Effect of carbon nanotubes grown temperature on the fracture behavior of carbon fiber reinforced magnesium matrix composites: Interlaminar shear strength and tensile strength

The design of an interfacial structure is particularly important for load transfer in composites. In this paper, different amounts of carbon nanotubes (CNTs) were grafted onto the carbon fiber (CF) surface by adjusting grown temperature using injection chemical vapor deposition (ICVD). The prepared CF preform grafted with CNTs (CNTs-CF) were used to reinforce magnesium alloy by squeeze casting process. The microstructures were analyzed by means of optical microscope (OM) and scanning electron microscope (SEM), and the interlaminar shear strength (ILSS) and tensile strength of the composites were determined by double-notch shear test and tensile test. The results indicated that moderate ILSS was more conducive to improving the tensile properties of carbon fiber reinforced magnesium matrix (C_f/Mg) composites. Compared with C_f/Mg, the tensile strength of composite with CNTs increased by about 80%. For C_f/Mg composites grafted with CNTs, CNTs had the effects of delaying crack propagation and increasing energy consumption by the pull-out and bridging mechanism, which were the main reasons for improving the strength. The analysis of shear fracture surface showed that the crack propagation path can be optimized by adjusting the amounts of grafted CNTs. The presence of CNTs affects the stress distribution and consequently the crack initiation as well as the crack propagation.     

Development and performance analysis of novel in situ Cu–Ni/Al2O3 nanocomposites

Cu–Ni/Al₂O₃ nanocomposite powders were manufactured using an in situ chemical reaction technique. This technique provides improved wettability and adhesion between the matrix and reinforcement phases. Aluminum nitrate, copper nitrate and nickel nitrate were used as start materials for the production of the composites. The powders were sintered in a hydrogen environment at 900 °C for 2 h after being cold pressed at 700 MPa. To determine the effect of Al₂O₃ on electrical and thermal conductivities and thermal expansion behaviors, the Cu–Ni matrix was supplemented with 3, 5, and 8 wt% Al₂O₃. The findings revealed that Al₂O₃ nanoparticles (20 nm) were dispersed uniformly throughout the copper-nickel matrix. Microhardness was improved from 53.3 HV for Cu–Ni matrix to 92.7 HV for Cu–Ni/8%Al₂O₃ nanocomposites. The electrical and thermal conductivities and thermal expansion coefficient were reduced as the amount of Al₂O₃ in the Cu–Ni matrix increased. The electrical conductivity was reduced by 38.7% by addition 5% Al₂O₃ nanoparticles to Cu–Ni matrix. The high interfacial bonding between Cu–Ni and Al₂O₃ nanoparticles was the main reason of the hardness improvement and maintaining relatively good electrical and thermal properties.     

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids, carbohydrates, and lipids, as well as protein synthesis from the consumed food, the liver has many diverse responsibilities and functions that are to be performed. Liver disease may impact the hormonal and nutritional balance in the human body. The earlier diagnosis of such critical conditions may help to treat the patient effectively. A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver. The proposed approach can recognize the abnormalities with better accuracy without training, unlike in supervisory procedures requiring considerable computational efforts for training. In the earlier stages, the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation. Then, the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted–-Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information, which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts. It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%. The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.     

基于改进LFM算法的主动解列断面搜索方法

针对传统解列断面算法复杂度高的问题,提出一种基于改进LFM算法的解列断面搜索方式。首先,基于节点间电气联系和能量转移分布熵完成电网加权复杂网络建模;其次,基于主动解列断面约束条件,对LFM算法做适应性改良;最后,通过改进LFM算法得到解列断面,并在IEEE39节点系统中验证了算法有效性。仿真结果表明,改进LFM算法可充分考虑传统解列断面的约束条件,在算法具有较低复杂度的同时对系统运行状态更强的适应性。     

Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds

This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.     

Full and reduced-order H∞ filtering of Takagi–Sugeno fuzzy time-varying delay systems: Input–output approach

This article addresses the issue of delay-dependent H_∞ filtering design for TakagiŮSugeno fuzzy time-varying delay systems using the input–output approach. A three-term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper-bound inequalities have been added to the obtained conditions. Based on the scaled small gain theorem, nonquadratic Lyapunov–Krasovskii functional approach and considering the bounds of the MF time-derivative, the H_∞ full- and reduced-order filters are designed and then formulated in terms of linear matrix inequalities. Finally, illustrative examples are presented to demonstrate the validity of the proposed methods.     

Core–shell NTC materials with low thermal constant and high resistivity for wide-temperature thermistor ceramics

Core–shell structures have been proposed to improve the electrical properties of negative-temperature coefficient (NTC) thermistor ceramics. In this work, Al₂O₃-modified Co_1.5Mn_1.2Ni_0.3O₄ NTC thermistor ceramics with adjustable electrical properties were prepared through citrate-chelation followed by conventional sintering. Co_1.5Mn_1.2Ni_0.3O₄ powder was coated with a thin Al₂O₃ shell layer to form a core–shell structure. Resistivity (ρ) increased rapidly with increasing thickness of the Al₂O₃ layer, and the thermal constant (B) varied moderately between 3706 and 3846 K. In particular, Co_1.5Mn_1.2Ni_0.3O₄@Al₂O₃ ceramic with 0.08 wt% Al₂O₃ showed the increase of ρ double, and the change in its B was less than 140 K. The Co_1.5Mn_1.2Ni_0.3O₄@Al₂O₃ NTC ceramics showed high stability, and their grain size was relatively uniform due to the protection offered by the shell. The aging coefficient of the ceramic was less than 0.2% after aging for 500 hours at 125°C. Taken together, the results indicate that as-prepared Co_1.5Mn_1.2Ni_0.3O₄@Al₂O₃ NTC ceramics with a core–shell structure may be promising candidates for application as wide-temperature NTC thermistor ceramics.     

The effects of surface-modified graphene nanoplatelets on the sliding wear properties of basalt fibers-reinforced epoxy composites

Possessing unique designs and properties absent in conventional materials, nanocomposites have made a remarkable imprint in science and technology. This is particularly true regarding the polymer matrix composites when they are further reinforced with nanoparticles. In this study, the effects of different weight percentages (0, 0.1, 0.2, 0.3, 0.4, and 0.5) of surface-modified graphene nanoplatelets (GNPs) on the microhardness and wear properties of basalt fibers/epoxy composites were investigated. The GNPs were surface modified by silane, and the composites were made by the hand lay-up method. The wear tests were conducted under two different loads of 20 and 40 N. The best wear properties were achieved at 0.3 wt % GNPs as a result of the GNPs' self-lubrication property and the formation of a stable transfer/lubricating film at the pin and disk interface. Moreover, the friction coefficient was lower at the higher normal load of 40 N. The microscopic studies by FESEM and SEM showed that the presence of GNPs up to 0.3 wt % led to the stability of the transfer/lubricating film by enhancing the adhesion of the basalt fibers to the epoxy resin. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47986.     

加权信息熵与增强局部二值模式结合的人脸识别

针对人脸识别因光照、姿态、表情、遮挡及噪声等多种因素的影响而导致的识别率不高的问题，提出一种加权信息熵（IEw）与自适应阈值环形局部二值模式（ATRLBP）算子相结合的人脸识别方法（IE （w） ATR-LBP）。首先，从原始人脸图像分块提取信息熵，得到每个子块的IEw；然后，利用ATRLBP算子分别对每个人脸子块提取特征从而得到概率直方图；最后，将各个块的IEw与概率直方图相乘，再串联成为原始人脸图像最后的特征直方图，并利用支持向量机（SVM）对人脸进行识别。在AR人脸库的表情、光照、遮挡A和遮挡B四个数据集上，IE （w） ATR-LBP方法分别取得了98.37%、94.17%、98.20%和99.34%的识别率。在ORL人脸库上，IE （w） ATR-LBP方法的最大识别率为99.85%；而且在ORL人脸库5次不同训练样本的实验中，与无噪声时相比，加入高斯和椒盐噪声后的平均识别率分别下降了14.04和2.95个百分点。实验结果表明，IE （w） ATR-LBP方法能够有效提高人脸在受光照、姿态、遮挡等影响时的识别率，尤其是存在表情变化及脉冲类噪声干扰时的识别率。