The Parkes quarter-Jansky flat-spectrum sample 3. Space density and evolution of QSOs

We analyze the Parkes quarter-Jansky flat-spectrum sample of QSOs in terms of space density, including the redshift distribution, the radio luminosity function, and the evidence for a redshift cutoff. With regard to the luminosity function, we note the strong evolution in space density from the present day to epochs corresponding to redshifts ~ 1. We draw attention to a selection effect due to spread in spectral shape that may have misled other investigators to consider the apparent similarities in shape of luminosity functions in different redshift shells as evidence for luminosity evolution. To examine the evolution at redshifts beyond 3, we develop a model-independent method based on the V_max test using each object to predict expectation densities beyond z=3. With this we show that a diminution in space density at z > 3 is present at a significance level >4 sigma. We identify a severe bias in such determinations from using flux-density measurements at epochs significantly later than that of the finding survey. The form of the diminution is estimated, and is shown to be very similar to that found for QSOs selected in X-ray and optical wavebands. The diminution is also compared with the current estimates of star-formation evolution, with less conclusive results. In summary we suggest that the reionization epoch is little influenced by powerful flat-spectrum QSOs, and that dust obscuration does not play a major role in our view of the QSO population selected at radio, optical or X-ray wavelengths.Comment: 18 pages, 11 figures, accepted 18 Dec 2004, Astron. & Astrophys. The accepted version is expanded to include an analysis of the form of the decline in radio-QSO space density at high redshifts. This is compared with the forms of epoch dependence derived for optically-selected QSOs, for X-ray-selected QSOs, and for star formation rat

Transmission Electron Study of Heteroepitaxial Growth in the BiSrCaCuO System

Films of Bi$\rm _2$Sr$\rm _2$CaCu$\rm _2$O$\rm _8$ and Bi$\rm _2$Sr$\rm _2$CuO$\rm _6$ have been grown using Atomic-Layer-by-Layer Molecular Beam Epitaxy (ALL-MBE) on lattice-matched substrates. These materials have been combined with layers of closely-related metastable compounds like Bi$\rm _2$Sr$\rm _2$Ca$\rm _7$Cu$\rm _8$O$\rm _{20}$ (2278) and rare-earth-doped compounds like Bi$\rm _2$Sr$\rm _2$Dy$\rm _x$Ca$\rm _{1-x}$Cu$\rm _2$O$\rm _8$ (Dy:2212) to form heterostructures with unique superconducting properties, including superconductor/insulator multilayers and tunnel junctions. Transmission electron microscopy (TEM) has been used to study the morphology and microstructure of these heterostructures. These TEM studies shed light on the physical properties of the films, and give insight into the growth mode of highly anisotropic solids like Bi$\rm _2$Sr$\rm _2$CaCu$\rm _2$O$\rm _8$.Comment: 17 pages, submitted to J. Materials Research. Email to [email protected] if you want to receive copies of the figure

An Innovative Approach Based on Machine Learning to Evaluate the Risk Factors Importance in Diagnosing Keratoconus

Background and objective: Keratoconus is a non-inflammatory corneal condition affecting both eyes and is present in one out of every 2,000 people worldwide. The cornea deforms into a conical shape and thins, resulting in high-order aberrations and gradual vision loss. Risk factor analysis in the degradation of keratoconus is under-researched. Methods: This research work investigates and uses effective machine learning models to gain insight into how much the risk factors of a patient contribute towards the progressive stages of keratoconus, as well as how significant these factors are in the creation of an accurate prediction model. This research demonstrates the value of machine learning approaches on a clinical dataset. This research paper employs several machine learning algorithms to classify the patients' stage of keratoconus using clinical information, such as measurements of the cornea's topography, elevation, and pachymetry taken using pentacam equipment at Sydney's Vision Eye Institute Chatswood. Results: Eight different machine learning techniques were investigated over three variations of a dataset and achieved an average accuracy of 68, 80, and 90% for the risk factor, pentacam, and cumulative datasets, respectively. The results show a significant increase in accuracy and a 97% increase in AUC upon addition of risk factor data compared to the models trained on pentacam data alone. The machine learning methods shown in this paper outperform those in current research. Conclusions: This research highlights the importance of machine learning methods and risk factor data in the diagnosis of keratoconus and highlights the patient's primary optical aid as the strongest risk factor. The goal of this research is to support the work of the ophthalmologists in diagnosing keratoconus and provide better care for the patient

Delocalization of Wannier-Stark ladders by phonons: tunneling and stretched polarons

We study the coherent dynamics of a Holstein polaron in strong electric fields. A detailed analytical and numerical analysis shows that even for small hopping constant and weak electron-phonon interaction, polaron states can become delocalized if a resonance condition develops between the original Wannier-Stark states and the phonon modes, yielding both tunneling and `stretched' polarons. The unusual stretched polarons are characterized by a phonon cloud that {\em trails} the electron, instead of accompanying it. In general, our novel approach allows us to show that the polaron spectrum has a complex nearly-fractal structure, due to the coherent coupling between states in the Cayley tree which describes the relevant Hilbert space. The eigenstates of a finite ladder are analyzed in terms of the observable tunneling and optical properties of the system.Comment: 7 pages, 4 figure

Arterial pathology in canine mucopolysaccharidosis-I and response to therapy.

Mucopolysaccharidosis-I (MPS-I) is an inherited deficiency of α-L-iduronidase (IdU) that causes lysosomal accumulation of glycosaminoglycans (GAG) in a variety of parenchymal cell types and connective tissues. The fundamental link between genetic mutation and tissue GAG accumulation is clear, but relatively little attention has been given to the morphology or pathogenesis of associated lesions, particularly those affecting the vascular system. The terminal parietal branches of the abdominal aorta were examined from a colony of dogs homozygous (MPS-I affected) or heterozygous (unaffected carrier) for an IdU mutation that eliminated all enzyme activity, and in affected animals treated with human recombinant IdU. High-resolution computed tomography showed that vascular wall thickenings occurred in affected animals near branch points, and associated with low endothelial shear stress. Histologically these asymmetric 'plaques' entailed extensive intimal thickening with disruption of the internal elastic lamina, occluding more than 50% of the vascular lumen in some cases. Immunohistochemistry was used to show that areas of sclerosis contained foamy (GAG laden) macrophages, fibroblasts and smooth muscle cells, with loss of overlying endothelial basement membrane and claudin-5 expression. Lesions contained scattered cells expressing nuclear factor-κβ (p65), increased fibronectin and transforming growth factor β-1 signaling (with nuclear Smad3 accumulation) in comparison to unaffected vessels. Intimal lesion development and morphology was improved by intravenous recombinant enzyme treatment, particularly with immune tolerance to this exogenous protein. The progressive sclerotic vasculopathy of MPS-I shares some morphological and molecular similarities to atherosclerosis, including formation in areas of low shear stress near branch points, and can be reduced or inhibited by intravenous administration of recombinant IdU

Serially-regulated biological networks fully realize a constrained set of functions

We show that biological networks with serial regulation (each node regulated by at most one other node) are constrained to {\it direct functionality}, in which the sign of the effect of an environmental input on a target species depends only on the direct path from the input to the target, even when there is a feedback loop allowing for multiple interaction pathways. Using a stochastic model for a set of small transcriptional regulatory networks that have been studied experimentally, we further find that all networks can achieve all functions permitted by this constraint under reasonable settings of biochemical parameters. This underscores the functional versatility of the networks.Comment: 9 pages, 3 figure

The contribution of the Unresolved Extragalactic Radio Sources to the Brightness Temperature of the sky

The contribution of the Unresolved Extragalactic Radio Sources to the diffuse brightness of the sky was evaluated using the source number - flux measurements available in literature. We first optimized the fitting function of the data based on number counts distribution. We then computed the brightness temperature at various frequencies from 151 MHz to 8440 MHz and derived its spectral dependence. As expected the frequency dependence can be described by a power law with a spectral index $\gamma \simeq -2.7$, in agreement with the flux emitted by the {\it steep spectrum} sources. The contribution of {\it flat spectrum} sources becomes relevant at frequencies above several GHz. Using the data available in literature we improved our knowledge of the brightness of the unresolved extragalactic radio sources. The results obtained have general validity and they can be used to disentangle the various contributions of the sky brightness and to evaluate the CMB temperature.Comment: Accepted for publication in the Astrophysical Journa