80 research outputs found

    The metabolic regimes of 356 rivers in the United States

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    A national-scale quantification of metabolic energy flow in streams and rivers can improve understanding of the temporal dynamics of in-stream activity, links between energy cycling and ecosystem services, and the effects of human activities on aquatic metabolism. The two dominant terms in aquatic metabolism, gross primary production (GPP) and aerobic respiration (ER), have recently become practical to estimate for many sites due to improved modeling approaches and the availability of requisite model inputs in public datasets. We assembled inputs from the U.S. Geological Survey and National Aeronautics and Space Administration for October 2007 to January 2017. We then ran models to estimate daily GPP, ER, and the gas exchange rate coefficient for 356 streams and rivers across the continental United States. We also gathered potential explanatory variables and spatial information for cross-referencing this dataset with other datasets of watershed characteristics. This dataset offers a first national assessment of many-day time series of metabolic rates for up to 9 years per site, with a total of 490,907 site-days of estimates.We thank Jill Baron and the USGS Powell Center for financial support for this collaborative effort (Powell Center Working Group title: "Continental-scale overview of stream primary productivity, its links to water quality, and consequences for aquatic carbon biogeochemistry"). Additional financial support came from the USGS NAWQA program and Office of Water Information. NSF grants DEB-1146283 and EF1442501 partially supported ROH. A post-doctoral grant from the Basque Government partially supported MA. NAG was supported by the U.S. Department of Energy's Office of Science, Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. Leah Colasuonno provided expert logistical support of our working group meetings. The developers of USGS ScienceBase were very helpful both in hosting this dataset and in responding to our requests. Randy Hunt and Mike Fienen of the USGS Wisconsin Modeling Center graciously provided access to their HTCondor cluster. Mike Vlah provided detailed and insightful reviews of the data and metadata

    “Am I my genes?”: Questions of identity among individuals confronting genetic disease

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    Purpose: To explore many questions raised by genetics concerning personal identities that have not been fully investigated. Methods: We interviewed in depth, for 2 hours each, 64 individuals who had or were at risk for Huntington disease, breast cancer, or alpha-1 antitrypsin deficiency. Results: These individuals struggled with several difficult issues of identity. They drew on a range of genotypes and phenotypes (e.g., family history alone; mutations, but no symptoms; or symptoms). They often felt that their predicament did not fit preexisting categories well (e.g., “sick,” “healthy,” “disabled,” “predisposed”), due in part to uncertainties involved (e.g., unclear prognoses, since mutations may not produce symptoms). Hence, individuals varied in how much genetics affected their identity, in what ways, and how negatively. Factors emerged related to disease, family history, and other sources of identity. These identities may, in turn, shape disclosure, coping, and other health decisions. Conclusions: Individuals struggle to construct a genetic identity. They view genetic information in highly subjective ways, varying widely in what aspects of genetic information they focus on and how. These data have important implications for education of providers (to assist patients with these issues), patients, and family members; and for research, to understand these issues more fully

    “Charity Begins at Home”: Informal Caring Barriers to Formal Volunteering Among Older People

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    Formal volunteering is an important economic and social activity. In many countries, prevalence of volunteering is decreasing overall, including among older people who constitute a major volunteering resource. This qualitative study explored reasons for non-volunteering among seniors, with a focus on those who attribute their non-volunteering to their existing helping commitments. Forty-nine Australian interviewees aged 60 + years described a range of social, psychological, and temporal factors that resulted in their prioritization of informal rather than formal volunteering activities. These factors are mapped onto a theoretical framework matrix, with social identity and social capital theories appearing to possess the most explanatory power. The findings suggest that programs designed to encourage formal volunteering among older people need to be implemented in a manner that recognizes that members of this group can hold many other responsibilities that limit their ability to participate, especially those assisting in the care of multiple generations

    Composing The Reflected Best-Self Portrait: Building Pathways For Becoming Extraordinary In Work Organizations

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    Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

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    Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≄ II, EF ≀35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

    Leveraging Symmetric Multiprocessors and System Area Networks in Software Distributed Shared Memory

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    Clusters of workstations have long provided a cost-effective, large-scale parallel computing platform. A Software Distributed Shared Memory (SDSM) system simplifies programming on these platforms by presenting the illusion of shared memory. SDSM performance has historically been limited by the high cost of inter-processor communication overhead. Recent hardware trends, such as commodity symmetric multiprocessors (SMPs) and system area networks, can be used to potentially lower this overhead. The Cashmere SDSM has been designed for clusters of SMPs connected by a low-latency, remote-memory-access system area network. Cashmere introduces several novel techniques to leverage SMP hardware coherence and also to exploit remote-memory-access and other special features found in today's emerging system area networks. The results of our prototype implementation show that the Cashmere design leads to an average improvement of 25% over a comparable protocol version that does not leverage the SMP hardware coherence. The results also isolate the performance impact of various network features, thereby providing network designers with an informative application study. In addition, we have investigated the impact of these new hardware trends on the most fundamental aspect of SDSM design: the coherence granularity. Our findings show that recent hardware trends help reduce the performance gap between fine and coarse granularity SDSM. We also provide additional techniques for further reducing the gap

    CRAUL: Compiler and Run-Time Integration for Adaptation Under Load

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    Clusters of workstations provide a cost-effective, high performance parallel computing environment. These environments, however, are often shared by multiple users, or may consist of heterogeneous machines. As a result, parallel applications executing in these environments must operate despite unequal computational resources. For maximum performance, applications should automatically adapt execution to maximize use of the available resources. Ideally, this adaptation should be transparent to the application programmer. In this paper, we present CRAUL (Compiler and Run-Time Integration for Adaptation Under Load), a system that dynamically balances computational load in a parallel application. Our target run-time is software-based distributed shared memory (SDSM). SDSM is a good target for parallelizing compilers since it reduces compile-time complexity by providing data caching and other support for dynamic load balancing. CRAUL combines compile-time support to identify data access patterns with a run-time system that uses the access information to intelligently distribute the parallel workload in loop-based programs. The distribution is chosen according to the relative power of the processors and so as to minimize SDSM overhead and maximize locality. We have evaluated the resulting load distribution in the presence of different types of load --- computational, computational and memory intensive, and network load. CRAUL performs within 5---23% of ideal in the presence of load, and is able to improve on naive compiler-based work distribution that does not take locality into account even in the absence of load
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