The Role of Galactic Winds on Molecular Gas Emission from Galaxy Mergers

We assess the impact of starburst and AGN feedback-driven winds on the CO emission from galaxy mergers, and, in particular, search for signatures of these winds in the simulated CO morphologies and emission line profiles. We do so by combining a 3D non-LTE molecular line radiative transfer code with smoothed particle hydrodynamics (SPH) simulations of galaxy mergers that include prescriptions for star formation, black hole growth, a multiphase interstellar medium (ISM), and the winds associated with star formation and black hole growth. Our main results are: (1) Galactic winds can drive outflows of masses ~10^8-10^9 Msun which may be imaged via CO emission line mapping. (2) AGN feedback-driven winds are able to drive imageable CO outflows for longer periods of time than starburst-driven winds owing to the greater amount of energy imparted to the ISM by AGN feedback compared to star formation. (3) Galactic winds can control the spatial extent of the CO emission in post-merger galaxies, and may serve as a physical motivation for the sub-kiloparsec scale CO emission radii observed in local advanced mergers. (4) Secondary emission peaks at velocities greater than the circular velocity are seen in the CO emission lines in all models. In models with winds, these high velocity peaks are seen to preferentially correspond to outflowing gas entrained in winds, which is not the case in the model without winds. The high velocity peaks seen in models without winds are typically confined to velocity offsets (from the systemic) < 1.7 times the circular velocity, whereas the models with AGN feedback-driven winds can drive high velocity peaks to ~2.5 times the circular velocity.Comment: Accepted by ApJ; Minor revisions; Resolution tests include

Variability selected high-redshift quasars on SDSS Stripe 82

The SDSS-III BOSS Quasar survey will attempt to observe z>2.15 quasars at a density of at least 15 per square degree to yield the first measurement of the Baryon Acoustic Oscillations in the Ly-alpha forest. To help reaching this goal, we have developed a method to identify quasars based on their variability in the u g r i z optical bands. The method has been applied to the selection of quasar targets in the SDSS region known as Stripe 82 (the Southern equatorial stripe), where numerous photometric observations are available over a 10-year baseline. This area was observed by BOSS during September and October 2010. Only 8% of the objects selected via variability are not quasars, while 90% of the previously identified high-redshift quasar population is recovered. The method allows for a significant increase in the z>2.15 quasar density over previous strategies based on optical (ugriz) colors, achieving a density of 24.0 deg^{-2} on average down to g~22 over the 220 deg^2 area of Stripe 82. We applied this method to simulated data from the Palomar Transient Factory and from Pan-STARRS, and showed that even with data that have sparser time sampling than what is available in Stripe 82, including variability in future quasar selection strategies would lead to increased target selection efficiency in the z>2.15 redshift range. We also found that Broad Absorption Line quasars are preferentially present in a variability than in a color selection.Comment: 14 pages, 21 figures, accepted for publication in A&

Precipitate Redistribution During Creep of Alloy 617

Nickel-based superalloys are being considered for applications within advanced nuclear power generation systems due to their high temperature strength and corrosion resistance. Alloy 617, a candidate for use in heat exchangers, derives its strength from both solid solution strengthening and the precipitation of carbide particles. However, during creep, carbides that are supposed to retard grain boundary motion are found to dissolve and re-precipitate on boundaries in tension. To quantify the redistribution, we have used electron backscatter diffraction and energy dispersive spectroscopy to analyze the microstructure of 617 after creep testing at 900 and 1000°C. The data were analyzed with respect to location of the carbides (e.g., intergranular vs. intragranular), grain boundary character, and precipitate type (i.e., Cr-rich or Mo-rich). We find that grain boundary character is the most important factor in carbide distribution; some evidence of preferential distribution to boundaries in tension is also observed at higher applied stresses. Finally, the results suggest that the observed redistribution is due to the migration of carbides to the boundaries and not the migration of boundaries to the precipitates

The Correlation between Running Economy and Maximal Oxygen Uptake: Cross-Sectional and Longitudinal Relationships in Highly Trained Distance Runners

A positive relationship between running economy and maximal oxygen uptake (V̇O2max) has been postulated in trained athletes, but previous evidence is equivocal and could have been confounded by statistical artefacts. Whether this relationship is preserved in response to running training (changes in running economy and V̇O2max) has yet to be explored. This study examined the relationships of (i) running economy and V̇O2max between runners, and (ii) the changes in running economy and V̇O2max that occur within runners in response to habitual training. 168 trained distance runners (males, n = 98, V̇O2max 73.0 ± 6.3 mLkg-1min-1; females, n = 70, V̇O2max 65.2 ± 5.9 mL kg-1min-1) performed a discontinuous submaximal running test to determine running economy (kcalkm-1). A continuous incre-mental treadmill running test to volitional exhaustion was used to determine V̇O2max 54 par-ticipants (males, n = 27; females, n = 27) also completed at least one follow up assessment. Partial correlation analysis revealed small positive relationships between running economy and V̇O2max (males r = 0.26, females r = 0.25; P&lt;0.006), in addition to moderate positive re-lationships between the changes in running economy and V̇O2max in response to habitual training (r = 0.35; P&lt;0.001). In conclusion, the current investigation demonstrates that only a small to moderate relationship exists between running economy and V̇O2max in highly trained distance runners. With&gt;85 % of the variance in these parameters unexplained by this relationship, these findings reaffirm that running economy and V̇O2max are primarily determined independently

Chemical vapour deposition synthetic diamond: materials, technology and applications

Substantial developments have been achieved in the synthesis of chemical vapour deposition (CVD) diamond in recent years, providing engineers and designers with access to a large range of new diamond materials. CVD diamond has a number of outstanding material properties that can enable exceptional performance in applications as diverse as medical diagnostics, water treatment, radiation detection, high power electronics, consumer audio, magnetometry and novel lasers. Often the material is synthesized in planar form, however non-planar geometries are also possible and enable a number of key applications. This article reviews the material properties and characteristics of single crystal and polycrystalline CVD diamond, and how these can be utilized, focusing particularly on optics, electronics and electrochemistry. It also summarizes how CVD diamond can be tailored for specific applications, based on the ability to synthesize a consistent and engineered high performance product.Comment: 51 pages, 16 figure

A connectome and analysis of the adult Drosophila central brain.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain

Structure-Guided Evolution of Potent and Selective CHK1 Inhibitors through Scaffold Morphing

Pyrazolopyridine inhibitors with low micromolar potency for CHK1 and good selectivity against CHK2 were previously identified by fragment-based screening. The optimization of the pyrazolopyridines to a series of potent and CHK1-selective isoquinolines demonstrates how fragment-growing and scaffold morphing strategies arising from a structure-based understanding of CHK1 inhibitor binding can be combined to successfully progress fragment-derived hit matter to compounds with activity in vivo. The challenges of improving CHK1 potency and selectivity, addressing synthetic tractability, and achieving novelty in the crowded kinase inhibitor chemical space were tackled by multiple scaffold morphing steps, which progressed through tricyclic pyrimido[2,3-b]azaindoles to N-(pyrazin-2-yl)pyrimidin-4-amines and ultimately to imidazo[4,5-c]pyridines and isoquinolines. A potent and highly selective isoquinoline CHK1 inhibitor (SAR-020106) was identified, which potentiated the efficacies of irinotecan and gemcitabine in SW620 human colon carcinoma xenografts in nude mice

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery