Magellanic Cloud Periphery Carbon Stars IV: The SMC

The kinematics of 150 carbon stars observed at moderate dispersion on the periphery of the Small Magellanic Cloud are compared with the motions of neutral hydrogen and early type stars in the Inter-Cloud region. The distribution of radial velocities implies a configuration of these stars as a sheet inclined at 73+/-4 degrees to the plane of the sky. The near side, to the South, is dominated by a stellar component; to the North, the far side contains fewer carbon stars, and is dominated by the neutral gas. The upper velocity envelope of the stars is closely the same as that of the gas. This configuration is shown to be consistent with the known extension of the SMC along the line of sight, and is attributed to a tidally induced disruption of the SMC that originated in a close encounter with the LMC some 0.3 to 0.4 Gyr ago. The dearth of gas on the near side of the sheet is attributed to ablation processes akin to those inferred by Weiner & Williams (1996) to collisional excitation of the leading edges of Magellanic Stream clouds. Comparison with pre LMC/SMC encounter kinematic data of Hardy, Suntzeff, & Azzopardi (1989) of carbon stars, with data of stars formed after the encounter, of Maurice et al. (1989), and Mathewson et al. (a986, 1988) leaves little doubt that forces other than gravity play a role in the dynamics of the H I.Comment: 30 pages; 7 figures, latex compiled, 1 table; to appear in AJ (June 2000

Immune Modulation through 4-1BB Enhances SIV Vaccine Protection in Non-Human Primates against SIVmac251 Challenge

Costimulatory molecules play a central role in the development of cellular immunity. Understanding how costimulatory pathways can be directed to positively influence the immune response may be critical for the generation of an effective HIV vaccine. Here, we evaluated the ability of intravenous administration of a blocking monoclonal antibody (mAb) directed against the negative costimulatory molecule CTLA-4, and an agonist mAb directed against the positive costimulatory molecule 4-1BB, either alone or in combination, to augment intramuscular SIV DNA immunizations. We then tested the ability these of these responses to impact a high-dose SIVmac251 challenge. Following immunization, the groups infused with the anti-4-1BB mAb exhibited enhanced IFN-γ responses compared to the DNA vaccine only group. Interestingly, although CTLA-4 blockade alone did not enhance IFN-γ responses it did increase the proliferative capacity of the CD4+ and CD8+ T cells. The combination of both mAbs enhanced the magnitude of the polyfunctional CD8+ T cell response. Following challenge, the group that received both mAbs exhibited a significant, ∼2.0 log, decrease in plasma viral load compared to the naïve group the included complete suppression of viral load in some animals. Furthermore, the use of the CTLA-4 blocking antibody resulted in significantly higher viral loads during chronic infection compared to animals that received the 4-1BB mAb, likely due to the higher CD4+ T cell proliferative responses which were driven by this adjuvant following immunization. These novel studies show that these adjuvants induce differential modulation of immune responses, which have dramatically different consequences for control of SIV replication, suggesting important implications for HIV vaccine development

Mapping Materials and Molecules

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the “big data” revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities. It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them. This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses. The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

Mapping Materials and Molecules.

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the "big data" revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities.It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them.This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses.The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

AIMES: advanced computation and I/O methods for earth-system simulations

Dealing with extreme scale Earth-system models is challenging from the computer science perspective, as the required computing power and storage capacity are steadily increasing. Scientists perform runs with growing resolution or aggregate results from many similar smaller-scale runs with slightly different initial conditions (the so-called ensemble runs). In the fifth Coupled Model Intercomparison Project (CMIP5), the produced datasets require more than three Petabytes of storage and the compute and storage requirements are increasing significantly for CMIP6. Climate scientists across the globe are developing next-generation models based on improved numerical formulation leading to grids that are discretized in alternative forms such as an icosahedral (geodesic) grid. The developers of these models face similar problems in scaling, maintaining and optimizing code. Performance portability and the maintainability of code are key concerns of scientists as, compared to industry projects, model code is continuously revised and extended to incorporate further levels of detail. This leads to a rapidly growing code base that is rarely refactored. However, code modernization is important to maintain productivity of the scientist working with the code and for utilizing performance provided by modern and future architectures. The need for performance optimization is motivated by the evolution of the parallel architecture landscape from homogeneous flat machines to heterogeneous combinations of processors with deep memory hierarchy. Notably, the rise of many-core, throughput-oriented accelerators, such as GPUs, requires non-trivial code changes at minimum and, even worse, may necessitate a substantial rewrite of the existing codebase. At the same time, the code complexity increases the difficulty for computer scientists and vendors to understand and optimize the code for a given system. Storing the products of climate predictions requires a large storage and archival system which is expensive. Often, scientists restrict the number of scientific variables and write interval to keep the costs balanced. Compression algorithms can reduce the costs significantly but can also increase the scientific yield of simulation runs. In the AIMES project, we addressed the key issues of programmability, computational efficiency and I/O limitations that are common in next-generation icosahedral earth-system models. The project focused on the separation of concerns between domain scientist, computational scientists, and computer scientists

A Two Micron All-Sky Survey View of the Sagittarius Dwarf Galaxy: II. Swope Telescope Spectroscopy of M Giant Stars in the Dynamically Cold Sagittarius Tidal Stream

We present moderate resolution (~6 km/s) spectroscopy of 284 M giant candidates selected from the Two Micron All Sky Survey photometry. Radial velocities (RVs) are presented for stars mainly in the south, with a number having positions consistent with association to the trailing tidal tail of the Sagittarius (Sgr) dwarf galaxy. The latter show a clear RV trend with orbital longitude, as expected from models of the orbit and destruction of Sgr. A minimum 8 kpc width of the trailing stream about the Sgr orbital midplane is implied by verified RV members. The coldness of this stream (dispersion ~10 km/s) provides upper limits on the combined contributions of stream heating by a lumpy Galactic halo and the intrinsic dispersion of released stars, which is a function of the Sgr core mass. The Sgr trailing arm is consistent with a Galactic halo containing one dominant, LMC-like lump, however some lumpier halos are not ruled out. An upper limit to the total M/L of the Sgr core is 21 in solar units. A second structure that roughly mimics expectations for wrapped, leading Sgr arm debris crosses the trailing arm in the Southern Hemisphere; however, this may also be an unrelated tidal feature. Among the <13 kpc M giants toward the South Galactic Pole are some with large RVs that identify them as halo stars, perhaps part of the Sgr leading arm near the Sun. The positions and RVs of Southern Hemisphere M giants are compared with those of southern globular clusters potentially stripped from the Sgr system and support for association of Pal 2 and Pal 12 with Sgr debris is found. Our discussion includes description of a masked-filtered cross-correlation methodology that achieves better than 1/20 of a resolution element RVs in moderate resolution spectra.Comment: 41 pages, 6 figures, Astronomical Journal, in press (submitted Nov. 24, 2003; tentatively scheduled for July 2004 issue

What is consumption, where has it been going, and does it still matter?

This article considers the relationships between consumption, the environment, and wider sociological endeavour. The current vogue for applying theories of practice to the policy domain of ‘sustainable consumption’ has been generative of conceptual renewal, however the field now sits closer to the applied environmental social sciences than to the sociology of consumption. The analysis proceeds via a close reading of the intellectual currents that have given rise to this situation, and it identifies a number of interrelated issues concerning conceptual slippage and the exclusion of core disciplinary concerns. Accordingly a more suitable definition of consumption is offered, an agenda for re-engaging with foundational approaches to consumer culture is established, and a renewal and reorientation of critique is proposed. Working through and building on the contributions of practice theoretical repertoires, this article suggests that consumption scholarship offers a distinctive set of resources to discussions of current ecological crises and uncertain social futures. These are briefly described and the conclusion argues that consumption still matters

The effect of S-substitution at the O6-guanine site on the structure and dynamics of a DNA oligomer containing a G:T mismatch

The effect of S-substitution on the O6 guanine site of a 13-mer DNA duplex containing a G:T mismatch is studied using molecular dynamics. The structure, dynamic evolution and hydration of the S-substituted duplex are compared with those of a normal duplex, a duplex with Ssubstitution on guanine, but no mismatch and a duplex with just a G:T mismatch. The S-substituted mismatch leads to cell death rather than repair. One suggestion is that the G:T mismatch recognition protein recognises the S-substituted mismatch (GS:T) as G:T. This leads to a cycle of futile repair ending in DNA breakage and cell death. We find that some structural features of the helix are similar for the duplex with the G:T mismatch and that with the S-substituted mismatch, but differ from the normal duplex, notably the helical twist. These differences arise from the change in the hydrogen-bonding pattern of the base pair. However a marked feature of the S-substituted G:T mismatch duplex is a very large opening. This showed considerable variability. It is suggested that this enlarged opening would lend support to an alternative model of cell death in which the mismatch protein attaches to thioguanine and activates downstream damage-response pathways. Attack on the sulphur by reactive oxygen species, also leading to cell death, would also be aided by the large, variable opening