Diagnostic Alleles From Electrophoresis Distinguish Two Noctuid Pest Species, \u3ci\u3eHydraecia Immanis\u3c/i\u3e and \u3ci\u3eH. Micacea\u3c/i\u3e (Lepidoptera: Noctuidae).

Native hop vine borer (Hydraecia immanis) and introduced potato stem borer (H. micacea) populations in Midwest corn have reached noticeable levels near the Great Lakes plant community ecotone between boreal forests and temperate deciduous forests. The hop vine borer is more specialized in its diet and occurs in corn generally south of the plant community ecotone, whereas the potato stem borer is polyphagous and occurs in corn mostly north of the Great Lakes plant transition zone. We analyzed the genetic composition of each species using cellulose acetate electrophoresis and resolved 19 loci of which 6 exhibited fixed or nearly fixed allelic differences. We expect that this will be useful in determining the degree of hybridization where the two species become sympatric due to expected continued range expansions in Michigan, Wisconsin, and New York State

Analysis of Uncharacterized mKiaa1211 Expression during Mouse Development and Cardiovascular Morphogenesis

Mammalian Kiaa1211 and Kiaa1211-like are a homologous pair of uncharacterized, highly conserved genes cloned from fetal and adult brain cDNA libraries. Herein we map the in utero spatiotemporal expression of mKiaa1211 and mKiaa1211L mRNA and their expression patterns in postnatal testis, skin, gastrointestinal, and adipose progenitor tissues. Significantly, mKiaa1211 is present throughout the early stages of mouse heart development, particularly in the second heart field (SHF) lineage as it differentiates from mesenchymal cells into cardiomyocytes. We also show that mKiaa1211 is expressed within several early neuronal tissues destined to give rise to central, peripheral, and sympathetic nervous system structures. Expression profiling revealed that the paralog mKiaa1211L is not expressed during the normal developmental process and that mKiaa1211 expression was noticeably absent from most adult terminally differentiated tissues. Finally, we confirm that a previously uncharacterized CRISPR/CAS-generated mKiaa1211 mouse mutant allele is hypomorphic

Optimal random search for a single hidden target

A single target is hidden at a location chosen from a predetermined probability distribution. Then, a searcher must find a second probability distribution from which random search points are sampled such that the target is found in the minimum number of trials. Here it will be shown that if the searcher must get very close to the target to find it, then the best search distribution is proportional to the square root of the target distribution. For a Gaussian target distribution, the optimum search distribution is approximately a Gaussian with a standard deviation that varies inversely with how close the searcher must be to the target to find it. For a network, where the searcher randomly samples nodes and looks for the fixed target along edges, the optimum is to either sample a node with probability proportional to the square root of the out degree plus one or not at all.Comment: 13 pages, 5 figure

Flexible electrical conductors for high-temperature switchgear

Arch-shaped conductors fabricated from flat strips of beryllium oxide dispersion-strengthened copper alloy serve as flexible electrical connectors capable of operating in 1000 deg F temperature range, under vacuum conditions for periods of 10,000 hours or more without failure

STATCOM power frequency model with VSC charging dynamics and its application in the power system stability analysis

In this paper the STATCOM power frequency model is derived with voltage source converter charging dynamics. The main control and supplementary control are then added for voltage regulation and damping power oscillation. The integrated STATCOM system model is used in power system transient stability analysis. Computer program is developed based on Power System Toolbox of MATLAB. Computer test results show clearly the effects of the STATCOM on system dynamic behavior and transfer limit.published_or_final_versio

(Teff,log g,[Fe/H]) Classification of Low-Resolution Stellar Spectra using Artificial Neural Networks

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic analysis are no longer practical. New tools are required that are capable of extracting quickly and with reasonable accuracy important basic stellar parameters coded in the spectra. Recent analyses of Artificial Neural Networks (ANNs) applied to the classification of astronomical spectra have demonstrated the ability of this concept to derive estimates of temperature and luminosity. We have adapted the back-propagation ANN technique developed by von Hippel et al. (1994) to predict effective temperatures, gravities and overall metallicities from spectra with resolving power ~ 2000 and low signal-to-noise ratio. We show that ANN techniques are very effective in executing a three-parameter (Teff,log g,[Fe/H]) stellar classification. The preliminary results show that the technique is even capable of identifying outliers from the training sample.Comment: 6 pages, 3 figures (5 files); to appear in the proceedings of the 11th Cambridge Workshop on Cool Stars, Stellar Systems and the Sun, held on Tenerife (Spain), October 1999; also available at http://hebe.as.utexas.ed

Local health department use of Twitter to disseminate diabetes information, United States

INTRODUCTION: Diabetes may affect one-third of US adults by 2050. Adopting a healthful diet and increasing physical activity are effective in preventing type 2 diabetes and decreasing the severity of diabetes-related complications. Educating and informing the public about health problems is a service provided by local health departments (LHDs). The objective of this study was to examine how LHDs are using social media to educate and inform the public about diabetes. METHODS: In June 2012 we used NVivo 10 to collect all tweets ever posted from every LHD with a Twitter account and identified tweets about diabetes. We used a 2010 National Association of County and City Health Officials survey to compare characteristics of LHDs that tweeted about diabetes with those that did not. Content analysis was used to classify each tweet topic. RESULTS: Of 217 LHDs with Twitter accounts, 126 had ever tweeted about diabetes, with 3 diabetes tweets being the median since adopting Twitter. LHDs tweeting about diabetes were in jurisdictions with larger populations and had more staff and higher spending than LHDs not tweeting about diabetes. They were significantly more likely to employ a public information specialist and provide programs in diabetes-related areas. There was also a weak positive association between jurisdiction diabetes rate and the percentage of all tweets that were about diabetes (r = .16; P = .049). CONCLUSION: LHDs are beginning to use social media to educate and inform their constituents about diabetes. An understanding of the reach and effectiveness of social media could enable public health practitioners to use them more effectively