Reduction of Noise from a Fan Stage for a Turbofan Engine by Use of Long-Chord Acoustically-Treated Stator Vanes

A set of acoustically-treated long-chord vanes was designed to replace the vanes in an existing fan stage to investigate the noise reduction possibilities of both increased stator chord length and a method of incorporating acoustic damping material. The vanes were tested with both active and inactive acoustic surfaces. Results of the inactive tests show significant broadband noise effects with noise reductions in the middle to high frequencies and an increase at low frequencies. No reduction in blade passage tone was observed, but decreases in the overtones were observed. Results of the tests with the active acoustic treatment show large noise reductions over a wide frequency range

Photoionization cross sections of O II, O III, O IV, and O V: benchmarking R-matrix theory and experiments

For crucial tests between theory and experiment, ab initio close coupling calculations are carried out for photoionization of O II, O III, O IV, O V. The relativistic fine structure and resonance effects are studied using the R-matrix and its relativistic variant the Breit Pauli R-matrix (BPRM) approximation. Detailed comparison is made with high resolution experimental measurements carried out in three different set-ups: Advanced Light Source at Berkeley, and synchrotron radiation experiments at University of Aarhus and University of Paris-Sud. The comparisons illustrate physical effects in photoionization such as (i) fine structure, (ii) resolution, and (iii) metastable components. Photoionization cross sections sigma{PI} of the ground and a few low lying excited states of these ions obtained in the experimental spectrum include combined features of these states. Theoretically calculated resonances need to be resolved with extremely fine energy mesh for precise comparison. In addition, prominent resonant features are observed in the measured spectra from transitions allowed with relativistic fine structure, but not in LS coupling. The sigma_{PI} are obtained for ground and metastable (i) 2s^22p^3(^4S^o, ^2D^o, ^2P^o) states of O II, (ii) 2s^22p^2(^3P,^1D,^1S) and 2s2p^3(^5S^o) states of O III, (iii) 2s^22p(^2P^o_J) and 2s2p^2(^4P_J) levels of O IV, and (iv) 2s^2(^1S) and 2s2p(^3P^o,^1P^o) states of O V. It is found that resonances in ground and metastable cross sections can be a diagnostic of experimental beam composition, with potential ap plications to astrophysical and laboratory plasma environments.Comment: 27 pages, 7 figs., submitted to Phys. Rev. A., text with high resolution figures at http://www.astronomy.ohio-state.edu/~pradhan/Oions.p

Barriers Inhibiting Industry from Partnering with Universities: Evidence from the Advanced Technology Program

A small sample of 38 Advanced Technology Projects funded between 1993 and 1996 are surveyed to explore the reasons for university non-participation, or, in the cases where they did participate, whether the partnerships encountered any difficulties from their participation. 32 percent report that intellectual property issues were an insurmountable barrier to university participation. Such barriers are more likely when the ATP share of funding is high and when the expected duration of the research is relatively short. They are also somewhat more likely for projects involving chemical technology, and when industrial participants have had previous experience with universities as research partners. These difficulties over IP may arise because the cultures in the two institutional forms differ, or because the original ATP guidelines do not recognize the existence of the Bayh-Dole Act (which grants universities title to inventions made by their employees using outside funding).

Universities as Research Partners

Universities are a key institution in the US innovation system and an important aspect of their involvement is the role they play in Private-Public Partnering activities. This study seeks to gain a better understanding of the performance of university-industry research partnerships using a sample survey of pre-commercial research projects funded the U.S. government's Advanced Technology Program. Although results must be interpreted cautiously due to the small size of the sample, the study finds that projects with university involvement tend to be in areas involving "new" science and therefore experience more difficulty and delay but also are more likely not to be aborted prematurely. We interpret this finding to imply that universities are contributing to basic research awareness and insight among the partners in ATP-funded projects.

Diffusion Approximations for Demographic Inference: DaDi

Models of demographic history (population sizes, migration rates, and divergence times) inferred from genetic data complement archeology and serve as null models in genome scans for selection. Most current inference methods are computationally limited to considering simple models or non-recombining data. We introduce a method based on a diffusion approximation to the joint frequency spectrum of genetic variation between populations. Our implementation, DaDi, can model up to three interacting populations and scales well to genome-wide data. We have applied DaDi to human data from Africa, Europe, and East Asia, building the most complex statistically well-characterized model of human migration out of Africa to date

Prediction of the functional properties of ceramic materials from composition using artificial neural networks

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the basis of their dielectric and ionic properties. Dielectric materials are of interest in telecommunication applications where they are used in tuning and filtering equipment. Ionic and mixed conductors are the subjects of a concerted effort in the search for new materials that can be incorporated into efficient, clean electrochemical devices of interest in energy production and greenhouse gas reduction applications. Multi-layer perceptron ANNs are trained using the back-propagation algorithm and utilise data obtained from the literature to learn composition-property relationships between the inputs and outputs of the system. The trained networks use compositional information to predict the relative permittivity and oxygen diffusion properties of ceramic materials. The results show that ANNs are able to produce accurate predictions of the properties of these ceramic materials which can be used to develop materials suitable for use in telecommunication and energy production applications

Classification of n-qubit states with minimum orbit dimension

The group of local unitary transformations acts on the space of n-qubit pure states, decomposing it into orbits. In a previous paper we proved that a product of singlet states (together with an unentangled qubit for a system with an odd number of qubits) achieves the smallest possible orbit dimension, equal to 3n/2 for n even and (3n + 1)/2 for n odd, where n is the number of qubits. In this paper we show that any state with minimum orbit dimension must be of this form, and furthermore, such states are classified up to local unitary equivalence by the sets of pairs of qubits entangled in singlets.Comment: 15 pages, latex, revision 2, conclusion added, some proofs shortene

Wheat Forward Contract Pricing: Evidence on Forecast Power and Risk Premia

While the risk premium hypothesis in futures markets has been the subject of a long and continuous controversy, the risk premium hypothesis in forward markets is also of interest among economists. The hypothesis is supported by some theoretical arguments and empirical evidence yet remains an open question. We in this study apply a two-equation regression model similar to those used in (Fama and French (1987} and de Roon et al. (1998) to analyze the risk premiums in forward markets, particularly, using the pre-harvest wheat forward markets in Illinois (1982-2004) and Kansas (1990-2004) as an example. The two-equation regression model consists of a forecasting equation, which uses a forward basis during a pre-harvest period to forecast the spot basis at the following harvest period, and a risk premium equation, which uses the forward basis to predict the risk premium to be realized at the harvest. The empirical results show that, first, the average realized risk premiums for Illinois fluctuate around a level during the entirety of a pre-harvest period, while the risk premiums for Kansas show a slight downward trend as time approaches the harvest. The average realized risk premiums are generally positive and bigger for Illinois than for Kansas, but all mean risk premiums are within one units of their corresponding standard deviations. Second, the pre-harvest forward bases have reliable forecasting power for the spot harvest bases and contain information regarding the risk premiums, which strongly recommend estimating risk premiums conditional on forward bases.Marketing,