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。     

Catalytic amplification based on hole-transporting materials as efficient metal-free electrocatalysts for non-enzymatic glucose sensing

Hole-transporting materials with tunable structures and properties are mainly applied in organic light-emitting diodes as transport layer. But their catalytic properties as signal amplifiers in biological assays are seldom reported. In this paper, a starburst molecule, 4,4,4″-tri(N-carbazolyl)-triphenylamine (TCT), containing a triphenylamine as the central core and three carbazoles as the peripheral functional groups was designed and synthesized. Subsequently, the hole-transporting material based on the TCT polymer, poly(TCT) (PTCT), was achieved via a low-cost electrochemical method and exploited as an efficient metal-free electrocatalyst for non-enzymatic glucose detection. Here, this hole-transporting material served three purposes: electrochemical recognition (owing to hydrogen bonding interaction and the biomimetic microenvironment created by the polymer), electrocatalysis (owing to the hole-transporting capability of triphenylamine and the catalytic property of carbazole), and signal amplification (owing to energy migration along the conductive polymer backbone). The electrocatalytic and sensing performances of the sensor based on PTCT were evaluated in detail. Results revealed that the PTCT film could efficiently catalyze the oxidation of glucose at a less-positive potential (+0.20 V) in the absence of any enzymes. The response to glucose was linear in the concentration range of 1.0–6000 μM, and the detection limit was 0.20 μM. With good stability and selectivity, the proposed sensor could be feasibly applied to detect glucose in practical samples. The encouraging sensing performances suggest that the hole-transporting material is one of the promising biomimetic catalysts for electrocatalysis and relevant fields.     

Digital image correlation in experimental mechanics and image registration in computer vision: Similarities,differences and complements

Digital image correlation and image registration or matching are among the most widely used techniques in the fields of experimental mechanics and computer vision, respectively. Despite their applications in separate fields, both techniques primarily involve detecting the same physical points in two or more images. In this paper, a brief technical comparison of the two techniques is reviewed, and their similarities and differences as well as complements are presented. It is shown that some concepts from the image registration or matching technique can be applied to the digital image correlation technique to substantially enhance its performance, which can help broaden the applications of digital image correlation in scientific research and engineering practice.     

Statistical analysis of S/N-curves by means of a fatigue database for polypropylene

Material databases of plastics are becoming more and more the focus of applied science and commercial use in industry. Material properties of material manufacturers are often provided in publicly accessible material databases, which usually contain processing and mechanical properties under static loadings. Fatigue strength values are usually not accessible. The fatigue data for thermoplastics is of particular interest, as these materials have a particularly high lightweight construction potential and can be processed with a high degree of automation and reproducibility.Individual fatigue strength parameters for a specific material, environmental condition, geometry and loadings have been investigated in numerous publications. However, no work has been found in which fundamental interactions of different materials, environmental conditions, geometries and loadings on the course of the S/N-Curve have been investigated.In this paper, different effect relationships between temperature, filler type and filler content, fiber orientation and load ratio will be presented for the material Polypropylene (PP). A fatigue strength database of 11 different material manufacturers, from 71 different S/N-Curves with 606 tested samples, serves as a basis. The fatigue database enables a digital twin, which is used for the design of structural components to add a third dimension with artificial intelligence, and which is trained by an engineer. From the determined effect relationships, fatigue factors are to be derived and can be used to evaluate the fatigue strength of a component in the design process and to train the digital twin. The fatigue-strength values from the database also allow a statistical consideration of the slope k and the scattering of the S/N-Curve. The different S/N-Curves are transferred into a Haigh diagram, from which the functional course of the mean stress is determined.     

A technique for in situ X-ray computed tomography of deformation-induced cavitation in thermoplastics

Deformation-induced cavitation influences the mechanical response of polymeric materials, but acquiring in situ measurements of the spatial evolution of cavities has typically necessitated the use of synchrotron radiation sources. The objective of this study is to develop and demonstrate a method allowing for in situ measurements of deformation-induced cavitation in axisymmetric polymer specimens, using a home-laboratory X-ray computed tomography setup. The method is demonstrated by assessing deformation-induced cavitation of mineral-filled PVC in a repeated loading-unloading experiment. A temporal resolution of about 3 s is obtained by exploiting the axisymmetry of notched round tensile specimens. The evolution of relative density was captured throughout the experiment, revealing an interplay between void nucleation and void growth. Combined with surface deformation measurements obtained by digital image correlation, the present technique yields data suitable for calibration and validation of material models.     

Disentangling stochastic signals superposed on short localized oscillations

We introduce a procedure for separating periodic oscillations superposed on a stochastic signal. The procedure combines empirical mode decomposition (EMD) of a signal with tools of data analysis based on stochastic differential equations, namely nonlinear Langevin equations. Taking the set of modes retrieved from the EMD of the signal, our procedure is able to separate them into two groups, one composing the periodic signal and another composing the stochastic signal. The framework is robust for a broad family of localized oscillations, in the range of large frequencies. In particular, we show that, in this context, the EMD method outperforms a low-pass filter and is robust for a wide interval of different frequency ranges and amplitudes of the periodic oscillation, as well as for a broad family of different non-linear Langevin processes.     

An experimental method for eliminating effect of rigid out-of-plane motion on 2D-DIC

The out-of-plane motion is one of the most important factors that affect the precision of two-dimensional digital image correlation (2D-DIC). In this paper, a novel solution is presented to improve conventional 2D-DIC by eliminating the effect of out-of-plane motion, including translation and rotation. Firstly, an experimental technique using two projected laser strips is proposed to measure the out-of-plane motion of a planar specimen. A theoretical model is then established to predict the pseudostrains caused by out-of-plane motion based on the pin-hole imaging model. Using the measured out-of-plane displacement, the captured deformed images used in 2D-DIC are amended to eliminate the effect of out-of-plane motion by the theoretical model. Finally, two experiments were conducted to validate the effectiveness of the proposed method. Results indicate that application of the proposed method can effectively eliminate the errors caused by out-of-plane motion.     

Comparative and evolutionary studies of mammalian arylsulfatase and sterylsulfatase genes and proteins encoded on the X-chromosome

At least 19 sulfatase genes have been reported on the human genome, including four arylsulfatase (ARS) genes (ARSD; ARSE; ARSF; ARSH) and a sterylsulfatase (STS) gene located together on the X-chromosome. Bioinformatic analyses of mammalian genomes were undertaken using known human STS and ARS amino acid sequences to study the evolution of these genes and proteins encoded on eutherian and marsupial genomes. Several domain regions and key residues were conserved including signal peptides, active site residues, metal (Ca²⁺) and substrate binding sequences, transmembranes and N-glycosylation sites. Phylogenetic analyses describe the relationships and potential origins of these genes during mammalian evolution. Primate ARSH enzymes lacked signal peptide sequences which may influence their biological functions. CpG117 and CpG92 were detected within the 5′ region of the human STS and ARSD genes, respectively, and miR-205 within the 3′-UTR for the human STS gene, using bioinformatic methods A proposal is described for a primordial invertebrate STS-like gene serving as an ancestor for unequal cross over events generating the gene complex on the eutherian mammalian X-chromosome.