Automated Classification of Stellar Spectra. II: Two-Dimensional Classification with Neural Networks and Principal Components Analysis

We investigate the application of neural networks to the automation of MK spectral classification. The data set for this project consists of a set of over 5000 optical (3800-5200 AA) spectra obtained from objective prism plates from the Michigan Spectral Survey. These spectra, along with their two-dimensional MK classifications listed in the Michigan Henry Draper Catalogue, were used to develop supervised neural network classifiers. We show that neural networks can give accurate spectral type classifications (sig_68 = 0.82 subtypes, sig_rms = 1.09 subtypes) across the full range of spectral types present in the data set (B2-M7). We show also that the networks yield correct luminosity classes for over 95% of both dwarfs and giants with a high degree of confidence. Stellar spectra generally contain a large amount of redundant information. We investigate the application of Principal Components Analysis (PCA) to the optimal compression of spectra. We show that PCA can compress the spectra by a factor of over 30 while retaining essentially all of the useful information in the data set. Furthermore, it is shown that this compression optimally removes noise and can be used to identify unusual spectra.Comment: To appear in MNRAS. 15 pages, 17 figures, 7 tables. 2 large figures (nos. 4 and 15) are supplied as separate GIF files. The complete paper can be obtained as a single gziped PS file from http://wol.ra.phy.cam.ac.uk/calj/p1.htm

The Application of Artificial Neural Networks to Stellar Classification

We are working on a project to automate the multi-parameter classification of stellar spectra using Principal Components Analysis (PCA) and Artificial Neural Networks. We present here the usefulness of PCA as a form of spectral data compression, and our results to date of classification on the MK system

Some of the Effects of Domestic Sewage Discharged Into Hickman and Jessamine Creeks in Jessamine County, Kentucky

A 6-week study was made in the summer of 1971 as an initial effort to determine the extent of pollution that the three sewage disposal plants in Jessamine County, Kentucky, are contributing to its streams. With the rapid population increase in Lexington and nearby municipalities, this study should furnish a basis of comparison for future investigations. Eighteen collecting stations were established in riffle areas of Hickman and Jessamine Creeks, and coliform bacteria, macro-invertebrate populations, fish populations and chemical water quality of each riffle area were studied. Hickman Creek\u27s flow was augmented by approximately 3,100,000 gallons/day (11,735 -m3/day) from one of the City of Lexington\u27s sewage disposal plants, and Jessamine Creek\u27s flow by 500,000 gallons/day (1,893 m3/day) from the cities of Nicholasville and Wilmore. The Lexington and Wilmore facilities were greatly overloaded. Chemical analyses were directed toward finding out the fluctuations of phosphates, sulfates, and nitrates. Water disappearing through limestone faults posed investigational problems. Hickman Creek showed evidences of pollution for a greater distance downstream than did Jessamine. Diversity of clean water indicator organisms was higher in lower Jessamine than in lower Hickman; this was particularly true for darters (Etheostoma) and stoneflies (Plecoptera). Jessamine Creek was also supporting limited game fishing

Diverse CD81 proteins support hepatitis C virus infection.

Hepatitis C virus (HCV) entry is dependent on CD81. To investigate whether the CD81 sequence is a determinant of HCV host range, we expressed a panel of diverse CD81 proteins and tested their ability to interact with HCV. CD81 large extracellular loop (LEL) sequences were expressed as recombinant proteins; the human and, to a low level, the African green monkey sequences bound soluble HCV E2 (sE2) and inhibited infection by retrovirus pseudotype particles bearing HCV glycoproteins (HCVpp). In contrast, mouse or rat CD81 proteins failed to bind sE2 or to inhibit HCVpp infection. However, CD81 proteins from all species, when expressed in HepG2 cells, conferred susceptibility to infection by HCVpp and cell culture-grown HCV to various levels, with the rat sequence being the least efficient. Recombinant human CD81 LEL inhibited HCVpp infectivity only if present during the virus-cell incubation, consistent with a role for CD81 after virus attachment. Amino acid changes that abrogate sE2 binding (I182F, N184Y, and F186S, alone or in combination) were introduced into human CD81. All three amino acid changes in human CD81 resulted in a molecule that still supported HCVpp infection, albeit with reduced efficiency. In summary, there is a remarkable plasticity in the range of CD81 sequences that can support HCV entry, suggesting that CD81 polymorphism may contribute to, but alone does not define, the HCV susceptibility of a species. In addition, the capacity to support viral entry is only partially reflected by assays measuring sE2 interaction with recombinant or full-length CD81 proteins

Our changing Sun

Stellar astronomy tells us much about the long-term evolution of our Sun while forensic evidence (for example, cosmic-ray products in ice cores) gives us indications of its fluctuations over the last millennium. However, such studies do not give us a sufficiently detailed understanding of solar change over the last century to allow us to detect and quantify any role that the Sun might have played in the observed rise in average surface temperatures on Earth. This paper describes recent research that has filled this gap by applying advances in our understanding of the effects and structure of the solar wind to historical data on the Earth's magnetic field

User-centered development of a Virtual Research Environment to support collaborative research events

This paper discusses the user-centred development process within the Collaborative Research Events on the Web (CREW) project, funded under the JISC Virtual Research Environments (VRE) programme. After presenting the project, its aims and the functionality of the CREW VRE, we focus on the user engagement approach, grounded in the method of co-realisation. We describe the different research settings and requirements of our three embedded user groups and the respective activities conducted so far. Finally we elaborate on the main challenges of our user engagement approach and end with the project’s next steps

2008 Farm Bill Decision Tools

This article describes a tool developed by Oklahoma Cooperative Extension Service to aid in the decision to enroll in a new commodity program contained in the 2008 Farm Bill. Producers have the option to enroll in the Direct Counter-Cyclical Payment (DCP) program or the Average Crop Revenue Election (ACRE) program. The choice between ACRE and DCP is an important decision for farm profitability. The ACRE program is complex, and the calculation of potential ACRE payments can be quite daunting. The ACRE decision tool was developed to perform the calculations necessary to estimate potential ACRE payments for the 2009-2012 crop years