226 research outputs found
Update statistics in conservative parallel discrete event simulations of asynchronous systems
We model the performance of an ideal closed chain of L processing elements
that work in parallel in an asynchronous manner. Their state updates follow a
generic conservative algorithm. The conservative update rule determines the
growth of a virtual time surface. The physics of this growth is reflected in
the utilization (the fraction of working processors) and in the interface
width. We show that it is possible to nake an explicit connection between the
utilization and the macroscopic structure of the virtual time interface. We
exploit this connection to derive the theoretical probability distribution of
updates in the system within an approximate model. It follows that the
theoretical lower bound for the computational speed-up is s=(L+1)/4 for L>3.
Our approach uses simple statistics to count distinct surface configuration
classes consistent with the model growth rule. It enables one to compute
analytically microscopic properties of an interface, which are unavailable by
continuum methods.Comment: 15 pages, 12 figure
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Energetic particle influence on the Earth's atmosphere
This manuscript gives an up-to-date and comprehensive overview of the effects of energetic particle precipitation (EPP) onto the whole atmosphere, from the lower thermosphere/mesosphere through the stratosphere and troposphere, to the surface. The paper summarizes the different sources and energies of particles, principally
galactic cosmic rays (GCRs), solar energetic particles (SEPs) and energetic electron precipitation (EEP). All the proposed mechanisms by which EPP can affect the atmosphere
are discussed, including chemical changes in the upper atmosphere and lower thermosphere, chemistry-dynamics feedbacks, the global electric circuit and cloud formation. The role of energetic particles in Earth’s atmosphere is a multi-disciplinary problem that requires expertise from a range of scientific backgrounds. To assist with this synergy, summary tables are provided, which are intended to evaluate the level of current knowledge of the effects of energetic particles on processes in the entire atmosphere
Stroke Incidence and Survival in American Indians, Blacks, and Whites: The Strong Heart Study and Atherosclerosis Risk in Communities Study
Background: American Indians (AIs) have high stroke morbidity and mortality. We compared stroke incidence and mortality in AIs, blacks, and whites. Methods and Results: Pooled data from 2 cardiovascular disease cohort studies included 3182 AIs from the SHS (Strong Heart Study), aged 45 to 74 years at baseline (1988–1990) and 3765 blacks and 10 413 whites from the ARIC (Atherosclerosis Risk in Communities) Study, aged 45 to 64 years at baseline (1987–1989). Stroke surveillance was based on self-report, hospital records, and death certificates. We estimated hazard ratios for incident stroke (ischemic and hemorrhagic combined) through 2008, stratified by sex and birth-year tertile, and relative risk for poststroke mortality. Incident strokes numbered 282 for AIs, 416 for blacks, and 613 for whites. For women and men, stroke incidence among AIs was similar to or lower than blacks and higher than whites. Covariate adjustment resulted in lower hazard ratios for most comparisons, but results for these models were not always statistically significant. After covariate adjustment, AI women and men had higher 30-day poststroke mortality than blacks (relative risk=2.1 [95% CI=1.0, 3.2] and 2.2 [95% CI=1.3, 3.1], respectively), and whites (relative risk=1.6 [95% CI=0.8, 2.5] and 1.7 [95% CI=1.1, 2.4]), and higher 1-year mortality (relative risk range=1.3–1.5 for all comparisons). Conclusions: Stroke incidence in AIs was lower than for blacks and higher than for whites; differences were larger for blacks and smaller for whites after covariate adjustment. Poststroke mortality was higher in AIs than blacks and whites
Patient-reported outcomes in CodeBreaK 200 : Sotorasib versus docetaxel for previously treated advanced NSCLC with KRAS G12C mutation
In the CodeBreaK 200 phase III, open-label trial, sotorasib significantly improved efficacy versus docetaxel in previously treated KRAS G12C-mutated advanced non-small cell lung cancer (NSCLC). Patient-reported outcomes (PROs) for global health status, physical functioning, dyspnea, and cough favored sotorasib over docetaxel. Here, we report sotorasib's additional impact on quality of life (QOL). In CodeBreaK 200, 345 patients who had progressed after prior therapy received sotorasib (960 mg orally daily) or docetaxel (75 mg/m intravenously every 3 weeks). Validated questionnaires captured patients' perception of their QOL and symptom burden for key secondary and exploratory PRO endpoints, including the European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30) and Quality-of-life Questionnaire Lung Cancer 13 (EORTC QLQ-LC13), question GP5 from the Functional Assessment of Cancer Therapy Tool General Form (FACT-G GP5), PRO-Common Terminology Criteria for Adverse Events (PRO-CTCAE), and 5-level EuroQOL-5 dimensions (EQ-5D-5L) including visual analog scale (EQ-5D VAS). Change from baseline to week 12 was assessed with generalized estimating equations for ordinal outcomes. Patients receiving sotorasib were less bothered by treatment side effects than those receiving docetaxel (odds ratio [OR] 5.7) and experienced symptoms at lower severity (pain: OR 2.9; aching muscles: OR 4.4; aching joints: OR 4.2; mouth or throat sores: OR 4.3). Further, patients' symptoms interfered less with usual/daily activities (pain: OR 3.2; aching muscles: OR 3.9; aching joints: OR 10.7). QOL remained stable with sotorasib but worsened with docetaxel (change from baseline in EQ-5D VAS score: 1.5 vs -8.4 at cycle 1 day 5 and 2.2 vs -5.8 at week 12). Patients receiving sotorasib reported less severe symptoms than those receiving docetaxel. In addition to improving clinical efficacy outcomes, sotorasib maintained QOL versus docetaxel, suggesting sotorasib may be a more tolerable treatment option for patients with pretreated, KRAS G12C-mutated advanced NSCLC
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts
In vivo and in vitro protein digestibility of formulated feeds for Artemesia longinaris (Crustacea, Penaeidae)
Quantum dots coordinated with conjugated organic ligands: new nanomaterials with novel photophysics
CdSe quantum dots functionalized with oligo-(phenylene vinylene) (OPV) ligands (CdSe-OPV nanostructures) represent a new class of composite nanomaterials with significantly modified photophysics relative to bulk blends or isolated components. Single-molecule spectroscopy on these species have revealed novel photophysics such as enhanced energy transfer, spectral stability, and strongly modified excited state lifetimes and blinking statistics. Here, we review the role of ligands in quantum dot applications and summarize some of our recent efforts probing energy and charge transfer in hybrid CdSe-OPV composite nanostructures
EuFeAs under high pressure: an antiferromagnetic bulk superconductor
We report the ac magnetic susceptibility and resistivity
measurements of EuFeAs under high pressure . By observing nearly
100% superconducting shielding and zero resistivity at = 28 kbar, we
establish that -induced superconductivity occurs at ~30 K in
EuFeAs. shows an anomalous nearly linear temperature dependence
from room temperature down to at the same . indicates that
an antiferromagnetic order of Eu moments with ~20 K persists
in the superconducting phase. The temperature dependence of the upper critical
field is also determined.Comment: To appear in J. Phys. Soc. Jpn., Vol. 78 No.
The evolution of lung cancer and impact of subclonal selection in TRACERx
Lung cancer is the leading cause of cancer-associated mortality worldwide. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource
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