New Trends in Beverage Packaging Systems: A Review

New trends in beverage packaging are focusing on the structure modification of packaging materials and the development of new active and/or intelligent systems, which can interact with the product or its environment, improving the conservation of beverages, such as wine, juice or beer, customer acceptability, and food security. In this paper, the main nutritional and organoleptic degradation processes of beverages, such as oxidative degradation or changes in the aromatic profiles, which influence their color and volatile composition are summarized. Finally, the description of the current situation of beverage packaging materials and new possible, emerging strategies to overcome some of the pending issues are discussed

The Second Generation of Mercator Data Assimilation System: Recent Developments and Last Results

Within the last decade, operational oceanography has considerably developed in particular thanks to the favourable research and development context offered by the GODAE project. Mercator, the French operational oceanography centre, contributes to this project by developing a series of ocean analysis / forecasting systems. The Mercator ocean analysis system is based on various assimilation techniques in order to optimally combine observations (sea level anomaly, sea surface temperature, in situ T&S profiles) with ocean model simulations. At present time, a series of ocean models ranging from global (2°, 1/4°) to basin scale eddy resolving (1/15° North Atlantic) resolution use data assimilation to produce operationally ocean analyses and 2 weeks forecasts. Several assimilation techniques are employed: multi data multivariate optimal interpolation or more advanced methods such as Kalman filter or variational methods. Optimal interpolation scheme called SAM1 was the first technique used to take advantage from both in situ and remotely sensed (sea level anomaly, sea surface temperature) data through fully multi variate assimilation. Mercator also developed a second assimilation scheme called SAM2 which is a reduced order Kalman filters using 3D multivariate modal decomposition of the forecast error covariance. The use of 3D modal representation for the error statistics is intended to improve analyses in highly inhomogeneous, anisotropic and nonseparable regions of the world ocean such as shallow areas, as well as in the surface layers. Advanced parametrisation and results of this second generation of Mercator assimilation system will be presented and discussed within the framework of different hindcast experiments using two different ocean forecasting systems (Global 2° and North Atlantic °)

Recent Developments of the Mercator Assimilation System (SAM): Towards the Seek Filter

The French MERCATOR project is developing several operational ocean forecasting systems to take part in the Global Ocean Data Assimilation Experiment (GODAE). Prototype systems are designed to simulate (1) the Atlantic and Mediterranean Sea (from 1/3o to 1/15o ), and (2) the global ocean circulation (from 2o to 1/4o ). The first generation assimilation scheme referred to as SAM1 has been implemented in the operational system. It provides routine weekly analyses and forecasts. SAM1 includes an altimetry-only version (SAM1-v1), and a fully multivariate version (SAM1-v2) permitting to assimilate vertical profiles and SST in addition to altimetry (JASON, ERS-2 and GFO). The SAM1 scheme is based on the SOFA reduced order interpolation scheme (LEGOS, Toulouse). It uses vertical/horizontal separation of error statistics, and order reduction in the vertical in terms of multivariate Empirical Orthogonal Functions (EOFs) of temperature: T, salinity: S, and barotropic streamfunction: ψ . The next generation assimilation system referred as SAM2 is being developed from the SEEK (Singular Evolutive Extended Kalman) algorithm (LEGI, Grenoble). This scheme is a Reduced Order Kalman Filter using a 3D multivariate modal decomposition of the forecast error covariance as well as an adaptive scheme to specify parameters of the forecast error. The use of the SEEK filter and its 3D modal representation for the error statistic is intended to overcome some of the limitations of SAM1 in highly inhomogeneous, anisotropic, and nonseparable regions of the world ocean such as shallow areas, as well as in the surface layer. A second objective for SAM2 will be to consistently propagate error estimates between successive assimilation cycles. We also developed several methods in order to generate 3D EOF basis both from local or global EOF calculation. Comparisons between these various multivariate approaches (SAM1 and SAM2) will be presented and discussed

Expected impact of the future SMOS and Aquarius Ocean surface salinity missions in the Mercator Ocean operational systems: new perspectives to monitor ocean circulation

International audienceSea Surface Salinity (SSS) has never been observed from space. The SSS from planned satellite missions such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius is a key to better understanding how ocean circulation is related to water cycle and how both these systems are changing through time. The Observing System Simulation Experiments (OSSEs) presented in this paper has been carried out with an ocean forecasting system developed within the French oceanographic Mercator Ocean context. They consist in hindcast experiments assimilating an operational dataset (Sea Surface Temperature (SST), in-situ profiles of temperature and salinity and Sea Level Anomalies (SLA)) and various simulated SMOS and Aquarius Sea Surface Salinity (SSS) data. These experiments use an eddy permitting model (1/3°) covering the North Atlantic from 20°S to 70°N. The new generation of fully multivariate assimilation system referred to as SAM2v1 which is being developed from the SEEK (Singular Evolutive Extended Kalman) algorithm is used. This scheme is a Reduced Order Kalman Filter using a 3D multivariate modal decomposition of the forecast error covariance. The OSSEs enabled us to show the positive impact of SSS assimilation on the Mercator Ocean operational forecasting system. These experiments particularly show the importance to specify appropriated observation errors and the impact of having and/or combining different observing system. Several conclusions can be highlighted such as the importance of the space/time scales consistency between the data products and our ocean prediction systems. This study has to be considered as an important step for assimilation of SSS measured from space. Further studies have to be conducted with other simulated data, other oceanic configurations and other improved assimilation schemes

Relaxation of a Spiking Mott Artificial Neuron

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Control of resistive switching in AM 4 Q 8 narrow gap Mott insulators: A first step towards neuromorphic applications

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