Experimental Investigation of Shock-Cell Noise Reduction for Single Stream Nozzles in Simulated Flight

Seven single stream model nozzles were tested in the Anechoic Free-Jet Acoustic Test Facility to evaluate the effectiveness of convergent divergent (C-D) flowpaths in the reduction of shock-cell noise under both static and mulated flight conditions. The test nozzles included a baseline convergent circular nozzle, a C-D circular nozzle, a convergent annular plug nozzle, a C-D annular plug nozzle, a convergent multi-element suppressor plug nozzle, and a C-D multi-element suppressor plug nozzle. Diagnostic flow visualization with a shadowgraph and aerodynamic plume measurements with a laser velocimeter were performed with the test nozzles. A theory of shock-cell noise for annular plug nozzles with shock-cells in the vicinity of the plug was developed. The benefit of these C-D nozzles was observed over a broad range of pressure ratiosin the vicinity of their design conditions. At the C-D design condition, the C-D annual nozzle was found to be free of shock-cells on the plug

Free jet feasibility study of a thermal acoustic shield concept for AST/VCE application: Single stream nozzles

A technology base for the thermal acoustic shield concept as a noise suppression device for single stream exhaust nozzles was developed. Acoustic data for 314 test points for 9 scale model nozzle configurations were obtained. Five of these configurations employed an unsuppressed annular plug core jet and the remaining four nozzles employed a 32 chute suppressor core nozzle. Influence of simulated flight and selected geometric and aerodynamic flow variables on the acoustic behavior of the thermal acoustic shield was determined. Laser velocimeter and aerodynamic measurements were employed to yield valuable diagnostic information regarding the flow field characteristics of these nozzles. An existing theoretical aeroacoustic prediction method was modified to predict the acoustic characteristics of partial thermal acoustic shields

Anti-phospholipid-antibodies in patients with relapsing polychondritis

Relapsing polychondritis (RP) is an extremly rare multisystemic disease thought to be of autoimmune origin. In order to assess if RP is associated with anti-phospholipid antibodies (aPL), clinical data and sera of 21 patients with RP were collected in a multicentre study. Concentration of anti-cardiolipin antibodies (aCL) (IgG-, IgM-and IgA-isotypes), anti-phosphatidylserine-antibodies (aPS) (IgG-and IgM-isotypes) and anti-β-2-glycoprotein I-antibodies (aβ2 GPI) were measured by ELISA. In eight patients aCL were found to be elevated. One patient had elevated aPS. No patient had elevated aβ2 GPI. No patient had clinical signs and symptoms of a aPL syndrome. Interestingly, the two RP patients with the highest aPL had concomitant systemic lupus erythematosus (SLE). Therefore the presence of elevated aPL in RP is probably more closely related to an associated SLE than to RP itself. There is no convincing evidence that aPL are associated with RP

Nematode communities from a natural oil seep off Svalbard

Cold-seep sediments, where active fluid seepage rich is observed, have been associated with the presence of endemic nematode communities. Under the scope of the AKMA project, a seep site located offshore Svalbard was sampled for the first time to investigate the Nematoda assemblages associated with methane and crude oil seepage. Replicated samples were collected by means of the blade- and push-cores, on a bacterial mat where active gas and oil seepage was observed, as well as in sediments nearby without evident seepage activity, as reference. Sediments collected were used to characterize the community structure and diversity of the meiofauna taxa, particularly the nematode assemblages, as well as key environmental parameters (i.e, sediment and pore-water geochemistry, organic content, grain size). Preliminary observations showed no major differences in total meiofauna density between microhabitats, with a predominance of nematodes (>90%), followed by harpacticoid copepods and nauplii larvae, as typically seen in other deep-sea environments. However, an in-depth investigation into the nematode assemblages, revealed a low nematode diversity in the bacterial mats sediments, by comparison, to the reference. Bacterial mat-associated assemblages were predominantly composed of Halomonhystera sp.1 (39%), followed by a single Chromadoridae species (32%). Evidence of morphological and reproductive adaptations were observed in several of the species present and could be indicative of how these organisms are able to survive the toxic environmental conditions at this seep site, namely high concentrations of hydrogen sulphide and crude oil. These observations contribute to a large gap in the understanding of how infauna thrive in extreme environments in the Arctic

Nematode communities from a natural oil seep off Svalbard.

Cold seeps are considered hotspots of energy on the seafloor, establishing unique conditions for life to thrive. In chemosynthetic-based habitats such as these, sediments from active sites are typically inhabited by endemic nematode communities which tolerate the local reduced environmental conditions, but no studies have been carried out on seep sites so far north in the Arctic. Under the scope of the AKMA project, an oil seep site located offshore Svalbard was sampled for the first time to investigate the associated meiofauna assemblages with methane and crude oil seepage. Replicated samples were collected by means of the blade and push cores handled by the ROV Ægir6000, both on bacterial mats with evident gas and oil seepage, as well as in sediments nearby without evident seepage activity, as reference. Sediments collected were used to characterize the community structure and diversity of the meiofauna taxa, particularly the nematode assemblages, as well as key environmental parameters (i.e, sediment and porewater geochemistry, organic content, grain size). Preliminary observations showed no major differences in total meiofauna density between microhabitats, with a predominance of nematodes (>90%), followed by harpacticoid copepods and nauplii larvae, typically seen in other deep-sea environments. However, an in-depth investigation into the nematode assemblages revealed that bacterial mats hosted an extremely low diversity of nematode species, by comparison, to the reference locations. Bacterial mat-associated assemblages were predominantly composed of a single species, Dichromadora sp.1, followed by Halomonhystera cf. disjuncta and Linhomoidae sp. 1. Evidence of morphological and reproductive adaptations in the species present seems to allow them to survive in this toxic environment, namely due to high concentrations of hydrogen sulfide and oil presence. The findings resulting from this study contribute to a large gap in the understanding of how infauna thrive in extreme environments with the presence of hydrocarbons in the Arcti

Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia

Hypophosphatasia (HPP) is a rare and underdiagnosed condition characterized by deficient bone and teeth mineralization. The aim of this study was first, to evaluate the diagnostic utility of employing alkaline phosphatase (ALP) threshold levels to identify adults with variants in ALPL among individuals with persistently low ALP levels and second, to determine the value of also including its substrates (serum pyridoxal-5′-phosphate—PLP—and urinary phosphoetanolamine-PEA) for this purpose in order to create a biochemical algorithm that could facilitate the diagnostic work-up of HPP. Results: The study population comprised 77 subjects with persistent hypophosphatasaemia. They were divided into two groups according to the presence (+GT) or absence (−GT) of pathogenic ALPL variants: 40 +GT and 37 −GT. Diagnostic utility measures were calculated for different ALP thresholds and Receiver Operating Characteristic (ROC) curves were employed to determine PLP and PEA optimal cut-off levels to predict the presence of variants. The optimal threshold for ALP was 25 IU/L; for PLP, 180 nmol/L and for PEA, 30 µmol/g creatinine. Biochemical predictive models were assessed using binary logistic regression analysis and bootstrapping machine learning technique and results were then validated. For ALP 180 nmol/L) that when combined, seem to be very useful to identify individuals with ALPL variant

An iterative identification procedure for dynamic modeling of biochemical networks

<p>Abstract</p> <p>Background</p> <p>Mathematical models provide abstract representations of the information gained from experimental observations on the structure and function of a particular biological system. Conferring a predictive character on a given mathematical formulation often relies on determining a number of non-measurable parameters that largely condition the model's response. These parameters can be identified by fitting the model to experimental data. However, this fit can only be accomplished when identifiability can be guaranteed.</p> <p>Results</p> <p>We propose a novel iterative identification procedure for detecting and dealing with the lack of identifiability. The procedure involves the following steps: 1) performing a structural identifiability analysis to detect identifiable parameters; 2) globally ranking the parameters to assist in the selection of the most relevant parameters; 3) calibrating the model using global optimization methods; 4) conducting a practical identifiability analysis consisting of two (<it>a priori </it>and <it>a posteriori</it>) phases aimed at evaluating the quality of given experimental designs and of the parameter estimates, respectively and 5) optimal experimental design so as to compute the scheme of experiments that maximizes the quality and quantity of information for fitting the model.</p> <p>Conclusions</p> <p>The presented procedure was used to iteratively identify a mathematical model that describes the NF-<it>κ</it>B regulatory module involving several unknown parameters. We demonstrated the lack of identifiability of the model under typical experimental conditions and computed optimal dynamic experiments that largely improved identifiability properties.</p