Analysis of binary spatial data by quasi-likelihood estimating equations

The goal of this paper is to describe the application of quasi-likelihood estimating equations for spatially correlated binary data. In this paper, a logistic function is used to model the marginal probability of binary responses in terms of parameters of interest. With mild assumptions on the correlations, the Leonov-Shiryaev formula combined with a comparison of characteristic functions can be used to establish asymptotic normality for linear combinations of the binary responses. The consistency and asymptotic normality for quasi-likelihood estimates can then be derived. By modeling spatial correlation with a variogram, we apply these asymptotic results to test independence of two spatially correlated binary outcomes and illustrate the concepts with a well-known example based on data from Lansing Woods. The comparison of generalized estimating equations and the proposed approach is also discussed.Comment: Published at http://dx.doi.org/10.1214/009053605000000057 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Arousal regulates frequency tuning in primary auditory cortex.

Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca2+ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412-423, (2017)]. This arousal-dependent "network suppression" gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity

UV-finite scalar field theory with unitarity

In this paper we show how to define the UV completion of a scalar field theory such that it is both UV-finite and perturbatively unitary. In the UV completed theory, the propagator is an infinite sum of ordinary propagators. To eliminate the UV divergences, we choose the coefficients and masses in the propagator to satisfy certain algebraic relations, and define the infinite sums involved in Feynman diagram calculation by analytic continuation. Unitarity can be proved relatively easily by Cutkosky's rules. The theory is equivalent to infinitely many particles with specific masses and interactions. We take the $\phi^4$ theory as an example and demonstrate our idea through explicit Feynman diagram computation.Comment: 14 pages, references adde

Kaluza-Klein dimensional reduction and Gauss-Codazzi-Ricci equations

In this paper we imitate the traditional method which is used customarily in the General Relativity and some mathematical literatures to derive the Gauss-Codazzi-Ricci equations for dimensional reduction. It would be more distinct concerning geometric meaning than the vielbein method. Especially, if the lower dimensional metric is independent of reduced dimensions the counterpart of the symmetric extrinsic curvature is proportional to the antisymmetric Kaluza-Klein gauge field strength. For isometry group of internal space, the SO(n) symmetry and SU(n) symmetry are discussed. And the Kaluza-Klein instanton is also enquired.Comment: 15 page

Outflow and dense gas emission from massive Infrared Dark Clouds

Infrared Dark Clouds are expected to harbor sources in different, very young evolutionary stages. To better characterize these differences, we observed a sample of 43 massive Infrared Dark Clouds, originally selected as candidate high-mass starless cores, with the IRAM 30m telescope covering spectral line tracers of low-density gas, high-density gas, molecular outflows/jets and temperature effects. The SiO(2-1) observations reveal detections toward 18 sources. Assuming that SiO is exclusively produced by sputtering from dust grains, this implies that at least in 40% of this sample star formation is on-going. A broad range of SiO line-widths is observed (between 2.2 and 65km/s), and we discuss potential origins for this velocity spread. While the low-density tracers 12CO(2-1) and 13CO(1-0) are detected in several velocity components, the high-density tracer H13CO+(1--0) generally shows only a single velocity component and is hence well suited for kinematic distance estimates of IRDCs. Furthermore, the H13CO+ line-width is on average 1.5 times larger than that of previously observed NH3(1,1). This is indicative of more motion at the denser core centers, either due to turbulence or beginning star formation activity. In addition, we detect CH3CN toward only six sources whereas CH3OH is observed toward approximately 40% of the sample. Estimates of the CH3CN and CH3OH abundances are low with average values of 1.2x10^{-10} and 4.3x10^{-10}, respectively. These results are consistent with chemical models at the earliest evolutionary stages of high-mass star formation. Furthermore, the CH3OH abundances compare well to recently reported values for low-mass starless cores.Comment: 22 pages (ApJ referee style), 7 figures, accepted for Ap

Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise

This study presents the results of a series of simulation experiments that evaluate and compare four different manifold alignment methods under the influence of noise. The data was created by simulating the dynamics of two slightly different double pendulums in three-dimensional space. The method of semi-supervised feature-level manifold alignment using global distance resulted in the most convincing visualisations. However, the semi-supervised feature-level local alignment methods resulted in smaller alignment errors. These local alignment methods were also more robust to noise and faster than the other methods.Comment: The final version will appear in ICONIP 2018. A DOI identifier to the final version will be added to the preprint, as soon as it is availabl