An improved attribute reduction scheme with covering based rough sets

Attribute reduction is viewed as an important preprocessing step for pattern recognition and data mining. Most of researches are focused on attribute reduction by using rough sets. Recently, Tsang et al. discussed attribute reduction with covering rough sets in the paper (Tsang et al., 2008), where an approach based on discernibility matrix was presented to compute all attribute reducts. In this paper, we provide a new method for constructing simpler discernibility matrix with covering based rough sets, and improve some characterizations of attribute reduction provided by Tsang et al. It is proved that the improved discernibility matrix is equivalent to the old one, but the computational complexity of discernibility matrix is relatively reduced. Then we further study attribute reduction in decision tables based on a different strategy of identifying objects. Finally, the proposed reduction method is compared with some existing feature selection methods by numerical experiments and the experimental results show that the proposed reduction method is efficient and effective.     

Microstructure evolution during fabrication and microstructure–property relationships in vapour-grown carbon nanofibre-reinforced aluminium matrix composites fabricated via powder metallurgy

Microstructure evolution of vapour-grown carbon nanofibre (VGCF)-reinforced aluminium matrix composites during fabrication and microstructure–property relationships of these materials were studied. Composites were fabricated using powder metallurgy, i.e. by mixing VGCFs and aluminium powder via ball-milling followed by sintering or hot extrusion. The mixing condition was selected to achieve small powder particle size and homogeneously dispersed VGCFs. Aluminium grains and VGCFs were elongated along the longitudinal direction of aluminium particles in the mixed powder. Detailed observation of the aluminium grains in the composites found grain size and morphology dominated by recrystallization. Apparently, grain growth was inhibited by VGCFs. Theoretical models considering strength increment due to grain refinement resulting from VGCF addition, load bearing of VGCFs, thermal mismatch of VGCFs and aluminium and Orowan effect were developed. Theoretical values coincided well with hardness, yield strength, and ultimate tensile strength of the composites, and thus the models could precisely explain the microstructure–property relationships.     

Structural performance of ballastless track slabs reinforced with BFRP and SFCB

Because of the inductive impedance caused by steel meshes in traditional reinforced ballastless track slabs, the electrical properties, primarily the rail resistance and inductance, of jointless track circuits are affected by electromagnetic induction between the slabs and the electric current in the rail. This problem results in poor transmission performance throughout the track circuit. Insulating sleeves or cards between the steel meshes have been used to improve the insulation capability of steel meshes in slabs; however, they reduce the bonding performance between the steel bars and concrete. Because of the good insulation properties of fiber-reinforced polymer composite bars (FRPs) and steel-fiber reinforced polymer composite bars (SFCBs), these composite materials have shown potential to overcome this insulation problem. However, the structural performance of the ballastless track slabs reinforced by basalt fiber reinforced polymer composite bars (BFRPs) and SFCBs, which play a key role in the structure and transportation safety, needs to be investigated. In this paper, six ballastless track slabs reinforced with BFRPs, SFCBs, and steel bars were constructed and tested. The following results were obtained. (1) Shear failures were observed for all slabs, both the BFRP and SFCB slabs meet the load level requirements, and SFCBs reinforcements have higher strength utilization compared with BFRPs reinforcements. (2) The bond-quality of SFCBs and BFRPs reinforcements proved slightly poorer than that of the steel bars. Because of the good corrosion resistance of the FRP, the maximum crack width limits can be slightly larger than that of the RC slabs. (3) Bischoff’s equation was initially used to calculate the deflection of partially prestressed concrete slabs under service loads. The results demonstrated a good agreement between the theoretical and experimental analysis. (4) Considering the tensile stiffness, the modified ACI equation was used to calculate the slabs’ crack width and the theoretical and experimental results showed a good agreement.     

The improvement of electro‐optical properties of polymer‐dispersed liquid crystals with graft copolymer matrix synthesized by reversible addition–fragmentation chain transfer and atom transfer radical polymerization

Aiming to decrease the memory effect of polymer‐dispersed liquid crystals (PDLCs), a type of graft macroinitiator, synthesized by reversible addition–fragmentation chain transfer and atom transfer radical polymerization, was employed to prepare PDLCs with graft copolymer matrix in our previous work. Compared with linear copolymer matrix PDLCs prepared using a linear macroinitiator, it was found that, although low‐memory‐effect PDLCs were obtained, the driving voltage and transmittance of the PDLCs were unfortunately sacrificed to some extent. Thus, it is necessary to improve the electro‐optical properties of PDLCs on the basis of the original research performed by us. In the work reported in this article, a kind of linear macroinitiator with high refractive index and another graft macroinitiator with flexible branched chains were employed to prepare PDLCs. The results showed that by using mixed macroinitiators, the electro‐optical properties of PDLCs could be improved, and a possible mechanism is proposed.     

Synthesis of hexacelsian barium aluminosilicate by film boiling chemical vapour process

An original oxide/oxide ceramic-matrix composite containing mullite-based fibers and a barium aluminosilicate matrix has been synthesized by the film boiling chemical vapour infiltration process. Alkoxides were used as liquid precursors for aluminum, silicon and barium oxides. The structure and microstructure of the oxide matrix were characterized by Scanning Electron Microscopy, Energy Dispersive Spectroscopy and X-ray diffraction. Apart from small residual mullite and amorphous phase amounts, the oxide matrix is composed of the hexacelsian phase, conferring to the material interesting perspectives for high-temperature electromagnetic and structural applications.     

A robust adaptive weighted constant modulus algorithm for blind equalization of wireless communications systems under impulsive noise environment

A robust adaptive weighted constant modulus algorithm is proposed for blind equalization of wireless communication systems under impulsive noise environment. The influence of the impulsive noise is analyzed based on numerical analysis method. Then an adaptive weighted constant modulus algorithm is constructed to adaptively suppress impulsive noise. Theoretical analysis is provided to illustrate that the proposed algorithm has a robust equalization performance since the impulsive noise is adaptively suppressed. Moreover, the proposed algorithm has stable and quick convergence due to avoidance of large misadjuntment and adoption of large step size. Simulation results are presented to show the robust equalization performance and the fast convergence speed of the proposed algorithm under both impulsive noise and Gaussian noise environments.     

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from ?0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.     

Translational aspects of the modern genetics in head and neck cancers

Oral Cancer (OC) is one of the most recurrent cancers in the head and neck squamous cancer (SCCHN) category. Recently, the genome-wide association studies (GWAS) have gained growing interest in the scientific community. GWAS have identified several pathways involved in the interactions among general risk factors and genomic variants affecting SCCHN. This systematic overview aims to critically evaluate the latest data reported within the scientific literature. The aim was to investigate the impact of genetic aspects on SCCHN onset and prognosis, involving other clinical and systemic co-factors. PubMed, Google Scholar, and Cancer Genetics Web databases have been systematically investigated for original articles published in the last two years, reporting studies on the main queries addressed in this work. This review also comparatively describes the impact of environmental and pathological co-factors in different types of cancers, clarifying and updating the role of genetic factors in SCCHN onset and development. The main outcomes reported may be helpful to drive clinicians towards their clinical evaluations for the most appropriate therapeutic approach in SCCHN.     

MDA-TOEPGA: A novel method to identify miRNA-disease association based on two-objective evolutionary programming genetic algorithm

The association between miRNA and disease has attracted more and more attention. Until now, existing methods for identifying miRNA related disease mainly rely on top-ranked association model, which may not provide a full landscape of association between miRNA and disease. Hence there is strong need of new computational method to identify the associations from miRNA group view. In this paper, we proposed a framework, MDA-TOEPGA, to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm, which identifies latent miRNAdisease associations from the view of functional module. To understand the miRNA functional module in diseases, the case study is presented. We have been compared MDA-TOEPGA with several state-of-the-art functional module algorithm. Experimental results showed that our method cannot only outperform classical algorithms, such as K-means, IK-means, MCODE, HC-PIN, and ClusterONE, but can also achieve an ideal overall performance in terms of a composite score consisting of f1, Sensitivity, and Accuracy. Altogether, our study showed that MDA-TOEPGA is a promising method to investigate miRNA-disease association from the landscapes of functional module.     

Strengthening Mechanism and Microstructure of Deformable Ti Particles Reinforced AZ91 Composite

In this study, the deformable titanium (Ti) particles reinforced AZ91 composite was successfully prepared by powder metallurgy and subsequent extrusion. The mechanical properties and microstructural evolution of pure AZ91 and 5Ti/AZ91 composite were studied. The yield strength, ultimate tensile strength, and elongation of 5Ti/AZ91 composite are measured to be 212 MPa, 323 MPa, and 10.1%, respectively. Microstructure analysis revealed that Ti particles are elongated along the extrusion direction, forming a discontinuous strip Ti particles, fine precipitated Mg₁₇Al₁₂ phase inhibits dynamic recrystallization (DRX) behavior through Zener pinning effect and hinders the growth of matrix grains, resulting in refiner grains of 5Ti/AZ91 composite. Heterogeneous deformed Ti particles and magnesium (Mg) matrix to generate additional heterogeneous deformation-induced (HDI) strengthening. Heterogeneous deformation-induced strengthening mainly contributed to the increment of yield strength for 5Ti/AZ91 composite.