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Purification of Natural Pigments Violacein and Deoxyviolacein Produced by Fermentation Using Yarrowia lipolytica
No full textInternational audienceViolacein and deoxyviolacein are bis-indole pigments synthesized by a number of microorganisms. The present study describes the biosynthesis of a mixture of violacein and deoxyviolacein using a genetically modified Y. lipolytica strain as a production chassis, the subsequent extraction of the intracellular pigments, and ultimately their purification using column chromatography. The results show that the optimal separation between the pigments occurs using an ethyl acetate/cyclohexane mixture with different ratios, first 65:35 until both pigments were clearly visible and distinguishable, then 40:60 to create a noticeable separation between them and recover the deoxyviolacein, and finally 80:20, which allows the recovery of the violacein. The purified pigments were then analyzed by thin-layer chromatography and nuclear magnetic resonance
Non-Parametric Conditional U-Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design
No full textInternational audienceStute presented the so-called conditional U-statistics generalizing the Nadaraya–Watson estimates of the regression function. Stute demonstrated their pointwise consistency and the asymptotic normality. In this paper, we extend the results to a more abstract setting. We develop an asymptotic theory of conditional U-statistics for locally stationary random fields {Xs,An:sinRn} observed at irregularly spaced locations in Rn=[0,An]d as a subset of Rd. We employ a stochastic sampling scheme that may create irregularly spaced sampling sites in a flexible manner and includes both pure and mixed increasing domain frameworks. We specifically examine the rate of the strong uniform convergence and the weak convergence of conditional U-processes when the explicative variable is functional. We examine the weak convergence where the class of functions is either bounded or unbounded and satisfies specific moment conditions. These results are achieved under somewhat general structural conditions pertaining to the classes of functions and the underlying models. The theoretical results developed in this paper are (or will be) essential building blocks for several future breakthroughs in functional data analysis
Synthesis of activated carbon materials derived from phenolic resin for CO2 separation
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A multi-port scattering matrix formalism for the acoustic prediction in duct networks
No full textInternational audienceDuct acoustic network modeling is commonly carried out using the transfer matrix formalism which is limited to the low frequency range. The aim of this work is to extend it to higher frequencies by taking into account the multi-mode acoustic propagation. The first step is to compute, via Finite Element Method (FEM), the multi-port multi-modal scattering matrix of each element. The second step is to transform it into a scattering matrix for the acoustic power, relying on assumptions which are often used for the study of medium-to-high frequency broadband noise. The method is applied to typical elements such as expansion chamber mufflers and air conditioning veins. In all cases, the power-flow model is compared to the FEM solution in terms of Transmission Losses. It is concluded that this simplified model is a reliable tool for the analysis of complex networks encountered in Heat and Ventilation Air Conditioning (HVAC) duct networks
New Trends on Photoswitchable Antibiotics: From Syntheses to Applications
No full textInternational audienceAntibiotics are excreted in the environment after being used to treat bacterial infections in human and animals. These residues are poorly eliminated by the actual wastewater treatment processes, affecting animal, human and environmental health. This has led to the emergence of antibiotic resistance in bacterial pathogens. To combat this problem, photopharmacology has emerged in the last decades. This approach, based on the coupling of a drug with a photochromic component, is a promising way to control antibiotic activity by light irradiation and consequently limit antibioresistance. Thus, this review summarizes the study on the effect of the irradiation light on the antimicrobial activity of coupling compounds
Robust Consumption Planning from Uncertain Power Demand Predictions
No full textInternational audienceA plug-in hybrid electric vehicle (PHEV) satisfies the driver's power demand with two types of energy potentials: fuel and electrical energy provided by a battery. Classically, the battery consumption is planned over a trip to minimize the expected fuel consumption. A cautious driver will save battery potential to cross restricted areas (with desired low or even zero fuel consumption) without the fuel engine. This paper proposes an approach to minimize energy consumption while controlling the risk of a PHEV falling short of battery potential when crossing a restricted area. We use a nonlinear Gaussian process, trained on real vehicle data, for predicting the vehicle consumption. We take into account prediction uncertainty by ensuring that the driver's highest power demand will be satisfied with a high probability. The interest of the approach is demonstrated by a simulated trip around Paris
Algorithme d’exploration de séquences et minimisation des pertes d’un Multi-Active Bridge à n ports
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Planification dans un service d'urgence, formulation linéaire et approche heuristique.
No full textInternational audienceIn this study, we investigate the real-world scheduling problem of the Medical Day Unit of the Emergency Department (MDU-ED) at Jeanne de Flandres University Hospital in Lille, France. We implemented a heuristic (PRH) based on hospital practitioners’ rules that we collected by observing the operation of MDU-ED. We propose an Integer Linear Programming (ILP) formulation that makes it feasible to solve small instances. Additionally, we suggest an Adaptive Iterative Destruction Construction Heuristic (IDCH) solution approach. The IDCH obtains better solutions than the PRH within reasonable processing times. We report on experiments performed on instances generated using real-world patient pathways of the MDU-ED.Dans cette étude, nous examinons le problème de planification du monde réel du service médical de jour du service des urgences (MDU-ED) de l'Hôpital universitaire Jeanne de Flandres à Lille (France). Nous avons mis en œuvre une heuristique (PRH) basée sur les règles des praticiens hospitaliers que nous avons recueillies en observant le fonctionnement du MDU-ED. Nous proposons une formulation de Programmation Linéaire Entière (ILP) qui rend possible la résolution de petites instances. Nous présentons une approche de solution heuristique de Destruction Construction Iterative Adaptative (IDCH). L'IDCH obtient des solutions meilleures que la PRH dans des délais de traitement raisonnables. Nous rendons compte des expériences réalisées sur des instances générées à l'aide de trajectoires de patients du monde réel du MDU-ED
Promoting Supply Chain Sustainability Through Industrial Packaging Eco-Designing
No full textInternational audienceThe climate change and the new regulations imposed to slow down this process have pushed major actors around the world to apply sustainable measures in order to meet governmental obligations. The packaging industry has a major role in fighting climate change and the environmental social and financial disasters. In fact, packaging requires substantial number of natural resources and is often disposed of in ways that harm the environment. Supply chain managers realized that packaging design is the root to solve all the problems packages create throughout their entire life cycle. Therefore, a thorough study about influencing the design process should be prioritized. This paper provides a systematic review of industrial packaging eco-design applied to the supply chain. It aims to conceptualize the definition of industrial packaging eco-design and supply chain sustainability to categorize main parameters to its implementation and to identify the limitations of current research and its prospects
Safety of autonomous vehicles: A survey on Model-based vs. AI-based approaches
No full textInternational audienceThe growing advancements in Autonomous Vehicles (AVs) have emphasized the critical need to prioritize the absolute safety of AV maneuvers, especially in dynamic and unpredictable environments or situations. This objective becomes even more challenging due to the uniqueness of every traffic situation/condition. To cope with all these very constrained and complex configurations, AVs must have appropriate control architectures with reliable and real-time Risk Assessment and Management Strategies (RAMS). These targeted RAMS must lead to reduce drastically the navigation risks. However, the lack of safety guarantees proves, which is one of the key challenges to be addressed, limit drastically the ambition to introduce more broadly AVs on our roads and restrict the use of AVs to very limited use cases. Therefore, the focus and the ambition of this paper is to survey research on autonomous vehicles while focusing on the important topic of safety guarantee of AVs. For this purpose, it is proposed to review research on relevant methods and concepts defining an overall control architecture for AVs, with an emphasis on the safety assessment and decision-making systems composing these architectures. Moreover, it is intended through this reviewing process to highlight researches that use either model-based methods or AI-based approaches. This is performed while emphasizing the strengths and weaknesses of each methodology and investigating the research that proposes a comprehensive multi-modal design that combines model-based and AI approaches. This paper ends with discussions on the methods used to guarantee the safety of AVs namely: safety verification techniques and the standardization/generalization of safety frameworks