Found 415 results
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R. A. Reinhardt, Johnson, G. K., and Tussing, G. J., Miniature fiber optics for improved detection of root irregularities., Gen Dent, vol. 36, no. 6, pp. 461-6, 1988.
K. Wollstein, O'Connor, C., Gear, J., and Hoagland, R., Minimize the Bad Days: Wildland Fire Response and Suppression Success, Rangelands, vol. 44, no. 3, pp. 187 - 193, 2022.
B. Sorte, G., C., M., C., D., H., C., K., and R., M., Minimum Parcel Size for Viable Adaptive Farms in Umatilla County: An Economic Analysis, 2010.
S. Buccola, Li, C., and Reimer, J., Minimum Wages, Immigration Control, and Agricultural Labor Supply, American Journal of Agricultural Economics, vol. 94, no. 2, pp. 464 - 470, 2012.
J. M. Antle, Diagana, B., Stoorvogel, J. J., and Valdivia, R. O., Minimum-data analysis of ecosystem service supply in semi-subsistence agricultural systems, Australian Journal of Agricultural and Resource Economics, vol. 54, no. 4, pp. 601 - 617, 2010.
R. Haapala and Murthy, G. S., Mir Abbas Bozorgirad, Hao Zhang, Karl, 2012.
L. K. Mathew, Andreasen, E. A., and Tanguay, R. L., Misexpression of R-Spondin1 Impairs Tissue Regeneration. 2007.
J. Lee, Dossett, M., and Finn, C. E., Mistaken Identity: Clarification of Rubus coreanus Miquel (Bokbunja), Molecules, vol. 193111718910777101739481339465659696944, no. 7, pp. 10524 - 10533, 2014.
J. H. Davis, Griffith, S. M., Horwath, W. R., Steiner, J. J., and Myrold, D. D., Mitigation of Shallow Groundwater Nitrate in a Poorly Drained Riparian Area and Adjacent Cropland, Journal of Environment Quality, vol. 36, no. 3, p. 628, 2007.
N. J. Patenaude, Portway, V., Bannister, J. L., Best, P., Payne, R., Rowntree, V., Rivarola, M., and C. Baker, S., Mitochondrial DNA diversity and population structure among southern right whales (Eubalaena australis), Journal of Heredity, 2007.
L. E. Pimper, C. Baker, S., R. Goodall, N. P., ía, C., and Remis, íaI., Mitochondrial DNA variation and population structure of Commerson’s dolphins (Cephalorhynchus commersonii) in their southernmost distribution, Conservation Genetics, vol. 11, no. 6, pp. 2157 - 2168, 2010.
S. Kolluri, Bruey-Sedano, N., Cao, X., Lin, B., Lin, F., Han, Y. - H., Dawson, M. I., and Zhang, X. -kun, Mitogenic effect of orphan receptor TR3 and its regulation by MEKK1 in lung cancer cells, Molecular and cellular biology, vol. 23, pp. 8651–8667, 2003.
N. T. Schmitt, MC, D., CS, B., N, G., Childerhouse, S., AM, P., DJ, S., Albertson, G. R., C, O., C, G., M. Poole, M., R, H., R, C., D, P., CS, J., SN, J., and R, P., Mixed stock analysis of humpback whales (Megaptera novaeangliae) on Antarctic feeding grounds, 2015.
J. - E. Kim, Kwon, J. Yeon, Lee, D. Eun, Kang, N. Joo, Heo, Y. - S., Lee, K. Won, and Lee, H. Joo, MKK4 is a novel target for the inhibition of tumor necrosis factor-alpha-induced vascular endothelial growth factor expression by myricetin., Biochem Pharmacol, vol. 77, no. 3, pp. 412-21, 2009.
S. L. Smith-Roe, Hegan, D. Campisi, Glazer, P. M., and Buermeyer, A. B., Mlh1-dependent suppression of specific mutations induced in vivo by the food-borne carcinogen 2-amino-1-methyl-6-phenylimidazo [4,5-b] pyridine (PhIP), Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, vol. 594, no. 1-2, pp. 101 - 112, 2006.
M. James Rinella and Sheley, R., A model for predicting invasive weed and grass dynamics. I. Model development, Weed Science, vol. 5365122612112881321131, no. 05, pp. 586 - 593, 2005.
M. James Rinella and Sheley, R., A model for predicting invasive weed and grass dynamics. II. Accuracy evaluation, Weed Science, vol. 5336511583335, no. 05, pp. 605 - 614, 2005.
F. W. R. Chaplen, Pérez, J., Bottomley, P. J., Buchanan, A., Murthy, G. S., Chang, J. H., and Sayavedra-Soto, L. A., Model integration for elucidating the coupled environmental dynamics of the nitrifying bacteria Nitrosomonas europaea and Nitrobacter winogradskyi, in ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2014.
R. äre, Wang, C., and Seavert, C., A model of site-specific nutrient management, Applied Economics, vol. 44131, no. 33, pp. 4369 - 4380, 2012.
S. L. Uesugi, Yarwood, R. R., Selker, J., and Bottomley, P. J., A model that uses the induction phase of lux gene-dependent bioluminescence in Pseudomonas fluorescens HK44 to quantify cell density in translucent porous media, Journal of microbiological methods, vol. 47, pp. 315–322, 2001.
B. Turner, Tidwell, V., Fernald, A. G., Rivera, é, Rodriguez, S., Guldan, S., Ochoa, C., Hurd, B., Boykin, K., and Cibils, A., Modeling Acequia Irrigation Systems Using System Dynamics: Model Development, Evaluation, and Sensitivity Analyses to Investigate Effects of Socio-Economic and Biophysical Feedbacks, Sustainability, vol. 85010, no. 10, p. 1019, 2016.
D. B. Hannaway, Modeling and Mapping Forage Potential Productivity in Sichuan Province and Oregon. 2013.
R. D. Stewart, Rupp, D. E., Najm, M. R. Abou, and Selker, J., Modeling effect of initial soil moisture on sorptivity and infiltration, Water Resources Research, vol. 49, pp. 7037–7047, 2013.
W. H. Bisson, Koch, D. C., Donnell, E. F. ’, Khalil, S. M., Kerkvliet, N. I., Tanguay, R. L., Abagyan, R., and Kolluri, S., Modeling of the Aryl Hydrocarbon Receptor (AhR) Ligand Binding Domain and Its Utility in Virtual Ligand Screening to Predict New AhR Ligands, Journal of Medicinal Chemistry, vol. 52, no. 18, pp. 5635 - 5641, 2009.
W. H. Bisson, Koch, D. C., O'Donnell, E. F., Khalil, S. M., Kerkvliet, N. I., Tanguay, R. L., Abagyan, R., and Kolluri, S. Kumar, Modeling of the aryl hydrocarbon receptor (AhR) ligand binding domain and its utility in virtual ligand screening to predict new AhR ligands., J Med Chem, vol. 52, no. 18, pp. 5635-41, 2009.