A study of methods to predict and measure the transmission of sound through the walls of light aircraft

Several research investigations are discussed. The development of a numerical/empirical noise source identification procedure using boundary element techniques, the identification of structure-borne paths using structural intensity and finite element methods, the development of a design optimization numerical procedure to be used to study active noise control in three-dimensional geometries, and the measurement of the dynamic properties of acoustical foams and the incorporation of these properties in models governing three-dimensional wave propagation in foams are discussed

The strong Novikov conjecture for low degree cohomology

We show that for each discrete group G, the rational assembly map K_*(BG) \otimes Q \to K_*(C*_{max} G) \otimes \Q is injective on classes dual to the subring generated by cohomology classes of degree at most 2 (identifying rational K-homology and homology via the Chern character). Our result implies homotopy invariance of higher signatures associated to these cohomology classes. This consequence was first established by Connes-Gromov-Moscovici and Mathai. Our approach is based on the construction of flat twisting bundles out of sequences of almost flat bundles as first described in our previous work. In contrast to the argument of Mathai, our approach is independent of (and indeed gives a new proof of) the result of Hilsum-Skandalis on the homotopy invariance of the index of the signature operator twisted with bundles of small curvature.Comment: 11 page

A Morphological and Multicolor Survey for Faint QSOs in the Groth-Westphal Strip

Quasars representative of the populous faint end of the luminosity function are frustratingly dim with m~24 at intermediate redshift; moreover groundbased surveys for such faint QSOs suffer substantial morphological contamination by compact galaxies having similar colors. In order to establish a more reliable ultrafaint QSO sample, we used the APO 3.5-m telescope to take deep groundbased U-band CCD images in fields previously imaged in V,I with WFPC2/HST. Our approach hence combines multicolor photometry with the 0.1" spatial resolution of HST, to establish a morphological and multicolor survey for QSOs extending about 2 magnitudes fainter than most extant groundbased surveys. We present results for the "Groth-Westphal Strip", in which we identify 10 high likelihood UV-excess candidates having stellar or stellar-nucleus+galaxy morphology in WFPC2. For m(606)<24.0 (roughly B<24.5) the surface density of such QSO candidates is 420 (+180,-130) per square degree, or a surface density of 290 (+160,-110) per square degree with an additional V-I cut that may further exclude compact emission line galaxies. Even pending confirming spectroscopy, the observed surface density of QSO candidates is already low enough to yield interesting comparisons: our measures agree extremely well with the predictions of several recent luminosity function models.Comment: 29 pages including 6 tables and 7 figures. As accepted for publication in The Astronomical Journal (minor revisions

Competing superconducting and magnetic order parameters and field-induced magnetism in electron doped Ba(Fe1−x_{1-x}Cox_{x})2_{2}As2_{2}

We have studied the magnetic and superconducting properties of Ba(Fe$_{0.95}$Co$_{0.05}$)$_{2}$As$_{2}$ as a function of temperature and external magnetic field using neutron scattering and muon spin rotation. Below the superconducting transition temperature the magnetic and superconducting order parameters coexist and compete. A magnetic field can significantly enhance the magnetic scattering in the superconducting state, roughly doubling the Bragg intensity at 13.5 T. We perform a microscopic modelling of the data by use of a five-band Hamiltonian relevant to iron pnictides. In the superconducting state, vortices can slow down and freeze spin fluctuations locally. When such regions couple they result in a long-range ordered antiferromagnetic phase producing the enhanced magnetic elastic scattering in agreement with experiments.Comment: 9 pages, 6 figure

Anomalous Fermi Liquid Behavior of Overdoped High-Tc Superconductors

According to a generic temperature vs. carrier-doping (T-p) phase diagram of high-temperature superconductors it has been proposed that as doping increases to the overdoped region they approach gradually a conventional (canonical) Fermi Liquid. However, Hall effect measurements in several systems reported by different authors show a still strong \emph{T}-dependence in overdoped samples. We report here electrical transport measurements of Y_{1-x}Ca_{x}Ba_{2}Cu_{3}O_{7-delta} thin films presenting a temperature dependence of the Hall constant, R_H, which does not present a gradual transition towards the T-independent behavior of a canonical Fermi Liquid. Instead, the T-dependence passes by a minimum near optimal doping and then increases again in the overdoped region. We discuss the theoretical predictions from two representative Fermi Liquid models and show that they can not give a satisfactory explanation to our data. We conclude that this region of the phase diagram in YBCO, as in most HTSC, is not a canonical Fermi Liquid, therefore we call it Anomalous Fermi Liquid.Comment: 9 pages, 12 figures, to be published in Phys. Rev.

Absence of long-range order in a spin-half Heisenberg antiferromagnet on the stacked kagome lattice

We study the ground state of a spin-half Heisenberg antiferromagnet on the stacked kagome lattice by using a spin-rotation-invariant Green's-function method. Since the pure two-dimensional kagome antiferromagnet is most likely a magnetically disordered quantum spin liquid, we investigate the question whether the coupling of kagome layers in a stacked three-dimensional system may lead to a magnetically ordered ground state. We present spin-spin correlation functions and correlation lengths. For comparison we apply also linear spin wave theory. Our results provide strong evidence that the system remains short-range ordered independent of the sign and the strength of the interlayer coupling

Anomalous peak in the superconducting condensate density of cuprate high T_{c} superconductors at a unique critical doping state

The doping dependence of the superconducting condensate density, n_{s}^{o}, has been studied by muon-spin-rotation for Y_{0.8}Ca_{0.2}Ba_{2}(Cu_{1-z}Zn_{z})_{3}O_{7-\delta} and Tl_{0.5-y}Pb_{0.5+y}Sr_{2}Ca_{1-x}Y_{x}Cu_{2}O_{7}. We find that n_{s}^{o} exhibits a pronounced peak at a unique doping state in the slightly overdoped regime. Its position coincides with the critical doping state where the normal state pseudogap first appears depleting the electronic density of states. A surprising correlation between n_{s}^{o} and the condensation energy U_{o} is observed which suggests unconventional behavior even in the overdoped region.Comment: 10 pages, 3 figure

Unconventional conductance plateau transitions in quantum Hall wires with spatially correlated disorder

Quantum transport properties in quantum Hall wires in the presence of spatially correlated random potential are investigated numerically. It is found that the potential correlation reduces the localization length associated with the edge state, in contrast to the naive expectation that the potential correlation increases it. The effect appears as the sizable shift of quantized conductance plateaus in long wires, where the plateau transitions occur at energies much higher than the Landau band centers. The scale of the shift is of the order of the strength of the random potential and is insensitive to the strength of magnetic fields. Experimental implications are also discussed.Comment: 5 pages, 4 figure

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models.

Knowing the catalytic turnover numbers of enzymes is essential for understanding the growth rate, proteome composition, and physiology of organisms, but experimental data on enzyme turnover numbers is sparse and noisy. Here, we demonstrate that machine learning can successfully predict catalytic turnover numbers in Escherichia coli based on integrated data on enzyme biochemistry, protein structure, and network context. We identify a diverse set of features that are consistently predictive for both in vivo and in vitro enzyme turnover rates, revealing novel protein structural correlates of catalytic turnover. We use our predictions to parameterize two mechanistic genome-scale modelling frameworks for proteome-limited metabolism, leading to significantly higher accuracy in the prediction of quantitative proteome data than previous approaches. The presented machine learning models thus provide a valuable tool for understanding metabolism and the proteome at the genome scale, and elucidate structural, biochemical, and network properties that underlie enzyme kinetics