Semiquantitative Infrared Analysis of Diketones and Anhydrides in a Reaction Mixture

The ozonolysis of a hydroxymethylene ketone yields a mixture of diketone and anhydride. Treatment of hydroxymethylene camphor with ozone affords, in addition to the expected camphor quinone, a surprisingly large amount of camphoric anhydride (56%) via Baeyer-Villager reaction. Use of infrared absorption to analyze the relative amounts of camphor quinone and camphoric anhydride in a reaction mixture was studied by comparing peak heights of their carbonyl stretching bands

Gamma-ray burst host galaxies and the link to star-formation

We briefly review the current status of the study of long-duration gamma-ray burst (GRB) host galaxies. GRB host galaxies are mainly interesting to study for two reasons: 1) they may help us understand where and when massive stars were formed throughout cosmic history, and 2) the properties of host galaxies and the localisation within the hosts where GRBs are formed may give essential clues to the precise nature of the progenitors. The main current problem is to understand to what degree GRBs are biased tracers of star formation. If GRBs are only formed by low-metallicity stars, then their host galaxies will not give a representative view of where stars are formed in the Universe (at least not a low redshifts). On the other hand, if there is no dependency on metallicity then the nature of the host galaxies leads to the perhaps surprising conclusion that most stars are formed in dwarf galaxies. In order to resolve this issue and to fully exploit the potential of GRBs as probes of star-forming galaxies throughout the observable universe it is mandatory that a complete sample of bursts with redshifts and host galaxy detections is built.Comment: 9 pages, 3 figures. To appear in the proceedings of the Eleventh Marcel Grossmann Meeting on General Relativity, eds. H. Kleinert, R. T. Jantzen & R. Ruffini, World Scientific, Singapore, 200

Image patch analysis and clustering of sunspots: a dimensionality reduction approach

Sunspots, as seen in white light or continuum images, are associated with regions of high magnetic activity on the Sun, visible on magnetogram images. Their complexity is correlated with explosive solar activity and so classifying these active regions is useful for predicting future solar activity. Current classification of sunspot groups is visually based and suffers from bias. Supervised learning methods can reduce human bias but fail to optimally capitalize on the information present in sunspot images. This paper uses two image modalities (continuum and magnetogram) to characterize the spatial and modal interactions of sunspot and magnetic active region images and presents a new approach to cluster the images. Specifically, in the framework of image patch analysis, we estimate the number of intrinsic parameters required to describe the spatial and modal dependencies, the correlation between the two modalities and the corresponding spatial patterns, and examine the phenomena at different scales within the images. To do this, we use linear and nonlinear intrinsic dimension estimators, canonical correlation analysis, and multiresolution analysis of intrinsic dimension.Comment: 5 pages, 7 figures, accepted to ICIP 201

Arrival direction distribution of cosmic rays of energy 10 (18) eV

The Haverah Park air-shower experiment recorded over 8500 events with primary energy 10 to the 18th power eV between 1963 and 1983. An analysis of these events for anisotropies in celestial and galactic coordinates is reported. No very striking anisotropies are observed

Image patch analysis of sunspots and active regions. II. Clustering via matrix factorization

Separating active regions that are quiet from potentially eruptive ones is a key issue in Space Weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature prevents systematic studies of an active region's evolution for example. We introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. We use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches. Two factorizations can be compared via the definition of appropriate metrics on the resulting factors. The distances obtained from these metrics are then used to cluster the active regions. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the $R$ value. We provide some recommendations for which metrics, matrix factorization techniques, and regions of interest to use to study active regions.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC). 33 pages, 12 figure

Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis

The flare-productivity of an active region is observed to be related to its spatial complexity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information present in the observations. Moreover, such categorical schemes hinder a systematic study of an active region's evolution for example. We propose fine-scale quantitative descriptors for an active region's complexity and relate them to the Mount Wilson classification. We analyze the local correlation structure within continuum and magnetogram data, as well as the cross-correlation between continuum and magnetogram data. We compute the intrinsic dimension, partial correlation, and canonical correlation analysis (CCA) of image patches of continuum and magnetogram active region images taken from the SOHO-MDI instrument. We use masks of sunspots derived from continuum as well as larger masks of magnetic active regions derived from the magnetogram to analyze separately the core part of an active region from its surrounding part. We find the relationship between complexity of an active region as measured by Mount Wilson and the intrinsic dimension of its image patches. Partial correlation patterns exhibit approximately a third-order Markov structure. CCA reveals different patterns of correlation between continuum and magnetogram within the sunspots and in the region surrounding the sunspots. These results also pave the way for patch-based dictionary learning with a view towards automatic clustering of active regions.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC). 23 pages, 11 figure

Observations of Cygnus X-3 above 10(15) eV from 1979 - 1984

The ultra high energy gamma-ray source, cygnus X-3, has been observed more or less continuously with an array sensitive to 10 to the 15th power ev primaries between 1 Jan. 1979 and 31 Dec. 1984. There is evidence for time variability in the phase of gamma-ray emission over this period

A Minimum-Labeling Approach for Reconstructing Protein Networks across Multiple Conditions

The sheer amounts of biological data that are generated in recent years have driven the development of network analysis tools to facilitate the interpretation and representation of these data. A fundamental challenge in this domain is the reconstruction of a protein-protein subnetwork that underlies a process of interest from a genome-wide screen of associated genes. Despite intense work in this area, current algorithmic approaches are largely limited to analyzing a single screen and are, thus, unable to account for information on condition-specific genes, or reveal the dynamics (over time or condition) of the process in question. Here we propose a novel formulation for network reconstruction from multiple-condition data and devise an efficient integer program solution for it. We apply our algorithm to analyze the response to influenza infection in humans over time as well as to analyze a pair of ER export related screens in humans. By comparing to an extant, single-condition tool we demonstrate the power of our new approach in integrating data from multiple conditions in a compact and coherent manner, capturing the dynamics of the underlying processes.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

The primary cosmic ray spectrum above 10 to the 19th power eV

Progress on a re-evaluation of the spectrum of cosmic rays determined with the Haverah Park shower array is described. Particular attention is paid to the reality of some giant showers