296 research outputs found

    Study of an advanced General Aviation Turbine Engine (GATE)

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    The best technology program for a small, economically viable gas turbine engine applicable to the general aviation helicopter and aircraft market for 1985-1990 was studied. Turboshaft and turboprop engines in the 112 to 746 kW (150 to 1000 hp) range and turbofan engines up to 6672 N (1500 lbf) thrust were considered. A good market for new turbine engines was predicted for 1988 providing aircraft are designed to capitalize on the advantages of the turbine engine. Parametric engine families were defined in terms of design and off-design performance, mass, and cost. These were evaluated in aircraft design missions selected to represent important market segments for fixed and rotary-wing applications. Payoff parameters influenced by engine cycle and configuration changes were aircraft gross mass, acquisition cost, total cost of ownership, and cash flow. Significant advantage over a current technology, small gas turbine engines was found especially in cost of ownership and fuel economy for airframes incorporating an air-cooled high-pressure ratio engine. A power class of 373 kW (500 hp) was recommended as the next frontier for technology advance where large improvements in fuel economy and engine mass appear possible through component research and development

    Changing a semantics: opportunism or courage?

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    The generalized models for higher-order logics introduced by Leon Henkin, and their multiple offspring over the years, have become a standard tool in many areas of logic. Even so, discussion has persisted about their technical status, and perhaps even their conceptual legitimacy. This paper gives a systematic view of generalized model techniques, discusses what they mean in mathematical and philosophical terms, and presents a few technical themes and results about their role in algebraic representation, calibrating provability, lowering complexity, understanding fixed-point logics, and achieving set-theoretic absoluteness. We also show how thinking about Henkin's approach to semantics of logical systems in this generality can yield new results, dispelling the impression of adhocness. This paper is dedicated to Leon Henkin, a deep logician who has changed the way we all work, while also being an always open, modest, and encouraging colleague and friend.Comment: 27 pages. To appear in: The life and work of Leon Henkin: Essays on his contributions (Studies in Universal Logic) eds: Manzano, M., Sain, I. and Alonso, E., 201

    Aptamer-based multiplexed proteomic technology for biomarker discovery

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    Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

    DUVET Survey: Mapping Outflows in the Metal-Poor Starburst Mrk 1486

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    We present a method to characterize star-formation driven outflows from edge-on galaxies and apply this method to the metal-poor starburst galaxy, Mrk 1486. Our method uses the distribution of emission line flux (from Hβ\beta and [OIII] 5007) to identify the location of the outflow and measure the extent above the disk, the opening angle, and the transverse kinematics. We show that this simple technique recovers a similar distribution of the outflow without requiring complex modelling of line-splitting or multi-Gaussian components, and is therefore applicable to lower spectral resolution data. In Mrk 1486 we observe an asymmetric outflow in both the location of the peak flux and total flux from each lobe. We estimate an opening angle of 173717-37^{\circ} depending on the method and assumptions adopted. Within the minor axis outflows, we estimate a total mass outflow rate of 2.5\sim2.5 M_{\odot} yr1^{-1}, which corresponds to a mass loading factor of η=0.7\eta=0.7. We observe a non-negligible amount of flux from ionized gas outflowing along the edge of the disk (perpendicular to the biconical components), with a mass outflow rate 0.9\sim0.9 M_{\odot} yr1^{-1}. Our results are intended to demonstrate a method that can be applied to high-throughput, low spectral resolution observations, such as narrow band filters or low spectral resolution IFS that may be more able to recover the faint emission from outflows.Comment: 12 Pages, 6 Figure

    DUVET: Spatially Resolved Observations of Star Formation Regulation via Galactic Outflows in a Starbursting Disk Galaxy

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    We compare 500~pc scale, resolved observations of ionised and molecular gas for the z0.02z\sim0.02 starbursting disk galaxy IRAS08339+6517, using measurements from KCWI and NOEMA. We explore the relationship of the star formation driven ionised gas outflows with colocated galaxy properties. We find a roughly linear relationship between the outflow mass flux (Σ˙out\dot{\Sigma}_{\rm out}) and star formation rate surface density (ΣSFR\Sigma_{\rm SFR}), Σ˙outΣSFR1.06±0.10\dot{\Sigma}_{\rm out}\propto\Sigma_{\rm SFR}^{1.06\pm0.10}, and a strong correlation between Σ˙out\dot{\Sigma}_{\rm out} and the gas depletion time, such that Σ˙outtdep1.1±0.06\dot{\Sigma}_{\rm out} \propto t_{dep}^{-1.1\pm0.06}. Moreover, we find these outflows are so-called ``breakout" outflows, according to the relationship between the gas fraction and disk kinematics. Assuming that ionised outflow mass scales with total outflow mass, our observations suggest that the regions of highest ΣSFR\Sigma_{\rm SFR} in IRAS08 are removing more gas via the outflow than through the conversion of gas into stars. Our results are consistent with a picture in which the outflow limits the ability for a region of a disk to maintain short depletion times. Our results underline the need for resolved observations of outflows in more galaxies.Comment: 16 pages, 7 figures, Submitted to Ap

    Single-Step Selection of Bivalent Aptamers Validated by Comparison with SELEX Using High-Throughput Sequencing

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    The identification of nucleic acid aptamers would be advanced if they could be obtained after fewer rounds of selection and amplification. In this paper the identification of bivalent aptamers for thrombin by SELEX and single-step selection are compared using next generation sequencing and motif finding informatics. Results show that similar aptamers are identified by both methods. This is significant because it shows that next generation sequencing and motif finding informatics have the potential to simplify the selection of aptamers by avoiding multiple rounds of enzymatic transcription and amplification

    K-Ras Mediated Murine Epidermal Tumorigenesis Is Dependent upon and Associated with Elevated Rac1 Activity

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    A common goal for potential cancer therapies is the identification of differences in protein expression or activity that would allow for the selective targeting of tumor vs. normal cells. The Ras proto-oncogene family (K-Ras, H-Ras and N-Ras) are amongst the most frequently mutated genes in human cancers. As a result, there has been substantial effort dedicated to determining which pathways are activated by Ras signaling and, more importantly, which of these contribute to cancer. Although the most widely studied Ras-regulated signaling pathway is the Raf/mitogen-activated protein kinase cascade, previous research in model systems has revealed that the Rac1 GTP-binding protein is also required for Ras-induced biological responses. However, what have been lacking are rigorous in vivo Rac1 target validation data and a clear demonstration that in Ras-driven hyperplastic lesions, Rac1 activity is increased. Using a combination of genetically-modified mouse models that allow for the tissue-selective activation or deletion of signaling molecules and an activation-state sensitive Rac1 antibody that detects GTP-bound Rac1, we found that Rac1 contributes to K-Ras induced epidermal papilloma initiation and growth and that Rac1 activity is elevated by oncogenic K-Ras in vivo. Previously, it was not practical to assess Rac1 activation status in the most commonly used format for clinical tumor specimens, formalin-fixed paraffin embedded (FFPE) tissues samples. However, this study clearly demonstrates that Rac1 is essential for K-Ras driven epithelial cell hyperproliferation and that Rac1 activity is elevated in tissues expressing mutant oncogenic K-Ras, while also characterizing the activation-state specific Rac1-GTP antibody as a probe to examine Rac1 activation status in FFPE samples. Our findings will facilitate further research on the status of Rac1 activity in human tumors and will help to define the tumor types of the patient population that could potentially benefit from therapies targeting Rac activation or downstream effector signaling pathways

    Integrated genomic analyses of ovarian carcinoma

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    A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients’ lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.National Institutes of Health (U.S.) (Grant U54HG003067)National Institutes of Health (U.S.) (Grant U54HG003273)National Institutes of Health (U.S.) (Grant U54HG003079)National Institutes of Health (U.S.) (Grant U24CA126543)National Institutes of Health (U.S.) (Grant U24CA126544)National Institutes of Health (U.S.) (Grant U24CA126546)National Institutes of Health (U.S.) (Grant U24CA126551)National Institutes of Health (U.S.) (Grant U24CA126554)National Institutes of Health (U.S.) (Grant U24CA126561)National Institutes of Health (U.S.) (Grant U24CA126563)National Institutes of Health (U.S.) (Grant U24CA143882)National Institutes of Health (U.S.) (Grant U24CA143731)National Institutes of Health (U.S.) (Grant U24CA143835)National Institutes of Health (U.S.) (Grant U24CA143845)National Institutes of Health (U.S.) (Grant U24CA143858)National Institutes of Health (U.S.) (Grant U24CA144025)National Institutes of Health (U.S.) (Grant U24CA143866)National Institutes of Health (U.S.) (Grant U24CA143867)National Institutes of Health (U.S.) (Grant U24CA143848)National Institutes of Health (U.S.) (Grant U24CA143843)National Institutes of Health (U.S.) (Grant R21CA135877
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