1862-02-12 Charles Sampson recommends Charles Watson for promotion

https://digitalmaine.com/cw_me_3rd_regiment_corr/1253/thumbnail.jp

1861-12-10 Charles A.L. Sampson recommends Woodbury Hall for appointment as Lieutenant

https://digitalmaine.com/cw_me_3rd_regiment_corr/1195/thumbnail.jp

1862-02-10 Charles Sampson cannot recommend any to fill the captain\u27s vacancy in Company C

https://digitalmaine.com/cw_me_3rd_regiment_corr/1251/thumbnail.jp

1861-12 Charles A.L. Sampson recommends Frank H. Rowland for a commission

https://digitalmaine.com/cw_me_3rd_regiment_corr/1185/thumbnail.jp

1862-02-20 Charles Sampson writes Governor Washburn regarding desertion of Mr. Chadwick after Bull Run

https://digitalmaine.com/cw_me_3rd_regiment_corr/1259/thumbnail.jp

Identification of QTLs for grain yield and other traits in tropical maize under high and low soil-nitrogen environments.

Article purchased; Published online: 03 Nov 2017Low soil Nitrogen (low-N) is one of the most important abiotic stresses responsible for significant yield losses in maize (Zea mays. L.). The development and commercialization of low N tolerant genotypes can contribute to improved food security in developing countries. However, selection for low N tolerance is difficult because it is a complex trait with strong interaction between genotypes and environments. Marker assisted breeding holds great promise for improving such complex traits more efficiently in less time, but requires markers associated with the trait of interest. In this study, 150 BC2F1 families of CML 444 x CML 494 were evaluated at two location for two consecutive seasons to identify SNP markers associated with quantitative trait loci (QTLs) for yield and other agronomic traits under low- and high-N environments. A total of 13 QTLs were identified with 158 SNP markers, of which nine and four QTLs were detected under low- and high-N environments, respectively. Five QTLs one each for grain yield (qgy-1), days to silking (qdts-1) and anthesis- silking interval (qasi-6), and two for stay green characteristic (qsg-1 and qsg-4) were close to their adjacent markers, with an interval of 0.7 to 5.2 cM between them and explained phenotypic variance of 9 to 21%. These QTLs would be invaluable for rapid introgression of genomic regions into maize populations using marker assisted selection (MAS) approaches. However, further validation of these QTLs is needed before use in MAS

Segregation effects on the properties of (AuAg)147

AuAg nanoclusters are promising supported co-catalysts for photocatalytic hydrogen reduction. However, beyond the quantum regime (N > 100) little is known about how the electronic properties of these nanoparticles are affected by chemical ordering. We investigate the effects of chemical ordering on the properties of 147-atom cuboctahedral AuAg nanoclusters, using empirical potentials coupled with an atomic-swap basin-hopping search to optimise the elemental distribution, with the lowest energy arrangements then reminimised using Density Functional Theory (DFT). Force-field calculations show Au atoms preferentially occupy sub-surface positions in the bimetallic structures, which results in the formation of a pseudo-onion structure for Ag-rich compositions. At the DFT-level, however, an Ag core surrounded by an Au shell (Ag@Au) is energetically favoured, as electron density can be drawn more readily when Au atoms are positioned on the nanocluster surface, thus resulting in a partial negative charge. Core@shell configurations are analogous to structures that can be chemically synthesised, and further detailed electronic analysis is discussed in the context of nanocluster applications to co-catalysed photocatalysis