Two New Species of Myxozoa, \u3ci\u3eMyxobolus inaequus\u3c/i\u3e sp. n. and \u3ci\u3eHenneguya theca\u3c/i\u3e sp. n. from the Brain of a South American Knife Fish, \u3ci\u3eEigemannia virescens\u3c/i\u3e (V.)

Two new species of Myxozoa from the brain of the green knife fish Eigemannia virescens are described: Myxobolus inaequus sp. n. has an unusually large spore body and extremely unequal polar capsules, and Henneguya theca sp. n. has an attenuated spore encased in a sheath not previously described in other Myxozoa. Only spores of the two species were observed, and infections caused no obvious pathological changes in the brain

Statistical Analysis of Nonlinearly Propagating Acoustic Noise in a Tube

Acoustic fields radiated from intense, turbulent sound sources such as military jets and rockets are not well understood. In addition to the inherent random nature of the field, the amplitudes of the acoustic vibration are great enough that nonlinear considerations are necessary for modeling. In order to better understand these complex fields, high-amplitude noise in a tube is measured and analyzed. The basics of nonlinear acoustics will be covered briefly in this talk. Additionally, some statistical tools that are useful in analyzing random systems, such as probability density functions and skewness, will be explained. The measured evolution of the skewness of the first time derivative of high-amplitude noise in a tube will be presented

Noncirculant Toeplitz matrices all of whose powers are Toeplitz

summary:Let $a$, $b$ and $c$ be fixed complex numbers. Let $M_n(a,b,c)$ be the $n\times n$ Toeplitz matrix all of whose entries above the diagonal are $a$, all of whose entries below the diagonal are $b$, and all of whose entries on the diagonal are $c$. For $1\leq k\leq n$, each $k\times k$ principal minor of $M_n(a,b,c)$ has the same value. We find explicit and recursive formulae for the principal minors and the characteristic polynomial of $M_n(a,b,c)$. We also show that all complex polynomials in $M_n(a,b,c)$ are Toeplitz matrices. In particular, the inverse of $M_n(a,b,c)$ is a Toeplitz matrix when it exists

A mode-based metric for evaluating global climate models

Climate models are software tools that simulate the climate system and require evaluation to assess their skill, guide their development, and assist in selecting model simulations from among the many different ones available. There are a variety of methods and approaches that can be used to evaluate models. But there is no one best method and many possible and valid approaches exist. Models contain inherent uncertainties which complicate their evaluation, and include limitations in the knowledge of climate process dynamics and structural errors in constructing the models. Similar to the multiplicity of methods for the evaluation of model simulations, there also exist many possible approaches to addressing these sources of uncertainty. The challenge with uncertainty, is the difficulty in disaggregating it from the underlying element of legitimate chaotic behaviour in complex systems. In response, this dissertation is primarily one of methodological development to contribute to new ways of addressing the model evaluation challenge. The work defines and demonstrates a new evaluation method which complements the existing toolset. Specifically, the method defines a model performance metric that focuses on the extent to which a model is able to simulate global modes of climate variability (modes, e.g.: ENSO) evident in the observed climate data. Modes are one aspect of the climate that can be evaluated and are fundamental to model skill. Therefore their credible simulation is a necessary (but not sufficient) condition to ensuring that models are producing the right result (appropriate variability on the range of spatial and temporal scales) for the right reason. By ranking models by this metric of their skill in capturing fundamental global modes, poorly performing model simulations can be identified for potential exclusion (discounted). This metric therefore serves as a potential method to assist in the management of uncertainty when assessing multi-model data. The method develops a novel application of Independent Component Analysis (ICA). ICA is used to find representations of modes in a record of the present day climate (represented by reanalysis data), and then their degree of manifestation in global models is assessed. Recognising the large volume of model data (highly autocorrelated in space and time) the technique includes a data reduction technique to facilitate the evaluation of multiple model simulations. The technique also includes a novel measure of variance to differentiate it from a similar technique (Principal Component Analysis), and offers an approach to improve the consistency of results (signals) when using an unmixing matrix initialized with random values. As reanalysis data is itself a model product (constrained by observations), the performance metric is tested for its strength in discriminating modes by using two different reanalysis datasets and a dataset containing only Gaussian noise. The metric is found to perform predictably, and clearly demonstrates the ability to discriminate signal from noise when using geopotential height (GHT, 700mb and 500mb) and near surface air temperature data (TAS). The dependency of model performance on the variable measured by any metric can be a problem for model evaluation, as it introduces the choice of which variable should be measured to assess model performance. The ICA-based metric is found to be slightly less sensitive to a change in model rank between GHT (700mb) and TAS, compared to a similar novel variance metric (Fourier Distance) and a mean climate metric (bias). The ICA application is also found to produce plausible representations of modes (static maps), while a direct association to known modes is left for future work due to inherit complexities. The plausibility, consistency, and rank sensitivity of the novel application of ICA, suggests it has value in assisting the evaluation of multi-model datasets and the ensemble members for any one model

Aminomethanol water elimination: Theoretical examination

The mechanism for the formation of hexamethylenetetraamine predicts the formation of aminomethanol from the addition of ammonia to formaldehyde. This molecule subsequently undergoes unimolecular decomposition to form methanimine and water. Aminomethanol is the predicted precursor to interstellar glycine, and is therefore of great interest for laboratory spectroscopic study, which would serve as the basis for observational searches. The height of the water loss barrier is therefore useful in the determination of an appropriate experimental approach for spectroscopic characterization of aminomethanol. We have determined the height of this barrier to be 55 kcal/mol at ambient temperatures. In addition, we have determined the infinite-pressure Rice-Ramsperger-Kassel-Marcus unimolecular decomposition rate to be < 10^(-25) s^(-1) at 300 K, indicating gas-phase kinetic stability for typical laboratory and hot core temperatures. Therefore, spectroscopic characterization of and observational searches for this molecule should be straightforward provided an efficient formation mechanism can be found

M–M Bond-Stretching Energy Landscapes for M_2(dimen)_(4)^(2+) (M = Rh, Ir; dimen = 1,8-Diisocyanomenthane) Complexes

Isomers of Ir_2(dimen)_(4)^(2+) (dimen = 1,8-diisocyanomenthane) exhibit different Ir–Ir bond distances in a 2:1 MTHF/EtCN solution (MTHF = 2-methyltetrahydrofuran). Variable-temperature absorption data suggest that the isomer with the shorter Ir–Ir distance is favored at room temperature [K = ~8; ΔH° = −0.8 kcal/mol; ΔS° = 1.44 cal mol^(–1) K^(–1)]. We report calculations that shed light on M_2(dimen)_(4)^(2+) (M = Rh, Ir) structural differences: (1) metal–metal interaction favors short distances; (2) ligand deformational-strain energy favors long distances; (3) out-of-plane (A_(2u)) distortion promotes twisting of the ligand backbone at short metal–metal separations. Calculated potential-energy surfaces reveal a double minimum for Ir_2(dimen)_(4)^(2+) (4.1 Å Ir–Ir with 0° twist angle and ~3.6 Å Ir–Ir with ±12° twist angle) but not for the rhodium analogue (4.5 Å Rh–Rh with no twisting). Because both the ligand strain and A_(2u) distortional energy are virtually identical for the two complexes, the strength of the metal–metal interaction is the determining factor. On the basis of the magnitude of this interaction, we obtain the following results: (1) a single-minimum (along the Ir–Ir coordinate), harmonic potential-energy surface for the triplet electronic excited state of Ir_2(dimen)_(4)^(2+) (R_(e,Ir–Ir) = 2.87 Å; F_(Ir–Ir) = 0.99 mdyn Å^(–1)); (2) a single-minimum, anharmonic surface for the ground state of Rh_2(dimen)_(4)^(2+) (R_(e,Rh–Rh) = 3.23 Å; F_(Rh–Rh) = 0.09 mdyn Å^(–1)); (3) a double-minimum (along the Ir–Ir coordinate) surface for the ground state of Ir_2(dimen)_(4)^(2+) (R_(e,Ir–Ir) = 3.23 Å; F_(Ir–Ir) = 0.16 mdyn Å^(–1))

Characterization of High-Power Rocket and Jet Noise Using Near-Field Acoustical Holography

Structural fatigue, hearing damage, and community disturbances are all consequences of rocket and jet noise, especially as they become more powerful. Noise-reduction schemes require accurate characterization of the noise sources within rocket plumes and jets. Nearfield acoustical holography (NAH) measurements were made to visualize the sound field in the jet exhaust region of an F-22 Raptor. This is one of the largest-scale applications of NAH since its development in the 1980s. A scan-based holographic measurement was made using a 90-microphone array with 15 cm regular grid spacing, for four engine power settings. The array was scanned through 93 measurement positions, along three different planes in a region near 7 m from the jet centerline and 23 m downstream. In addition, 50 fixed reference microphones were placed along the ground 11.6 m from the jet centerline, spanning 30.8 m. The reference microphones have been used to perform virtual coherence on the measurement planes. Statistically-optimized NAH (SONAH) has been used to backpropagate the sound field to the source region for low frequencies, and to identify jet noise characteristics. Ground reflection interference and other non-ideal measurement conditions must be dealt with. Details relating to jet coherence lengths and their relation to reference microphone requirements will be discussed. Preliminary results of this ongoing work will be presented. [Work supported by Air Force SBIR.

Characterization of Rocket and Jet Noise using Near-Field Acoustic Holography Methods

As rockets and jets on military aircraft become more powerful, the noise they produce can lead to structural fatigue, hearing damage, and community disturbances. Noise-reduction technologies and sound radiation prediction require accurate characterization of the noise sources within rocket plumes and jets. Near-field acoustical holography techniques were used to visualize the sound field in the region of the jet exhaust on a high-performance military jet. Holography requires a coherent measurement of the sound field, but the size of the jet made a dense measurement over the entire source region impractical. Thus, a scan-based measurement was performed, after which a partial field decomposition (PFD) procedure was used to tie together incoherent scans. Then, the effective aperture of the measurement was extended utilizing the rigid ground reflection and a processing technique called analytic continuation. Finally, the three-dimensional sound field was reconstructed using statistically-optimized near-field acoustical holography (SONAH). This is the first time such a map has been obtained for a full-scale military aircraft. [Work supported by Air Force SBIR.

A synthesis of aquatic science for management of Lakes Mead and Mohave: U.S. Geological Survey Circular 1381

Lake Mead provides many significant benefits that have made the modern development of the southwestern United States possible. The lake also provides important aquatic habitat for a wide variety of wildlife including endangered species, and a diversity of world-class water based recreational opportunities for more than 8 million visitors annually. It is one of the most extensively used and intensively monitored reservoirs in the United States. The largest reservoir by volume in the United States, it supplies critical storage of water supplies for more than 25 million people in three western states (California, Arizona, and Nevada). Storage within Lake Mead supplies drinking water and the hydropower to provide electricity for major cities including Las Vegas, Phoenix, Los Angeles, Tucson, and San Diego, and irrigation of greater than 2.5 million acres of croplands. Due to the importance of Lake Mead, multiple agencies are actively involved in its monitoring and research. These agencies have a long history of collaboration in the assessment of water quality, water-dependent resources, and ecosystem health. In 2004, the National Park Service obtained funds from the Southern Nevada Public Lands Management Act to enhance this partnership and expand monitoring and research efforts to increase the overall understanding of Lake Mead and Lake Mohave. Participating agencies included the National Park Service, Southern Nevada Water Authority, U.S. Geological Survey, Nevada Department of Wildlife, Bureau of Reclamation, U.S. Fish and Wildlife Service, University of Nevada, Las Vegas, and University of Nevada, Reno. Results of these important efforts have been presented in Lake Mead Science Symposia conducted in 2009 and 2012. The relationships forged by the collaboration led to the development in 2012 of the Lake Mead Ecosystem Monitoring (LaMEM) Work Group, which has formalized the partnership and documented an interagency purpose and mission statement with common objectives for protection of Lake Mead and Lake Mohave water quality and water-dependent resources. This Circular has been developed to summarize the state of the knowledge related to the interests and objectives of the LaMEM Work Group, to inform management and the public of current lake conditions, and identify future needs for monitoring and research. It is hoped that this report will provide a framework for continued long-term investigations and analysis of the environmental health of Lakes Mead and Mohave

Multi-scale Habitat Use of Male Ruffed Grouse in the Black Hills National Forest

Ruffed grouse (Bonasa umbellus) are native upland game birds and a management indicator species (MIS) for aspen (Populus tremuloides) in the Black Hills National Forest (Black Hills). Our objective was to assess resource selection of male ruffed grouse to identify the most appropriate scale to manage for aspen and ruffed grouse in the Black Hills. During spring 2007 and 2008, we conducted drumming surveys throughout the central and northern Black Hills to locate used and unused sites from which we compared habitat characteristics at increasing spatial scales. Aspen with \u3e70% overstory canopy cover (OCC) was important to the occurrence of ruffed grouse across all spatial scales, but was most influential within 1600 m of drumming sites. Probability of a site being used was maximized when 20% of the 1600-m scale (~804 ha) had aspen with \u3e70% OCC. Ruffed grouse also selected for areas with many small, regular shaped patches of aspen over those with few large patches. At the smallest scale evaluated of 200 m (~12.5 ha), ruffed grouse selected drumming logs in close proximity to high stem densities of aspen with a minimal presence of roads. Ponderosa pine (Pinus ponderosa) had a negative influence on site selection at the 400-m (~50 ha), 1600-m (~804 ha), and 4800-m (~7200 ha) scales. Management for ruffed grouse in the Black Hills as the MIS for aspen should focus on increasing the extent of aspen with a goal of at least 20% occurrence on the landscape. Management efforts also should incorporate multiple age and size classes of aspen with an emphasis on enhancing early successional habitat to provide valuable cover through increased stem densities