited from North American genetics and endocrinology clinics. Phenotype assessment included measures of stature, ovarian function, and detailed neurocognitive testing. The neurocognitive phenotype was measured as a quantitative trait, the Turner Syndrome Cognitive Summary (TSCS) score, derived from discriminant function analysis. Genetic analysis included karyotyping, X inactivation studies, fluorescent in situ hybridization, microsatellite marker genotyping, and array comparative genomic hybridization. RESULTS: We report statistical evidence that deletion of Xp22.3, an interval containing 31 annotated genes, is sufficient to cause the neurocognitive phenotype described by the TSCS score. Two other cardinal TS features, ovarian failure and short stature, as well as X chromosome inactivation pattern and subject\u27s age, were unrelated to the TSCS score. CONCLUSION: Detailed mapping suggests that haploinsufficiency of one or more genes in Xp22.3, the distal 8.3 megabases (Mb) of the X chromosome, is responsible for a TS neurocognitive phenotype. This interval includes the 2.6 Mb Xp-Yp pseudoautosomal region (PAR1). Haploinsufficiency of the short stature gene SHOX in PAR1 probably does not cause this TS neurocognitive phenotype. Two genes proximal to PAR1 within the 8.3 Mb critical region, STS and NLGN4X, are attractive candidates for this neurocognitive phenotype

    Multi-agent Coordination in Directed Moving Neighborhood Random Networks

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    In this paper, we consider the consensus problem of dynamical multiple agents that communicate via a directed moving neighborhood random network. Each agent performs random walk on a weighted directed network. Agents interact with each other through random unidirectional information flow when they coincide in the underlying network at a given instant. For such a framework, we present sufficient conditions for almost sure asymptotic consensus. Some existed consensus schemes are shown to be reduced versions of the current model.Comment: 9 page

    A Quantum Langevin Formulation of Risk-Sensitive Optimal Control

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    In this paper we formulate a risk-sensitive optimal control problem for continuously monitored open quantum systems modelled by quantum Langevin equations. The optimal controller is expressed in terms of a modified conditional state, which we call a risk-sensitive state, that represents measurement knowledge tempered by the control purpose. One of the two components of the optimal controller is dynamic, a filter that computes the risk-sensitive state. The second component is an optimal control feedback function that is found by solving the dynamic programming equation. The optimal controller can be implemented using classical electronics. The ideas are illustrated using an example of feedback control of a two-level atom

    A stochastic approximation algorithm with multiplicative step size modification

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    An algorithm of searching a zero of an unknown function \vphi : \, \R \to \R is considered: xt=xt1γt1yt\, x_{t} = x_{t-1} - \gamma_{t-1} y_t,\, t=1, 2,t=1,\ 2,\ldots, where yt=φ(xt1)+ξty_t = \varphi(x_{t-1}) + \xi_t is the value of \vphi measured at xt1x_{t-1} and ξt\xi_t is the measurement error. The step sizes \gam_t > 0 are modified in the course of the algorithm according to the rule: \, \gamma_t = \min\{u\, \gamma_{t-1},\, \mstep\} if yt1yt>0y_{t-1} y_t > 0, and γt=dγt1\gamma_t = d\, \gamma_{t-1}, otherwise, where 0<d<100 < d < 1 0. That is, at each iteration \gam_t is multiplied either by uu or by dd, provided that the resulting value does not exceed the predetermined value \mstep. The function \vphi may have one or several zeros; the random values ξt\xi_t are independent and identically distributed, with zero mean and finite variance. Under some additional assumptions on \vphi, ξt\xi_t, and \mstep, the conditions on uu and dd guaranteeing a.s. convergence of the sequence {xt}\{ x_t \}, as well as a.s. divergence, are determined. In particular, if (ξ1>0)=(ξ1<0)=1/2\P (\xi_1 > 0) = \P (\xi_1 < 0) = 1/2 and (ξ1=x)=0\P (\xi_1 = x) = 0 for any xRx \in \R, one has convergence for ud1ud 1. Due to the multiplicative updating rule for \gam_t, the sequence {xt}\{ x_t \} converges rapidly: like a geometric progression (if convergence takes place), but the limit value may not coincide with, but instead, approximates one of the zeros of \vphi. By adjusting the parameters uu and dd, one can reach arbitrarily high precision of the approximation; higher precision is obtained at the expense of lower convergence rate

    Surface electrons at plasma walls

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    In this chapter we introduce a microscopic modelling of the surplus electrons on the plasma wall which complements the classical description of the plasma sheath. First we introduce a model for the electron surface layer to study the quasistationary electron distribution and the potential at an unbiased plasma wall. Then we calculate sticking coefficients and desorption times for electron trapping in the image states. Finally we study how surplus electrons affect light scattering and how charge signatures offer the possibility of a novel charge measurement for dust grains.Comment: To appear in Complex Plasmas: Scientific Challenges and Technological Opportunities, Editors: M. Bonitz, K. Becker, J. Lopez and H. Thomse

    Heisenberg Picture Approach to the Stability of Quantum Markov Systems

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    Quantum Markovian systems, modeled as unitary dilations in the quantum stochastic calculus of Hudson and Parthasarathy, have become standard in current quantum technological applications. This paper investigates the stability theory of such systems. Lyapunov-type conditions in the Heisenberg picture are derived in order to stabilize the evolution of system operators as well as the underlying dynamics of the quantum states. In particular, using the quantum Markov semigroup associated with this quantum stochastic differential equation, we derive sufficient conditions for the existence and stability of a unique and faithful invariant quantum state. Furthermore, this paper proves the quantum invariance principle, which extends the LaSalle invariance principle to quantum systems in the Heisenberg picture. These results are formulated in terms of algebraic constraints suitable for engineering quantum systems that are used in coherent feedback networks
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