395 research outputs found

    Many-Task Computing and Blue Waters

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    This report discusses many-task computing (MTC) generically and in the context of the proposed Blue Waters systems, which is planned to be the largest NSF-funded supercomputer when it begins production use in 2012. The aim of this report is to inform the BW project about MTC, including understanding aspects of MTC applications that can be used to characterize the domain and understanding the implications of these aspects to middleware and policies. Many MTC applications do not neatly fit the stereotypes of high-performance computing (HPC) or high-throughput computing (HTC) applications. Like HTC applications, by definition MTC applications are structured as graphs of discrete tasks, with explicit input and output dependencies forming the graph edges. However, MTC applications have significant features that distinguish them from typical HTC applications. In particular, different engineering constraints for hardware and software must be met in order to support these applications. HTC applications have traditionally run on platforms such as grids and clusters, through either workflow systems or parallel programming systems. MTC applications, in contrast, will often demand a short time to solution, may be communication intensive or data intensive, and may comprise very short tasks. Therefore, hardware and software for MTC must be engineered to support the additional communication and I/O and must minimize task dispatch overheads. The hardware of large-scale HPC systems, with its high degree of parallelism and support for intensive communication, is well suited for MTC applications. However, HPC systems often lack a dynamic resource-provisioning feature, are not ideal for task communication via the file system, and have an I/O system that is not optimized for MTC-style applications. Hence, additional software support is likely to be required to gain full benefit from the HPC hardware

    Association between physical activity and body fat percentage, with adjustment for BMI:a large cross-sectional analysis of UK Biobank

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    Objectives The objective of this study was to examine if, in the general population, physically active adults have less body fat after taking body mass index (BMI) into account. Design A cross-sectional analysis of participants recruited into UK Biobank in 2006–2010. Setting UK Biobank assessment centres throughout the UK. Participants 119 230 men and 140 578 women aged 40–69 years, with complete physical activity information, and without a self-reported long-term illness, disability or infirmity. Exposures Physical activity measured as excess metabolic equivalent (MET)-hours per week, estimated from a combination of walking, and moderate and vigorous physical activity. BMI from measured height and weight. Main outcome measure Body fat percentage estimated from bioimpedance. Results BMI and body fat percentage were highly correlated (r=0.85 in women; r=0.79 in men), and both were inversely associated with physical activity. Compared with <5 excess MET-hours/week at baseline, ≥100 excess MET-hours/week were associated with a 1.1 kg/m2 lower BMI (27.1 vs 28.2 kg/m2) and 2.8 percentage points lower body fat (23.4% vs 26.3%) in men, and 2.2 kg/m2 lower BMI (25.6 vs 27.7 kg/m2) and 4.0 percentage points lower body fat (33.9% vs 37.9%) in women. For a given BMI, greater physical activity was associated with lower average body fat percentage (for a BMI of 22.5–24.99 kg/m2: 2.0 (95% CI 1.8 to 2.2), percentage points lower body fat in men and 1.8 (95% CI 1.6 to 2.0) percentage points lower body fat in women, comparing ≥100 excess MET-hours per week with <5 excess MET-hours/week). Conclusions In this sample of middle-aged adults, drawn from the general population, physical activity was inversely associated with BMI and body fat percentage. For people with the same BMI, those who were more active had a lower body fat percentage

    Adherence of Individuals in Upper Extremity Rehabilitation: A Qualitative Study

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    OBJECTIVE: To describe the rehabilitation experiences, expectations, and treatment adherence of patients receiving upper extremity (UE) rehabilitation who demonstrated discrepancy between functional gains and overall improvement. DESIGN: Qualitative (phenomenologic) interviews and analysis. SETTING: Outpatient UE rehabilitation. PARTICIPANTS: Patients with acute UE injuries (N=10). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Concerns related to UE rehabilitation patients demonstrating discrepancy between outcome measures. RESULTS: Five key themes emerged from the interviews of patients demonstrating discrepancy in their self-reported patient outcomes: (1) desire to return to normal, (2) initial anticipation of brief recovery, (3) trust of therapist, (4) cannot stop living, and (5) feelings of ambivalence. Challenges included living with the desire to move back into life. Multiple factors affected patient adherence: cost of treatment, patient-provider relation (difference between therapist and patient understanding on what is important for treatment), and patients expecting the treating therapists to be an expert and fix their problem. CONCLUSIONS: Patient adherence to UE rehabilitation presents many challenges. Patients view themselves as laypersons and seek the knowledge of a dedicated therapist who they trust to spend time with them to understand what they value as important and clarify their injury, collaboratively make goals, and explain the intervention to get them in essence, back into life, in the minimal required time. When categorized according to the World Health Organization\u27s multidimensional adherence model, domains identified in this model include social and economic, health care team and system, condition-related, therapy-related, and patient-related dimensions. Assessing factors identified to improve efficiency and effectiveness of clinical management can enhance patient adherence

    The pH-responsive PacC transcription factor of Aspergillus fumigatus governs epithelial entry and tissue invasion during pulmonary aspergillosis

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    Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. Raw data have been deposited in the Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE54810. Funding: This work was supported in part by grants to EMB from the MRC (G0501164) and BBSRC (BB/G009619/1), to EMB and NDR from the Wellcome Trust (WT093596MA), to MB from Imperial College London (Division of Investigative Sciences PhD Studentship), to HH from the ERA-NET PathoGenoMics project TRANSPAT, Austrian Science Foundation (FWF I282-B09), to SGF from the National Institutes of Health, USA (R01AI073829). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD
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