North-South Distribution of Solar Flares during Cycle 23

In this paper, we investigate the spatial distribution of solar flares in the northern and southern hemisphere of the Sun that occurred during the period 1996 to 2003. This period of investigation includes the ascending phase, the maximum and part of descending phase of solar cycle 23. It is revealed that the flare activity during this cycle is low compared to previous solar cycle, indicating the violation of Gnevyshev-Ohl rule. The distribution of flares with respect to heliographic latitudes shows a significant asymmetry between northern and southern hemisphere which is maximum during the minimum phase of the solar cycle. The present study indicates that the activity dominates the northern hemisphere in general during the rising phase of the cycle (1997-2000). The dominance of northern hemisphere is shifted towards the southern hemisphere after the solar maximum in 2000 and remained there in the successive years. Although the annual variations in the asymmetry time series during cycle 23 are quite different from cycle 22, they are comparable to cycle 21.Comment: 6 pages, 2 figures, 1 table; Accepted for the publication in the proceedings of international solar workshop held at ARIES, Nainital, India on "Transient Phenomena on the Sun and Interplanetary Medium" in a special issue of "Journal of Astrophysics and Astronomy (JAA)

Measurement of Muon Capture on the Proton to 1% Precision and Determination of the Pseudoscalar Coupling g_P

The MuCap experiment at the Paul Scherrer Institute has measured the rate L_S of muon capture from the singlet state of the muonic hydrogen atom to a precision of 1%. A muon beam was stopped in a time projection chamber filled with 10-bar, ultra-pure hydrogen gas. Cylindrical wire chambers and a segmented scintillator barrel detected electrons from muon decay. L_S is determined from the difference between the mu- disappearance rate in hydrogen and the free muon decay rate. The result is based on the analysis of 1.2 10^10 mu- decays, from which we extract the capture rate L_S = (714.9 +- 5.4(stat) +- 5.1(syst)) s^-1 and derive the proton's pseudoscalar coupling g_P(q^2_0 = -0.88 m^2_mu) = 8.06 +- 0.55.Comment: Updated figure 1 and small changes in wording to match published versio

Modification of HDL by reactive aldehydes alters select cardioprotective functions of HDL in macrophages

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154382/1/febs15034_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154382/2/febs15034.pd

Measurement of the Rate of Muon Capture in Hydrogen Gas and Determination of the Proton's Pseudoscalar Coupling gPg_P

The rate of nuclear muon capture by the proton has been measured using a new experimental technique based on a time projection chamber operating in ultra-clean, deuterium-depleted hydrogen gas at 1 MPa pressure. The capture rate was obtained from the difference between the measured $\mu^-$ disappearance rate in hydrogen and the world average for the $\mu^+$ decay rate. The target's low gas density of 1% compared to liquid hydrogen is key to avoiding uncertainties that arise from the formation of muonic molecules. The capture rate from the hyperfine singlet ground state of the $\mu p$ atom is measured to be $\Lambda_S=725.0 \pm 17.4 s^{-1}$, from which the induced pseudoscalar coupling of the nucleon, $g_P(q^2=-0.88 m_\mu^2)=7.3 \pm 1.1$, is extracted. This result is consistent with theoretical predictions for $g_P$ that are based on the approximate chiral symmetry of QCD.Comment: submitted to Phys.Rev.Let

Inference and Evolutionary Analysis of Genome-Scale Regulatory Networks in Large Phylogenies

Changes in transcriptional regulatory networks can significantly contribute to species evolution and adaptation. However, identification of genome-scale regulatory networks is an open challenge, especially in non-model organisms. Here, we introduce multi-species regulatory network learning (MRTLE), a computational approach that uses phylogenetic structure, sequence-specific motifs, and transcriptomic data, to infer the regulatory networks in different species. Using simulated data from known networks and transcriptomic data from six divergent yeasts, we demonstrate that MRTLE predicts networks with greater accuracy than existing methods because it incorporates phylogenetic information. We used MRTLE to infer the structure of the transcriptional networks that control the osmotic stress responses of divergent, non-model yeast species and then validated our predictions experimentally. Interrogating these networks reveals that gene duplication promotes network divergence across evolution. Taken together, our approach facilitates study of regulatory network evolutionary dynamics across multiple poorly studied species. Keywords: regulatory networks; network inference; evolution of gene regulatory networks; evolution of stress response; yeast; probabilistic graphical model; phylogeny; comparative functional genomicsNational Science Foundation (U.S.) (Grant DBI-1350677)National Institutes of Health (U.S.) (Grant R01CA119176-01)National Institutes of Health (U.S.) (Grant DP1OD003958-01