Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence–structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended β-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.     

基于颜色四通道及空间金字塔的鱼类图像检索

随着计算机视觉技术在海洋水产领域中的应用不断加深，鱼类图像检索在渔业资源调查、鱼类行为学分析等方面发挥了巨大的作用。通过研究发现，鱼类图像的背景信息会对鱼类图像检索造成极大干扰，而且鱼类图像中颜色、纹理、形状等特征由于空间位置信息的缺乏而使检索的准确率不高。为解决以上问题，提出了一种新的基于颜色四通道及空间金字塔的鱼类图像检索算法。首先，提取视觉显著性图将鱼类图像的前景和背景分开，从而减少图像背景对检索的干扰；其次，为了使图像特征包含一定的空间位置信息，利用空间金字塔的理论对图像进行分割，在此基础上，将图像转为HSVG四通道图并提取SURF特征；；最后，得到检索结果。为验证所提算法的有效性，在QUT_fish_data数据集和DLOU_fish_data数据集上对算法的查全率、查准率与经典的HSVG算法和显著性分块算法进行对比：在两个数据集上查准率分别比传统的HSVG算法最多分别提高12%和5%，查全率最多分别提高7%和22%；比传统的显著性分块算法查准率最多分别提高15%和5%，查全率最多分别提高36%和22%；从而证明所提算法是有效的，能有效提升鱼类图像的检索效果。     

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.     

Methods and Applications of In Silico Aptamer Design and Modeling

Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphates, nucleobases, amino acids, and drugs. During nucleic acid modeling and in silico design, a full set of in silico methods can be applied, such as docking, molecular dynamics (MD), and statistical analysis. The typical modeling workflow starts with structure prediction. Then, docking of target and aptamer is performed. Next, MD simulations are performed, which allows for an evaluation of the stability of aptamer/ligand complexes and determination of the binding energies with higher accuracy. Then, aptamer/ligand interactions are analyzed, and mutations of studied aptamers made. Subsequently, the whole procedure of molecular modeling can be reiterated. Thus, the interactions between aptamers and their ligands are complex and difficult to understand using only experimental approaches. Docking and MD are irreplaceable when aptamers are studied in silico.     

Grain size dependence of hardness in nanocrystalline silicon carbide

The response of nanocrystalline silicon carbide (nc-SiC) to nanoindentation is investigated using molecular dynamics (MD) simulation. It is found that the hardness of the nc-SiC decreases with decreasing grain size, showing an inverse Hall-Petch relationship. The behavior is primarily attributed to the reduced number of intact covalent bonds with grain refinement. Dislocation nucleation and growth in nc-SiC are strongly suppressed by the grain boundaries (GBs). In addition to the dislocation region in the grains, the indentation-induced amorphization of nanograins proceeds preferentially from the GBs, leading to grain shrinkage until the grains are fully amorphized. The results provide an improved understanding of the mechanical properties in nc-SiC and other nanostructured covalent materials.     

基于聚类的数据加权优化在犯罪预测中的应用

近年来，我国传统暴力犯罪与成年人犯罪呈下降态势，但是，犯罪案由层出不穷。为有效提升公安实践工作中犯罪预测能力，打击各类违法犯罪事件,本文针对犯罪数据，提出一种新型犯罪预测模型。利用密度聚类分析方法将犯罪数据分类，然后进行数据降维提取关键属性生成特征数据，继而对特征数据进行加权优化并采用机器学习的方式对特征数据进行学习，从而预测犯罪案由。实验结果表明，与传统方法相比，本文方法具有更好的预测效果，为公安实践工作中类似案件的侦破和预防，提供新的路径支撑。     

萃取塔数学模型及过程强化的若干研究进展

萃取塔因生产能力大、占地面积小、密闭性好等优点，在石油、化工、生物、医药和环境工程等多领域被广泛应用。本文从以下几个方面介绍了萃取塔近些年的研究进展：综述了传统萃取塔（脉冲萃取塔、转盘塔与Kühni塔等）的水力学、轴向扩散与传质模型的发展，分析比较了表面张力、传质方向、放大效应等因素对模型的影响；介绍了计算流体动力学（CFD）在萃取塔中单液滴、单相流模拟、液-液两相流模拟、外加能量模拟、与群体平衡模型（PBM）耦合模拟中的应用进展；介绍了国内外设计开发的新型萃取塔，包括改变传统塔的内构件和引入多种外场能量等方式来强化相间传质。研究表明，将先进实验研究方法、准确经验模型和可靠理论计算相结合，将会是萃取塔研究的重要手段和方向。     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

基于密集神经网络的灰度图像着色算法

针对在灰度图像着色领域中，传统算法信息提取率不高、着色效果不理想的问题，提出了基于密集神经网络的灰度图像着色算法，以实现改善着色效果，让人眼更好地观察图片信息的目的。利用密集神经网络的信息提取高效性，构建并训练了一个端到端的深度学习模型，对图像中的各类信息及特征进行提取。训练网络时与原图像进行对比，以逐渐减小网络输出结果的信息、分类等各类型的损失。训练完成后，只需向网络输入一张灰度图片，即可生成一张颜色饱满、鲜明逼真的彩色图片。实验结果表明，引入密集网络后，可有效改善着色过程中的漏色、细节信息损失、对比度低等问题，所提算法着色效果较基于VGG网络及U-Net、双流网络结构、残差网络（ResNet）等性能优异的先进着色算法而言取得了显著的改进。     

PDC钻头水力结构优化设计研究

在PDC钻头工作过程中，钻井液对钻头体表面的冲洗、冷却和润滑是保证钻头正常工作的一个非常重要的条件。对PDC钻头而言，水力结构（主要是中心水眼和冠部水道）设计的重要性尤其突出。以前,对钻头水力系统研究只能通过实验的方法进行,研究周期长、成本高、结构调整不方便，而数值模拟的方法在几年前还不成熟，甚至静态的复杂结构流场问题基本无法解决。为此，在提出PDC钻头水力结构优化设计原则的基础上，对PDC钻头的三维流场进行了数值模拟。模拟中考虑了钻头的喷嘴布置位置、直径、数量以及切削齿对流场的影响。计算结果表明，原设计在喷嘴布置位置和喷射角度上存在不足，以此为基础进行了水力结构的优化设计。文中的研究成果成功地应用在新型钻头水力结构的设计中，研究方法为PDC钻头水力结构优化分析奠定了理论基础。