For Heavy-duty vehicles (HDVs), the distribution of vehicle miles traveled (VMT) by vehicle type is the most significant parameters for onroad mobile source emissions modeling used in the development of air quality management and regional transportation plans. There are two approaches for the development of the HDV VMT distribution; one approach uses HDV registration data and annual mileage accumulation rates, and another uses HDV VMT counts/observations collected with the FHWA truck classification. For the purpose of emissions modeling, the FHWA truck classes are converted to those used by the MOBILE6.2 emissions rate model by using either the EPA guidance or the National Research Council conversion factors. However, both these approaches have uncertainties in the development of onroad HDV VMT distributions that can lead to large unknowns in the modeled HDV emissions. This dissertation reports a new heavy-duty vehicle visual classification and activity estimation method that minimizes uncertainties in current HDV conversion methods and the vehicle registration based HDV VMT estimation guidance. The HDV visual classification scheme called the X-scheme, which classifies HDV/truck classes by vehicle physical characteristics (the number of axles, gross vehicle weight ratings, tractor-trailer configurations, etc.) converts FHWA truck classes into EPA HDV classes without losing the original resolution of HDV/truck activity and emission characteristics. The new HDV activity estimation method using publicly available HDV activity databases minimizes uncertainties in the vehicle registration based VMT estimation method suggested by EPA. The analysis of emissions impact with the new method indicates that emissions with the EPA HDV VMT estimation guidance are underestimated by 22.9% and 25.0% for oxides of nitrogen and fine particulate matter respectively within the 20-county Atlanta metropolitan area. Because the new heavy-duty vehicle visual classification and activity estimation method has the ability to provide accurate HDV activity and emissions estimates, this method has the potential to significantly influence policymaking processes in regional air quality management and transportation planning. In addition, the ability to estimate link-specific emissions benefits Federal and local agencies in the development of project (microscale), regional (mesoscale), and national (macroscale) level air quality management and transportation plans.

The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock initiated recognizable changes in transportation dynamics: transit operators realized that commuters switched to transit as a way to save gasoline costs, consumers began to search the market for more efficient vehicles leading car manufactures to close 'gas guzzlers' plants, and the government enacted a new law entitled the Energy Independence Act of 2007, which called for the progressive improvement of the fuel efficiency indicator of the light vehicle fleet up to 35 miles per gallon in year 2020. The past trend of gasoline consumption will probably change; so in the context of the problem a gasoline consumption model was developed in this thesis to ascertain how some of the changes will impact future gasoline demand. Gasoline demand was expressed in oil equivalent million barrels per day, in a two steps Ordinary Least Square (OLS) explanatory variable model. In the first step, vehicle miles traveled expressed in trillion vehicle miles was regressed on the independent variables: vehicles expressed in million vehicles, and price of oil expressed in dollars per barrel. In the second step, the fuel consumption in million barrels per day was regressed on vehicle miles traveled, and on the fuel efficiency indicator expressed in miles per gallon. The explanatory model was run in EVIEWS that allows checking for normality, heteroskedasticty, and serial correlation. Serial correlation was addressed by inclusion of autoregressive or moving average error correction terms. Multicollinearity was solved by first differencing. The 36 year sample series set (1970-2006) was divided into a 30 years sub-period for calibration and a 6 year "hold-out" sub-period for validation. The Root Mean Square Error or RMSE criterion was adopted to select the "best model" among other possible choices, although other criteria were also recorded. Three scenarios for the size of the light vehicle fleet in a forecasting period up to 2020 were created. These scenarios were equivalent to growth rates of 2.1, 1.28, and about 1 per cent per year. The last or more optimistic vehicle growth scenario, from the gasoline consumption perspective, appeared consistent with the theory of vehicle saturation. One scenario for the average miles per gallon indicator was created for each one of the size of fleet indicators by distributing the fleet every year assuming a 7 percent replacement rate. Three scenarios for the price of oil were also created: the first one used the average price of oil in the sample since 1970, the second was obtained by extending the price trend by exponential smoothing, and the third one used a longtime forecast supplied by the Energy Information Administration. The three scenarios created for the price of oil covered a range between a low of about 42 dollars per barrel to highs in the low 100's. The 1970-2006 gasoline consumption trend was extended to year 2020 by ARIMA Box-Jenkins time series analysis, leading to a gasoline consumption value of about 10 millions barrels per day in year 2020. This trend line was taken as the reference or baseline of gasoline consumption. The savings that resulted by application of the explanatory variable OLS model were measured against such a baseline of gasoline consumption. Even on the most pessimistic scenario the savings obtained by the progressive improvement of the fuel efficiency indicator seem enough to offset the increase in consumption that otherwise would have occurred by extension of the trend, leaving consumption at the 2006 levels or about 9 million barrels per day. The most optimistic scenario led to savings up to about 2 million barrels per day below the 2006 level or about 3 millions barrels per day below the baseline in 2020. The "expected" or average consumption in 2020 is about 8 million barrels per day, 2 million barrels below the baseline or 1 million below the 2006 consumption level. More savings are possible if technologies such as plug-in hybrids that have been already implemented in other countries take over soon, are efficiently promoted, or are given incentives or subsidies such as tax credits. The savings in gasoline consumption may in the future contribute to stabilize the price of oil as worldwide demand is tamed by oil saving policy changes implemented in the United States.

Le métabolisme des phénylpropanoïdes est un métabolisme secondaire spécifique au règne végétal. Il conduit, à partir de la phénylalanine, à la synthèse d'une grande variété de substances telles que les anthocyanes, les isoflavonoïdes, les stilbènes, des esters d'acides hydroxycinnamiques, ou encore à la lignine. Ces métabolites secondaires interviennent dans la pigmentation florale ou encore la protection des tissus végétaux contre divers stress biotiques et abiotiques. Quant à la lignine, elle assure rigidité aux parois cellulaires végétales et imperméabilité aux tissus conducteurs. La lignine est un polymère tridimensionnel constitué de trois unités monomériques qui possèdent le même squelette carboné phénylpropane mais diffèrent par leur degré de méthoxylation et d'hydroxylation. Une partie de mon travail de thèse a consisté à étudier la relation structure/fonction de la caféoyl-coenzyme A O-méthyltransférase (CCoAOMT) de N. tabacum, responsable de l'introduction de la première des deux fonctions méthyles. Des études bioinformatiques couplées à des approches de biochimie et de mutagenèse dirigée, nous ont permis de modéliser l'interaction de la CCoAOMT avec son substrat, le caféoyl-CoA. Trois acides aminés du site actif ont notamment été identifiés comme intervenant dans la reconnaissance spécifique de la chaîne latérale de CoA. J'ai également caractérisé, chez N. tabacum, une nouvelle acyltransférase à activité HydroxyCinnamoyl-CoA : shikimate/quinate hydroxycinnamoyl Transférase (HCT) impliquée dans le métabolisme des phénylpropanoïdes. Nous avons montré que l'enzyme HCT recombinante synthétisait, in vitro, les substrats de l'hydroxylation en position 3 du noyau aromatique. De plus, la répression de l'expression du gène HCT par le «VIGS» conduit à un ralentissement de la croissance des plantes, à une perturbation importante du pool d'acide chlorogénique, ainsi qu'à une diminution de la quantité et à une modification de la composition de la lignine synthétisée.

This diploma thesis deals with a project of asphalt mixtures with high stiffness modulus using R-material. The theoretical part describes the characteristics of these mixtures in the Czech Republic and in Switzerland. Further this part deals with the use of R-material in the Czech Republic and chosen other countries of the world, it also deals with the ways of recycling roads. The theoretical part also deals with the testing methods used. In the practical part two new asphalt mixtures of the high stiffness modulus type with the addition of 25 % R-material are suggested. As a base for these two mixtures a mixture of the high stiffness modulus type, which was taken from an asphalt mixing plant, was used. Tests were run on the binders and several functional tests (stiffness modulus, fatigue resistance, low temperature qualities) wer done on the suggested asphalt mixtures and also the mixture taken from the mixing plant. Consequently, the results were compared. The conclusion of the thesis is devoted to modelling a construction of a road using the program LayEps, which verified if the suggested mixtures could reduce the thickness of roads.

Planning, optimalization, production management, process management, production, ERP