5,199 research outputs found
Supersonic wings with significant leading-edge thrust at cruise
Experimental/theoretical correlations are presented which show that significant levels of leading edge thrust are possible at supersonic speeds for certain planforms which match the theoretical thrust distribution potential with the supporting airfoil geometry. The analytical process employed spanwise distribution of both it and/or that component of full theoretical thrust which acts as vortex lift. Significantly improved aerodynamic performance in the moderate supersonic speed regime is indicated
Estimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models
In this paper we review an approach to estimating the causal effect of a
time-varying treatment on time to some event of interest. This approach is
designed for the situation where the treatment may have been repeatedly adapted
to patient characteristics, which themselves may also be time-dependent. In
this situation the effect of the treatment cannot simply be estimated by
conditioning on the patient characteristics, as these may themselves be
indicators of the treatment effect. This so-called time-dependent confounding
is typical in observational studies. We discuss a new class of failure time
models, structural nested failure time models, which can be used to estimate
the causal effect of a time-varying treatment, and present methods for
estimating and testing the parameters of these models
Psychoneuroimmunology-Based Stress Management during Adjuvant Chemotherapy for Early Breast Cancer
Objective. In a randomized trial of women with early stage breast cancer undergoing adjuvant chemotherapy, two stress management interventions, tai chi training and spiritual growth groups, were compared to a usual care control group, to evaluate psychosocial functioning, quality of life (QOL), and biological markers thought to reflect cancer- and treatment-specific mechanisms. Method. The sample consisted of 145 women aged 27–75 years; 75% were Caucasian and 25% African American. A total of 109 participants completed the study, yielding a 75% retention rate. Grounded in a psychoneuroimmunology framework, the overarching hypothesis was that both interventions would reduce perceived stress, enhance QOL and psychosocial functioning, normalize levels of stress-related neuroendocrine mediators, and attenuate immunosuppression. Results. While interesting patterns were seen across the sample and over time, the interventions had no appreciable effects when delivered during the period of chemotherapy. Conclusions. Findings highlight the complex nature of biobehavioral interventions in relation to treatment trajectories and potential outcomes. Psychosocial interventions like these may lack sufficient power to overcome the psychosocial or physiological stress experienced during the chemotherapy treatment period. It may be that interventions requiring less activity and/or group attendance would have enhanced therapeutic effects, and more active interventions need to be tested prior to and following recovery from chemotherapy
Semiparametric theory and empirical processes in causal inference
In this paper we review important aspects of semiparametric theory and
empirical processes that arise in causal inference problems. We begin with a
brief introduction to the general problem of causal inference, and go on to
discuss estimation and inference for causal effects under semiparametric
models, which allow parts of the data-generating process to be unrestricted if
they are not of particular interest (i.e., nuisance functions). These models
are very useful in causal problems because the outcome process is often complex
and difficult to model, and there may only be information available about the
treatment process (at best). Semiparametric theory gives a framework for
benchmarking efficiency and constructing estimators in such settings. In the
second part of the paper we discuss empirical process theory, which provides
powerful tools for understanding the asymptotic behavior of semiparametric
estimators that depend on flexible nonparametric estimators of nuisance
functions. These tools are crucial for incorporating machine learning and other
modern methods into causal inference analyses. We conclude by examining related
extensions and future directions for work in semiparametric causal inference
Noisy Monte Carlo: Convergence of Markov chains with approximate transition kernels
Monte Carlo algorithms often aim to draw from a distribution by
simulating a Markov chain with transition kernel such that is
invariant under . However, there are many situations for which it is
impractical or impossible to draw from the transition kernel . For instance,
this is the case with massive datasets, where is it prohibitively expensive to
calculate the likelihood and is also the case for intractable likelihood models
arising from, for example, Gibbs random fields, such as those found in spatial
statistics and network analysis. A natural approach in these cases is to
replace by an approximation . Using theory from the stability of
Markov chains we explore a variety of situations where it is possible to
quantify how 'close' the chain given by the transition kernel is to
the chain given by . We apply these results to several examples from spatial
statistics and network analysis.Comment: This version: results extended to non-uniformly ergodic Markov chain
Genome-Wide Association with Select Biomarker Traits in the Framingham Heart Study
BACKGROUND: Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. METHODS: We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001. RESULTS: With GEE, 58 SNPs had p < 10-6: the top SNPs were rs2494250 (p = 1.00*10-14) and rs4128725 (p = 3.68*10-12) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10-8) and rs2808629 (p = 3.19*10-8) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10-6: the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10-8, and rs2494250, p = 3.55*10-8), and also included B-type natriuretic peptide (rs437021, p = 1.01*10-6) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10-6). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at . CONCLUSION: The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC25195); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1); National Institutes of Health (HL064753, HL076784, AG028321, HL71039, 2 K24HL04334, 1K23 HL083102); Doris Duke Charitable Foundation; American Diabetes Association Career Developement Award; National Center for Research Resources (GCRC M01-RR01066); US Department of Agriculture Agricultural Research Service (58-1950-001, 58-1950-401); National Institute of Aging (AG14759
Superradiant scattering from a hydrodynamic vortex
We show that sound waves scattered from a hydrodynamic vortex may be
amplified. Such superradiant scattering follows from the physical analogy
between spinning black holes and hydrodynamic vortices. However a sonic horizon
analogous to the black hole event horizon does not exist unless the vortex
possesses a central drain, which is challenging to produce experimentally. In
the astrophysical domain, superradiance can occur even in the absence of an
event horizon: we show that in the hydrodynamic analogue, a drain is not
required and a vortex scatters sound superradiantly. Possible experimental
realization in dilute gas Bose-Einstein condensates is discussed.Comment: 10 pages, 1 figur
Universal Rights and Wrongs
This paper argues for the important role of customers as a source of competitive advantage and firm growth, an issue which has been largely neglected in the resource-based view of the firm. It conceptualizes Penrose’s (1959) notion of an ‘inside track’ and illustrates how in-depth knowledge about established customers combines with joint problem-solving activities and the rapid assimilation of new and previously unexploited skills and resources. It is suggested that the inside track represents a distinct and perhaps underestimated way of generating rents and securing long-term growth. This also implies that the sources of sustainable competitive advantage in important respects can be sought in idiosyncratic interfirm relationships rather than within the firm itself
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