As the number falls,alternatives to the Hagberg–Perten falling number method: A review

This review examines the application, limitations, and potential alternatives to the Hagberg–Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.     

STATIONARY TANGENT: THE DISCRETE AND NON-SMOOTH CASE

Abstract. In Keich (2000 ),we define a stationary tangent process, or a locally optimal stationary approximation, to a real non-stationary smooth Gaussian process. This paper extends the idea by constructing a discrete tangent – a `locally' optimal stationary approximation – for a discrete time, real Gaussian process. Analogously to the smooth case, our construction relies on a generalization of the recursion formula for the orthogonal polynomials of the spectral distribution function. More precisely, we use a generalization of the Schur parameters to identify the stationary tangent. By way of discretizing, we later demonstrate how this tangent can be used to obtain `good' local stationary approximations to non-smooth continuous time, real Gaussian processes. Further, we demonstrate how, analogously to the curvatures in the smooth case, the Schur parameters can be used to determine the order of stationarity of a non-smooth process.     

Wave dynamics on a thin-liquid film falling down a heated wall

The dynamics of a thin liquid film falling down a uniformly heated wall is studied. The model introduced by Kalliadasis et al. [J. Fluid Mech. 475 (2003) 377] for the same problem is revisited and its deficiencies, namely the prediction of a critical Reynolds number with 20% error, cured. For the energy equation a high-order Galerkin projection in terms of polynomial test functions is developed. It is shown that not only does this more refined formulation correct the critical Reynolds number, but it also gives, with an appropriate expansion close to criticality, the long-wave theory. Bifurcation diagrams for permanent solitary waves are constructed and compared with the solution branches obtained from different models. It is shown that, in all cases, the long-wave theory exhibits limit points and branch multiplicity, while the other models predict the continuing existence of solitary waves. Time-dependent computations show that the free surface and interfacial temperature approach a train of coherent structures that resemble the infinite-domain stationary solitary pulses.     

Terminal velocity of non-spherical particles falling through a Carreau model liquid

A procedure has been proposed for the estimation of the terminal falling velocity of non-spherical particles moving in a Carreau model fluid in the transition flow region. The procedure is based on a modification of the relationship formerly developed for the fall of spherical particles including the particle dynamic shape factor. The suitability of the proposed procedure has been confirmed by good agreement between experimental and calculated terminal falling velocity data. In the experiments, the terminal falling velocity of short cylinders and rectangular prisms in polymer solutions of different measure of shear thinning and elasticity has been measured.     

Bootstrapping the Local Periodogram of Locally Stationary Processes

Abstract. Locally stationary processes are non‐stationary stochastic processes the second‐order structure of which varies smoothly over time. In this paper, we develop a method to bootstrap the local periodogram of a locally stationary process. Our method generates pseudo local periodogram ordinates by combining a parametric time and non‐parametric frequency domain bootstrap approach. We first fit locally a time varying autoregressive model so as to capture the essential characteristics of the underlying process. A locally calculated non‐parametric correction in the frequency domain is then used so as to improve upon the locally parametric autoregressive fit. As an application, we investigate theoretically the asymptotic properties of the bootstrap method proposed applied to the class of local spectral means, local ratio statistics and local spectral density estimators. Some simulations demonstrate the ability of our method to give accurate estimates of the quantities of interest in finite sample situations and an application to a real‐life data‐set is presented.     

Locally Weighted Learning

This paper surveys locally weighted learning, a form of lazy learning and memory-based learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, assessing predictions, handling noisy data and outliers, improving the quality of predictions by tuning fit parameters, interference between old and new data, implementing locally weighted learning efficiently, and applications of locally weighted learning. A companion paper surveys how locally weighted learning can be used in robot learning and control.     

局部散射源参数估计的非线性算子方法

本文利用单次快摄数据的两个非线性算子估计局部散射源中心波达方向和角扩展,与多维参数搜索和其他低复杂性的局部散射源参数估计算法不同,非线性算子方法给出了单次快摄的局部散射源参数估计的闭式解,无需进行多维搜索和子空间分解。     

微重力落塔电磁悬吊、释放技术研究

论述了微重力落塔电磁悬吊、释放、提升机构的关键技术,电磁释放过程的特性分析以及微重力落塔实际试验的情况。分析说明:悬吊、释放性能的好坏决定了试验落舱的微重力水平,也是微重力落塔试验能否成功的关键技术。     

降膜蒸发过程的数值模拟和传热传质分析

利用CFD软件对逆流降膜蒸发过程进行了实验模拟研究,研究了速度边界层、热边界层和浓度边界层的变化对降膜蒸发传热传质特性的影响规律;通过建立一维逆流降膜蒸发的数学方程编程求解出了对流传热传质的Nu数和Sh数,利用Fluent软件模拟出的实验结果采用回归分析得出了气液流量比Raw、流道的长宽比αL、空气进口无量纲温度θai以及空气进口Re数与Nu数、Sh数之间的无量纲关系式,可为降膜蒸发换热器的设计提供参考。     

基于局部线性嵌入和支持向量机回归的TBM施工参数预测

依托吉林引松工程开展隧道掘进机（TBM）施工参数预测研究,提出TBM施工数据分段提取算法,提取上升段前30 s的总推进力、刀盘转速、推进速度、刀盘扭矩、刀盘转速电位器设定值、推进速度电位器设定值、贯入度、贯入度指数(FPI)、扭矩切深指数(TPI)9个参数作为输入;通过局部线性嵌入（LLE）完成对上升段数据特征的降维;基于支持向量机回归（SVR）建立TBM施工控制参数（推进速度、刀盘转速）和负载参数（总推进力、刀盘扭矩）预测模型. 分析是否结合前一掘进循环的FPI、TPI指数进行预测对预测效果的影响. 结果表明,上述方法在推进速度、刀盘转速、总推进力、刀盘扭矩的预测中均取得了较好的预测效果,平均预测绝对百分比误差均小于15%,验证了该预测方法的有效性,该方法可以为TBM现场施工提供指导.