Parasite-Drag Measurements of Five Helicopter Rotor Hubs

An investigation has been conducted in the Langley full-scale tunnel to determine the parasite drag of five production-type helicopter rotor hubs. Some simple fairing arrangements were attempted in an effort to reduce the hub drag. The results indicate that, within the range of the tests, changes in angle of attack, hub rotational speed, and forward speed generally had only a small effect on the equivalent flat-plate area representing parasite drag. The drag coefficients of the basic hubs, based on projected hub frontal area, increased with hub area and varied from 0.5 to 0.76 for the hubs tested

Piloted simulation study of two tilt-wing flap control concepts, phase 2

A two phase piloted simulation study has been conducted in the Ames Vertical Motion Simulator to investigate alternative wing and flap controls for tilt-wing aircraft. This report documents the flying qualities results and findings of the second phase of the piloted simulation study and describes the simulated tilt-wing aircraft, the flap control concepts, the experiment design and the evaluation tasks. The initial phase of the study compared the flying qualities of both a conventional programmed flap and an innovative geared flap. The second phase of the study introduced an alternate method of pilot control for the geared flap and further studied the flying qualities of the programmed flap and two geared flap configurations. In general, the pilot ratings showed little variation between the programmed flap and the geared flap control concepts. Some differences between the two control concepts were noticed and are discussed in this report. The geared flap configurations had very similar results. Although the geared flap concept has the potential to reduce or eliminate the pitch control power requirements from a tail rotor or a tail thruster at low speeds and in hover, the results did not show reduced tail thruster pitch control power usage with the geared flap configurations compared to the programmed flap configuration. The addition of pitch attitude stabilization in the second phase of simulation study greatly enhanced the aircraft flying qualities compared to the first phase

A General Bayesian Approach to Analyzing Diallel Crosses of Inbred Strains

The classic diallel takes a set of parents and produces offspring from all possible mating pairs. Phenotype values among the offspring can then be related back to their respective parentage. When the parents are diploid, sexed, and inbred, the diallel can characterize aggregate effects of genetic background on a phenotype, revealing effects of strain dosage, heterosis, parent of origin, epistasis, and sex-specific versions thereof. However, its analysis is traditionally intricate, unforgiving of unplanned missing information, and highly sensitive to imbalance, making the diallel unapproachable to many geneticists. Nonetheless, imbalanced and incomplete diallels arise frequently, albeit unintentionally, as by-products of larger-scale experiments that collect F1 data, for example, pilot studies or multiparent breeding efforts such as the Collaborative Cross or the Arabidopsis MAGIC lines. We present a general Bayesian model for analyzing diallel data on dioecious diploid inbred strains that cleanly decomposes the observed patterns of variation into biologically intuitive components, simultaneously models and accommodates outliers, and provides shrinkage estimates of effects that automatically incorporate uncertainty due to imbalance, missing data, and small sample size. We further present a model selection procedure for weighing evidence for or against the inclusion of those components in a predictive model. We evaluate our method through simulation and apply it to incomplete diallel data on the founders and F1's of the Collaborative Cross, robustly characterizing the genetic architecture of 48 phenotypes

Doxorubicin-Induced Cardiotoxicity in Collaborative Cross (CC) Mice Recapitulates Individual Cardiotoxicity in Humans.

Anthracyclines cause progressive cardiotoxicity whose ultimate severity is individual to the patient. Genetic determinants contributing to this variation are difficult to study using current mouse models. Our objective was to determine whether a spectrum of anthracycline induced cardiac disease can be elicited across 10 Collaborative Cross mouse strains given the same dose of doxorubicin. Mice from ten distinct strains were given 5 mg/kg of doxorubicin intravenously once weekly for 5 weeks (total 25 mg/kg). Mice were killed at acute or chronic timepoints. Body weight was assessed weekly, followed by terminal complete blood count, pathology and a panel of biomarkers. Linear models were fit to assess effects of treatment, sex, and sex-by-treatment interactions for each timepoint. Impaired growth and cardiac pathology occurred across all strains. Severity of these varied by strain and sex, with greater severity in males. Cardiac troponin I and myosin light chain 3 demonstrated strain- and sex-specific elevations in the acute phase with subsequent decline despite ongoing progression of cardiac disease. Acute phase cardiac troponin I levels predicted the ultimate severity of cardiac pathology poorly, whereas myosin light chain 3 levels predicted the extent of chronic cardiac injury in males. Strain- and sex-dependent renal toxicity was evident. Regenerative anemia manifested during the acute period. We confirm that variable susceptibility to doxorubicin-induced cardiotoxicity observed in humans can be modeled in a panel of CC strains. In addition, we identified a potential predictive biomarker in males. CC strains provide reproducible models to explore mechanisms contributing to individual susceptibility in humans

Valley-spin blockade and spin resonance in carbon nanotubes

Manipulation and readout of spin qubits in quantum dots made in III-V materials successfully rely on Pauli blockade that forbids transitions between spin-triplet and spin-singlet states. Quantum dots in group IV materials have the advantage of avoiding decoherence from the hyperfine interaction by purifying them with only zero-spin nuclei. Complications of group IV materials arise from the valley degeneracies in the electronic bandstructure. These lead to complicated multiplet states even for two-electron quantum dots thereby significantly weakening the selection rules for Pauli blockade. Only recently have spin qubits been realized in silicon devices where the valley degeneracy is lifted by strain and spatial confinement. In carbon nanotubes Pauli blockade can be observed by lifting valley degeneracy through disorder. In clean nanotubes, quantum dots have to be made ultra-small to obtain a large energy difference between the relevant multiplet states. Here we report on low-disorder nanotubes and demonstrate Pauli blockade based on both valley and spin selection rules. We exploit the bandgap of the nanotube to obtain a large level spacing and thereby a robust blockade. Single-electron spin resonance is detected using the blockade.Comment: 31 pages including supplementary informatio

The Genome of C57BL/6J Eve , the Mother of the Laboratory Mouse Genome Reference Strain.

Isogenic laboratory mouse strains enhance reproducibility because individual animals are genetically identical. For the most widely used isogenic strain, C57BL/6, there exists a wealth of genetic, phenotypic, and genomic data, including a high-quality reference genome (GRCm38.p6). Now 20 years after the first release of the mouse reference genome, C57BL/6J mice are at least 26 inbreeding generations removed from GRCm38 and the strain is now maintained with periodic reintroduction of cryorecovered mice derived from a single breeder pair, aptly named Adam and Eve. To provide an update to the mouse reference genome that more accurately represents the genome of today\u27s C57BL/6J mice, we took advantage of long read, short read, and optical mapping technologies to generate a de novo assembly of the C57BL/6J Eve genome (B6Eve). Using these data, we have addressed recurring variants observed in previous mouse genomic studies. We have also identified structural variations, closed gaps in the mouse reference assembly, and revealed previously unannotated coding sequences. This B6Eve assembly explains discrepant observations that have been associated with GRCm38-based analyses, and will inform a reference genome that is more representative of the C57BL/6J mice that are in use today

Enjoyment of the shopping experience:impact on customers’ repatronage intentions and gender influence

In this paper the authors investigate enjoyment of the shopping experience, its influence on consumers’ intention to repatronise a regional shopping centre and the effect of gender differences on shopping enjoyment. Four dimensions of shopping enjoyment are proposed and a 16-item measure is developed to assess 536 consumer perceptions of the shopping experience across five counties in the United Kingdom. Findings indicate that shopping experience enjoyment has a significant positive influence upon customers’ repatronage intentions. Furthermore, men are found to have a stronger relationship of enjoyment with repatronage than women. The implications of these results are discussed, together with managerial implications, study limitations, and future research directions

What Can Causal Networks Tell Us about Metabolic Pathways?

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies

Stochastic variation of transcript abundance in C57BL/6J mice

<p>Abstract</p> <p>Background</p> <p>Transcripts can exhibit significant variation in tissue samples from inbred laboratory mice. We have designed and carried out a microarray experiment to examine transcript variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice and to partition variation into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript abundance between genetically identical mice.</p> <p>Results</p> <p>The nature and extent of transcript variation differs across tissues. Adipose has the largest total variance and the largest within-mouse variance. Liver has the smallest total variance, but it has the most between-mouse variance. Genes with high variability can be classified into groups with correlated patterns of expression that are enriched for specific biological functions. Variation between mice is associated with circadian rhythm, growth hormone signaling, immune response, androgen regulation, lipid metabolism, and the extracellular matrix. Genes showing correlated patterns of within-mouse variation are also associated with biological functions that largely reflect heterogeneity of cell types within tissues.</p> <p>Conclusions</p> <p>Genetically identical mice can experience different individual outcomes for medically important traits. Variation in gene expression observed between genetically identical mice can identify functional classes of genes that are likely to vary in the absence of experimental perturbations, can inform experimental design decisions, and provides a baseline for the interpretation of gene expression data in interventional studies. The extent of transcript variation among genetically identical mice underscores the importance of stochastic and micro-environmental factors and their phenotypic consequences.</p