A Commander’s Power, A Civilian’s Reason: Justice Jackson’s Korematsu Dissent

Barrett examines the dissent opinion of Supreme Court Justice Robert Houghwout Jackson in Korematsu v. United States, which centered on the internment of Japanese Americans during WWII. Although the dissent has been criticized as incoherent, it contains strong legal implications within its complexity

Anomalous pattern based clustering of mental tasks with subject independent learning – some preliminary results

In this paper we describe a new method for EEG signal classification in which the classification of one subject’s EEG signals is based on features learnt from another subject. This method applies to the power spectrum density data and assigns class-dependent information weights to individual features. The informative features appear to be rather similar among different subjects, thus supporting the view that there are subject independent general brain patterns for the same mental task. Classification is done via clustering using the intelligent k-means algorithm with the most informative features from a different subject. We experimentally compare our method with others.</jats:p

Keeping New Teachers: A First Look at the Influences of Induction in the Chicago Public Schools

Examines whether participation in a formal induction program can improve teachers' experiences and job satisfaction, and demonstrates that strong levels of mentoring and support for new teachers greatly improve their desire to continue teaching

Non-Equilibrium Ionization Model for Stellar Cluster Winds and its Application

We have developed a self-consistent physical model for super stellar cluster winds based on combining a 1-D steady-state adiabatic wind solution and a non-equilibrium ionization calculation. Comparing with the case of collisional ionization equilibrium, we find that the non-equilibrium ionization effect is significant in the regime of a high ratio of energy to mass input rate and manifests in a stronger soft X-ray flux in the inner region of the star cluster. Implementing the model in X-ray data analysis softwares (e.g., XSPEC) directly facilitates comparisons with X-ray observations. Physical quantities such as the mass and energy input rates of stellar winds can be estimated by fitting observed X-ray spectra. The fitted parameters may then be compared with independent measurements from other wavelengths. Applying our model to the star cluster NGC 3603, we find that the wind accounts for no more than 50% of the total "diffuse" emission, and the derived mass input rate and terminal velocity are comparable to other empirical estimates. The remaining emission most likely originate from numerous low-mass pre-main-sequence stellar objects.Comment: 29 pages, 17 figures. accepted by MNRA

Wavelet Lifting over Information-Based EEG Graphs for Motor Imagery Data Classification

The imagination of limb movements offers an intuitive paradigm for the control of electronic devices via brain computer interfacing (BCI). The analysis of electroencephalographic (EEG) data related to motor imagery potentials has proved to be a difficult task. EEG readings are noisy, and the elicited patterns occur in different parts of the scalp, at different instants and at different frequencies. Wavelet transform has been widely used in the BCI field as it offers temporal and spectral capabilities, although it lacks spatial information. In this study we propose a tailored second generation wavelet to extract features from these three domains. This transform is applied over a graph representation of motor imaginary trials, which encodes temporal and spatial information. This graph is enhanced using per-subject knowledge in order to optimise the spatial relationships among the electrodes, and to improve the filter design. This method improves the performance of classifying different imaginary limb movements maintaining the low computational resources required by the lifting transform over graphs. By using an online dataset we were able to positively assess the feasibility of using the novel method in an online BCI context

The correlation space of Gaussian latent tree models and model selection without fitting

We provide a complete description of possible covariance matrices consistent with a Gaussian latent tree model for any tree. We then present techniques for utilising these constraints to assess whether observed data is compatible with that Gaussian latent tree model. Our method does not require us first to fit such a tree. We demonstrate the usefulness of the inverse-Wishart distribution for performing preliminary assessments of tree-compatibility using semialgebraic constraints. Using results from Drton et al. (2008) we then provide the appropriate moments required for test statistics for assessing adherence to these equality constraints. These are shown to be effective even for small sample sizes and can be easily adjusted to test either the entire model or only certain macrostructures hypothesized within the tree. We illustrate our exploratory tetrad analysis using a linguistic application and our confirmatory tetrad analysis using a biological application.Comment: 15 page

Abell 2111: An Optical and Radio Study of the Richest Butcher-Oemler Cluster

We present an in-depth analysis of the Butcher-Oemler cluster A2111, including new optical spectroscopy plus a deep Very Large Array (VLA) radio continuum observation. These are combined with optical imaging from the Sloan Digital Sky Survey (SDSS) to assess the activity and properties of member galaxies. Prior X-ray studies have suggested A2111 is a head-on cluster merger, a dynamical state which might be connected to the high level of activity inferred from its blue fraction. We are able to directly assess this claim, using our spectroscopic data to identify 95 cluster members among 196 total galaxy spectra. These galaxy velocities do not themselves provide significant evidence for the merger interpretation, however they are consistent with it provided the system is viewed near the time of core passage and at a viewing angle >~30 degrees different from the merger axis. The SDSS data allow us to confirm the high blue fraction for A2111, f_b = 0.15 +/- 0.03 based on photometry alone and f_b = 0.23 +/- 0.03 using spectroscopic data to remove background galaxies. We are able to detect 175 optical sources from the SDSS in our VLA radio data, of which 35 have redshift information. We use the SDSS photometry to determine photometric redshifts for the remaining 140 radio-optical sources. In total we identify up to 26 cluster radio galaxies, 14 of which have spectroscopic redshifts. The optical spectroscopy and radio data reveal a substantial population of dusty starbursts within the cluster. The high blue fraction and prevalence of star formation is consistent with the hypothesis that dynamically-active clusters are associated with more active member galaxies than relaxed clusters.Comment: To appear in AJ; 53 pages including 10 figures and several long table

Censoring, Factorizations, and Spectral Analysis for Transition Matrices with Block-Repeating Entries

In this paper, we use the Markov chain censoring technique to study infinite state Markov chains whose transition matrices possess block-repeating entries. We demonstrate that a number of important probabilistic measures are invariant under censoring. Informally speaking, these measures involve first passage times or expected numbers of visits to certain levels where other levels are taboo;they are closely related to the so-called fundamental matrix of the Markov chain which is also studied here. Factorization theorems for the characteristic equation of the blocks of the transition matrix are obtained. Necessary and sufficient conditions are derived for such a Markov chain to be positive recurrent, null recurrent, or transient based either on spectral analysis, or on a property of the fundamental matrix. Explicit expressions are obtained for key probabilistic measures, including the stationary probability vector and the fundamental matrix, which could be potentially used to develop various recursivealgorithms for computing these measures.block-Toeplitz transition matrices, factorization of characteristic functions, spectral analysis, fundamental matrix, conditions of recurrence and transience.