Transport Map sampling with PGD model reduction for fast dynamical Bayesian data assimilation

The motivation of this work is to address real-time sequential inference of parameters with a full Bayesian formulation. First, the proper generalized decomposition (PGD) is used to reduce the computational evaluation of the posterior density in the online phase. Second, Transport Map sampling is used to build a deterministic coupling between a reference measure and the posterior measure. The determination of the transport maps involves the solution of a minimization problem. As the PGD model is quasi-analytical and under a variable separation form, the use of gradient and Hessian information speeds up the minimization algorithm. Eventually, uncertainty quantification on outputs of interest of the model can be easily performed due to the global feature of the PGD solution over all coordinate domains. Numerical examples highlight the performance of the method.     

New approach to identify the initial condition in degenerate hyperbolic equation

This paper deals with the determination of an initial condition in degenerate hyperbolic equation from final observations. With the aim of reducing the execution time, this inverse problem is solved using an approach based on double regularization: a Tikhonov’s regularization and regularization in equation by viscose-elasticity. So, we obtain a sequence of weak solutions of degenerate linear viscose-elastic problems. Firstly, we prove the existence and uniqueness of each term of this sequence. Secondly, we prove the convergence of this sequence to the weak solution of the initial problem. Also we present some numerical experiments to show the performance of this approach.     

Biotransformation of hop derived compounds by Brettanomyces yeast strains

Several hop derived compounds in wort are known to be converted by yeast during fermentation, influencing the overall perception of the beer. A deeper understanding of such metabolic processes during fermentation is needed to achieve better control of the outcome. Here, the interaction between hop derived compounds and the yeast genera Brettanomyces was studied. Several Brettanomyces strains with different genomic backgrounds were selected, focusing on two traits: beta-glucosidase activity and nitrate assimilation. The role of three beta-glucosidases present in Brettanomyces bruxellensis and Brettanomyces anomalus and their impact on the final monoterpene alcohol profile was analysed. The beta-glucosidase activity was highly strain dependent, with B. anomalus CRL-49 exhibiting the highest conversion. Such activity could not be related to the release of aglycones from hops during fermentation, as a substantial part of such activity was intracellular. Nevertheless, the reduction of geraniol to β-citronellol was remarkably efficient for all Brettanomyces strains during fermentation, and it is suggested that two oxidoreductases BbHye2 and BbHye3 may have an influence. Moreover, the transfer of nitrate from hops to wort and its further assimilation by Brettanomyces species was analysed. The amount of nitrate in wort proved to be linearly proportional to the contact time of the hops with the wort. The level of nitrate assimilation by yeast was shown to be dependent on the nitrate assimilation cluster (YNR, YNI, YNT). Hence, the desired yeast strains may be selected according to the genetic make-up. © 2020 The Authors. Journal of the Institute of Brewing published by John Wiley & Sons Ltd on behalf of The Institute of Brewing & Distilling     

生物氧化预处理中进气量实时预测数学模型研究

精准预测生物氧化预处理中的进气量对提高黄金提取率和节能降耗具有重要意义。以气体管流连续性方程和运动方程为控制方程，采用Preissmann隐格式法作为差分方法。同时，根据集合卡尔曼滤波(Ensemble Kalman filter，EnKF)算法原理，构造进气量、压强的状态空间模型。结果表明，基于气体管流控制方程建立的进气量模型预测结果与实际进气量观测值具有较好的一致性；与传统静态预测方法相比，EnKF同化方法引入实时观测值和模型参数的更新，有效提高了进气量的预测精度，其平均绝对误差、平均相对误差和均方根误差有明显的降低。可见，基于气体管流控制方程建立的预测模型结合EnKF同化方法是提高生物氧化槽进气量预测精度的有效手段。     

Rice PIN Auxin Efflux Carriers Modulate the Nitrogen Response in a Changing Nitrogen Growth Environment

Auxins play an essential role in regulating plant growth and adaptation to abiotic stresses, such as nutrient stress. Our current understanding of auxins is based almost entirely on the results of research on the eudicot Arabidopsis thaliana, however, the role of the rice PIN-FORMED (PIN) auxin efflux carriers in the regulation of the ammonium-dependent response remains elusive. Here, we analyzed the expression patterns in various organs/tissues and the ammonium-dependent response of rice PIN-family genes (OsPIN genes) via qRT–PCR, and attempted to elucidate the relationship between nitrogen (N) utilization and auxin transporters. To investigate auxin distribution under ammonium-dependent response after N deficiency in rice roots, we used DR5::VENUS reporter lines that retained a highly active synthetic auxin response. Subsequently, we confirmed that ammonium supplementation reduced the DR5::VENUS signal compared with that observed in the N-deficient condition. These results are consistent with the decreased expression patterns of almost all OsPIN genes in the presence of the ammonium-dependent response to N deficiency. Furthermore, the ospin1b mutant showed an insensitive phenotype in the ammonium-dependent response to N deficiency and disturbances in the regulation of several N-assimilation genes. These molecular and physiological findings suggest that auxin is involved in the ammonium assimilation process of rice, which is a model crop plant.     

Estimating post-disaster traffic conditions using real-time data streams

This article presents a technique to determine the effects of an earthquake on road traffic conditions by linking seismic hazard and bridge fragility models with a traffic model and traffic sensor data. Using the earthquake characteristics as an input to the traffic model, the traffic conditions are sequentially estimated given traffic sensor measurements using an ensemble Kalman filter. The proposed algorithm is tested on a numerical experiment on Interstate 155 West near the New Madrid Seismic Zone in New Madrid, Missouri. The results show that the proposed technique improves the post-disaster traffic estimate. The supporting source code and data are available for download at https://github.com/rotsuka/postDisaster_EnKF..     

How neutral coloured backgrounds affect the attractiveness and expensiveness of fresh produce

The colour of the background on which products are presented may affect their perceived attractiveness. In order to find out on which type of background various fresh food products look most attractive, we presented five different vegetables (tomato, carrot, yellow bell pepper, eggplant, mushroom) on five different backgrounds with neutral grey colours varying in degree of blackness: 5, 30, 50, 65, and 90%. Forty-six participants provided colour matches for the vegetables and evaluated them on 10 attributes.Overall, the blackness of the backgrounds had little or no effect on the perceived colour of the vegetable. Only for carrots we found a small but significant difference, mainly between the 5% and 90% blackness backgrounds. On the darkest background, the carrot would be perceived as a bit lighter, more saturated, and more yellow rather than red, compared to the lightest background.Differences in perceived attractiveness on the grey backgrounds varied between 0.3 and 1.0 units on a 9-point scale. Attractiveness and expensiveness ratings for most vegetables were highest on the 90% blackness background. In comparison to our previous study where we presented vegetables on hued backgrounds, differences between mean attractiveness ratings were smaller. Because mean attractiveness ratings in the current study were higher, we expect that grey backgrounds are more likely to present vegetable assortments with a variety of hues in an attractive way than hued backgrounds.     

Optimal design of measurement network for neutronic activity field reconstruction by data assimilation

An optimal reconstruction of the neutronic activity field can be determined for a nuclear reactor core using a data assimilation framework to merge information from models and measurements. In this paper, we focus on solving the inverse problem of determining an optimal repartition of the measuring instruments within the core, to get the best possible results from the data assimilation reconstruction procedure. The position optimisation is realised using a Simulated Annealing algorithm, based on the Metropolis-Hastings proposition. Moreover, algebraic improvements of data assimilation have been developed, optimising their computational performance, and are presented here.     

A real-time probabilistic channel flood-forecasting model based on the Bayesian particle filter approach

Reliable real-time probabilistic flood forecasting is critical for effective water management and flood protection all over the world. In this study, we develop a real-time probabilistic channel flood-forecasting model by combining a channel hydraulic model with the Bayesian particle filter approach. The new model is tested in the upstream river reach of Three Gorges Dam (TGD) on the Yangtze River, China. Stage observations at seven hydrological stations are used simultaneously to adjust the Manning's roughness coefficients and to update discharges and stages along the river reach to attain reliable probabilistic flood forecasting. The synthetic experiments are applied to demonstrate the new model's correction and forecasting performances. The real-world experiments show that the new model can make accurate flood forecasting as well as derive reliable intervals for different confidence levels. The new probabilistic flood forecasting model not only outperforms the existing deterministic channel flood-forecasting models in accuracy, but also provides a more robust tool with which to incorporate uncertainty into flood-control efforts.     

WRF-LTNGDA: A lightning data assimilation technique implemented in the WRF model for improving precipitation forecasts

This study introduces WRF-LTNGDA, a lightning data assimilation technique implemented in the Weather Research and Forecasting (WRF) model. This technique employs lightning for improving the representation of convection by means of controlling the triggering of the model's convection parameterization scheme. The development and implementation of WRF-LTNGDA was carried out in a framework that could easily allow for its exploitation in real-time forecasting activities. The assimilation algorithm was evaluated over eight precipitation events that took place in Greece in the years 2010–2013. Results clearly show that lightning forcing has a positive impact on model performance. The conducted analysis revealed that the employment of WRF-LTNGDA induces statistically significant improvements in precipitation verification scores, especially for high rainfall accumulations. Separate examination of one of the eight case studies highlighted the overall better agreement between the modelled and observed spatial distribution of precipitation when lightning data assimilation was applied, than in the control simulation.