63 research outputs found

    Propfan test assessment propfan propulsion system static test report

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    The propfan test assessment (PTA) propulsion system successfully completed over 50 hours of extensive static ground tests, including a 36 hour endurance test. All major systems performed as expected, verifying that the large-scale 2.74 m diameter propfan, engine, gearbox, controls, subsystems, and flight instrumentation will be satisfactory with minor modifications for the upcoming PTA flight tests on the GII aircraft in early 1987. A test envelope was established for static ground operation to maintain propfan blade stresses within limits for propfan rotational speeds up to 105 percent and power levels up to 3880 kW. Transient tests verified stable, predictable response of engine power and propfan speed controls. Installed engine TSFC was better than expected, probably due to the excellent inlet performance coupled with the supercharging effect of the propfan. Near- and far-field noise spectra contained three dominant components, which were dependent on power, tip speed, and direction. The components were propfan blade tones, propfan random noise, and compressor/propfan interaction noise. No significant turbine noise or combustion noise was evident

    Exploratory Investigation of Forebody Strakes for Yaw Control of a Generic Fighter with a Symmetric 60 deg Half-Angle Chine Forebody

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    Forebody strakes were tested in a low-speed wind tunnel to determine their effectiveness producing yaw control on a generic fighter model with a symmetric 60 deg half-angle chine forebody. Previous studies conducted using smooth, conventionally shaped forebodies show that forebody strakes provide increased levels of yaw control at angles of attack where conventional rudders are ineffective. The chine forebody shape was chosen for this study because chine forebodies can be designed with lower radar cross section (RCS) values than smooth forebody shapes. Because the chine edges of the forebody would fix the point of flow separation, it was unknown if any effectiveness achieved could be modulated as was successfully done on the smooth forebody shapes. The results show that use of forebody strakes on a chine forebody produce high levels of yaw control, and when combined with the rudder effectiveness, significant yaw control is available for a large range of angles of attack. The strake effectiveness was very dependent on radial location. Very small strakes placed at the tip of the forebody were nearly as effective as very long strakes. An axial translation scheme provided almost linear increments of control effectiveness

    Determinants of antibody persistence across doses and continents after single-dose rVSV-ZEBOV vaccination for Ebola virus disease: an observational cohort study.

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    BACKGROUND: The recombinant vesicular stomatitis virus (rVSV) vaccine expressing the Zaire Ebola virus (ZEBOV) glycoprotein is efficacious in the weeks following single-dose injection, but duration of immunity is unknown. We aimed to assess antibody persistence at 1 and 2 years in volunteers who received single-dose rVSV-ZEBOV in three previous trials. METHODS: In this observational cohort study, we prospectively followed-up participants from the African and European phase 1 rVSV-ZEBOV trials, who were vaccinated once in 2014-15 with 300 000 (low dose) or 10-50 million (high dose) plaque-forming units (pfu) of rVSV-ZEBOV vaccine to assess ZEBOV glycoprotein (IgG) antibody persistence. The primary outcome was ZEBOV glycoprotein-specific IgG geometric mean concentrations (GMCs) measured yearly by ELISA compared with 1 month (ie, 28 days) after immunisation. We report GMCs up to 2 years (Geneva, Switzerland, including neutralising antibodies up to 6 months) and 1 year (Lambaréné, Gabon; Kilifi, Kenya) after vaccination and factors associated with higher antibody persistence beyond 6 months, according to multivariable analyses. Trials and the observational study were registered at ClinicalTrials.gov (Geneva: NCT02287480 and NCT02933931; Kilifi: NCT02296983) and the Pan-African Clinical Trials Registry (Lambaréné PACTR201411000919191). FINDINGS: Of 217 vaccinees from the original studies (102 from the Geneva study, 75 from the Lambaréné study, and 40 from the Kilifi study), 197 returned and provided samples at 1 year (95 from the Geneva study, 63 from the Lambaréné, and 39 from the Kilifi study) and 90 at 2 years (all from the Geneva study). In the Geneva group, 44 (100%) of 44 participants who had been given a high dose (ie, 10-50 million pfu) of vaccine and who were seropositive at day 28 remained seropositive at 2 years, whereas 33 (89%) of 37 who had been given the low dose (ie, 300 000 pfu) remained seropositive for 2 years (p=0·042). In participants who had received a high dose, ZEBOV glycoprotein IgG GMCs decreased significantly between their peak (at 1-3 months) and month 6 after vaccination in Geneva (p0·05). Neutralising antibodies seem to be less durable, with seropositivity dropping from 64-71% at 28 days to 27-31% at 6 months in participants from the Geneva study. INTERPRETATION: Antibody responses to single-dose rVSV-ZEBOV vaccination are sustained across dose ranges and settings, a key criterion in countries where booster vaccinations would be impractical. FUNDING: The Wellcome Trust and Innovative Medicines Initiative 2 Joint Undertaking

    Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain

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    his paper proposes a compromise programming (CP) model to help investors decide whether to construct photovoltaic power plants with government financial support. For this purpose, we simulate an agreement between the government, who pursues political prices (guaranteed prices) as low as possible, and the project sponsor who wants returns (stochastic cash flows) as high as possible. The sponsor s decision depends on the positive or negative result of this simulation, the resulting simulated price being compared to the effective guaranteed price established by the country legislation for photovoltaic energy. To undertake the simulation, the CP model articulates variables such as ranges of guaranteed prices, tech- nical characteristics of the plant, expected energy to be generated over the investment life, investment cost, cash flow probabilities, and others. To determine the CP metric, risk aver- sion is assumed. As an actual application, a case study on photovoltaic power investment in Extremadura, western Spain, is developed in detail.Garcia-Bernabeu, A.; Benito Benito, A.; Bravo Selles, M.; Pla Santamaría, D. (2015). Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain. Annals of Operations Research. 1-12. doi:10.1007/s10479-015-1836-2S112Andrews, R. W., Pollard, A., & Pearce, J. M. (2012). Improved parametric empirical determination of module short circuit current for modelling and optimization of solar photovoltaic systems. Solar Energy, 86(9), 2240–2254.Anwar, Y., & Mulyadi, M. S. (2011). Income tax incentives on renewable energy industry: Case of geothermal industry in USA and Indonesia. African Journal of Business Management, 5(31), 12264–12270.Aouni, B., & Kettani, O. (2001). Goal programming model: A glorious history and a promising future. European Journal of Operational Research, 133(2), 225–231.Ballestero, E. (1997). Selecting the CP metric: A risk aversion approach. European Journal of Operational Research, 97(3), 593–596.Ballestero, E. (2000). Project finance: A multicriteria approach to arbitration. Journal of Operational Research Society, 51, 183–197.Ballestero, E. (2007). Compromise programming: A utility-based linear-quadratic composite metric from the trade-off between achievement and balanced (non-corner) solutions. European Journal of Operational Research, 182(3), 1369–1382.Ballestero, E., Pérez-Gladish, B., Arenas-Parra, M., & BilbaoTerol, A. (2009). Selecting portfolios given multiple Eurostoxx-based uncertainty scenarios: A stochastic goal programming approach from fuzzy betas. INFOR: Information Systems and Operational Research, 47(1), 59–70.Ballestero, E., & Plà-Santamaría, D. (2003). Portfolio selection on the Madrid exchange: A compromise programming model. International Transactions in Operational Research, 10(1), 33–51.Ballestero, E., & Pla-Santamaria, D. (2004). Selecting portfolios for mutual funds. Omega, 32(5), 385–394.Ballestero, E., & Pla-Santamaria, D. (2005). Grading the performance of market indicators with utility benchmarks selected from Footsie: A 2000 case study. Applied Economics, 37(18), 2147–2160.Ballestero, E., & Romero, C. (1996). Portfolio selection: A compromise programming solution. Journal of the Operational Research Society, 47, 1377–1386.Bastian-Pinto, C., Brandão, L., & de Lemos Alves, M. (2010). Valuing the switching flexibility of the ethanol–gas flex fuel car. Annals of Operations Research, 176(1), 333–348.Branker, K., Pathak, M., & Pearce, J. M. (2011). A review of solar photovoltaic levelized cost of electricity. Renewable and Sustainable Energy Reviews, 15(9), 4470–4482.Casares, F., Lopez-Luque, R., Posadillo, R., & Varo-Martinez, M. (2014). Mathematical approach to the characterization of daily energy balance in autonomous photovoltaic solar systems. Energy, 72, 393–404.Chatterji, A. K., Levine, D. I., & Toffel, M. W. (2009). How well do social ratings actually measure corporate social responsibility? Journal of Economics & Management Strategy, 18(1), 125–169.Copeland, T. E., & Weston, J. (1988). Financial theory and corporate policy. Reading, Massachusetts: Addison-Wesley.Gallagher, K. S. (2013). Why & how governments support renewable energy. Daedalus, 142(1), 59–77.García-Cascales, M. S., Lamata, M. T., & Sánchez-Lozano, J. M. (2012). Evaluation of photovoltaic cells in a multi-criteria decision making process. Annals of Operations Research, 199(1), 373–391.Gupta, S. (2012). Financing renewable energy. In F. L. Toth (Ed.), Energy for development (pp. 171–186). Springer.Karaarslan, A. (2012). Obtaining renewable energy from piezoelectric ceramics using Sheppard–Taylor converter. International Review of Electrical Engineering, 7(2), 3949–3956.Koellner, T., Weber, O., Fenchel, M., & Scholz, R. (2005). Principles for sustainability rating of investment funds. Business Strategy and the Environment, 14(1), 54–70.Lorenzo, E., & Navarte, L. (2000). On the usefulness of stand-alone PV sizing methods. Progress in Photovoltaics: Research and Applications, 8(4), 391–409.Lüdeke-Freund, F., & Loock, M. (2011). Debt for brands: Tracking down a bias in financing photovoltaic projects in Germany. Journal of Cleaner Production, 19(12), 1356–1364.Mavrotas, G., Diakoulaki, D., & Capros, P. (2003). Combined MCDA-IP approach for project selection in the electricity market. Annals of Operations Research, 120(1–4), 159–170.Mendez-Rodriguez, P., Garcia Bernabeu, A., Hilario, A., & Perez-Gladish, B. (2013). Some effects on the efficient frontier of the investment strategy: A preliminary approach. Recta, 14, 131–144.Michelson, G., Wailes, N., Van Der Laan, S., & Frost, G. (2004). Ethical investment processes and outcomes. Journal of Business Ethics, 52(1), 1–10.Mills, S. J. (1994). Project finance for renewable energy. Renewable energy, 5(1–4), 700–708.ORourke, A. (2003). The message and methods of ethical investment. Journal of Cleaner Production, 11(6), 683–693.Pla-Santamaria, D., & Bravo, M. (2013). Portfolio optimization based on downside risk: A mean-semivariance efficient frontier from Dow Jones blue chips. Annals of Operations Research, 205(1), 189–201.Richter, N. (2009). Renewable project finance options: ITC, PTC, or cash grant? Power, 153(5), 90–92.Schrader, U. (2006). Ignorant advice-customer advisory service for ethical investment funds. Business Strategy and the Environment, 15(3), 200–214.Sitarz, S. (2013). Compromise programming with tehebycheff norm for discrete stochastic orders. Annals of Operations Research, 211(1), 433–446.van de Kaa, G., Rezaei, J., Kamp, L., & de Winter, A. (2014). Photovoltaic technology selection: A fuzzy MCDM approach. Renewable and Sustainable Energy Reviews, 32, 662–670.Yaqub, M., Shahram Sarkni, P., & Mazzuchi, T. (2012). Feasibility analysis of solar photovoltaic commercial power generation in California. Engineering Management Journal, 24(4), 36–49.Yazdani-Chamzini, A., Fouladgar, M. M., Zavadskas, E. K., & Moini, S. H. H. (2013). Selecting the optimal renewable energy using multi criteria decision making. Journal of Business Economics and Management, 14(5), 957–978.Yu, P. (1985). Multiple criteria decision making: Concepts, techniques and extensions. New York: Springer.Zeleny, M. (1982). Multiple criteria decision making (Vol. 25). New York: McGraw-Hill.Zhao, R., Shi, G., Chen, H., Ren, A., & Finlow, D. (2011). Present status and prospects of photovoltaic market in China. Energy Policy, 39(4), 2204–2207

    How clonal are bacteria?

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    Data from multilocus enzyme electrophoresis of bacterial populations were analyzed using a statistical test designed to detect associations between genes at different loci. Some species (e.g., Salmonella) were found to be clonal at all levels of analysis. At the other extreme, Neisseria gonorrhoeae is panmictic, with random association between loci. Two intermediate types of population structure were also found. Neisseria meningitidis displays what we have called an "epidemic" structure. There is significant association between loci, but this arises only because of the recent, explosive, increase in particular electrophoretic types; when this effect is eliminated the population is found to be effectively panmictic. In contrast, linkage disequilibrium in a population of Rhizobium meliloti exists because the sample consisted of two genetically isolated divisions, often fixed for different alleles: within each division association between loci was almost random. The method of analysis is appropriate whenever there is doubt about the extent of genetic recombination between members of a population. To illustrate this we analyzed data on protozoan parasites and again found panmictic, epidemic, and clonal population structures
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