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.

Contribution of geophysical methods to karst-system exploration: an overview

Abstract: The karst environment is one of the most challenging in terms of groundwater, engineering and environmental issues. Geophysical methods can provide useful subsurface information in karst regions concerning , for instance, hazard estimation or groundwater exploration and vulnerability assessment. However, a karst area remains a very difficult environment for any geophysical exploration; selection of the best-suited geophysical method is not always straightforward, due to the highly variable and unpredictable target characteristics. The state of the art is presented, in terms of the contributions made by geophysical methods to karst-system exploration, based on extensive analysis of the published scientific results. This report is an overview and should be used as a preliminary meth-odological approach, rather than a guideline.

In Vitro Models for Studying Secondary Plant Metabolite Digestion and Bioaccessibility

Abstract: There is an increased interest in secondary plant metabolites, such as polyphenols and carotenoids, due to their proposed health benefits. Much attention has focused on their bioavailability, a prerequisite for further physiological functions. As human studies are time consuming, costly, and restricted by ethical concerns, in vitro models for investigating the effects of digestion on these compounds have been developed and employed to predict their release from the food matrix, bioaccessibility, and assess changes in their profiles prior to absorption. Most typically, models simulate digestion in the oral cavity, the stomach, the small intestine, and, occasionally, the large intestine. A plethora of models have been reported, the choice mostly driven by the type of phytochemical studied, whether the purpose is screening or studying under close physiological conditions, and the availability of the model systems. Unfortunately, the diversity of model conditions has hampered the ability to compare results across different studies. For example, there is substantial variability in the time of digestion, concentrations of salts, enzymes, and bile acids used, pH, the inclusion of various digestion stages; and whether chosen conditions are static (with fixed concentrations of enzymes, bile salts, digesta, and so on) or dynamic (varying concentrations of these constituents). This review presents an overview of models that have been employed to study the digestion of both lipophilic and hydrophilic phytochemicals, comparing digestive conditions in vitro and in vivo and, finally, suggests a set of parameters for static models that resemble physiological conditions.

On Dynamic Service Function Chain Deployment and Readjustment

Abstract: Network function virtualization (NFV) is a promising technology to decouple the network functions from dedicated hardware elements, leading to the significant cost reduction in network service provisioning. As more and more users are trying to access their services wherever and whenever, we expect the NFV-related service function chains (SFCs) to be dynamic and adaptive, i.e., they can be readjusted to adapt to the service requests’ dynamics for better user experience. In this paper, we study how to optimize SFC deployment and readjustment in the dynamic situation. Specifically, we try to jointly optimize the deployment of new users’ SFCs and the readjustment of in-service users’ SFCs while considering the trade-off between resource consumption and operational overhead. We first formulate an integer linear programming (ILP) model to solve the problem exactly. Then, to reduce the time complexity, we design a column generation (CG) model for the optimization. Simulation results show that the proposed CG-based algorithm can approximate the performance of the ILP and outperform an existing benchmark in terms of the profit from service provisioning.