Uncertainty assessment from robustness testing applied on an LC assay for R-timolol and other related substances in S-timolol maleate

The robustness testing of a normal-phase liquid chromatographic (LC) method for the determination of R-timolol and other related substances in S-timolol maleate was performed applying a two-level Plackett-Burman design. Two qualitative and five quantitative factors were examined. Two types of responses were considered, qualitative, i.e. chromatographic performance criteria, and quantitative ones. The latter were taken into account to determine if the analytical procedure was robust. The quantitative responses were the contents of R-timolol in two S-timolol maleate samples. Even though some significant factor effects were observed on the qualitative responses, the R-timolol contents were not significantly different from those observed at nominal conditions, which demonstrated the robustness of the procedure.Since the experiments of the Plackett-Burman design can be assimilated to laboratories in an interlaboratory study, uncertainty can be evaluated using the robustness test data. The robustness test was set-up in such a way that the required variances could be estimated. It was shown that the robustness set-up allows estimating the reproducibility uncertainty without performing an interlaboratory study.     

复杂框支剪力墙结构模型试验

针对某楼板开洞的复杂框支剪力墙结构高层商住楼制作了1／20整体试验模型，进行了模型的振动台试验，得到了结构在不同裂度地震作用下的加速度、速度、位移及应力一应变曲线，分析了结构的动力特性和动力荷载下的受力特点。研究结果表明，合理的楼板开洞可有效减小转换层以上结构的侧向刚度，避免结构沿竖向产生较大的刚度突变。     

连体构架避雷针风振计算的简化方法

为简化构架避雷针风振时域计算从而有效降低计算耗时,以单跨和三跨构架避雷针结构为例,根据构架体系的结构特性和风振特点,提出一种简化计算方法,即对每个塔架单独建模并考虑结构刚度和质量系统的一致性和横梁荷载的等效加载,从而对每个塔架单独进行动力计算,并对这种简化方法的合理性进行了验证。研究发现,构架避雷针的频率较小,风振效应较为显著,但在各方向均以一阶振型为绝对主力;构架避雷针的塔架在平面外的荷载耦联效应极小,平面内也仅表现有位移均值的耦联效应:这两个结构特性也为风振简化计算提供了便利。对每个塔架的简化模型,通过在塔架与原横梁连接处设置弹簧和附加质量来实现对原结构一阶振型的等效,并通过影响线法将横梁分布风荷载等效为塔架的集中荷载。由此简化方法所得的结构风振静动力响应结果均与原始结构有良好一致性,并且计算效率得以显著提升。     

土工格栅加固路桥过渡段的动测试分析

在秦沈铁路客运专线乙试验工点现场试验的基础上,对土工格栅加固后的路桥过渡段基床动响应特性及其影响因素进行了分析和研究.研究结果表明:随着行车速度增大,过渡段基床动应力增量为正;但当行车速度超过临界速度(220～230 km/h)后,基床动应力不再增加,反而减小;基床动应力的变化特征与其在基床中的位置密切相关,沿线路纵向水平方向上,动应力随距桥台背距离的增大而呈减小趋势;沿深度方向上,动应力随深度的增加而呈衰减趋势;过渡段沉降差的存在导致基床动应力增大,严格控制过渡段沉降差是高速铁路设计和施工的关键.     

双盘悬臂转子系统碰磨响应的分叉与混沌特性分析

建立了八自由度16阶的双盘转子在2个盘上分别存在碰磨力情况的运动方程，结合摩擦学Coulomgb模型给出了新的碰磨力表达关系式，分析了双盘转子系统的碰磨现象和非线性响应特性，分析了系统的各种参数对系统分叉的影响和系统进入混沌的通道，发现了由拟周期进入混沌的通道和由阵发性进入混沌的通道，研究表明，支承1与圆盘1间的距离变小或支承2与圆盘2的距离变小容易导致系统不稳定，碰磨刚度或圆盘1的不平衡参数变大将导致系统更加不稳定。     

The Microbiome and Its Implications in Cancer Immunotherapy

Cancer is responsible for ~18 million deaths globally each year, representing a major cause of death. Several types of therapy strategies such as radiotherapy, chemotherapy and more recently immunotherapy, have been implemented in treating various types of cancer. Microbes have recently been found to be both directly and indirectly involved in cancer progression and regulation, and studies have provided novel and clear insights into the microbiome-mediated emergence of cancers. Scientists around the globe are striving hard to identify and characterize these microbes and the underlying mechanisms by which they promote or suppress various kinds of cancer. Microbes may influence immunotherapy by blocking various cell cycle checkpoints and the production of certain metabolites. Hence, there is an urgent need to better understand the role of these microbes in the promotion and suppression of cancer. The identification of microbes may help in the development of future diagnostic tools to cure cancers possibly associated with the microbiome. This review mainly focuses on various microbes and their association with different types of cancer, responses to immunotherapeutic modulation, physiological responses, and prebiotic and postbiotic effects.     

Efficient computation of operator‐type response sensitivities for uncertainty quantification and predictive modeling: illustrative application to a spent nuclear fuel dissolver model

This work honors the 75th birthday of Professor Ionel Michael Navon by presenting original results highlighting the computational efficiency of the adjoint sensitivity analysis methodology for function‐valued operator responses by means of an illustrative paradigm dissolver model. The dissolver model analyzed in this work has been selected because of its applicability to material separations and its potential role in diversion activities associated with proliferation and international safeguards. This dissolver model comprises eight active compartments in which the 16 time‐dependent nonlinear differential equations modeling the physical and chemical processes comprise 619 scalar and time‐dependent model parameters, related to the model's equation of state and inflow conditions. The most important response for the dissolver model is the time‐dependent nitric acid in the compartment furthest away from the inlet, where measurements are available at 307 time instances over the transient's duration of 10.5 h. The sensitivities to all model parameters of the acid concentrations at each of these instances in time are computed efficiently by applying the adjoint sensitivity analysis methodology for operator‐valued responses. The uncertainties in the model parameters are propagated using the above‐mentioned sensitivities to compute the uncertainties in the computed responses. A predictive modeling formalism is subsequently used to combine the computational results with the experimental information measured in the compartment furthest from the inlet and then predict optimal values and uncertainties throughout the dissolver. This predictive modeling methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution for the a priori known mean values and uncertainties characterizing the model parameters and the computed and experimentally measured model responses. This approximate a priori distribution is subsequently combined using Bayes' theorem with the “likelihood” provided by the multi‐physics computational models. Finally, the posterior distribution is evaluated using the saddle‐point method to obtain analytical expressions for the optimally predicted values for the parameters and responses of both multi‐physics models, along with corresponding reduced uncertainties. This work shows that even though the experimental data pertains solely to the compartment furthest from the inlet (where the data were measured), the predictive modeling procedure used herein actually improves the predictions and reduces the predicted uncertainties for the entire dissolver, including the compartment furthest from the measurements, because this predictive modeling methodology combines and transmits information simultaneously over the entire phase‐space, comprising all time steps and spatial locations. Copyright © 2016 John Wiley & Sons, Ltd.     

Generating Artificial Reverberation via Genetic Algorithms for Real-Time Applications

We introduce a Virtual Studio Technology (VST) 2 audio effect plugin that performs convolution reverb using synthetic Room Impulse Responses (RIRs) generated via a Genetic Algorithm (GA). The parameters of the plugin include some of those defined under the ISO 3382-1 standard (e.g., reverberation time, early decay time, and clarity), which are used to determine the fitness values of potential RIRs so that the user has some control over the shape of the resulting RIRs. In the GA, these RIRs are initially generated via a custom Gaussian noise method, and then evolve via truncation selection, random weighted average crossover, and mutation via Gaussian multiplication in order to produce RIRs that resemble real-world, recorded ones. Binaural Room Impulse Responses (BRIRs) can also be generated by assigning two different RIRs to the left and right stereo channels. With the proposed audio effect, new RIRs that represent virtual rooms, some of which may even be impossible to replicate in the physical world, can be generated and stored. Objective evaluation of the GA shows that contradictory combinations of parameter values will produce RIRs with low fitness. Additionally, through subjective evaluation, it was determined that RIRs generated by the GA were still perceptually distinguishable from similar real-world RIRs, but the perceptual differences were reduced when longer execution times were used for generating the RIRs or the unprocessed audio signals were comprised of only speech.     

Second harmonic magnetoacoustic responses of magnetic nanoparticles in magnetoacoustic tomography with magnetic induction

Due to the unique magnetic, mechanical and thermal properties, magnetic nanoparticles(MNPs) have comprehensive applications as the contrast and therapeutic agents in biomedical imaging and magnetic hyperthermia. The linear and nonlinear magnetoacoustic responses determined by the magnetic properties of MNPs have attracted more and more attention in biomedical engineering. By considering the relaxation time of MNPs, we derive the formulae of second harmonic magnetoacoustic responses(2H-MARs) for a cylindrical MNP solution model based on the mechanical oscillations of MNPs in magnetoacoustic tomography with magnetic induction(MAT-MI). It is proved that only the second harmonic magnetoacoustic oscillations can be generated by MNPs under an alternating magnetic excitation. The acoustic pressure of the 2H-MAR is proportional to the square of the magnetic field intensity and exhibits a linear increase with the concentration of MNPs. Numerical simulations of the 2H-MAR are confirmed by the experimental measurements for various magnetic field intensities and solution concentrations using a laser vibrometer. The favorable results demonstrate the feasibility of the harmonic measurements without the fundamental interference of the electromagnetic excitation, and suggest a new harmonic imaging strategy of MAT-MI for MNPs with enhanced spatial resolution and improved signal-to-noise ratio in biomedical applications.     

The application of digital image recognition to the analysis of two-dimensional fingerprints

High-performance liquid chromatography (HPLC) fingerprint has been commonly used in the quality control and assessment of herbal medicines, and two-dimensional (2D) fingerprint obtained by means of HPLC-diode array detector (HPLC/DAD) can provide higher reliability. In this paper, an approach to the analysis of the 2D HPLC/DAD fingerprints, which was based on digital image recognition techniques, was developed for the first time. First, wavelet transform was employed to eliminate noise signal in the 2D fingerprint, and then the 2D fingerprint was converted into grayscale image. Second, several features of the image were calculated, and hierarchical clustering. This approach was applied to the qualitative analysis of the different samples of coptis chinensis, and the clustering result of samples was all highly consistent with the real situation. Based on the densities in grayscale image, three components in standard samples were quantitative analyzed, and the obtained correlation coefficients between concentration and grayscale density were more than 0.999. Our study indicated that the analysis of the 2D HPLC/DAD fingerprint was successful based on the idea and techniques of digital image recognition techniques, and this proposed approach provided a new pathway for the analysis of two-dimensional spectrums.