紫色球杆菌视紫红质光谱特性的机器学习研究

近年来，机器学习等人工智能技术被应用于蛋白质工程，其在蛋白质结构、功能预测、催化活性等研究中具有独特优势。在未知蛋白质结构的情况下，将蛋白质序列和功能特性与机器学习相结合，基于序列-活性关系（innovative sequence-activity relationship，ISAR）算法，将蛋白质氨基酸序列数字化，用快速傅里叶变换（fast four transform，FFT）进行预处理，再进行偏最小二乘回归建模，可在数据集较少情况下拟合得到最佳模型。通过机器学习对紫色球杆菌视紫红质（gloeobacter violaceus rhodopsin，GR）的突变体蛋白质氨基酸序列与光谱最大吸收波长进行建模，获得了最佳模型。用最佳索引LEVM760106建模得到的确定系数R² 为0.944，均方误差E为11.64。用小波变换进行的预处理，其R² 虽也约为0.944，但E大于11.64，不及FFT进行的预处理。方法较好地解决了蛋白质序列与功能特性之间的数学建模问题，在蛋白质工程中可为预测更优的突变体提供支持。     

Stochastic sensitivity analysis of coupled acoustic-structural systems under non-stationary random excitations

This paper presents a new sensitivity analysis method for coupled acoustic–structural systems subjected to non-stationary random excitations. The integral of the response power spectrum density (PSD) of the coupled system is taken as the objective function. The thickness of each structural element is used as a design variable. A time-domain algorithm integrating the pseudo excitation method (PEM), direct differentiation method (DDM) and high precision direct (HPD) integration method is proposed for the sensitivity analysis of the objective function with respect to design variables. Firstly, the PEM is adopted to transform the sensitivity analysis under non-stationary random excitations into the sensitivity analysis under pseudo transient excitations. Then, the sensitivity analysis equation of the coupled system under pseudo transient excitations is derived based on the DDM. Moreover, the HPD integration method is used to efficiently solve the sensitivity analysis equation under pseudo transient excitations in a reduced-order modal space. Numerical examples are presented to demonstrate the validity of the proposed method.     

一种非正交对称条带束流位置监测器设计

介绍了一种条带束流位置监测器(BPM)的设计与仿真方法。在国家同步辐射实验室"太赫兹近场高通量材料物性测试系统"工程项目中,针对波荡器出口处真空室非正交对称性的问题,设计了矩形真空室和跑道形真空室下的两种非正交对称性条带BPM,并与传统的圆形真空室下条带BPM进行对比。基于边界元法,利用MATLAB软件分别对三种真空室下的条带BPM进行建模和仿真。仿真结果表明:相对于传统的圆形真空室下条带BPM,矩形和跑道形真空室下条带BPM灵敏度提高了30%,阻抗匹配误差相对降低了20%,束流位置拟合误差降低了80%。考虑加工精度,矩形真空室下的条带BPM更适用于该工程。     

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.     

Biomolecular Release Stimulated by Electrochemical Signals at a Very Small Potential Applied

DNA release electrochemically stimulated by applying ?10 mV on the modified electrode was studied. The release process was based on the local (interfacial) pH change produced upon H₂O₂ reduction electrocatalyzed by the immobilized microperoxidase‐11. SiO₂ nanoparticles attached to the electrode surface and functionalized with trigonelline and boronic acid species changed their electrical charge from positive to negative upon the interfacial pH change, thus allowing electrostatic adsorption of negatively charged DNA on the positive interface and then its repulsion/release from the negative interface. The loaded/released DNA molecules were labeled with a fluorescent dye to allow easy detection of the released DNA molecules. The important feature of the developed system is the controlled DNA release upon applying very small electrical potential on the modified electrode.     

Dual‐signal amplification strategy for ultrasensitive chemiluminescence detection of PDGF–BB in capillary electrophoresis

Many efforts have been made toward the achievement of high sensitivity in capillary electrophoresis coupled with chemiluminescence detection (CE‐CL). This work describes a novel dual‐signal amplification strategy for highly specific and ultrasensitive CL detection of human platelet‐derived growth factor–BB (PDGF–BB) using both aptamer and horseradish peroxidase (HRP) modified gold nanoparticles (HRP–AuNPs–aptamer) as nanoprobes in CE. Both AuNPs and HRP in the nanoprobes could amplify the CL signals in the luminol–H₂O₂ CL system, owing to the excellent catalytic behavior of AuNPs and HRP in the CL system. Meanwhile, the high affinity of aptamer modified on the AuNPs allows detection with high specificity. As proof‐of‐concept, the proposed method was employed to quantify the concentration of PDGF–BB from 0.50 to 250 fm with a detection limit of 0.21 fm. The applicability of the assay was further demonstrated in the analysis of PDGF–BB in human serum samples with acceptable accuracy and reliability. The result of this study exhibits distinct advantages, such as high sensitivity, good specificity, simplicity, and very small sample consumption. The good performances of the proposed strategy provide a powerful avenue for ultrasensitive detection of rare proteins in biological sample, showing great promise in biochemical analysis. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive signal enhancement for overlapped peaks based on weighting factor selection

Peak-sharpening is an effective method for the peak position detection of overlapped spectra. However, the weighing factor parameter strongly affects the sharpening performance, and the derivative adopted in the peak-sharpening method is sensitive to noise. In this paper, an adaptive peak-sharpening method based on weighting factor selection is proposed. The relationship between the sharpening ratio and weighting factor is studied. In addition, the Savitzky–Golay filter is adopted due to its excellent noise reduction and peak shape retention abilities. First, the smoothed signal and second-order derivative signal are obtained by the Savitzky–Golay filter. Then, the parameters of the overlapped peaks are estimated for the weighting factor selection. Next, the peak position is detected by the peak-sharpening method. After that step, the estimated parameters are updated, and the above steps are iterated until the detection of the peak position converges. Finally, the converged results are considered to be the final detection results. The experimental results using a simulated dataset, a virtual mass spectra dataset and a polarography dataset show that the proposed method is effective for peak position detection.     

多聚螯合物酶联抗体交联磁性纳米乳胶的脂联素免疫透射比浊方法研究

采用多聚螯合物酶联抗体交联磁性纳米乳胶的脂联素免疫透射比浊法检测了血清中脂联素.发现多聚螯合物酶上含有大量HRP酶,可以极大地放大检测信号;在优化条件下,免疫比浊信号强度在脂联素0.005~0.2 ng·m L-1范围内变化时,并随着ADPN浓度的增加呈线性关系(R2=0.998),检出限为2 pg·m L-1.该方法能成功用于血清样本中脂联素的检测.     

A new class of conformable spectral observers for signal reconstruction

In this work, the design of spectral observers for signal reconstruction based on Kalman filters is performed and evaluated. The conformable derivative and the beta‐derivative were used to design the Kalman filters. Both derivatives satisfy the same formulas of the classical derivation, eg, the chain rule. The derivative order, the Ricatti equation parameters, and the observers tuning parameters were optimized using an optimization algorithm based on the bat's echolocation behavior (Bat algorithm). The simulation results showed the advantages of using the proposed observers for the signal reconstruction.     

Molecular signal suppression by in situ microextraction in nuclear magnetic resonance spectroscopy

The detailed characterization of complex mixtures by NMR is often hampered by the presence of signals from uninformative compounds, the resonances of which overlap with those of the molecules of interest. We provide here a proof of principle for an approach to NMR signal suppression in complex samples using Molecularly Imprinted Polymers (MIPS). Addition of a few milligrams of polymer to a solution traps the target molecule in typical micromolar to millimolar concentration, thus achieving in situ signal suppression, without altering any other spectral features. This method minimized any manipulation or perturbation of the spectrum and was applied to a complex mixture of known compounds and to a plant extract, in both cases spiked with a compound (bisphenol A), which was subsequently removed by selective binding to a complementary MIP. What is described in this report is comparable with microextraction and may in due course be applied to a large number of analytical challenges. Copyright © 2014 John Wiley & Sons, Ltd.