Spontaneous and induced hyperplasia and neoplasia in the mouse lung.

,SINCE Livingood (1896) first described a spontaneous pulmonary tumour in a mouse, much has been written on the histogenesis of this common tumour, vet it is still difficult to decide whether an early lesion should be classified as hyperplastic or neoplastic. Since the introduction of line-bred strains of mice by Strong (1936) and their general use by research workers, genetic differences in susceptibility have been extensively investigated by Heston (1940) and manv others. It is accepted that the susceptibility to spontaneous development of pulmonary tumours is high in A Strain and low in C57 Black, but that there is no essential difference between the type or range of tumours seen in different strains (Stewart, 1953). As to the sites of origin and distribution of these tumours, most authors describe them as subpleural and as originating in the alveolar epithelium. As far as we know, there has been no evidence as to localising factors which cause one alveolus rather than another to develop neoplastic growth

Refining Finite-Time Lyapunov Exponent Ridges and the Challenges of Classifying Them

While more rigorous and sophisticated methods for identifying Lagrangian based coherent structures exist, the finite-time Lyapunov exponent (FTLE) field remains a straightforward and popular method for gaining some insight into transport by complex, time-dependent two-dimensional flows. In light of its enduring appeal, and in support of good practice, we begin by investigating the effects of discretization and noise on two numerical approaches for calculating the FTLE field. A practical method to extract and refine FTLE ridges in two-dimensional flows, which builds on previous methods, is then presented. Seeking to better ascertain the role of a FTLE ridge in flow transport, we adapt an existing classification scheme and provide a thorough treatment of the challenges of classifying the types of deformation represented by a FTLE ridge. As a practical demonstration, the methods are applied to an ocean surface velocity field data set generated by a numerical model. (C) 2015 AIP Publishing LLC.ONR N000141210665Center for Nonlinear Dynamic

Analytic Approach to the Cloud-in-cloud Problem for Non-Gaussian Density Fluctuations

We revisit the cloud-in-cloud problem for non-Gaussian density fluctuations. We show that the extended Press-Schechter (EPS) formalism for non-Gaussian fluctuations has a flaw in describing mass functions regardless of type of filtering. As an example, we consider non-Gaussian models in which density fluctuations at a point obeys a \chi^2 distribution with \nu degrees of freedom. We find that mass functions predicted by using an integral formula proposed by Jedamzik, and Yano, Nagashima and Gouda, properly taking into account correlation between objects at different scales, deviate from those predicted by using the EPS formalism, especially for strongly non-Gaussian fluctuations. Our results for the mass function at large mass scales are consistent with those by Avelino and Viana obtained from numerical simulations.Comment: 10 pages, 7 EPS files, submitted to Ap

Cluster Correlation in Mixed Models

We evaluate the dependence of the cluster correlation length r_c on the mean intercluster separation D_c, for three models with critical matter density, vanishing vacuum energy (Lambda = 0) and COBE normalized: a tilted CDM (tCDM) model (n=0.8) and two blue mixed models with two light massive neutrinos yielding Omega_h = 0.26 and 0.14 (MDM1 and MDM2, respectively). All models approach the observational value of sigma_8 (and, henceforth, the observed cluster abundance) and are consistent with the observed abundance of Damped Lyman_alpha systems. Mixed models have a motivation in recent results of neutrino physics; they also agree with the observed value of the ratio sigma_8/sigma_25, yielding the spectral slope parameter Gamma, and nicely fit LCRS reconstructed spectra. We use parallel AP3M simulations, performed in a wide box (side 360/h Mpc) and with high mass and distance resolution, enabling us to build artificial samples of clusters, whose total number and mass range allow to cover the same D_c interval inspected through APM and Abell cluster clustering data. We find that the tCDM model performs substantially better than n=1 critical density CDM models. Our main finding, however, is that mixed models provide a surprisingly good fit of cluster clustering data.Comment: 22 pages + 10 Postscript figures. Accepted for publication in Ap

Simulated Extragalactic Observations with a Cryogenic Imaging Spectrophotometer

In this paper we explore the application of cryogenic imaging spectrophotometers. Prototypes of this new class of detector, such as superconducting tunnel junctions (STJs) and transition edge sensors (TESs), currently deliver low resolution imaging spectrophotometry with high quantum efficiency (70-100%) and no read noise over a wide bandpass in the visible to near-infrared. In order to demonstrate their utility and the differences in observing strategy needed to maximize their scientific return, we present simulated observations of a deep extragalactic field. Using a simple analytic technique, we can estimate both the galaxy redshift and spectral type more accurately than is possible with current broadband techniques. From our simulated observations and a subsequent discussion of the expected migration path for this new technology, we illustrate the power and promise of these devices.Comment: 30 pages, 10 figures, accepted for publication in the Astronomical Journa

Measuring the galaxy power spectrum with future redshift surveys

Precision measurements of the galaxy power spectrum P(k) require a data analysis pipeline that is both fast enough to be computationally feasible and accurate enough to take full advantage of high-quality data. We present a rigorous discussion of different methods of power spectrum estimation, with emphasis on the traditional Fourier method, the linear (Karhunen-Loeve; KL), and quadratic data compression schemes, showing in what approximations they give the same result. To improve speed, we show how many of the advantages of KL data compression and power spectrum estimation may be achieved with a computationally faster quadratic method. To improve accuracy, we derive analytic expressions for handling the integral constraint, since it is crucial that finite volume effects are accurately corrected for on scales comparable to the depth of the survey. We also show that for the KL and quadratic techniques, multiple constraints can be included via simple matrix operations, thereby rendering the results less sensitive to galactic extinction and mis-estimates of the radial selection function. We present a data analysis pipeline that we argue does justice to the increases in both quality and quantity of data that upcoming redshift surveys will provide. It uses three analysis techniques in conjunction: a traditional Fourier approach on small scales, a pixelized quadratic matrix method on large scales and a pixelized KL eigenmode analysis to probe anisotropic effects such as redshift-space distortions.Comment: Major revisions for clarity. Matches accepted ApJ version. 23 pages, with 2 figs included. Color figure and links at http://www.sns.ias.edu/~max/galpower.html (faster from the US), from http://www.mpa-garching.mpg.de/~max/galpower.html (faster from Europe) or from [email protected]

A Constraint on the Distance Scale to Cosmological Gamma--Ray Bursts

If \g--ray bursts are cosmological in origin, the sources are expected to trace the large--scale structure of luminous matter in the universe. I use a new likelihood method that compares the counts--in--cells distribution of \g--ray bursts in the BATSE 3B catalog with that expected from the known large--scale structure of the universe, in order to place a constraint on the distance scale to cosmological bursts. I find, at the 95\% confidence level, that the comoving distance to the ``edge'' of the burst distribution is greater than $630~h^{-1}$~Mpc ($z > 0.25$), and that the nearest burst is farther than $40~h^{-1}$~Mpc. The median distance to the nearest burst is $170~h^{-1}$~Mpc, implying that the total energy released in \g--rays during a burst event is of order $3\times 10^{51}~h^{-2}$ ergs. None of the bursts that have been observed by BATSE are in nearby galaxies, nor is a signature from the Coma cluster or the ``Great Wall'' likely to be seen in the data at present.Comment: 15 LaTeX pages with 2 encapsulated Postscript figures included, uses AASTeX (v. 4.0) available at ftp://ftp.aas.org/pubs

The Angular Power Spectrum of EDSGC Galaxies

We determine the angular power spectrum, C_l, of the Edinburgh/Durham Southern Galaxy Catalog (EDSGC) and use this statistic to constrain cosmological parameters. Our methods for determining C_l, and the parameters that affect it are based on those developed for the analysis of cosmic microwave background maps. We expect them to be useful for future surveys. Assuming flat cold dark matter models with a cosmological constant (constrained by COBE/DMR and local cluster abundances), and a scale--independent bias, b, we find good fits to the EDSGC angular power spectrum with 1.11 < b < 2.35 and 0.2 < Omega_m < 0.55 at 95% confidence. These results are not significantly affected by the ``integral constraint'' or extinction by interstellar dust, but may be by our assumption of Gaussianity.Comment: 11 pages, 9 figures, version to appear in Ap

Measuring the Deviation from the Linear and Deterministic Bias through Cosmic Gravitational Lensing Effects

Since gravitational lensing effects directly probe inhomogeneities of dark matter, lensing-galaxy cross-correlations can provide us important information on the relation between dark matter and galaxy distributions, i.e., the bias. In this paper, we propose a method to measure the stochasticity/nonlinearity of the galaxy bias through correlation studies of the cosmic shear and galaxy number fluctuations. Specifically, we employ the aperture mass statistics $M_{ap}$ to describe the cosmic shear. We divide the foreground galaxy redshift $z_f<z_s$ into several bins, where $z_s$ is the redshift of the source galaxies, and calculate the quantity $^2/$ for each redshift bin. Then the ratio of the summation of $^2/< N_g^2(z_f)>$ over the bins to $$ gives a measure of the nonlinear/stochastic bias. Here $N_g(z_f)$ is the projected surface number density fluctuation of foreground galaxies at redshift $z_f$, and $M_{ap}$ is the aperture mass from the cosmic-shear analysis. We estimate that for a moderately deep weak-lensing survey with $z_s=1$, source galaxy surface number density $n_b=30 \hbox {gal}/\hbox {arcmin}^2$ and a survey area of $25 \hbox {deg}^2$, the effective $r$-parameter that represents the deviation from the linear and deterministic bias is detectable in the angular range of 1'-10' if |r-1|\gsim 10%. For shallow, wide surveys such as the Sloan Digital Sky Survey with $z_s=0.5$, $n_b=5 \hbox {gal}/\hbox {arcmin}^2$, and a survey area of $10^4 \hbox {deg}^2$, a 10% detection of $r$ is possible over the angular range $1'-100'$.Comment: ApJ in pres