A study of major mergers using a multi-phase ISM code

Galaxy interactions are a common phenomenon in clusters of galaxies. Especially major mergers are of particular importance, because they can change the morphological type of galaxies. They have an impact on the mass function of galaxies and they trigger star formation - the main driver of the Galactic Matter Cycle. Therefore, we conducted a study of major mergers by means of a multi-phase ISM code. This code is based on a TREE-SPH-code combined with a sticky particle method allowing for star formation controlled by the properties of a multi-phase ISM. This is in contrast to the usually implemented Schmidt law depending mainly on the gas density. Previously, this code was used on isolated galaxies. Since our star formation recipe is not restricted to a special type of galaxy, it is interesting to apply it to interacting galaxies, too. Our study on major mergers includes a research of global properties of the interacting system, namely the star formation rate and the star formation efficiency, the evaporation and condensation rates, as well as the mass exchange of distinct components, namely stars, diffuse ISM, and clouds. Investigating these properties provides insight to interrelations between various physical processes. The results indicate that the star formation efficiency as well as the evaporation and condensation rates are influenced by the interaction.Comment: 6 pages, 7 figures, to be published in Astronomische Nachrichten (proceedings of Symposium 6 of the JENAM 2008, Vienna

Infectious titer determination of lentiviral vectors using a temporal immunological real-time imaging approach

The analysis of the infectious titer of the lentiviral vector samples obtained during upstream and downstream processing is of major importance, however, also the most challenging method to be performed. Currently established methods like flow cytometry or qPCR lack the capability of enabling high throughput sample processing while they require a lot of manual handling. To address this limitation, we developed an immunological real-time imaging method to quantify the infectious titer of anti-CD19 CAR lentiviral vectors with a temporal readout using the Incucyte® S3 live-cell analysis system. The infective titers determined with the Incucyte® approach when compared with the flow cytometry-based assay had a lower standard deviation between replicates and a broader linear range. A major advantage of the method is the ability to obtain titer results in real-time, enabling an optimal readout time. The presented protocol significantly decreased labor and increased throughput. The ability of the assay to process high numbers of lentiviral samples in a high throughput manner was proven by performing a virus stability study, demonstrating the effects of temperature, salt, and shear stress on LV infectivity

Simulating magnetic fields in the Antennae galaxies

We present self-consistent high-resolution simulations of NGC4038/4039 (the "Antennae galaxies") including star formation, supernova feedback and magnetic fields performed with the N-body/SPH code Gadget, in which magnetohydrodynamics are followed with the SPH method. We vary the initial magnetic field in the progenitor disks from 1 nG to 100 muG. At the time of the best match with the central region of the Antennae system the magnetic field has been amplified by compression and shear flows to an equilibrium field of approximately 10 muG, independent of the initial seed field. These simulations are a proof of the principle that galaxy mergers are efficient drivers for the cosmic evolution of magnetic fields. We present a detailed analysis of the magnetic field structure in the central overlap region. Simulated radio and polarization maps are in good morphological and quantitative agreement with the observations. In particular, the two cores with the highest synchrotron intensity and ridges of regular magnetic fields between the cores and at the root of the southern tidal arm develop naturally in our simulations. This indicates that the simulations are capable of realistically following the evolution of the magnetic fields in a highly non-linear environment. We also discuss the relevance of the amplification effect for present day magnetic fields in the context of hierarchical structure formation.Comment: 18 pages, 14 figures, accepte

MSI-CIEC: MSI Cyberinfrastructure Empowerment Coalition and the TeraGrid

Paper written as a collaboration of the following institutions and presented at the 2006 TeraGrid Conference, Indianapolis, IN June 12-16: 1. University of Houston Downtown 2. NAFEO: National Association for Equal Opportunity in Higher Education 3. SDSC: San Diego Supercomputer Center 4. Indiana University, Computer Science Department 5. AIHEC: The American Indiana Highter Education Consortium 6. HACU: Hispanic Association of Colleges and Universitie

Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures.

BackgroundImproved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.ObjectivesTo examine whether baseline measures and their 1-year change predict longer-term progression in early PD.MethodsParkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.ResultsAmong 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.ConclusionsBaseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding

A dataset for autonomous aircraft refueling on the ground (AGR)

Automatic aircraft ground refueling (AAGR) can improve the safety, efficiency, and cost-effectiveness of aircraft ground refueling (AGR), a critical and frequent operation on almost all aircraft. Recent AAGR relies on machine vision, artificial intelligence, and robotics to implement automation. An essential step for automation is AGR scene recognition, which can support further component detection, tracking, process monitoring, and environmental awareness. As in many practical and commercial applications, aircraft refueling data is usually confidential, and no standardized workflow or definition is available. These are the prerequisites and critical challenges to deploying and benefitting advanced data-driven AGR. This study presents a dataset (the AGR Dataset) for AGR scene recognition using image crawling, augmentation, and classification, which has been made available to the community. The AGR dataset crawled over 3k images from 13 databases (over 26k images after augmentation), and different aircraft, illumination, and environmental conditions were included. The ground-truth labeling is conducted manually using a proposed tree-formed decision workflow and six specific AGR tags. Various professionals have independently reviewed the AGR dataset to keep it no-bias. This study proposes the first aircraft refueling image dataset, and an image labeling software with a UI to automate the labeling workflow

'A light in a very dark place' : The role of a voluntary organisation providing support for those affected by encephalitis

Voluntary organisations are seen as contributing to the ‘democratisation’ of health and social care. Little, however, is written about their role and this paper, by focusing on the work of The Encephalitis Society, provides insights into the challenges facing voluntary organisations as they manage twin roles as service providers and advocates, of people with neurological disorders. Two studies are presented: a review conducted by the Society, focusing on patient’s experiences of neurological services; and an external evaluation of the Society’s current provision. The first, based on a postal survey of its members affected by encephalitis (n = 339), illustrates the Society’s advocacy role. The survey provided support for the Association of British Neurologists’ recommendation for nationally agreed standards of care. The second study, a postal survey of recent contacts (n = 76) and in-depth telephone interviews (n = 22), illustrates the Society’s value role as a service provider and supports its role in helping rehabilitate affected individuals and their families. These studies provided the Society with information for policy and service development. Importantly, providing the basis of informed action and partnership with stakeholders and informing the organisation’s sense of purpose, in the changing context of welfare provision in the UK

Star Formation in Galaxy Mergers with Realistic Models of Stellar Feedback & the Interstellar Medium

We use simulations with realistic models for stellar feedback to study galaxy mergers. These high resolution (1 pc) simulations follow formation and destruction of individual GMCs and star clusters. The final starburst is dominated by in situ star formation, fueled by gas which flows inwards due to global torques. The resulting high gas density results in rapid star formation. The gas is self gravitating, and forms massive (~10^10 M_sun) GMCs and subsequent super-starclusters (masses up to 10^8 M_sun). However, in contrast to some recent simulations, the bulk of new stars which eventually form the central bulge are not born in superclusters which then sink to the center of the galaxy, because feedback efficiently disperses GMCs after they turn several percent of their mass into stars. Most of the mass that reaches the nucleus does so in the form of gas. The Kennicutt-Schmidt law emerges naturally as a consequence of feedback balancing gravitational collapse, independent of the small-scale star formation microphysics. The same mechanisms that drive this relation in isolated galaxies, in particular radiation pressure from IR photons, extend over seven decades in SFR to regulate star formation in the most extreme starbursts (densities >10^4 M_sun/pc^2). Feedback also drives super-winds with large mass loss rates; but a significant fraction of the wind material falls back onto the disks at later times, leading to higher post-starburst SFRs in the presence of stellar feedback. Strong AGN feedback is required to explain sharp cutoffs in star formation rate. We compare the predicted relic structure, mass profile, morphology, and efficiency of disk survival to simulations which do not explicitly resolve GMCs or feedback. Global galaxy properties are similar, but sub-galactic properties and star formation rates can differ significantly.Comment: 17 pages, 13 figures (+appendices), MNRAS accepted (matches published). Movies of the simulations are available at http://www.tapir.caltech.edu/~phopkins/Site/Movies_sbw_mgr.htm