SHAPE MEMORY EFFECT OF PU IONOMERS WITH IONIC GROUPS ON HARD-SEGMENTS

SMPU （shape memory polyurethane） non-ionomers and ionomers, synthesized with poly（c-caprolactone） （PCL）, 4, 4＇-diphenylmethane diisocyanate （MDI）, 1,4-butanediol （BDO）, dimethylolpropionic acid （DMPA） were measured with cyclic tensile test and strain recovery test. The relations between the structure and shape memory effect of these two series were studied with respect to the ionic group content and the effect of neutralization. The resulting data indicate that, with the introduction of asymmetrical extender, the stress at 100% elongation is decreased for PU non-ionomer and ionomer series, especially lowered sharply for non-ionomer series; the fixation ratio of ionomer series is not affected obviously by the ionic group content; the total recovery ratio of ionomer series is decreased greatly. After sufficient relaxation time for samples stretched beforehand, the switching temperature is raised slightly, whereas the recovery ratio measured with strain recovery test method is lowered with increased DMPA content. The characterization with FT-IR, DSC, DMA elucidated that, the ordered hard domain of the two series is disrupted with the introduction of DMPA which causes more hard segments to dissolve in soft phase; ionic groups on hard segment enhance the cohesion between hard segments especially at high ionic group content and significantly facilitate the phase separation compared with the corresponding non-ionomer at moderate ionic group content.     

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.     

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.     

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.     

Synthesis and Characterization of Novel Liquid Crystalline Epoxides with Lateral Substituent Showing Imposing Shape Memory Properties

In this work, a series of novel shape memory liquid crystalline (LC) epoxides with lateral substituent were prepared and characterized. Dynamic mechanical analysis (DMA) and shape memory testing were used to investigate on the thermo-mechanical properties and shape memory effects of prepared samples. The results showed that the modulus in the rubbery region (E_R ) decreased as the length of lateral alkyl group increases. And more than 95% of the deformation can be fixed as the sample was cooled down below the glass transition temperature (T_g), which was determined by differential scanning calorimetry (DSC) measurement, and can be recovered completely as heating. Effects of the curing agent and substituent on the shape memory behavior were also studied. We found that LC epoxides cured by aromatic diamine have a higher recovery speed. The recovering speeds of the shape memory decreased as the length of lateral alkyl group inscreased. The local ordered structures and the lateral substituent played an important role in shape memory effects.     

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.     

悬索大挠度风振响应的有限体积法分析

基于Lagrange原理,建立了一套新的悬索大挠度动力特性和动力响应分析的有限体积法列式,推导了结点力向量、质量矩阵和单元刚度矩阵的显式表达式。该列式的一个显著特点是直接利用工程应变定义结构变形,其物理意义明确,列式简单,适用于各种垂度和荷载情况的悬索大挠度动力分析。实例动力特性和随机风振响应分析表明,该有限体积列式不仅计算效率高,而且具有良好的计算精度。     

爆炸荷载作用下钢筋混凝土梁的动力响应及破坏形态分析

对基于Timoshenko梁理论建立的非线性动力有限元法作了改进。根据压区理论得到混凝土的平均剪应力和平均剪应变关系,建立了能反映箍筋的抗剪作用的材料模型;此外,对结构在爆炸荷载作用下可能出现的各种响应现象进行了描述,以准确地预测梁破坏时不同位置截面上钢筋和混凝土的受力、变形及破坏情况。应用改进的材料模型,对爆炸荷载作用下的五个钢筋混凝土试验梁的动力响应和破坏形态进行了数值模拟,结果表明,该数值方法能较好地模拟钢筋混凝土梁的弯曲、弯剪和剪切等破坏形态。