University of Avignon

About: University of Avignon is a education organization based out in Avignon, Provence-Alpes-Côte-d'Azur, France. It is known for research contribution in the topics: Population & Speaker recognition. The organization has 1526 authors who have published 3766 publications receiving 88928 citations.

Dietary calcium impairs tomato lycopene bioavailability in healthy humans.

Abstract: Lycopene (LYC) bioavailability is relatively low and highly variable, because of the influence of several factors. Recent in vitro data have suggested that dietary Ca can impair LYC micellarisation, but there is no evidence whether this can lead to decreased LYC absorption efficiency in humans. Our objective was to assess whether a nutritional dose of Ca impairs dietary LYC bioavailability and to study the mechanism(s) involved. First, in a randomised, two-way cross-over study, ten healthy adults consumed either a test meal that provided 19-mg (all-E)-LYC from tomato paste or the same meal plus 500-mg calcium carbonate as a supplement. Plasma LYC concentration was measured at regular time intervals over 7 h postprandially. In a second approach, an in vitro digestion model was used to assess the effect of increasing Ca doses on LYC micellarisation and on the size and zeta potential of the mixed micelles produced during digestion of a complex food matrix. LYC bioavailability was diminished by 83 % following the addition of Ca in the test meal. In vitro, Ca affected neither LYC micellarisation nor mixed micelle size but it decreased the absolute value of their charge by 39 %. In conclusion, a nutritional dose of Ca can impair dietary LYC bioavailability in healthy humans. This inhibition could be due to the fact that Ca diminishes the electrical charge of micelles. These results call for a thorough assessment of the effects of Ca, or other divalent minerals, on the bioavailability of other carotenoids and lipophilic micronutrients.

Bio-inspired delayed evolutionary game dynamics with networking applications

Abstract: We study in this paper some evolutionary games where competition between individuals from a large population occurs through many local interactions between randomly selected individuals We focus on games that have the property of possessing a single interior evolutionarily stable strategy (ESS) We study in particular the effect of the time delays on the convergence of evolutionary dynamics to the ESS in an evolutionary game in which each pure strategy is associated with its own delay In particular, we study a multiple access game as well as a Hawk and Dove game We study the properties of the ESS in these games and also the effect of time delays on the convergence of various bio-inspired evolutionary game dynamics to the ESS

How errors on meteorological variables impact simulated ecosystem fluxes: a case study for six French sites

Abstract: . We analyze how biases of meteorological drivers impact the calculation of ecosystem CO2, water and energy fluxes by models. To do so, we drive the same ecosystem model by meteorology from gridded products and by meteorology from local observation at eddy-covariance flux sites. The study is focused on six flux tower sites in France spanning across a climate gradient of 7–14 °C annual mean surface air temperature and 600–1040 mm mean annual rainfall, with forest, grassland and cropland ecosystems. We evaluate the results of the ORCHIDEE process-based model driven by meteorology from four different analysis data sets against the same model driven by site-observed meteorology. The evaluation is decomposed into characteristic time scales. The main result is that there are significant differences in meteorology between analysis data sets and local observation. The phase of seasonal cycle of air temperature, humidity and shortwave downward radiation is reproduced correctly by all meteorological models (average R2 = 0.90). At sites located in altitude, the misfit of meteorological drivers from analysis data sets and tower meteorology is the largest. We show that day-to-day variations in weather are not completely well reproduced by meteorological models, with R2 between analysis data sets and measured local meteorology going from 0.35 to 0.70. The bias of meteorological driver impacts the flux simulation by ORCHIDEE, and thus would have an effect on regional and global budgets. The forcing error, defined by the simulated flux difference resulting from prescribing modeled instead of observed local meteorology drivers to ORCHIDEE, is quantified for the six studied sites at different time scales. The magnitude of this forcing error is compared to that of the model error defined as the modeled-minus-observed flux, thus containing uncertain parameterizations, parameter values, and initialization. The forcing error is on average smaller than but still comparable to model error, with the ratio of forcing error to model error being the largest on daily time scale (86%) and annual time scales (80%). The forcing error incurred from using a gridded meteorological data set to drive vegetation models is therefore an important component of the uncertainty budget of regional CO2, water and energy fluxes simulations, and should be taken into consideration in up-scaling studies.