Molecular Parataxonomy as Taxon Description: Examples from Recently Named Zoanthidea (Cnidaria: Anthozoa) with Revision Based on Serial Histology of Microanatomy.

Current taxonomic practices require corroboration from multiple lines of evidence to provide sufficient rigor for species discovery and description. However, many recently named taxa (species–families) are defined by nucleotide sequence with little or no description of the features that traditionally define higher taxa and link nucleotide-based information to the existing taxonomic system. Without knowledge of form, it may be impossible to identify conspecifics, congeners, and confamiliars of new taxa among the hundreds of specimens and described species for which nucleotide sequencing is not now, and may never be, available. Additionally, some nucleotide sequences are invariant or inconsistently differentiated between congeners; severely limiting the utility of nucleotide-based taxon definitions. Here we use serial histology of paratypes to reveal the microanatomy of internal structures and revise the definitions of the Zoanthidea taxa Corallizoanthus tsukaharai Reimer, Antipathozoanthus hickmani Reimer & Fujii, Parazoanthus darwini Reimer & Fujii, Terrazoanthus onoi Reimer & Fujii, Terrazoanthus sinnigeri Reimer & Fujii, Microzoanthus kagerou Fujii & Reimer, and Zoanthus kuroshio Reimer & Ono; examination of Mesozoanthus lilkweminensis Reimer & Sinniger failed to produce interpretable sections. The results described here, with individual measurements documented in Morphbank (collection 829724) and Encyclopedia of Life (by taxon name), indicate a notably rich diversity of form for an order that is often characterized as depauperate in morphological diversity. One prominent example is a novel marginal muscle structure (cyclically transitional) that is not observable without serial sections. These findings may renew interest in morphological characters and provide the foundation for revision of Zoanthidea higher taxa, particularly now that phylogenetic relationships for these taxa can be inferred

Massive relic neutrinos in the galactic halo and the knee in the cosmic ray spectrum

Despite many efforts to find a reasonable explanation, the origin of the "knee" in the cosmic ray spectrum at energy around 10**15.5 eV remains mysterious. In this letter we suggest that the "knee" may be due to a GZK-like effect of cosmic rays interacting with massive neutrinos in the galactic halo. Simple kinematics connects the location of the "knee" with the mass of the neutrinos, and, while the required interaction cross section is larger than that predicted by the Standard Model, it can be accommodated by a small neutrino magnetic dipole moment. The values for the neutrino parameters obtained from the analysis of existing experimental data are compatible with present laboratory bounds.Comment: 8 pages, 1 figure, uses RevTe

An exploration of Keyes’ two-continuum model of mental health in athletes: resilience, mental illness and performance

Keyes’ (2005) two-continuum model of mental health posits two related, but distinct dimensions (1: the presence or absence of mental health – MH; 2: the presence or absence of mental illness - MI). Theoretically, athletes could experience both positive MH and symptoms of MI. Alternatively, athletes could be free from MI, but experience low levels of MH (what Keyes, 2005 terms languishing). This study presents preliminary results from an online survey examining (a) associations between resilience, MH, and MI, and (b) associations between MH, MI and performance. Participants comprised (male, n = 29; female, n = 28) athletes from a range of team (e.g., soccer, netball) and individual (e.g., triathlon, golf) sports (mean age = 23 ± 7 years). The survey comprised measures of MH (Keyes et al., 2008), MI (Connell et al., 2007), resilience (Wagnild & Young, 1987), and performance [the mean of 3 items assessing satisfaction in training, competition, and in sport generally from 0 (totally dissatisfied) to 100 (totally satisfied)]. Using proposed cut-off criteria (Connell et al, 2007; Keyes et al, 2008), some individuals (12%) reported both severe MI and high MH. In addition, a modest, negative relationship (r = -.40, p = .003) between MH and MI lends some support to Keyes’ model. Resilience (personal competence) was associated with MH (r = .50, p < .01), and MI(r = -.34, p = .01). Resilience (acceptance of self and life) was not associated with MI (r = -.24, p = .08), but was associated with MH (r = .39, p = .003). Zero-order correlations between MH and performance (r = .63, p < .001), and MI and performance (r = -.40, p = .003) are qualified by partial correlation analyses. The correlation between MH and performance remains significant when MI is controlled for (r = .59, p < .001). When MH is controlled for, the relationship between MI and performance (r = -.05, p = .76) is attenuated. Collectively, results provide some support for Keyes’ model and for considering MI and MH as separate factors influencing sport performance

Processing techniques development, volume 3

The author has identified the following significant results. Analysis of the geometric characteristics of the aircraft synthetic aperture radar (SAR) relative to LANDSAT indicated that relatively low order polynominals would model the distortions to subpixel accuracy to bring SAR into registration for good quality imagery. Also the area analyzed was small, about 10 miles square, so this is an additional constraint. For the Air Force/ERIM data, none of the tested methods could achieve subpixel accuracy. Reasons for this is unknown; however, the noisy (high scintillation) nature of the data and attendent unrecognizability of features contribute to this error. It is concluded that the quadratic model would adequately provide distortion modeling for small areas, i.e., 10 to 20 miles square

Plasma Physics

Contains reports on two research projects.U. S. Atomic Energy Commission (Contract AT(30-1)-1842

Implementation of ILLIAC 4 algorithms for multispectral image interpretation

Research has focused on the design and partial implementation of a comprehensive ILLIAC software system for computer-assisted interpretation of multispectral earth resources data such as that now collected by the Earth Resources Technology Satellite. Research suggests generally that the ILLIAC 4 should be as much as two orders of magnitude more cost effective than serial processing computers for digital interpretation of ERTS imagery via multivariate statistical classification techniques. The potential of the ARPA Network as a mechanism for interfacing geographically-dispersed users to an ILLIAC 4 image processing facility is discussed

Visualization of hydrogen injection in a scramjet engine by simultaneous PLIF imaging and laser holographic imaging

Flowfield characterization has been accomplished for several fuel injector configurations using simultaneous planar laser induced fluorescence (PLIF) and laser holographic imaging (LHI). The experiments were carried out in the GASL-NASA HYPULSE real gas expansion tube facility, a pulsed facility with steady test times of about 350 microsec. The tests were done at simulated Mach numbers 13.5 and 17. The focus of this paper is on the measurement technologies used and their application in a research facility. The HYPULSE facility, the models used for the experiments, and the setup for the LHI and PLIF measurements are described. Measurement challenges and solutions are discussed. Results are presented for experiments with several fuel injector configurations and several equivalence ratios

Estimation of ocean subsurface thermal structure from surface parameters : a neural network approach

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 31 (2004): L20308, doi:10.1029/2004GL021192.Satellite remote sensing provides diverse and useful ocean surface observations. It is of interest to determine if such surface observations can be used to infer information about the vertical structure of the ocean's interior, like that of temperature profiles. Earlier studies used either sea surface temperature or dynamic height/sea surface height to infer the subsurface temperature profiles. In this study we have used neural network approach to estimate the temperature structure from sea surface temperature, sea surface height, wind stress, net radiation, and net heat flux, available from an Arabian Sea mooring from October 1994 to October 1995, deployed by the Woods Hole Oceanographic Institution. On the average, 50% of the estimations are within an error of ±0.5°C and 90% within ±1.0°C. The average RMS error between the estimated temperature profiles and in situ observations is 0.584°C with a depth-wise average correlation coefficient of 0.92.This work is carried out as a part of the Department of Ocean Development project

Estimation of mixed-layer depth from surface parameters

Author Posting. © Sears Foundation for Marine Research, 2006. This article is posted here by permission of Sears Foundation for Marine Research for personal use, not for redistribution. The definitive version was published in Journal of Marine Research 64 (2006): 745-758, doi:10.1357/002224006779367285.Mixed layer depth (MLD) is an important oceanographic parameter. However, the lack of direct observations of MLD hampers both specification and investigation of its spatial and temporal variability. An important alternative to direct observation would be the ability to estimate MLD from surface parameters easily available from satellites. In this study, we demonstrate estimation of MLD using Artificial Neural Network methods and surface meteorology from a surface mooring in the Arabian Sea. The estimated MLD had a root mean square error of 7.36 m and a coefficient of determination (R2) of 0.94. About 67% (91%) of the estimates lie within ± 5 m (± 10 m) of the MLD determined from temperature sensors on the mooring