Galactic Cannibalism: the Origin of the Magellanic Stream

We are in a privileged location in the Universe which allows us to observe galactic interactions from close range -- the merger of our two nearest dwarf satellite galaxies, the LMC and SMC. It is important to understand the local merger process before we can have confidence in understanding mergers at high redshift. We present high resolution Nbody+SPH simulations of the disruption of the LMC and SMC and the formation of the Magellanic Stream, and discuss the implications for galaxy formation and evolution.Comment: 2 pages, 1 figure, to appear in "The Evolution of Galaxies II: Basic Building Blocks", (2002) ed. M. Sauvage et al. (Kluwer

Uneconomical Diagnosis of Cladograms: Comments on Wheeler and Nixon's Method for Sankoff Optimization

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74972/1/j.1096-0031.1997.tb00249.x.pd

Upstream cyclone influence on the predictability of block onsets over the Euro-Atlantic region

Atmospheric blocking has been shown to be a phenomenon that models struggle to predict accurately, particularly the onset of a blocked state following a more zonal flow. This struggle is, in part, due to the lack of a complete dynamical theory for block onset and maintenance. Here, we evaluate the impact cyclone representation had on the forecast of block onset in two case studies from the North Atlantic Waveguide and Downstream Impact Experiment field campaign and the 20 most unpredictable block onsets over the Euro-Atlantic region in medium-range forecasts from the ECMWF. The six-day forecast of block onset in the case studies is sensitive to changes in the forecast location and intensity of upstream cyclones (one cyclone for one case and two for the other case) in the days preceding the onset. Ensemble sensitivity analysis reveals that this is often the case in unpredictable block onset cases: a one-standard deviation change in 1000-hPa geopotential height near an upstream cyclone, or 320-K potential vorticity near the tropopause, two or three days prior to block onset is associated with more than a 10% change in block area on the analyzed onset day in 17 of the 20 onset cases. These results imply that improvement in the forecasts of upstream cyclone location and intensity may help improve block onset forecasts

Detecting retinal cell stress and apoptosis with DARC: Progression from lab to clinic

DARC (Detection of Apoptosing Retinal Cells) is a retinal imaging technology that has been developed within the last 2 decades from basic laboratory science to Phase 2 clinical trials. It uses ANX776 (fluorescently labelled Annexin A5) to identify stressed and apoptotic cells in the living eye. During its development, DARC has undergone biochemistry optimisation, scale-up and GMP manufacture and extensive preclinical evaluation. Initially tested in preclinical glaucoma and optic neuropathy models, it has also been investigated in Alzheimer, Parkinson's and Diabetic models, and used to assess efficacy of therapies. Progression to clinical trials has not been speedy. Intravenous ANX776 has to date been found to be safe and well-tolerated in 129 patients, including 16 from Phase 1 and 113 from Phase 2. Results on glaucoma and AMD patients have been recently published, and suggest DARC with an AI-aided algorithm can be used to predict disease activity. New analyses of DARC in GA prediction are reported here. Although further studies are needed to validate these findings, it appears there is potential of the technology to be used as a biomarker. Much larger clinical studies will be needed before it can be considered as a diagnostic, although the relatively non-invasive nature of the nasal as opposed to intravenous administration would widen its acceptability in the future as a screening tool. This review describes DARC development and its progression into Phase 2 clinical trials from lab-based research. It discusses hypotheses, potential challenges, and regulatory hurdles in translating technology

New constraints on the millimetre emission of six debris discs

The presence of dusty debris around main-sequence stars denotes the existence of planetary systems. Such debris discs are often identified by the presence of excess continuum emission at infrared and (sub-)millimetre wavelengths, with measurements at longer wavelengths tracing larger and cooler dust grains. The exponent of the slope of the disc emission at submillimetre wavelengths, ‘q’, defines the size distribution of dust grains in the disc. This size distribution is a function of the rigid strength of the dust producing parent planetesimals. As a part of the survey ‘PLAnetesimals around TYpical Pre-main seqUence Stars’, we observed six debris discs at 9 mm using the Australian Telescope Compact Array. We obtain marginal (∼3σ) detections of three targets: HD 105, HD 61005 and HD 131835. Upper limits for the three remaining discs, HD 20807, HD 109573 and HD 109085 provide further constraint of the (sub-)millimetre slope of their spectral energy distributions. The values of q (or their limits) derived from our observations are all smaller than the oft-assumed steady-state collisional cascade model (q = 3.5), but lie well within the theoretically expected range for debris discs q ∼ 3–4. The measured q values for our targets are all <3.3, consistent with both collisional modelling results and theoretical predictions for parent planetesimal bodies being ‘rubble piles’ held together loosely by their self-gravity

An attempt to observe economy globalization: the cross correlation distance evolution of the top 19 GDP's

Economy correlations between the 19 richest countries are investigated through their Gross Domestic Product increments. A distance is defined between increment correlation matrix elements and their evolution studied as a function of time and time window size. Unidirectional and Bidirectional Minimal Length Paths are generated and analyzed for different time windows. A sort of critical correlation time window is found indicating a transition for best observations. The mean length path decreases with time, indicating stronger correlations. A new method for estimating a realistic minimal time window to observe correlations and deduce macroeconomy conclusions from such features is thus suggested.Comment: to be published in the Dyses05 proceedings, in Int. J. Mod Phys C 15 pages, 5 figures, 1 tabl

Evaluation of a Scalar Eddy Transport Coefficient Based on Geometric Constraints

A suite of idealized models is used to evaluate and compare several previously proposed scalings for the eddy transport coefficient in downgradient mesoscale eddy closures. Of special interest in this comparison is a scaling introduced as part of the eddy parameterization framework of Marshall et al. (2012), which is derived using the inherent geometry of the Eliassen–Palm eddy flux tensor. The primary advantage of using this coefficient in a downgradient closure is that all dimensional terms are explicitly specified and the only uncertainty is a nondimensional parameter, α, which is bounded by one in magnitude. In each model a set of passive tracers is initialized, whose flux statistics are used to invert for the eddy- induced tracer transport. Unlike previous work, where this technique has been employed to diagnose the tensor coefficient of a linear flux-gradient relationship, the idealization of these models allows the lateral eddy transport to be described by a scalar coefficient. The skill of the extant scalings is then measured by comparing their predicted values against the coefficients diagnosed using this method. The Marshall et al. (2012) scaling is shown to scale most closely with the diagnosed coefficients across all simulations. It is shown that the skill of this scaling is due to its functional dependence on the total eddy energy, and that this scaling provides an excellent match to the diagnosed fluxes even in the limit of constant α. Possible extensions to this work, including how to incorporate the resultant transport coefficient into the Gent and McWilliams parameterization, are discussed

Ultraconserved element (UCE) probe set design: Base genome and initial design parameters critical for optimization

This work is licensed under a Creative Commons Attribution 4.0 International License.Targeted capture and enrichment approaches have proven effective for phylogenetic study. Ultraconserved elements (UCEs) in particular have exhibited great utility for phylogenomic analyses, with the software package phyluce being among the most utilized pipelines for UCE phylogenomics, including probe design. Despite the success of UCEs, it is becoming increasing apparent that diverse lineages require probe sets tailored to focal taxa in order to improve locus recovery. However, factors affecting probe design and methods for optimizing probe sets to focal taxa remain underexplored. Here, we use newly available beetle (Coleoptera) genomic resources to investigate factors affecting UCE probe set design using phyluce. In particular, we explore the effects of stringency during initial design steps, as well as base genome choice on resulting probe sets and locus recovery. We found that both base genome choice and initial bait design stringency parameters greatly alter the number of resultant probes included in final probe sets and strongly affect the number of loci detected and recovered during in silico testing of these probe sets. In addition, we identify attributes of base genomes that correlated with high performance in probe design. Ultimately, we provide a recommended workflow for using Phyluce to design an optimized UCE probe set that will work across a targeted lineage, and use our findings to develop a new, open‐source UCE probe set for beetles of the suborder Adephaga.NIH IRACDA postdoctoral fellowship (5K12GM063651)Harold E. and Leona M. Rice Endowment Fund at Oregon State Universit

Optimal Economic Growth under Stochastic Environmental Impact: Sensitivity Analysis

In this work we present an approach toward the sensitivity analysis of optimal economic growth to a negative environmental impact driven by random natural hazards that damage the production output . We use a simplified model of the GDP whose growth leads to the increase of GHG in the atmosphere provided investment in cleaning is insufficient. The hypothesis of the Poisson probability distribution of the natural hazards is used at the first stage of the research. We apply the standard utility function - the discounted integral consumption and construct an optimal investment policy in production and cleaning together with optimal GDP trajectories. We calibrate the model in the global scale and analyze the sensitivity of obtained optimal growth scenarios with respect to uncertain parameters of the Poisson distribution