Roosevelt County Courthouse Square Improvements

The goal of this process was to provide as much knowledge and insight as possible to the city of Portales with the intention that they would use this knowledge and this booklet as a tool to write an RFP that would get them the type of end product they want. While shifting from design issues to RFP issues it quickly became apparent that the RFP written for this project would need to be written better than what the current standard of RFP is in the state. This led me on a search for an RFP suited for this project. I found many advanced RFP around the country in cities that are getting very high levels of work done. A key component of these cities however, was a defined official policy on how their city is looking at projects covered by an RFP in addition to how the city does business as a whole. Therefore this booklet is indeed an attempt to shed light on the important issues that surround the Roosevelt county courthouse and in turn the city of Portales. In addition to this booklet, an RFP will be included that will give its users a clear understanding and direction from which to move forward. Lastly I have assembled a policy agenda that will support the issues set out in this report.https://digitalrepository.unm.edu/dpac_projects/1000/thumbnail.jp

The Massive Pulsar PSR J1614-2230: Linking Quantum Chromodynamics, Gamma-ray Bursts, and Gravitational Wave Astronomy

The recent measurement of the Shapiro delay in the radio pulsar PSR J1614-2230 yielded a mass of 1.97 +/- 0.04 M_sun, making it the most massive pulsar known to date. Its mass is high enough that, even without an accompanying measurement of the stellar radius, it has a strong impact on our understanding of nuclear matter, gamma-ray bursts, and the generation of gravitational waves from coalescing neutron stars. This single high mass value indicates that a transition to quark matter in neutron-star cores can occur at densities comparable to the nuclear saturation density only if the quarks are strongly interacting and are color superconducting. We further show that a high maximum neutron-star mass is required if short duration gamma-ray bursts are powered by coalescing neutron stars and, therefore, this mechanism becomes viable in the light of the recent measurement. Finally, we argue that the low-frequency (<= 500 Hz) gravitational waves emitted during the final stages of neutron-star coalescence encode the properties of the equation of state because neutron stars consistent with this measurement cannot be centrally condensed. This will facilitate the measurement of the neutron star equation of state with Advanced LIGO/Virgo.Comment: Accepted for publication in ApJ

Prediction of the functional properties of ceramic materials from composition using artificial neural networks

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the basis of their dielectric and ionic properties. Dielectric materials are of interest in telecommunication applications where they are used in tuning and filtering equipment. Ionic and mixed conductors are the subjects of a concerted effort in the search for new materials that can be incorporated into efficient, clean electrochemical devices of interest in energy production and greenhouse gas reduction applications. Multi-layer perceptron ANNs are trained using the back-propagation algorithm and utilise data obtained from the literature to learn composition-property relationships between the inputs and outputs of the system. The trained networks use compositional information to predict the relative permittivity and oxygen diffusion properties of ceramic materials. The results show that ANNs are able to produce accurate predictions of the properties of these ceramic materials which can be used to develop materials suitable for use in telecommunication and energy production applications

Rapid differentiation of sexual signals in invasive toads: call variation among populations

Advertisement calls tend to differ among populations, based on morphological and environmental factors, or simply geographic distance, in many taxa. Invasive cane toads (Rhinella marina) were introduced to Australia in 1935 and their distribution has expanded at increasing rates over time. Rapid evolution occurred in morphological and behavioural characters that accelerate dispersal, but the effects of rapid expansion on sexual signals have not been examined. We collected advertisement calls from four populations of different ages since invasion, and analysed the geographic differentiation of seven call parameters. Our comparisons indicate that the calls of R. marina differ among Australian populations. The signal variation was not simply clinal with respect to population age, climate, or morphological differentiation. We suggest that selection on signalling among populations has been idiosyncratic and may reflect local female preferences or adaptation to environmental factors that are not clinal such as energy availability

Soluble ephrin a1 is necessary for the growth of HeLa and SK-BR3 cells

<p>Abstract</p> <p>Background</p> <p>Ephrin A1 (EFNA1) is a member of the A-type ephrin family of cell surface proteins that function as ligands for the A-type Eph receptor tyrosine kinase family. In malignancy, the precise role of EFNA1 and its preferred receptor, EPHA2, is controversial. Several studies have found that EFNA1 may suppress EPHA2-mediated oncogenesis, or enhance it, depending on cell type and context. However, little is known about the conditions that influence whether EFNA1 promotes or suppresses tumorigenicity. EFNA1 exists in a soluble form as well as a glycophosphatidylinositol (GPI) membrane attached form. We investigated whether the contradictory roles of EFNA1 in malignancy might in part be related to the existence of both soluble and membrane attached forms of EFNA1 and potential differences in the manner in which they interact with EPHA2.</p> <p>Results</p> <p>Using a RNAi strategy to reduce the expression of endogenous EFNA1 and EPHA2, we found that both EFNA1 and EPHA2 are required for growth of HeLa and SK-BR3 cells. The growth defects could be rescued by conditioned media from cells overexpressing soluble EFNA1. Interestingly, we found that overexpression of the membrane attached form of EFNA1 suppresses growth of HeLa cells in 3D but not 2D. Knockdown of endogenous EFNA1, or overexpression of full-length EFNA1, resulted in relocalization of EPHA2 from the cell surface to sites of cell-cell contact. Overexpression of soluble EFNA1 however resulted in more EPHA2 distributed on the cell surface, away from cell-cell contacts, and promoted the growth of HeLa cells.</p> <p>Conclusions</p> <p>We conclude that soluble EFNA1 is necessary for the transformation of HeLa and SK-BR3 cells and participates in the relocalization of EPHA2 away from sites of cell-cell contact during transformation.</p

Prediction of the functional properties of ceramic materials from composition using artificial neural networks

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the basis of their dielectric and ionic properties. Dielectric materials are of interest in telecommunication applications, where they are used in tuning and filtering equipment. Ionic and mixed conductors are the subjects of a concerted effort in the search for new materials that can be incorporated into efficient, clean electrochemical devices of interest in energy production and greenhouse gas reduction applications. Multi-layer perceptron ANNs are trained using the back-propagation algorithm and utilise data obtained from the literature to learn composition–property relationships between the inputs and outputs of the system. The trained networks use compositional information to predict the relative permittivity and oxygen diffusion properties of ceramic materials. The results show that ANNs are able to produce accurate predictions of the properties of these ceramic materials, which can be used to develop materials suitable for use in telecommunication and energy production applications