Preliminary Observations on New Images of the Elysium Frozen Sea Deposits from HRSC Mars Express

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Synthetic biology for evolutionary engineering: from perturbation of genotype to acquisition of desired phenotype

With the increased attention on bio-based industry, demands for techniques that enable fast and effective strain improvement have been dramatically increased. Evolutionary engineering, which is less dependent on biological information, has been applied to strain improvement. Currently, synthetic biology has made great innovations in evolutionary engineering, particularly in the development of synthetic tools for phenotypic perturbation. Furthermore, discovering biological parts with regulatory roles and devising novel genetic circuits have promoted high-throughput screening and selection. In this review, we first briefly explain basics of synthetic biology tools for mutagenesis and screening of improved variants, and then describe how these strategies have been improved and applied to phenotypic engineering. Evolutionary engineering using advanced synthetic biology tools will enable further innovation in phenotypic engineering through the development of novel genetic parts and assembly into well-designed logic circuits that perform complex tasks.11Ysciescopu

BKB_K using HYP-smeared staggered fermions in Nf=2+1N_f=2+1 unquenched QCD

We present results for kaon mixing parameter $B_K$ calculated using HYP-smeared improved staggered fermions on the MILC asqtad lattices. We use three lattice spacings ($a\approx 0.12$, $0.09$ and $0.06\;$fm), ten different valence quark masses ($m\approx m_s/10-m_s$), and several light sea-quark masses in order to control the continuum and chiral extrapolations. We derive the next-to-leading order staggered chiral perturbation theory (SChPT) results necessary to fit our data, and use these results to do extrapolations based both on SU(2) and SU(3) SChPT. The SU(2) fitting is particularly straightforward because parameters related to taste-breaking and matching errors appear only at next-to-next-to-leading order. We match to the continuum renormalization scheme (NDR) using one-loop perturbation theory. Our final result is from the SU(2) analysis, with the SU(3) result providing a (less accurate) cross check. We find $B_K(\text{NDR}, \mu = 2 \text{GeV}) = 0.529 \pm 0.009 \pm 0.032$ and $\hat{B}_K =B_K(\text{RGI})= 0.724 \pm 0.012 \pm 0.043$, where the first error is statistical and the second systematic. The error is dominated by the truncation error in the matching factor. Our results are consistent with those obtained using valence domain-wall fermions on lattices generated with asqtad or domain-wall sea quarks.Comment: 37 pages, 31 figures, most updated versio