Aero-Acoustics of Modern Transonic Fans—— Fan Noise Reduction from Its Sources

The noise of aerodynamics nature from modern transonic fan is examined from its sources with the perspective of noise reduction through aero-acoustics design using advanced Computational Fluid Dynamics (CFD) tools. In particular the problems associated with the forward propagating noise in the front is addressed. It is identified that the shock wave spillage from the leading edge near the fan tip is the main source of the tone noise. Two different approaches have been studied to reduce the forward arc tone noise and two state-of-art transonic fans are designed using the strategies developed. The following rig tests show that while the fans exhibit other noise problems, the primary goals of noise reduction have been achieved through both fans and the novel noise reduction concept vindicated.     

Resection of the right middle lobe and lingula for mycobacterial infection

BACKGROUND: In a series of 229 patients infected with mycobacterial organisms, we noted a specific female phenotype that involves isolated infections of the middle lobe and lingula. METHODS: Thirteen patients were found to have infections of the middle lobe, lingula, or both. All of them were infected with Mycobacterium other then Mycobacterium tuberculosis, all were women, 12 of the 13 were slender, and most had variable combinations of skeletal abnormalities. All underwent resection of the middle lobe, lingula, or both. RESULTS: There were no operative deaths. Only 2 patients have had reactivation requiring additional antibiotic therapy. All patients have had a decreased number of pulmonary infections in the postoperative period. Anatomic findings at operation included a complete major fissure and at least a partially complete minor fissure with middle lobe resections or an elongated lingula. CONCLUSIONS: Mycobacterial infection of the middle lobe and lingula is primarily a disease of asthenic women and is often associated with skeletal abnormalities and complete fissures or an elongated lingula. We recommend that surgical intervention be performed early once the condition is identified.     

Effects of aging on polyimide: A study of bulk and interface chemistry

We are investigating the bulk and interfacial chemistry of polyimide (PI) exposed to heat and relative humidity (RH) stress (85°C/85% RH) over long periods to understand the long-term reliability aspects of PI for microelectronic applications. The PI surface chemistry and the PI–Si interface chemistry was followed with electron spectroscopy for chemical analysis (ESCA). For exposure times greater than 550 h, the PI surface exhibits significant changes in emission structure and atomic concentration. The PI–Si interface indicates little change in the PI chemistry when compared to control samples. The water-contact angle at the PI surface shows no statistically significant change as a function of exposure time. Bulk and surface chemistry were followed with Fourier transform infrared spectroscopy (FTIR) in a grazing incidence reflection configuration. There were measurable differences in FTIR spectra between aged and control samples only for the case of very thin PI layers. These results suggest that for exposure times of less than 1100 h, chemical changes in PI occur primarily at the PI–air interface for samples 1 μm thick and greater. These changes represent a possible rearrangement of the imide structure and may be a form of deimidization of the polymer, but the final state is not polyamic acid. The PI surface chemistry changes observed with ESCA are reversible upon reheating to the cure temperature.     

A rapid computational filter for predicting the rate of human renal clearance

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.     

Subspace sums for extracting non-random data from massive noise

An algorithm is introduced that distinguishes relevant data points from randomly distributed noise. The algorithm is related to subspace clustering based on axis-parallel projections, but considers membership in any projected cluster of a given side length, as opposed to a particular cluster. An aggregate measure is introduced that is based on the total number of points that are close to the given point in all possible 2 ^d projections of a d-dimensional hypercube. No explicit summation over subspaces is required for evaluating this measure. Attribute values are normalized based on rank order to avoid making assumptions on the distribution of random data. Effectiveness of the algorithm is demonstrated through comparison with conventional outlier detection on a real microarray data set as well as on time series subsequence data.

Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. I: Comparison with branched-chain amino acids and forage source in ruminal batch cultures

Three experiments assessed branched-chain volatile fatty acid (BCVFA) stimulation of neutral detergent fiber (NDF) disappearance after 24 h of incubation in batch cultures derived from ruminal fluid inocula that were enriched with particulate-phase bacteria. In experiment 1, a control was compared with 3 treatments with isomolar doses of all 3 BCVFA (plus valerate), all 3 branched-chain AA (BCAA), or half of each BCVFA and BCAA mix with either alfalfa or grass hays (50%) and ground corn grain (50%). A portion of the BCAA and BCVFA doses were enriched with ¹³C, and valerate (also enriched with ¹³C) was added with BCVFA. Although BCAA yielded a similar production of BCVFA compared with dosing BCVFA, equimolar substitution of BCVFA for BCAA decreased the percentage of N in bacterial pellets when alfalfa hay was fed but increased N when grass hay was fed. Substituting BCVFA for BCAA increased total fatty acid (FA) concentration with alfalfa hay. Dosing of BCAA or BCVFA did not affect total branched-chain FA, iso-FA, or anteiso-FA percentages in bacterial total FA, whereas numerous individual FA isomers and their ¹³C enrichments were affected by these treatments. Increasing recovery of the ¹³C dose from respective labeled BCVFA primers indicated facilitated BCVFA uptake and incorporation into FA compared with BCAA, whereas increased recovery of ¹³C from labeled BCAA in the bacteria pellet but not in the FA fraction suggested direct assimilation into bacterial protein. The BCVFA and valerate were dosed in varying combinations that either summed to 4 mM (experiment 2) or had only 1 mM no matter what combination (experiment 3). In general, grass hay was more responsive to stimulation in NDF digestibility by BCVFA than was alfalfa hay, which was attributed to the higher degradable protein in the latter. The net production of the BCVFA (after subtracting dose) was affected by source and combination of BCVFA. Isovalerate dosing tended to increase its own net production; in contrast, isobutyrate seemed to be used more when it was added alone, but 2-methylbutyrate seemed to be preferred over isobutyrate when 2-methylbutyrate was added. Results supported potential interactions, including potential feedback in production from feed BCAA or increased concentration-dependent competition for dosed BCVFA into cellular products. Under our conditions, the BCVFA appear to be more readily available than BCAA, probably because of regulated BCAA transport and metabolism. Valerate consistently provided no benefit. Using nonparametric ranking, all 3 BCVFA or either isovalerate or isobutyrate (both yielding iso-FA) should be combined with 2-methylbutyrate (yielding anteiso-FA) as a potential opportunity to improve NDF digestibility when rumen-degraded BCAA are limited in diets to decrease environmental impact from N in waste.     

Lessons from Rotor 37

INTanDUCTIONhi1992theturbomachinerycommittee0ftheIoter-nationalGasTurbineInstitute(IGTI)decidedtosetuPatestcaseforCFDcalculations.Aftersomedebateitwasdecidedthatthetestcasesh0uldbecalculated'blind',i.e.thattheexperimentalresultssh0uldn0tbemadeawilableulltilafterthesolutionshadbeensubndtted.NASA(LewisResearchCenter)offeredasuitabletestca-seintheformofahighlyloadedtransoniccompressorrot0rwhichwasthenbeingtestedwitheXtensiveuseoflaseranemometrytomeasuretheiliternalflow.Themeasurementsw…     

Data mining of vector–item patterns using neighborhood histograms

The representation of multiple continuous attributes as dimensions in a vector space has been among the most influential concepts in machine learning and data mining. We consider sets of related continuous attributes as vector data and search for patterns that relate a vector attribute to one or more items. The presence of an item set defines a subset of vectors that may or may not show unexpected density fluctuations. We test for fluctuations by studying density histograms. A vector–item pattern is considered significant if its density histogram significantly differs from what is expected for a random subset of transactions. Using two different density measures, we evaluate the algorithm on two real data sets and one that was artificially constructed from time series data.