Section 17

EurekaMag Full Text Articles Chapter 16,726


Diop, H.; Keithly, W., R.J.; Kazmierczak, R., F.J.; Shaw, R., F. 2007: Predicting the abundance of white shrimp (Litopenaeus setiferus) from environmental parameters and previous life stages. Fisheries Research 86(1): 31-41
Bordel, S.; Muñoz, R.; Diaz, L.F.; Villaverde, S. 2007: Predicting the accumulation of harmful metabolic byproducts during the treatment of VOC emissions in suspended growth bioreactors. Environmental Science and Technology 41(16): 5875-5881
Corwin, D.; Rhoades, J.; Vaughan, P. 1994: Predicting the areal distribution of a non-point source pollutant at a regional scale. Paper er 1994 (2567 2581)
Nicholls, P.H. 1989: Predicting the availability of soil-applied pesticides. Aspects of Applied Biology (1): 173-186
Weegels, P.L.; Hamer, R.J. 1989: Predicting the baking quality of gluten. Cereal Foods World 34(2): 210-212
Van-Lent, T. 1995: Predicting the behavior of watersheds: the James River as an example. Bulletin (720) 7-8
Andac, C.A.; Andac, M.; Denizli, A. 2007: Predicting the binding properties of cibacron blue F3GA in affinity separation systems. International Journal of Biological Macromolecules 41(4): 430-438
Majumdar, P.; Majumdar, A. 2004: Predicting the breaking elongation of ring spun cotton yarns using mathematical, statistical, and artificial neural network models. Textile research journal 74(7): 652-655
Sauerbeck, D.; Styperek, P. 1984: Predicting the cadmium availability from different soils by CaC1 2-extraction. Processing and use of sewae sludge: proceedings of the third international symposium held at Brighton September 27-30-1983 edited by P L'Hermite and H Ott: 434
Gallian, J.; Peterson, C.; Stanger, C. 1984: Predicting the change in value of sugarbeets for different harvest dates. Current information series Cooperative Extension Service University of Idaho: 84 (747)
Panfilov, V.P. 1975: Predicting the changes in physical properties of soils in connection with the transfer of the river water in the south of western Siberia. Pochvovedenie 8 58-65
Bashir, M.A.; Radke, W. 2007: Predicting the chromatographic retention of polymers: poly(methyl methacrylate)s and polyacryate blends. Journal of Chromatography. a 1163(1-2): 86-95
Saj, T.; Sicotte, P. 2007: Predicting the competitive regime of female Colobus vellerosus from the distribution of food resources. International Journal of Primatology il; 28(2): 315-336
Carroll, N.M.htar, R.S.gerling, L. 1996: Predicting the cooling time for irregular shaped food products. Journal of food process engineering 19(4): 385-401
Carroll, N.M.htar, R.S.gerlind, L. 1994: Predicting the cooling time for irregular shapes. Paper er 1994 (3579 3599)
Albright, L.; Scott, N. 1974: Predicting the daily variations of air temperature inside buildings. Annual progress report: 1st 42-45
Tabuenca, M.C. 1976: Predicting the date of harvest in function of the climate. Fruit belge: th Quarter 44 (376) 277-280
Mikkelsen, S.A. 1981: Predicting the date of harvest of vining peas by means of growing-degree-days models. Acta Horticulturae 122: 211-221
Gigurova, M. 1983: Predicting the date of soybean seeding. Rasteniev'dni Nauki 7: 43-48
Cocozzelli, C. 1989: Predicting the decision of biological mothers to retain or relinquish their babies for adoption: implications for open placement. Child welfare 68(1): 33-44
Fletcher, R. 1992: Predicting the demand for grazed forages. Forestry research west US Department of Agriculture Forest Service: 12-16
Gallichand, J.L.gace, R. 1986: Predicting the depth of sediment in subsurface drains. American Society of Agricultural Engineers Microfiche collection: (fiche no 86-2565)
Jin, Y.; Xu, Y.; Xue, S.; Liu, H.; Zhao, J.; Xu, M. 2007: Predicting the development of early skin test sensitization in offspring of parents with asthma. European Journal of Clinical Investigation 37(6): 522-527
Coetzee, J.-A.B.rne, M.-J.H.ll, M., P. 2007: Predicting the distribution of Eccritotarsus catarinensis, a natural enemy released on water hyacinth in South Africa. Entomologia experimentalis et applicata 125(3): 237-247
Dawson, D.; Darr, L.; Robbins, C. 1993: Predicting the distribution of breeding forest birds in a fragmented landscape. Transactions of the North American Wildlife and Natural Resources Conference: 8th) 35-43
Annandale, G.W. 1984: Predicting the distribution of deposited sediment in southern African reservoirs. Challenges in African hydrology and water resources: proceedings Harare Symposium July 1984 edited by DE Walling SSD Foster P Wurzel: 558
Matero, S.; Pajander, J.; Soikkeli, A.-M.; Reinikainen, S.-P.; Lahtela-Kakkonen, M.; Korhonen, O.; Ketolainen, J.; Poso, A. 2007: Predicting the drug concentration in starch acetate matrix tablets from ATR-FTIR spectra using multi-way methods. Analytica Chimica Acta 595(1-2): 190-197
Henson, S., M.; Dennis, B.; Hayward, J., L.; Cushing, J.M.; Galusha, J., G. 2007: Predicting the dynamics of animal behaviour in field populations. Animal Behaviour 74(Part 1): 103-110
Cook, D.C.; Thomas, M.B.; Cunningham, S.A.; Anderson, D.L.; De Barro, P.J. 2007: Predicting the economic impact of an invasive species on an ecosystem service. Ecological Applications: a Publication of the Ecological Society of America 17(6): 1832-1840
Westphal, J.; Lieber, S. 1986: Predicting the effect of alternative trail design on visitor satisfaction in park settings. Landscape journalng 5(1): 39-44
Mckenzie, D.; Peterson, D.L.; Alvarado, E. 1996: Predicting the effect of fire on large-scale vegetation patterns in North America. U S Forest Service Research Paper PNW 1996(489): I, 1-38
Rehfisch, M.; Holloway, S.; Yates, M.; Clarke, R.; Austin, G.C., N.; Durell, S.-Le, V.D.; Eastwood, J.; Goss-Custard, J.; Swetnam, R. 1997: Predicting the effect of habitat change on waterfowl communities: a novel empirical approach. Effect of habitat loss and change on waterbirds: proceedings of 10th International Waterfowl Ecology Symposium held at the University of Aveiro Portugal 18-21 September 1995 126
Moore, J.A. 1980: Predicting the effect of tussock moth defoliation on juvenile tree growth and stand dynamics--a simulation approach. Mitteilungen der Forstlichen Bundesversuchsanstalt: 30) 187-201
Drogalin, P.; Negovelov, S.; Kazankova, V. 1971: Predicting the effectiveness of mineral fertilizers on the winter wheat variety Bezostaia 1 on leached Chernozems of the Krasnodar Territory. Agrokhimiia 10 61-68
Tolkamp, B.J.; Yearsley, J.M.; Gordon, I.J.; Illius, A.W.; Speakman, J.R.; Kyriazakis, I. 2007: Predicting the effects of body fatness on food intake and performance of sheep. British Journal of Nutrition 97(6): 1206-1215
Petit, L.; Petit, D.; Martin, T.; Thill, R.; Taulman, J. 1994: Predicting the effects of ecosystem management harvesting treatments on breeding birds in pine-hardwood forests. General technical report SO (112) 117-125
Smith, V.H. 1982: Predicting the effects of eutrophication: responses in the phytoplankton. Prediction in water quality: proceedings symposium sponsored by Australian Academy of Science and the Institution of Engineers Australia held in Canberra 30 Nov 2 Dec 1982 edited by EM O'Loughlin P Cullen: 264
Batty, L. 1997: Predicting the effects of habitat loss and change on estuarine birds: are we asking the right questions?. Effect of habitat loss and change on waterbirds: proceedings of 10th International Waterfowl Ecology Symposium held at the University of Aveiro Portugal 18-21 September 1995 6
Hench, J.; Flyger, V.G.bbs, R.V.n-Ness, K. 1985: Predicting the effects of land-use changes on wildlife. Transactions of the North American Wildlife and Natural Resources Conference: 0th) 345-351
Buongiorno, J.K.ng, Y.C.nnaughton, K. 1988: Predicting the effects of macro-economic variables on timber harvest in small regions: method and application. Agricultural systems 8(4): 241-257
Suttle, N.F. 1982: Predicting the effects of molybdenum and sulphur concentrations on the absorbability of copper in grass and forage crops to ruminants. Proceedings symposium on Trace element metabolism in man and animals: ub 1982) (4th) 545-548
Ogola, J.B.O.; Wheeler, T.R.; Harris, P.M. 2007: Predicting the effects of nitrogen and planting density on maize water use in semi-arid Kenya. South African Journal of Plant and Soil 24(1): 51-57
Daubert, C.; Steffe, J.; Srivastava, A. 1998: Predicting the electrorheological behavior of milk chocolate. Journal of food process engineering 21(3): 249-261
Muñoz, M.; Planas, E.àl.; Ferrero, F.; Casal, J. 2007: Predicting the emissive power of hydrocarbon pool fires. Journal of Hazardous Materials 144(3): 725-729
Wiseman, J.C.le, D. 1983: Predicting the energy content of pig feeds. Recent advances in animal nutrition 1983 W Haresign: 0
Bull, L.S. 1988: Predicting the energy value of feeds from laboratory analysis--How good are we at doing this?. Beef cattle Science handbook 2(22): 80-87
Seem, R.; Russo, J. 1983: Predicting the environment. Challenging problems in plant health edited by Thor Kommendahl and Paul H Williams: 238
Turk, L.J. 1976: Predicting the environmental impact of urban development in a karst area. Karst Hydrology and Water Resources Proceedings of the U: ub 1976), 2 681-702
Valle, P.; Martin, S.; Larssen, R. 1998: Predicting the epidemic curve of bovine virus diarrhoea (BVD) in More and Romsdal County, Norway. Proceedings of a meeting held at the on the 72-183
Volker, R.E. 1981: Predicting the extent of sea water intrusion in a coastal aquifer. Proceedings Groundwater Pollution Conference: ub 1981) 167-182
Meador, J.P. 2000: Predicting the fate and effects of tributyltin in marine systems. Reviews of Environmental Contamination and Toxicology 166: 1-48
Rodgers, P.; Depinto, J. 1979: Predicting the fate of organics: conceptual model and experimental approaches. PB U S National Technical Information Service: (298254) 296-311
Waech, T.; Sze, D. 2000: Predicting the fluting tendency of lightweight coated paper. TAPPI Journal 83(4)
Worrall, F.-; Burt, T.-; Adamson, J.-; Reed, M.-; Warburton, J.-; Armstrong, A.-; Evans, M. 2007: Predicting the future carbon budget of an upland peat catchment. Climatic change 85(1-2): 139-158
Ludwig, B. 1997: Predicting the future: have you considered using the Delphi methodology?. Journal of extension 35(5): n
Melo, C.-De; Carneiro, J.-De-S.C.rneiro, P.; Silva, L.-Da; Cintra, J.; Pereira, A.; Moreira, M.; Barros, E. 2006: Predicting the genetic potential in segregating populations of common bean (Phaseolus vulgaris L.). Annual report 49(49): 139-140
Woods, J.; Favier, J.; Briggs, D. 1994: Predicting the germinative energy of dormant malting barley during storage. Journal of the Institute of Brewing 100(4): 257-269
Dickson, J.; Siragusa, G.; Wray, J.J. 1993: Predicting the growth of salmonellae on beef. ARS (71) 121-122
Land, C.; Blum, W.F.; Shavrikova, E.; Kloeckner, K.; Stabrey, A.; Schoenau, E. 2007: Predicting the growth response to growth hormone (GH) treatment in prepubertal and pubertal children with isolated GH deficiency--model validation in an observational setting (GeNeSIS). Journal of Pediatric Endocrinology and Metabolism: Jpem 20(6): 685-693
Myatt, M.M. 1987: Predicting the habitat geography of sensitive plants and community types. Conservation and management of rare and endangered plants: proceedings of a California Conference on the Conservation and Management of Rare and Endangered Plants edited by Thomas S Elias foreward by Jim Nelson: 179
Morooka, T.-; Homma, Y.-; Norimoto, M. 2007: Predicting the humidity control capacity of material based on a linear excitation-response relationship. Journal of wood science e 53(3): 199-203
Oster, J.; Shainberg, I. 1980: Predicting the hydraulic properties of sodic soils Interaction between soil colloids and the soil-solution composition. International Symposium on Salt Affected Soils: 18 to 21 1980: 201
Andersson, K.M.; Owens, D.K.; Vardas, E.; Gray, G.E.; McIntyre, J.A.; Paltiel, A.David. 2007: Predicting the impact of a partially effective HIV vaccine and subsequent risk behavior change on the heterosexual HIV epidemic in low- and middle-income countries: A South African example. Journal of Acquired Immune Deficiency Syndromes 46(1): 78-90
Ziska, L.H.; Bunce, J.A. 2007: Predicting the impact of changing CO(2) on crop yields: some thoughts on food. New phytologist 175(4): 607-618
Brandao, E.M.carl, B.; Schuh, G. 1984: Predicting the impact of new cropping practices upon subsistence farming: a farm level analysis in Brazil. Western journal of agricultural economics 9(2): 329-341
Allen, S. 1985: Predicting the impacts of a high-voltage transmission line on big game hunting opportunities in western Montana. USDA Forest Service general technical report INT Intermountain Forest and Range Experiment Station: (184) 86-100
De-Silva, C.S.; Weatherhead, E.K.; Knox, J.W.; Rodriguez-Diaz, J.A. 2007: Predicting the impacts of climate change - A case study of paddy irrigation water requirements in Sri Lanka. Agricultural Water Management 93(1-2): 19-29
Yorke, T.H. 1980: Predicting the impacts of surface coal mining on trout populations in the Yampa River Basin: a discussion. Energy development in the Southwest: problems of water fish and wildlife in the Upper Colorado River Basin Walter O Spofford Jr Alfred L Parker and Allen V Kneese editors: 457
Mohammadpoorasl, A.; Fakhari, A.; Rostami, F.; Vahidi, R. 2007: Predicting the initiation of substance abuse in Iranian adolescents. Addictive Behaviors 32(12): 3153-3159
Fliurtse, I.; Stramous, E. 1974: Predicting the irrigation system of a palmette orchard according to climatic factors. Sadovodstvo vinogradarstvo i vinodelie Moldavii: 11 11-14
Kirsch, H.E.; Zhu, Z.; Honma, S.; Findlay, A.; Berger, M.S.; Nagarajan, S.S. 2007: Predicting the location of mouth motor cortex in patients with brain tumors by using somatosensory evoked field measurements. Journal of Neurosurgery 107(3): 481-487
Shelopaev, E.I. 1981: Predicting the moisture content and modulus of elasticity of grounds of the earth road-bed. Izvestiia vysshikh uchebnykh zavedenii: lesnoi zhurnal: ) 42-45
Taylor, R.A. 1988: Predicting the moisture content of materials containing oven sensitive volatiles by NIRS. Analytical applications of spectroscopy edited by CS Creaser and AMC Davies: 163
Starcevic, A.; Jaspars, M.; Cullum, J.; Hranueli, D.; Long, P.F. 2006: Predicting the nature and timing of epimerisation on a modular polyketide synthase. Chembiochem: a European Journal of Chemical Biology 8(1): 28-31
Frydrych, I.M.tusiak, M. 2002: Predicting the nep number in cotton yarn--determining the critical nep size. Textile research journal: ication of Textile Research Institute Inc and the Textile Foundation 72(10): 917-923
Chalaganidze, S.; Kitsitadze, D. 1983: Predicting the number of capital repairs of forestry tractors. Lesnoe khoziaistvo: 2) 42-43
Sparks, D. 1978: Predicting the nutrient needs of pecan--a review. Pecan South 5(6): 280-284
Guido, L.-Ferreira-; Curto, A.-; Boivin, P.-; Benismail, N.-; Gonc'-Alves, C.-; Barros, A.-Aracjo 2007: Predicting the organoleptic stability of beer from chemical data using multivariate analysis. Zeitschrift fur Lebensmittel Untersuchung und Forschung A European food research and technology 226(1-2): 57-62
Crookston, N.L. 1979: Predicting the outcome of management activities in mountain pine beetle susceptible lodgepole pine stands. Proceedings 76-280
Harding, C.; Robson, W.; Drinnan, M.; Sajeel, M.; Ramsden, P.; Griffiths, C.; Pickard, R. 2007: Predicting the outcome of prostatectomy using noninvasive bladder pressure and urine flow measurements. European Urology 52(1): 186-192
Quy, R.; Cowan, D.; Haynes, P.I.glis, I.; Swinney, T. 1994: Predicting the outcome of rodenticide trials against Norway rats living on farms. Proceedings Vertebrate Pest Conference: (16th) 133-137
Rathwell, P.; Ridley, J.; Wells, G. 1985: Predicting the peach market. Extension review United States Department of Agricultureng 56(2): 36
Comis, D. 2002: Predicting the perfect moments in farming--from planting to harvest. Agricultural research 50(11): 4-7
Slack, D.; Eshenaur, W.; Berkas, T. 1984: Predicting the performance of a water-pumping hydraulic ram. International journal for development technology 2(4): 261-271
Taylor, W.R. 1987: Predicting the performance of alternative harvesting systems in small timber. USDA Forest Service general technical report INT Intermountain Research Station: (237) 67-70
Wei, W.Y.ng, C. 1999: Predicting the performance of durable press finished cotton fabric with infrared spectroscopy. Textile research journal: ication of Textile Research Institute Inc and the Textile Foundation 69(2): 145-151
Woomer, P.; Asano, W.; Bohlool, B.B. 1992: Predicting the persistence of introduced Bradyrhizobium japonicum in tropical soils. Mulongoy, K, Gueye, M, Spencer, D S C Biological nitrogen fixation and sustainability of tropical agriculture: 235-244
Howells, L.M.; Moiseeva, E.P.; Neal, C.P.; Foreman, B.E.; Andreadi, C.K.; Sun, Y-yang.; Hudson, E.Ann.; Manson, M.M. 2007: Predicting the physiological relevance of in vitro cancer preventive activities of phytochemicals. Acta Pharmacologica Sinica 28(9): 1274-1304
Beltran, R.W.ng, L.W.ng, X. 2005: Predicting the pilling propensity of fabrics through artificial neural network modeling. Textile research journal 75(7): 557-561
Giercuszkiewicz-Bajtlik, M.G.abski, E. 1981: Predicting the pollution of Great Masurian lakes from point and nonpoint sources. Ekologia Polska 29(3): 361-374
Knock, C.; Davison, M. 2007: Predicting the position of the source of blood stains for angled impacts. Journal of forensic sciences 52(5): 1044-1049
Chen-Hao; Chen-Lijun; Albright, T., P. 2007: Predicting the potential distribution of invasive exotic species using GIS and information-theoretic approaches: A case of ragweed (Ambrosia artemisiifolia L.) distribution in China. CHINESE SCIENCE BULLETIN 52(9): 1223-1230
Schoettle, A.W. 1995: Predicting the potential sensitivity of high elevation wilderness vegetation to changes in atmospheric chemistry--a strategy. General technical report RM (262) 63-67
Bolliger, J.; Bergamini, A.; Stofer, S.; Kienast, F.; Scheidegger, C. 2007: Predicting the potential spatial distributions of epiphytic lichen species at the landscape scale. Lichenologist 39(Part 3): 279-291
Harvey, G. 1978: Predicting the predations of aphids. New Scientist 771095: 804-806
Mcdonald, D.A.ini, J. 2000: Predicting the press dewatering of heavyweight grades. TAPPI Journal 83(2): 79-82
Haarstad, K. 1999: Predicting the probability distribution of yield from boreholes in crystalline bedrock. Ground water 37(1): 4
Reams, G.; Brann, T. 1986: Predicting the probability of survival for balsam fir, red spruce and white spruce during a spruce budworm outbreak in Maine. Miscellaneous ication University of Maine Agricultural Experiment Station: (691) 116-121
Poliakov, M. 1974: Predicting the productivity of labor. Ekonomika sel'skogo khoziaistva: 10 69-75
Lebel, L.; Dubeau, D. 2007: Predicting the productivity of motor-manual workers in precommercial thinning operations. Forestry chronicle 83(2): 215-220
Gevaert, O.; De Smet, F.; Timmerman, D.; Moreau, Y.; De Moor, B. 2006: Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks. Bioinformatics 22(14): E184-E190
Achanta, S.O.os, M. 1996: Predicting the quality of dehydrated foods and biopolymers--research needs and opportunities. Drying technology 4(6): 1329-1368
Gansner, D.; Herrick, O. 1982: Predicting the rate of change in timber value for forest stands infested with gypsy moth Lymantria dispar, Pennsylvania, robust regression analysis, models. Forest Service research note NE Northeastern Forest Experiment Station Forest Service US Department of Agriculture: (311)
Draganic, M.S.iljkovic, H. 1983: Predicting the resistance of the maize stalk to different isolates of Gibberella zeae based on the degree of resistance of parent components. Zastita bilja = Plant protection 4(1): 27-32
Reynolds, J.; Acock, B. 1985: Predicting the response of plants to increasing carbon dioxide: a critique of plant growth models. Ecological modelling 29(1-4): 107-129
Sanghani, M.; Balk, E.; Cady, B.; Wazer, D. 2007: Predicting the risk of local recurrence in patients with breast cancer: an approach to a new computer-based predictive tool. American Journal of Clinical Oncology 30(5): 473-480
Maclean, D.A. 1985: Predicting the risk of spruce budworm damage using hazard and vulnerability rating systems. USDA Forest Service general technical report NE United States Northeastern Forest Experiment Station: 9) 113-120
Neuert, G.; Albrecht, C.H.; Gaub, H.E. 2007: Predicting the rupture probabilities of molecular bonds in series. Biophysical Journal 93(4): 1215-1223
Kean, J.M.; Kumarasinghe, L.B. 2007: Predicting the seasonal phenology of fall webworm (Hyphantria cunea) in New Zealand. New Zealand Plant Protection 60: 279-285
Smart, G.M. 1984: Predicting the sediment capacity of a channel. Challenges in African hydrology and water resources: proceedings Harare Symposium July 1984 edited by DE Walling SSD Foster P Wurzel: 401
Young, A.; Travina, R. 1983: Predicting the setting season of the oyster Crassostrea iredalei in Himamaylan River, Negros Occidental. Kalikasan: the Philippine journal of biology 2(1-2): 107-114
Einarsson, H. 1992: Predicting the shelf life of cod (Gadus morhua) fillets stored in air and modified atmosphere at temperatures between -4 degrees C and +16 degrees C. Developments in food Science 30: 479-488
Mitsuda, Y.-; Ito, S.-; Sakamoto, S. 2007: Predicting the site index of sugi plantations from GIS-derived environmental factors in Miyazaki Prefecture. Journal of forest research 12(3): 177-186
Chen, J.; Hale, S.; Myerson, J. 2007: Predicting the size of individual and group differences on speeded cognitive tasks. Psychonomic Bulletin and Review 14(3): 534-541
Gleiser, R.M.; Gorla, D.E. 2007: Predicting the spatial distribution of Ochlerotatus albifasciatus (Diptera: Culicidae) abundance with NOAA imagery. Bulletin of Entomological Research 97(6): 607-612
Zhu, L.-; Sun, O., J.; Sang, W.-; Li, Z.-; Ma, K. 2007: Predicting the spatial distribution of an invasive plant species (Eupatorium adenophorum) in China. Landscape ecology 22(8): 1143-1154
Tatsuhara, S.-; Antatsu, Y. 2007: Predicting the spatial distribution of the abundance of Siebold's beech in a montane cool-temperate region based on environmental factors. Journal of forest research 12(6): 442-451
Baskin, C.C. 1980: Predicting the storability of soybean seed lots Germination, accelerated aging, regression analysis. Journal of seed technology(2): 1-6
Kortschot, M.; Trakas, K. 1998: Predicting the strength of paper containing holes or cracks with the point stress criterion. TAPPI Journal 81(1): 254-259
Wang, X. 2000: Predicting the strength variation of wool from its diameter variation. Textile research journal: ication of Textile Research Institute Inc and the Textile Foundation 7(3): 191-194
Reggiani, B.; Cristofolini, L.; Varini, E.; Viceconti, M. 2007: Predicting the subject-specific primary stability of cementless implants during pre-operative planning: preliminary validation of subject-specific finite-element models. Journal of Biomechanics 40(11): 2552-2558
Smith, V.; Willen, E.K.rlsson, B. 1987: Predicting the summer peak biomass of four species of blue-green algae (Cyanophyta. Water resources bulletin 23(3): 397-402
Gaffield, S.; Potter, K.; Wang, L. 2005: Predicting the summer temperature of small streams in southwestern Wisconsin. Journal of the American Water Resources Association 41(1): 25-36
Allen, C., A.W.; Watts, K.C.ris-; Ackman, R., G. 1999: Predicting the surface tension of biodiesel fuels from their fatty acid composition. Journal of the American Oil Chemists' Society 76(3): 317-323
Grose, P.E.erdale, F.K.tz, L. 1983: Predicting the surface transport of oil pollutants in the Gulf of Mexico. Marine Pollution Bulletin 14(10): 372-377
Sutherst, R.W. 1991: Predicting the survival of immigrant insect pests in new environments. Crop Protection 10(5): 331-333
Simard, C.C.staigne, F.B.udreau, A. 1983: Predicting the texture of sausage containing soy protein from their emulsifying capacity and efficiency. Sciences des aliments(2): 299-309
Kashmanian, R.M. 1993: Predicting the tonnage of yard trimmings to be composted in 1996. BioCycle 34(9): 51-53
Wagner, J.; Feuz, D. 1994: Predicting the value of feeder cattle placed into an accelerated finishing program under dynamic market conditions. South Dakota beef report: (94-20) 84-91
Steinitz, C. 1979: Predicting the visual quality impacts of development: a simulation of alternative policies for implementing the Massachusetts Scenic and Recreational Rivers Act. USDA Forest Service general technical report PSW: (35) 598-609
Oleckno, W.A. 1976: Predicting the water pollution potential of proposed sanitary landfills. I. Sanitary landfill leachate, what it is. Journal of environmental health 38(5): 331-333
Oleckno, W.A. 1976: Predicting the water pollution potential of proposed sanitary landfills. II. An index of the water pollution potential of sanitary landfills. Journal of environmental health 38(5): 334-336
Light, G.; Dotray, P.; Mahan,. Jr.; 1998: Predicting thermal dependence of pyrithiobac efficacy in palmer amaranth (Amaranthus palmeri) with inhibition kinetics. Proceedings Southern Weed Science Society 1(51): 207
Edwards, W.M. 1982: Predicting tillage effects on infiltration Soil hydraulic properties. ASA special ication American Society of Agronomy: 4) 105-115
Oskoui, K.; Voorhees, W. 1991: Predicting timeliness penalties from weather and crop data. Paper er 1991 (911549)
Allen, R.J.; Kidder, G.G.scho, G. 1978: Predicting tons of sugarcane per acre using solar radiation, temperature and percent plant cane, 1971 through 1976. Proceedings New Seriesub e 1978) 7(7): 18-22
Bigano, A.-; Hamilton, J., M.; Maddison, D., J.; Tol, R., S.J. 2006: Predicting tourism flows under climate change. Climatic change 79(3-4): 175-180
Sidorenko, G.I.; Pinigin, M.A. 1979: Predicting toxicometric parameters on the basis of studying the concentration--time dependence. Environmental Health Perspectives 30: 19-21
Chahota, R.K.; Kishore, N.; Dhiman, K.C.; Sharma, T.R.; Sharma, S.K. 2007: Predicting transgressive segregants in early generation using single seed descent method-derived micro-macrosperma genepool of lentil (Lens culinaris Medikus). Euphytica 156(3): 305-310
Townley, S.; Carslake, D.; Kellie-Smith, O.; Mccarthy, D.; Hodgson, D. 2007: Predicting transient amplification in perturbed ecological systems. Journal of applied ecology 44(6): 1243-1251
Kerekes, J. 1983: Predicting trophic response to phosphorus addition in a Cape Breton Island Lake. Proceedings of the a Scotian Institute of Science 3(1): 7-18
Gelernter, W.S.owell, L. 2006: Predicting turf performance. Grounds maintenance 41(8): 12-14
Irving, A.D.; Connell, S.D. 2006: Predicting understorey structure from the presence and composition of canopies: an assembly rule for marine algae. Oecologia 148(3): 491-502
Bebber, D.P.; Marriott, F.H.C.; Gaston, K.J.; Harris, S.A.; Scotland, R.W. 2007: Predicting unknown species numbers using discovery curves. Proceedings. Biological Sciences 274(1618): 1651-1658
Gao, F.S.cks, J.W.lch, W. 1996: Predicting urban ozone levels and trends with semiparametric modeling. Journal of agricultural biological and environmental statistics 1(4): 404-425
Montgomery, R.; Lee, V.; Reckhow, K. 1983: Predicting variability in a Lake Ontario phosphorus model. Journal of Great Lakes research(1): 74-82
Smith, R.S.; Rushton, S.P.; Wadesworth, R.A. 1992: Predicting vegetation change in an upland environment. Whitby, M C Land use change: The causes and consequences: 118-130
Delong, C. 1989: Predicting vegetation management problems. FRDA report: (030) 108-109
Billikopf, G.E. 1988: Predicting vineyard pruner performance. California agriculture California Agricultural Experiment Station 42(2): 13-14
Le Meur, O.; Le Callet, P.; Barba, D. 2007: Predicting visual fixations on video based on low-level visual features. Vision Research 47(19): 2483-2498
Lang, K.; Steinberg, M. 1981: Predicting water activity from 0.30 to 0.95 of a multicomponent food formulation. Journal of food science 46(3): 670-672
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Wang-Xue-Hai; Mao-Ya-Fei; Yan-Jie 2007: Prediction of epitopes in urease subunit B of Helicobacter pylori and screening by phage display. Zhonghua Weishengwuxue He Mianyixue Zazhi 27(5): 432-437
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Inkrott, D.G.uld, W. 1979: Prediction of finished product juice color from raw product tomato color. Research circular: (250) 10-13
Heap, S.; Greenwood, P.; Leah, R.; Eaton, J.; Stevens, J.; Keher, P. 1985: Prediction of finished relaxed dimensions of cotton knits--the Starfish project. II. Shrinkage and the reference state. Textile research journal 55(4): 211-222
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Barton, F.I.; Burdick, D. 1983: Prediction of forage quality with NIR Near-infrared reflectance spectroscopy. Proceedings of the XVI International Grassland Congress: held at Lexington Kentucky USA June 15-24-1981 edited by J Allan Smith and Virgil W Hays: 534
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Jahandideh, S.; Abdolmaleki, P.; Asadabadi, E.Barzegari. 2007: Prediction of future citations of a research paper from number of its internet downloads. Medical Hypotheses 69(2): 458-459
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Paiva, Jr; Miranda-Filho, Jbo 1979: Prediction of genetic gain for some traits in rubber tree (Hevea sp.) under three selection schemes Brazil.1. Relatorio cientifico Escola Superior de Agricultura "Luiz de Queiroz" Departamento de Genetica Instituto de Genetica: 3) 213-225
Obayashi, T.A.ada, Y.T.rawaki, Y. 2000: Prediction of genetic progress using embryo production models developed for the Japanese MOET Holstein population. Asian Australasian journal of animal sciences: 1371
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Xiao ChunHua; Li ShaoKun; Lu YanLi; Wang KeRu; Xie RuiZhi; Gao ShiJu; Li XiaoJun; Sui XueYan 2007: Prediction of grain protein content based on parallel plane spectral characteristics of winter wheat canopy. Acta Agronomica Sinica 33(9): 1468-1473
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Fidaleo, M.; Moresi, M. 2007: Prediction of grape sugar solubility in water/ethanol systems. Industrie delle Bevande 36(210): 341-344
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Kawaji, M.S.en, X.; Tran, H.E.aki, S.D.es, C. 1995: Prediction of heat transfer in the kraft recovery boiler superheater region. TAPPI Journal 78(10): 214-221
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Wilson, P.W.F.; Meigs, J.B.; Sullivan, L.; Fox, C.S.; Nathan, D.M.; D'Agostino, R.B. 2007: Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Archives of Internal Medicine 167(10): 1068-1074
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Surajit Chattopadhyay 2007: Prediction of mean monthly total ozone time series - application of radial basis function network. International Journal of Remote Sensing 28(17/18): 4037-4046
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