Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

An efficient edge based data structure for the compressible Reynolds-averaged Navier–Stokes equations on hybrid unstructured meshes

An efficient edge based data structure has been developed in order to implement an unstructured vertex based finite volume algorithm for the Reynolds-averaged Navier–Stokes equations on hybrid meshes. In the present approach, the data structure is tailored to meet the requirements of the vertex based algorithm by considering data access patterns and cache efficiency. The required data are packed and allocated in a way that they are close to each other in the physical memory. Therefore, the proposed data structure increases cache performance and improves computation time. As a result, the explicit flow solver indicates a significant speed up compared to other open-source solvers in terms of CPU time. A fully implicit version has also been implemented based on the PETSc library in order to improve the robustness of the algorithm. The resulting algebraic equations due to the compressible Navier–Stokes and the one equation Spalart–Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the FGMRES Krylov subspace algorithm. In order to further improve the computational accuracy, the multiscale metric based anisotropic mesh refinement library PyAMG is used for mesh adaptation. The numerical algorithm is validated for the classical benchmark problems such as the transonic turbulent flow around a supercritical RAE2822 airfoil and DLR-F6 wing-body-nacelle-pylon configuration. The efficiency of the data structure is demonstrated by achieving up to an order of magnitude speed up in CPU times.     

Determination of sulfa antibiotic residues in river and particulate matter by field-amplified sample injection-capillary zone electrophoresis

In the present research, field-amplified sample injection–CZE (FASI–CZE) coupled with a diode array detector was established to determine trace level sulfa antibiotic. Sulfathiazole, sulfadiazine, sulfamethazine, sulfadimethoxine, sulfamethoxazole, and sulfisoxazole were selected as analytes for the experiments. The background electrolyte solution consisted of 70.0 mmol/L borax and 60.0 mmol/L boric acid (including 10% methanol, pH 9.1). The plug was 2.5 mmol/L borax, which was injected into the capillary at a pressure of 0.5 psi for 5 s. Then the sample was injected into the capillary at an injection voltage of –10 kV for 20 s. The electrophoretic separation was carried out under a voltage of +19 kV. The capillary temperature was maintained at 20˚C throughout the analysis, and six sulfonamides were completely separated within 35 min. Compared with pressure injection-CZE, the sensitivity of FASI-CZE was increased by 6.25–10.0 times, and the LODs were reduced from 0.2–0.5 to 0.02–0.05 μg/mL. The method was applied to the determination of sulfonamides in river water and particulate matter samples. The recoveries were 78.59–106.59%. The intraday and interday precisions were 2.89–7.35% and 2.77–7.09%, respectively. This provides a simpler and faster method for the analysis of sulfa antibiotic residues in environmental samples.     

Nucleophilic Activation of Sulfur Hexafluoride by N-Heterocyclic Carbenes and N-Heterocyclic Olefins: A Computational Study

Sulfur hexafluoride (SF₆) is considered as a potent greenhouse gas, whose effective degradation is challenging. Here we report a computational study on the nucleophilic activation of sulfur hexafluoride by N-heterocyclic carbenes and N-heterocyclic olefins. The result shows that the activation of SF₆ is both thermodynamically and kinetically favorable at mild condition using NHOs with fluoro-substituted azolium and sulfur pentafluoride anion being formed. The Gibbs free energy barrier during the activation of SF₆ has a linear relationship with the energy of HOMO of substrates, which could be a guideline for applying those compounds that feature higher energy in HOMO to activate SF₆ in high efficiency.     

Definition and detection of data-based uniqueness in evaluating bilinear (two-way) chemical measurements

Multivariate curve resolution methods, frequently used in analyzing bilinear data sets, result in ambiguous decomposition in general. Implementing the adequate constraints may lead to reduce the so-called rotational ambiguity drastically, and in the most favorable cases to the unique solution. However, in some special cases, non-negativity constraint as minimal information of the system is a sufficient condition to resolve profiles uniquely. Although, several studies on exploring the uniqueness of the bilinear non-negatively constrained multivariate curve resolution methods have been made in the literature, it has still remained a mysterious question. In 1995, Manne published his profile-based theorems giving the necessary and sufficient conditions of the unique resolution. In this study, a new term, i.e., data-based uniqueness is defined and investigated in details, and a general procedure is suggested for detection of uniquely recovered profile(s) on the basis of data set structure in the abstract space. Close inspection of Borgen plots of these data sets leads to realize the comprehensive information of local rank, and these argumentations furnish a basis for data-based uniqueness theorem. The reported phenomenon and its exploration is a new stage (it can be said fundament) in understanding and describing the bilinear (matrix-type) chemical data in general.     

Semilinear wave models with friction and viscoelastic damping

In this paper, we study the global (in time) existence of small data solutions to the Cauchy problem for the semilinear wave equation with friction, viscoelastic damping, and a power nonlinearity. We are interested in the connection between regularity assumptions for the data and the admissible range of exponents p in the power nonlinearity.     

Spectral estimates for saddle point matrices arising in weak constraint four‐dimensional variational data assimilation

We consider the large sparse symmetric linear systems of equations that arise in the solution of weak constraint four‐dimensional variational data assimilation, a method of high interest for numerical weather prediction. These systems can be written as saddle point systems with a 3 × 3 block structure but block eliminations can be performed to reduce them to saddle point systems with a 2 × 2 block structure, or further to symmetric positive definite systems. In this article, we analyse how sensitive the spectra of these matrices are to the number of observations of the underlying dynamical system. We also obtain bounds on the eigenvalues of the matrices. Numerical experiments are used to confirm the theoretical analysis and bounds.     

Enhancing signal-to-noise ratio and resolution in low-field NMR relaxation measurements using post-acquisition digital filters

The traditional way to enhance signal-to-noise ratio (SNR) of nuclear magnetic resonance (NMR) signals is to increase the number of scans. However, this procedure increases the measuring time that can be prohibitive for some applications. Therefore, we have tested the use of several post-acquisition digital filters to enhance SNR up to one order of magnitude in time domain NMR (TD-NMR) relaxation measurements. The procedures were studied using continuous wave free precession (CWFP-T₁) signals, acquired with very low flip angles that contain six times more noise than the Carr–Purcell–Meiboom–Gill (CPMG) signal of the same sample and experimental time. Linear (LI) and logarithmic (LO) data compression, low-pass infinity impulse response (LP), Savitzky–Golay (SG), and wavelet transform (WA) post-acquisition filters enhanced the SNR of the CWFP-T₁ signals by at least six times. The best filters were LO, SG, and WA that have high enhancement in SNR without significant distortions in the ILT relaxation distribution data. Therefore, it was demonstrated that these post-acquisition digital filters could be a useful way to denoise CWFP-T₁, as well as CPMG noisy signals, and consequently reducing the experimental time. It was also demonstrated that filtered CWFP-T₁ method has the potential to be a rapid and nondestructive method to measure fat content in beef and certainly in other meat samples.     

基于吸收系数的生脉注射液中聚山梨酯80含量测定新方法

聚山梨酯80又名吐温80，为一种亲水型非离子表面活性剂，是食品、保健品和药品中常用的辅料，作为增溶剂和澄清剂广泛用于中药注射剂。近年来，不良反应的发生使得聚山梨酯80的质量和应用愈加受到重视，有研究认为其加入可能引起注射剂不良反应增加。为避免超量使用，有必要对该辅料的投料加以严格控制。中药注射剂中聚山梨酯80的含量测定是当下研究的热点和难点，可以通过分光光度法、分子排阻-蒸发光散射检测法(SEC-ELSD)、液质联用法(LC-MS)直接测定，也可以水解后法经液相色谱-紫外检测法(HPLC-UV)或气相色谱法(GC)间接测定。但由于聚山梨酯80为聚氧乙烯聚合数目不同的混合物、不同厂家生产的聚山梨酯80化学组分及比例存在较大差异，难以采用统一的转换公式或对照品准确定量。此外，中药注射剂的复杂基质造成的假阳性干扰也对定量提出了挑战。为解决以上问题，以生脉注射液为例，提出基于吸收系数的中药注射剂中聚山梨酯80含量测定新方法。优化检测波长、显色剂种类、液液萃取过程振荡和静置时间，在6个不同品牌仪器上测得聚山梨酯80-硫氰酸钴配合物的吸收系数(E1%_{1 cm})为104.23，相对标准偏差(RSD)为2.08%。生脉注射液稀释10倍后，精密量取供试品溶液1.0 mL，精密加入硫氰酸钴溶液10 mL，二氯甲烷20 mL，涡旋振荡3 min。将混合液移至分液漏斗中，静置30 min，取下层二氯甲烷液，将前1 mL弃去，接收约15 mL，在320 nm处测定吸光度，再根据Lambert-Beer定律，利用获得的吸收系数计算得到聚山梨酯80的含量。方法阴性无干扰，精密度和重复性相对标准偏差均低于3%，平均回收率为98.42%。为进一步验证方法的准确性，分别采用吸收系数法和标准曲线法测定了2个厂家的10批生脉注射液，并与实际投料量比较。配对t检验结果表明，当置信度为95%时，两种方法无显著性差异，吸收系数法测得结果与企业生产中聚山梨酯的实际投料量也无显著性差异。研究采用前人未采用的、灵敏度更高的320 nm为检测波长，显著降低了基质干扰，克服了中药注射剂中聚山梨酯80测定结果与实际投料量难以吻合的问题。吸收系数法无需使用对照品，亦不用制备标准曲线，可为中药注射剂中聚山梨酯80的检查标准提供切实可行的解决方案。所建方法灵敏、准确、快速、简便，为含聚山梨酯80制剂的质量控制提供了关键常数及新的思路。     

The visible and ultraviolet organic light-emitting diodes with germanium dioxide as facile solution-processed anode buffer layer

Germanium dioxide (GeO₂) aqueous solutions are facilely prepared and the corresponding anode buffer layers (ABLs) with solution process are demonstrated. Atomic force microscopy, X-ray photoelectron spectroscopy and ultraviolet photoelectron spectroscopy measurements show that solution-processed GeO₂ behaves superior film morphology and enhanced work function. Using GeO₂ as ABL of organic light-emitting diodes (OLEDs), the visible device with tris(8-hydroxy-quinolinato)aluminium as emitter gives maximum luminous efficiency of 6.5 cd/A and power efficiency of 3.5 lm/W, the ultraviolet device with 3-(4-biphenyl)-4-phenyl-5-tert-butylphenyl-1,2,4-triazole as emitter exhibits short-wavelength emission with peak of 376 nm, full-width at half-maximum of 42 nm, maximum radiance of 3.36 mW/cm² and external quantum efficiency of 1.5%. The performances are almost comparable to the counterparts with poly (3,4-ethylenedioxythiophene):poly (styrenesulfonate) as ABL. The current, impedance, phase and capacitance as a function of voltage characteristics elucidate that the GeO₂ ABL formed from appropriate concentration of GeO₂ aqueous solution favors hole injection enhancement and accordingly promoting device performance.