The varying w spread spectrum effect for radio interferometric imaging

We study the impact of the spread spectrum effect in radio interferometry on the quality of image reconstruction. This spread spectrum effect will be induced by the wide field-of-view of forthcoming radio interferometric telescopes. The resulting chirp modulation improves the quality of reconstructed interferometric images by increasing the incoherence of the measurement and sparsity dictionaries. We extend previous studies of this effect to consider the more realistic setting where the chirp modulation varies for each visibility measurement made by the telescope. In these first preliminary results, we show that for this setting the quality of reconstruction improves significantly over the case without chirp modulation and achieves almost the reconstruction quality of the case of maximal, constant chirp modulation.Comment: 1 page, 1 figure, Proceedings of the Biomedical and Astronomical Signal Processing Frontiers (BASP) workshop 201

Carbohydrate and protein contents of grain dusts in relation to dust morphology.

Grain dusts contain a variety of materials which are potentially hazardous to the health of workers in the grain industry. Because the characterization of grain dusts is incomplete, we are defining the botanical, chemical, and microbial contents of several grain dusts collected from grain elevators in the Duluth-Superior regions of the U.S. Here, we report certain of the carbohydrate and protein contents of dusts in relation to dust morphology. Examination of the gross morphologies of the dusts revealed that, except for corn, each dust contained either husk or pericarp (seed coat in the case of flax) fragments in addition to respirable particles. When viewed with the light microscope, the fragments appeared as elongated, pointed structures. The possibility that certain of the fragments within corn, settled, and spring wheat were derived from cell walls was suggested by the detection of pentoses following colorimetric assay of neutralized 2 N trifluoroacetic acid hydrolyzates of these dusts. The presence of pentoses together with the occurrence of proteins within water washings of grain dusts suggests that glycoproteins may be present within the dusts. With scanning electron microscopy, each dust was found to consist of a distinct assortment of particles in addition to respirable particles. Small husk fragments and "trichome-like" objects were common to all but corn dust

Shift-Symmetric Configurations in Two-Dimensional Cellular Automata: Irreversibility, Insolvability, and Enumeration

The search for symmetry as an unusual yet profoundly appealing phenomenon, and the origin of regular, repeating configuration patterns have long been a central focus of complexity science and physics. To better grasp and understand symmetry of configurations in decentralized toroidal architectures, we employ group-theoretic methods, which allow us to identify and enumerate these inputs, and argue about irreversible system behaviors with undesired effects on many computational problems. The concept of so-called configuration shift-symmetry is applied to two-dimensional cellular automata as an ideal model of computation. Regardless of the transition function, the results show the universal insolvability of crucial distributed tasks, such as leader election, pattern recognition, hashing, and encryption. By using compact enumeration formulas and bounding the number of shift-symmetric configurations for a given lattice size, we efficiently calculate the probability of a configuration being shift-symmetric for a uniform or density-uniform distribution. Further, we devise an algorithm detecting the presence of shift-symmetry in a configuration. Given the resource constraints, the enumeration and probability formulas can directly help to lower the minimal expected error and provide recommendations for system's size and initialization. Besides cellular automata, the shift-symmetry analysis can be used to study the non-linear behavior in various synchronous rule-based systems that include inference engines, Boolean networks, neural networks, and systolic arrays.Comment: 22 pages, 9 figures, 2 appendice

Lack of clustering in low-redshift 21-cm intensity maps cross-correlated with 2dF galaxy densities

We report results from 21-cm intensity maps acquired from the Parkes radio telescope and cross-correlated with galaxy maps from the 2dF galaxy survey. The data span the redshift range $0.057<z<0.098$ and cover approximately 1,300 square degrees over two long fields. Cross correlation is detected at a significance of $5.18\sigma$. The amplitude of the cross-power spectrum is low relative to the expected dark matter power spectrum, assuming a neutral hydrogen (HI) bias and mass density equal to measurements from the ALFALFA survey. The decrement is pronounced and statistically significant at small scales. At $k\sim1.5$ $h \mathrm{Mpc^{-1}}$, the cross power spectrum is more than a factor of 6 lower than expected, with a significance of $14.8\,\sigma$. This decrement indicates either a lack of clustering of neutral hydrogen (HI), a small correlation coefficient between optical galaxies and HI, or some combination of the two. Separating 2dF into red and blue galaxies, we find that red galaxies are much more weakly correlated with HI on $k\sim1.5$ $h \mathrm{Mpc^{-1}}$ scales, suggesting that HI is more associated with blue star-forming galaxies and tends to avoid red galaxies.Comment: 12 pages, 3 figures; fixed typo in meta-data title and paper author

Cellular automaton supercolliders

Gliders in one-dimensional cellular automata are compact groups of non-quiescent and non-ether patterns (ether represents a periodic background) translating along automaton lattice. They are cellular-automaton analogous of localizations or quasi-local collective excitations travelling in a spatially extended non-linear medium. They can be considered as binary strings or symbols travelling along a one-dimensional ring, interacting with each other and changing their states, or symbolic values, as a result of interactions. We analyse what types of interaction occur between gliders travelling on a cellular automaton `cyclotron' and build a catalog of the most common reactions. We demonstrate that collisions between gliders emulate the basic types of interaction that occur between localizations in non-linear media: fusion, elastic collision, and soliton-like collision. Computational outcomes of a swarm of gliders circling on a one-dimensional torus are analysed via implementation of cyclic tag systems

The EREBOS project -- Investigating the effect of substellar and low-mass stellar companions on late stellar evolution

Eclipsing post-common envelope binaries are highly important for resolving the poorly understood, very short-lived common envelope phase. Most hot subdwarfs (sdO/Bs) are the bare He-burning cores of red giants which have lost almost all of their hydrogen envelopes. This mass loss is often triggered by common envelope interactions with close stellar or even sub-stellar companions. In the recently published catalog of eclipsing binaries in the Galactic Bulge and in the ATLAS survey, we discovered 161 new eclipsing systems showing a reflection effect by visual inspection of the light curves and using a machine-learning algorithm. The EREBOS (Eclipsing Reflection Effect Binaries from Optical Surveys) project aims at analyzing all newly discovered eclipsing binaries with reflection effect based on a spectroscopic and photometric follow up. To constrain the nature of the primary we derived the absolute magnitude and the reduced proper motion of all our targets with the help of the parallaxes and proper motions measured by the Gaia mission and compared those to the Gaia white dwarf catalogue. For a sub-set of our targets with observed spectra the nature could be derived by measuring the atmospheric parameter of the primary confirming that less than 10\% of our systems are not sdO/Bs with cool companions but white dwarfs or central stars of planetary nebula. This large sample of eclipsing hot subdwarfs with cool companions allowed us to derive a significant period distribution for hot subdwarfs with cool companions for the first time showing that the period distribution is much broader than previously thought and ideally suited to find the lowest mass companions to hot subdwarf stars. In the future several new photometric surveys will be carried out, which will increase the sample of this project even more giving the potential to test many aspects of common envelope theory and binary evolution.Comment: accepted in A&A, 29 pages, 18 figure

Star/galaxy separation at faint magnitudes: application to a simulated Dark Energy Survey

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper. We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information. We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SExtractor), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 2

Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer's Disease

The role of structural brain magnetic resonance imaging (MRI) is becoming more and more emphasized in the early diagnostics of Alzheimer's disease (AD). This study aimed to assess the improvement in classification accuracy that can be achieved by combining features from different structural MRI analysis techniques. Automatically estimated MR features used are hippocampal volume, tensor-based morphometry, cortical thickness and a novel technique based on manifold learning. Baseline MRIs acquired from all 834 subjects (231 healthy controls (HC), 238 stable mild cognitive impairment (S-MCI), 167 MCI to AD progressors (P-MCI), 198 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were used for evaluation. We compared the classification accuracy achieved with linear discriminant analysis (LDA) and support vector machines (SVM). The best results achieved with individual features are 90% sensitivity and 84% specificity (HC/AD classification), 64%/66% (S-MCI/P-MCI) and 82%/76% (HC/P-MCI) with the LDA classifier. The combination of all features improved these results to 93% sensitivity and 85% specificity (HC/AD), 67%/69% (S-MCI/P-MCI) and 86%/82% (HC/P-MCI). Compared with previously published results in the ADNI database using individual MR-based features, the presented results show that a comprehensive analysis of MRI images combining multiple features improves classification accuracy and predictive power in detecting early AD. The most stable and reliable classification was achieved when combining all available features