Styrene Butadiene Rubber/Epoxidized Natural Rubber (SBR/ENR50) Nanocomposites Containing Nanoclay and Carbon Black as Fillers for Application in Tire-Tread Compounds

Nanocomposite vulcunizates based on a SBR/ENR50 (50/50%wt) rubber blend containing nanoclay (5 or 10 phr) with and without carbon black (CB 20 phr) were prepared by melt blending in an internal mixer. The compound containing 35 phr carbon black (only) was prepared as a reference sample. Microstructure of nanocomposite samples was investigated by using X-ray diffraction (XRD), melt rheo-mechanical spectroscopy (RMS), and scanning electron microscopy (SEM). The XRD patterns revealed that the distance between the clay layers were increased by adding CB to the nanocomposite samples; they caused better diffusion of chains between the layers and resulted in an intercalated structure. The RMS results also indicated the formation of the filler-filler networks. SEM images of fracture surfaces showed the presence of much roughness in the samples containing both nanoclay and CB compared to the other samples. The results obtained from application of the Flory–Rhener equation showed a high crosslink density for the sample with 10 phr nanoclay and 20 phr CB. Dynamic mechanical behavior, mechanical properties, and abrasion resistance of the nanocomposites were evaluated. The results indicated that the sample containing 10 phr nanoclay and 20 phr CB had an increased dynamic elastic modulus, reduced maximum loss factor (tanδ)_max,, and an improved tensile strength and abrasion resistance compared to the reference sample. Also, this sample showed the lowest maximum loss factor, at 50–60°C, so it can be a candidate for tire-tread application.     

The rotating Morse potential energy eigenvalues solved by using the analytical transfer matrix method

We study the eigenvalues of the rotating Morse potential by using the quantization condition from the analytical transfer matrix(ATM) method.A hierarchy of supersymmetric partner potentials is obtained with Pekeris approximation,which can be used to calculate the energies of higher rotational states from the energies of lower states.The energies of rotational states of the hydrogen molecule are calculated by the ATM condition,and comparison of the results with those from the hypervirial perturbation method reveals that the accuracy of the approximate expression of Pekeris for the eigenvalues of the rotating Morse potential can be improved substantially in the framework of supersymmetric quantum mechanics.     

Deep learning-based channel estimation using Gaussian mixture distribution and expectation maximum algorithm

In massive multiple-input multiple-output (MIMO), it is much challenging to obtain accurate channel state information (CSI) after radio frequency (RF) chain reduction due to the high dimensions. With the fast development of machine learning(ML), it is widely acknowledged that ML is an effective method to deal with channel models which are typically unknown and hard to approximate. In this paper, we use the low complexity vector approximate messaging passing (VAMP) algorithm for channel estimation, combined with a deep learning framework for soft threshold shrinkage function training. Furthermore, in order to improve the estimation accuracy of the algorithm for massive MIMO channels, an optimized threshold function is proposed. This function is based on Gaussian mixture (GM) distribution modeling, and the expectation maximum Algorithm (EM Algorithm) is used to recover the channel information in beamspace. This contraction function and deep neural network are improved on the vector approximate messaging algorithm to form a high-precision channel estimation algorithm. Simulation results validate the effectiveness of the proposed network.     

“String” formulation of the dynamics of the forward interest rate curve

We propose a formulation of the term structure of interest rates in which the forward curve is seen as the deformation of a string. We derive the general condition that the partial differential equations governing the motion of such string must obey in order to account for the condition of absence of arbitrage opportunities. This condition takes a form similar to a fluctuation-dissipation theorem, albeit on the same quantity (the forward rate), linking the bias to the covariance of variation fluctuations. We provide the general structure of the models that obey this constraint in the framework of stochastic partial (possibly non-linear) differential equations. We derive the general solution for the pricing and hedging of interest rate derivatives within this framework, albeit for the linear case (we also provide in the appendix a simple and intuitive derivation of the standard European option problem). We also show how the “string” formulation simplifies into a standard N-factor model under a Galerkin approximation. Received: 30 January 1998 / Revised: 12 February 1998 / Accepted: 16 February 1998     

局部建模方法用于烟草样品的近红外光谱定量分析

采用近红外光谱在主成分空间的距离作为样本相似性的判据,建立了一种用于近红外光谱定量分析的局部建模方法。该方法首先对校正集的光谱进行主成分分析(PCA),然后基于主成分空间中预测样本与校正集样本的距离选择校正子集并建立局部偏最小二乘(PLS)回归模型。对欧氏距离和马氏距离的比较表明,欧氏距离可以更好地表达样本之间的相似性。将所建立的方法用于烟草样品中氯和尼古丁含量的测定,结果表明局部建模方法比常用的全局建模方法具有更好的预测准确性,特别是在低含量成分的预测中具有明显优势。     

Quantum statistics of the degenerate four-wave mixing process

A quantum mechanical treatment is given of the degenerate four-wave mixing process. The approximate Heisenberg equation of motion for creation and annihilation operators is solved taking into account attenuation and noise. The solution and the statistics of the modes are discussed both below and above the threshold condition.     

不同温度的牛血清白蛋白的太赫兹光谱研究

利用太赫兹时域光谱技术，测量了加热到298，308，328和348 K的牛血清白蛋白(BSA)固体样本的低频光谱，测量过程中获得了BSA样本的折射系数曲线、吸收系数曲线。由于BSA样本的THz折射系数和吸收系数光谱曲线存在重叠现象，采用主成分分析法对BSA样本的折射系数、吸收系数、复介电系数虚部及介电损耗角正切，共四个太赫兹光谱参数进行分析，发现样本未变性前，介电损耗角的正切与牛血清白蛋白样本的温度最相关，相关系数达到99.76%。采用模糊聚类方法区分变性前后的BSA固体样本，建立不同温度的BSA模糊识别模型，发现可以将未变性的样本与已经变性的样本区分开，为检测不同温度蛋白质特性的太赫兹光谱法提供新的途径。     

Approximate solution of optical soliton in lossless fibres with third-order dispersion

A near zero-dispersion regime, fundamental soliton with third-order dispersion is considered. There are three different waves radiated from the soliton. We find a threshold condition for the radiated waves. Below the threshold condition a stable soliton exists; an approximate soliton solution is obtained.     

The impact of spin coupling signal loss on fat content characterization in multi-echo acquisitions with different echo spacing

PurposeThis study aimed to assess the effect of echo spacing in transverse magnetization (T2) signal decay of gel and fat (oil) samples. Additionally, we assess the feasibility of using spin coupling as a determinant of fat content.MethodsPhantoms of known T2 values, as well as vegetable oil phantoms, were scanned at 1.5 T scanner with a multi echo FSE sequence of variable echo spacing above and below the empirical threshold of 20 ms for echo train signal modulation (6.7, 13.6, 26.8, and 40 ms). T2 values were calculated from monoexponential fitting of the data. Relative signal loss between the four acquisitions of different echo spacing was calculated.ResultsAgreement in the T2 values of water gel phantom was observed in all acquisitions as opposed to fat phantom (oil) samples. Relative differences in signal intensity between two successive sequences of different echo spacing on composite fat/water regions of interest was found to be linearly correlated to fat fraction of the ROI.ConclusionThe sample specific degree of signal loss that was observed between different fat samples (vegetable oils) can be attributed to the composition of each sample in J coupled fat components. Hence, spin coupling may be used as a determinant of fat content.     

Measurements of the ns-laserpulse induced expansion of (111) silicon below and above the melting threshold on the nanosecond time scale

The surface displacement of 111-silicon wafers of 0.675 mm and 3.05 mm thickness, respectively, during intense ns laser irradiation is determined on the nm-vertical and ns-time scale using an optimized Michelson interferometer. The surface dynamics is observed below as well as above the melting threshold. We show that the obtained surface expansion below the melting threshold is in good agreement with theoretical heat transfer calculations. Additionally, thickness-dependent bending in the samples is illustrated and the acoustic reflections from the backside of the sample are observed. Maximum thermal displacement at the first expansion plateau is around 6 nm before melting occurs. We show that qualitative agreement between experimental results and simulation above the melting threshold can be established for the first time by taking the phase shift change in the reflection for molten silicon into account.     

基于改进ABC的LSSVM氧化还原电位预测研究

针对氧化还原电位对于生物氧化提金预处理过程的控制和优化具有重要作用,提出了一种基于改进的ABC算法优化最小二乘支持向量机的预测方法。该算法是在标准人工蜂群算法的基础上,通过引入欧氏距离,使得在一定邻域内观察蜂采用不同于雇佣蜂的搜索策略。采用改进的ABC算法优化最小二乘支持向量机的参数,取得最优解并赋予最小二乘支持向量机进行预测。以新疆某金矿的生产数据进行仿真研究,结果表明：基于改进的ABC算法优化的最小二乘支持向量机具有较高的预测精度,该方法能使模型取得较好的预测效果。     

薄膜电致发光器件中SiO2加速作用的直接证据

本文通过包含CdS层的薄膜电致发光(TFEL)器件的有关特性的研究,直接证明了SIO₂对CdS中产生的电子有良好的加速作用,并获得了阈值电压低、B-V特性好,亮度较高的红色TFEL器件.我们将硫化镉蒸镀于电致发光器件中,测量这些器件的电学和光学特性,发现含CdS的样品的传导电荷明显大于不含CdS的样品,这说明硫化镉层可以提供较多的电子.但是,样品ITO/SiO₂/ZnS:Sm³⁺/SiO₂/CdS/Al的发光效率低于不含硫化镐的样品,这说明这些电子在进入ZnS层的过程中能量有所降低.为了提高这些电子的能量,我们制备了样品ITO/SiO₂/ZnS:Sm³⁺/SiO₂/CdS/Al,使硫化镉中产生的电子先经过SiO₂层,再进入发光层.测量结果表明这一样品的最大亮度和发光效率与上述含硫化镉的样品相比分别提高了2.5个和0.5个数量级,与不含硫化镉的样品的亮度接近,但其阈值电压较低,亮度-电压(B-V)曲线上升部分较陡,且有一段饱和区.在这一样品达到饱和的电压下,不含硫化镉的样品才刚刚起亮,这说明该样品的发光主要是由于硫化镉增加的电子数目对发光的贡献.同时这些电子在SiO₂中得到了明显的加速.     

基于强影响度的近红外奇异样本识别算法研究

校正样本选择以及奇异样本剔除对于近红外光谱定量和定性建模非常重要。现有的识别奇异样本的方法一般都基于数据重心估计,需要一个经验的判断阈值,在很大程度上限制了其识别准确性和实用性。针对现有方法奇异样本识别准确率低的问题,改进了一种现有度量尺度-杠杆值,构造出一种新的基于强影响度的奇异样本识别算法。这种度量尺度在一定程度上减少了对数据重心的依赖,使正常样本更加聚集,拉开了奇异样本与正常样本的距离;同时,为了避免人工根据经验设定阈值的不合理性,引入统计学领域中跳跃度的概念,提出了一种自动阈值设定方法判别奇异样本。为了验证该算法的有效性,利用马氏距离、杠杆值-光谱残差法与该算法分别对200个代表性校正集样本中的异常样品进行剔除,然后通过偏最小二乘法(PLS)对剩余的校正集样本(以烟碱为指标)定量建模,并对60个代表性测试集样本进行预测,以交互验证均方根误差(RMSECV)、相关系数(r)和预测均方根误差(RMSEP)为评价指标比较各算法的优劣。实验对比结果表明,基于强影响度的奇异样本识别算法较现有方法明显提高了奇异样本识别的准确率,具有较低的RMSECV(0.104),RMSEP(0.112)以及较高的R(0.983),提高了模型的稳定性和预测能力。     

Depixelation of coherent fiber bundle endoscopy based on learning patterns of image prior

We present an iterative method of eliminating pixelation artifacts from an endoscopic image acquired from a coherent fiber bundle imager. Our proposed approach for decoupling the honeycomb effect from the obtained sample image was formulated by using the prior probability for an approximate Bayesian framework in which the ideal complete image can be estimated by maximizing the posterior probability from the observed image. The maximization of the posterior probability from the original mask image (the mirrored fiber bundle imager structure) and the observed image (the sample image of the United States Air Force chart) has been performed by learning the image priors in the space of Markov random fields. By iteratively estimating the probability distribution, we reduced the noise effects from the mask image and recovered the ideal shape of the image. This method was efficient for automatically learning the sliding patch from the combination of projected kernels. The mask and observed images were obtained from en face images of the Fourier domain optical coherence tomography based on a common path interferometry scheme.     

Sampling the Variational Posterior with Local Refinement

Variational inference is an optimization-based method for approximating the posterior distribution of the parameters in Bayesian probabilistic models. A key challenge of variational inference is to approximate the posterior with a distribution that is computationally tractable yet sufficiently expressive. We propose a novel method for generating samples from a highly flexible variational approximation. The method starts with a coarse initial approximation and generates samples by refining it in selected, local regions. This allows the samples to capture dependencies and multi-modality in the posterior, even when these are absent from the initial approximation. We demonstrate theoretically that our method always improves the quality of the approximation (as measured by the evidence lower bound). In experiments, our method consistently outperforms recent variational inference methods in terms of log-likelihood and ELBO across three example tasks: the Eight-Schools example (an inference task in a hierarchical model), training a ResNet-20 (Bayesian inference in a large neural network), and the Mushroom task (posterior sampling in a contextual bandit problem).     

非平坦样品激光诱导等离子体光谱特性研究

激光诱导击穿光谱（LIBS）作为一种快速、实时的元素分析技术,由于其在痕量元素探测、地质环境监测等领域有着广阔的应用前景,而受到人们极大的关注。在实际应用中,样品表面是影响等离子体产生及其特性的关键环境因素之一。在大气环境下,利用脉宽为8 ns、波长为1 064 nm的纳秒脉冲激光产生等离子体,对比研究了天然岩石样品在非平坦和平坦表面条件下等离子体的发射光谱。基于激光辅助辐射波模型,阐释了非平坦样品表面对其光谱特性的影响。通过对比等离子体时间积分光谱,发现非平坦样品的谱线强度相比于平坦样品的谱线强度减弱了近70%,该结果说明非平坦样品表面对LIBS真实测量数据的负面影响不可忽视。针对褐铁矿样品中的谱线Fe Ⅰ 404.58 nm和Fe Ⅰ 438.35 nm,研究了在平坦和非平坦样品表面下的峰值强度以及其衰减因子随激光能量的变化规律,结果表明非平坦样品表面条件下采集的光谱强度始终低于平坦样品表面的光谱强度。光谱强度的衰减因子先随激光能量增大而逐渐降低,并在激光能量33 mJ达到最小值,后随激光能量的进一步增大而增大。实验结果进一步表明在非平坦样品表面条件下产生了密度较低的等离子体,并且非平坦与平坦样品的电子密度的比值在激光能量33 mJ时达到最小,此结果与光谱强度的衰减因子随激光能量的变化趋势一致,这是源于非平坦样品表面会形成较大激光入射角度,使得激光等离子体能量吸收区厚度变薄,产生等离子体屏蔽效应所对应的激光能量阈值升高。此外,样品表面状态和激光能量对等离子体温度的影响甚微。阐述了非正入射时等离子体特征参数与正入射时等离子体特征参数的联系和差异,揭示了非平坦样品激光等离子体特征参量变化的内在物理机制,为室外LIBS探测技术在元素定性和定量分析中光谱强度的校正提供参考。     

Dependence of the induced loss factor on the coupling forms and coupling strengths: energy analysis

In two recent papers, the induced loss factor is determined via the modification to the loss factor in the linear impedance of a master oscillator caused by its coupling to a set of satellite oscillators. A loss factor is basically an energetic quantity and, therefore, one may inquire whether the induced loss factor may be estimated via an energy analysis (EA). An answer to this question is sought. It is shown that the linear impedance analysis and EA yields identical results for the induced loss factor in the appropriate frequency range. This frequency range spans the distribution of resonance frequencies of the satellite oscillators. In this frequency range, the identity of the results is not only in terms of gross features but also in detail. Finally, the relationship of EA to statistical energy analysis (SEA) is explored. The loss factors assigned to the satellite oscillators are cast in terms of modal overlap parameters. It is found necessary for the validation of SEA, in the light of EA, that these parameters exceed a certain threshold. In specific situations of interest the threshold values may exceed unity.     

放大器间距对应用相敏光放大器的平均光孤子系统传输性能影响的研究

本文采用计算机系统仿真方法,研究了相敏光放大器(PSA) 作为在线放大器时光孤子系统中放大器间距对系统传输性能的影响,研究了平均孤子传输方案.仿真结果表明：当放大器间距与色散距离比值小于0.1时,系统能够保持良好的传输性能;在比值大于0.1情况下,系统的传输性能劣化较快.这是由于PSA增益的相敏特性导致孤子脉冲能量的损失所引起的.采用微调放大器增益的方法能在一定程度上补偿PSA放大导致的孤子能量损失,但这种改善是以增大孤子脉冲旁瓣幅度为代价的.     

Multi-modal analysis for low energy neutron-induced fission of ~(235)U

Low energy neutron induced fission of ~(235)U is studied in the framework of the multi-modal fission model. The fission fragment properties, such as the yields, the average total kinetic energy distribution and the average neutron separation energy, are investigated for incident neutron energies from thermal to 6.0 MeV. The multi-modal fission approach is also used to evaluate the prompt fission neutron multiplicity and spectra for the neutron-induced fission of ~(235)U with an improved version of the Los Alamos model for incident neutrons below the (n, nf) threshold. The three most dominant fission modes are taken into account. The model parameters are determined on the basis of experimental data. The calculated results are in good agreement with the experimental data.