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Recently proposed L2-norm linear discriminant analysis criterion via the Bhattacharyya error bound estimation (L2BLDA) is an effective improvement of linear discriminant analysis (LDA) for feature extraction. However, L2BLDA is only proposed to cope with vector input samples. When facing with two-dimensional (2D) inputs, such as images, it will lose some useful information, since it does not consider intrinsic structure of images. In this paper, we extend L2BLDA to a two-dimensional Bhattacharyya bound linear discriminant analysis (2DBLDA). 2DBLDA maximizes the matrix-based between-class distance which is measured by the weighted pairwise distances of class means and meanwhile minimizes the matrix-based within-class distance. The weighting constant between the between-class and within-class terms is determined by the involved data that makes the proposed 2DBLDA adaptive. In addition, the criterion of 2DBLDA is equivalent to optimizing an upper bound of the Bhattacharyya error. The construction of 2DBLDA makes it avoid the small sample size problem while also possess robustness, and can be solved through a simple standard eigenvalue decomposition problem. The experimental results on image recognition and face image reconstruction demonstrate the effectiveness of the proposed methods.

To explore the differential expression of messenger RNA (mRNA) in myocardial tissues of rats with sudden coronary death (SCD), and to provide ideas for the forensic identification of SCD.The rat SCD model was established, and the transcriptome sequencing was performed by next-generation sequencing technology. Differentially expressed genes (DEGs) in myocardial tissues of SCD rats were screened by using the R package limma. A protein-protein interaction (PPI) network was constructed by using the STRING database and Cytoscape 3.8.2 on DEG, and hub genes were screened based on cytoHubba plug-in. Finally, the R package clusterProfiler was used to analyze the biological function and signal pathway enrichment of the selected DEG.A total of 177 DEGs were associated with SCD and were mainly involved in the renin-angiotensin system and PI3K-Akt signaling pathway. The genes including angiotensinogen (AGT), complement component 4a (C4a), Fos proto-oncogene (FOS) and others played key roles in the development of SCD.Genes such as

To explore the mRNA differential expressions and the sequential change pattern in acute myocardial infarction (AMI) mice.The AMI mice relevant dataset GSE4648 was downloaded from Gene Expression Omnibus (GEO). In the dataset, 6 left ventricular myocardial tissue samples were selected at 0.25, 1, 4, 12, 24 and 48 h after operation in AMI group and sham control group, and 6 left ventricular myocardial tissue samples were selected in blank control group, a total of 78 samples were analyzed. Differentially expressed genes (DEGs) were analyzed by R/Bioconductor package limma, functional pathway enrichment analysis was performed by clusterProfiler, protein-protein interaction (PPI) network was constructed by STRING database and Cytoscape software, the key genes were identified by Degree topological algorithm, cluster sequential changes on DEGs were analyzed by Mfuzz.A total of 1 320 DEGs were associated with the development of AMI. Functional enrichment results included cellular catabolic process, regulation of inflammatory response, development of muscle system and vasculature system, cell adhesion and signaling pathways mainly enriched in mitogen-activated protein kinase (MAPK) signaling pathway. The key genes of AMI includedThe functional signaling pathway of DEGs and the sequential expression of key genes in AMI may provide a reference for the forensic identification of AMI.

In general, data contain noises which come from faulty instruments, flawed measurements or faulty communication. Learning with data in the context of classification or regression is inevitably affected by noises in the data. In order to remove or greatly reduce the impact of noises, we introduce the ideas of fuzzy membership functions and the Laplacian twin support vector machine (Lap-TSVM). A formulation of the linear intuitionistic fuzzy Laplacian twin support vector machine (IFLap-TSVM) is presented. Moreover, we extend the linear IFLap-TSVM to the nonlinear case by kernel function. The proposed IFLap-TSVM resolves the negative impact of noises and outliers by using fuzzy membership functions and is a more accurate reasonable classifier by using the geometric distribution information of labeled data and unlabeled data based on manifold regularization. Experiments with constructed artificial datasets, several UCI benchmark datasets and MNIST dataset show that the IFLap-TSVM has better classification accuracy than other state-of-the-art twin support vector machine (TSVM), intuitionistic fuzzy twin support vector machine (IFTSVM) and Lap-TSVM.

We describe a tert-butyl nitrite-catalyzed oxidative dehydrogenation of hydrazobenzenes for producing azobenzenes. This method proceeds at ambient temperature and under an atmospheric environment by employing eco-friendly EtOH as the medium, representing a mild, general route to the synthesis of various symmetrical and nonsymmetrical azobenzenes in excellent yields with broad functional group tolerance.

Supplemental Digital Content is available in the text., Objective: METTL3 (methyltransferase-like protein 3)-mediated N6-methyladenosine modification is the most abundant RNA modification on eukaryote mRNAs and plays a crucial role in diverse physiological and pathological processes. However, whether N6-methyladenosine modification has function in thrombosis is unknown. This study aims to determine the role of METTL3 in the endothelial cells-mediated thrombosis. Approach and Results: RNA-sequencing and real-time quantitative PCR revealed that the expression of PAI-1 (plasminogen activator inhibitor-1) was downregulated in METTL3 knockdown human umbilical vein endothelial cells. In vitro experiments showed that METTL3 suppressed fibrinolysis. Mechanically, RNA methylation sequencing and meRIP-quantitative real-time PCR showed that METTL3 catalyzed N6-methyladenosine modification on 3′ UTR of JUN mRNA. Western blotting analysis showed that METTL3 promoted JUN protein expression. Chromatin immunoprecipitation analysis demonstrated that JUN bound to the PAI-1 promoter in human umbilical vein endothelial cells. Furthermore, mice challenged with lipopolysaccharide resulted in higher METTL3 expression in vessels. Endothelial-specific knockdown of Mettl3 decreased expression of active PAI-1 in plasma and attenuated fibrin deposition in livers and lungs during endotoxemia. Conclusions: Our study reveals that METTL3-mediated N6-methyladenosine modification plays a crucial role in fibrinolysis and is an underlying target for the therapy of thrombotic disorders.

The effects of grain size on the tellurium corrosion behaviors have been investigated systematically in GH3535 alloy. After the exposure to Te vapor, the triple-layer scales, which consist of Ni3Te2, Cr3Te4, MnTe, M6C carbides and Fe-riched γ phase, occur in both the fine-grained and coarse-grained specimens. The thicker outer layer, the more discrete inner layer, the shallower Te permeation and Cr3Te4 existence along grain boundaries can be observed in the fine-grained specimens. By comparing the Gibbs free energies and calculating the effective diffusion coefficients, the tellurization mechanism and the role of grain size were discussed.

Hydrogen sulfide (H2S) is an endogenous gaseous signaling molecule that plays important roles in the cardiovascular system. In our previous studies, we demonstrated that H2S regulates lipid metabolism. In the present study, we aimed to explore the mechanisms through which H2S regulates lipid metabolism in HepG2 cells in vitro. Treatment of the HepG2 cells with H2S inhibited the expression of proprotein convertase subtilisin/kexin type 9 (PCSK9) and increased the level of low‑density lipoprotein receptor (LDLR) in a time‑ and dose‑dependent manner. The knockdown of PCSK9 by siRNA effectively increased the levels of LDLR and 1,1'‑dioctadecyl‑3,3,3',3'‑tetramethyl‑indocarbocyanine perchlorate‑labeled LDL (DiI‑LDL) uptake in the H2S‑treated HepG2 cells. Furthermore, the phosphoinositide 3‑kinase (PI3K)/protein kinase B (Akt)‑sterol regulatory element binding proteins 2 (SREBP‑2) signaling pathway was confirmed to be involved in H2S‑regulated PCSK9 expression. Notably, the HepG2 cells were incubated with 30% serum and DiI‑LDL for 24 h, and the results revealed that H2S increased lipid uptake, but caused no increase in lipid accumulation. On the whole, the findings of this study demonstrate that H2S is involved in the regulation of lipid metabolism in HepG2 cells through the regulation of the expression of PCSK9 via the PI3K/Akt‑SREBP‑2 signaling pathway. To the very best of our knowledge, this study is the first to report that H2S can regulate the expression of PCSK9.

The molecular mechanisms underlying the variation in N-use efficiency (NUE) in pepper (Capsicum annuum L.) genotypes are poorly understood. In this work, two genotypes (750-1, low-N tolerant, ZCFB, low-N sensitive) with contrasting low-N tolerance were selected from 100 pepper cultivars on the basis of their relative leaf areas, shoot dry weights, root dry weights, and plant dry weights at the seedling stage. Subsequently, using RNA-Seq, the transcriptome of these two pepper genotypes under N starvation for 28 days was analyzed. We detected 2621/2470 and 3936/4218 different expressed genes (DEGs) in the leaves/roots of 750-1 and ZCFB, respectively. The changes in the expression of basic N metabolism genes were similar between 750-1 and ZCFB. However, different DEGs not directly involved in N metabolism were identified between the 750-1 and ZCFB cultivars. In 750-1, 110 unique DEGs were detected in the leaves, of which 103 were down-regulated, including genes associated with protein metabolism, photosynthesis, secondary metabolism, cell wall metabolism, stress response, and disease resistance. In ZCFB, 142 unique DEGs were detected in the roots, of which 117 were up-regulated, resulting in enhancement of processes such as protein degradation, secondary metabolites synthesis, lipid metabolism, endocytosis, the tricarboxylic acid cycle (TCA), transcriptional regulation, stress response, and disease resistance. Our results not only facilitate an understanding of the different regulatory process in low-N-tolerant and low-N-sensitive pepper cultivars, but also provide abundant candidate genes for improving the low-N tolerance of pepper cultivars.

The interaction between microglia and astrocytes significantly influences neuroinflammation. Microglia/astrocytes, part of the neurovascular unit (NVU), are activated by various brain insults. The local extracellular and intracellular signals determine their characteristics and switch of phenotypes. Microglia and astrocytes are activated into two polarization states: the pro-inflammatory phenotype (M1 and A1) and the anti-inflammatory phenotype (M2 and A2). During neuroinflammation, induced by stroke or lipopolysaccharides, microglia are more sensitive to pathogens, or damage; they are thus initially activated into the M1 phenotype and produce common inflammatory signals such as IL-1 and TNF-α to trigger reactive astrocytes into the A1 phenotype. These inflammatory signals can be amplified not only by the self-feedback loop of microglial activation but also by the unique anatomy structure of astrocytes. As the pathology further progresses, resulting in local environmental changes, M1-like microglia switch to the M2 phenotype, and M2 crosstalk with A2. While astrocytes communicate simultaneously with neurons and blood vessels to maintain the function of neurons and the blood-brain barrier (BBB), their subtle changes may be identified and responded by astrocytes, and possibly transferred to microglia. Although both microglia and astrocytes have different functional characteristics, they can achieve immune "optimization" through their mutual communication and cooperation in the NVU and build a cascaded immune network of amplification.

This paper studies the tensor maximal correlation problem, which aims at optimizing correlations between sets of variables in many statistical applications. We reformulate the problem as an equivalent polynomial optimization problem, by adding the first order optimality condition to the constraints, then construct a hierarchy of semidefinite relaxations for solving it. The global maximizers of the problem can be detected by solving a finite number of such semidefinite relaxations. Numerical experiments show the efficiency of the proposed method.

The intergranular cracking and the grain boundary network along the cracks in an austenitic stainless steel 316L after stress corrosion cracking (SCC) test in simulated BWR water were investigated in terms of three-dimensional characterization. It was found that the twin boundaries not only show a strong resistance to cracking, but they could also prevent their neighboring boundaries from cracking, as the cracking probability is lower for boundaries that have higher fraction of neighboring twin boundaries. The propagation of intergranular SCC can be hindered by triple junctions or quadruple junctions in the presence of twin boundaries.

Grain boundary engineering was applied to a 316L stainless steel. The proportion of low-Σ coincidence site lattice boundaries was increased to more than 70% in the GBE specimen. The effect of grain boundary character distribution formed through GBE on the mechanical properties at different strain rates (4 × 10−2, 4 × 10−3, 4 × 10−4, 4 × 10−5 s−1) was studied by tensile test at room temperature. The results showed that the GBE specimens exhibited higher uniform elongation than the non-GBE specimens. With the strain rate decreasing, the uniform elongations of GBE specimens had a greater extent of increase. The local misorientation, average Schmid factor ( $$ \overline{m} $$ ) and Taylor factor (M) in GBE and non-GBE specimens at uniform plastic deformation area were studied by using electron backscatter diffraction. The results indicate that the micro-zone strain was more uniformly distributed and the activation process of the slip system was apt to happen in the GBE specimens.

Grain boundary engineering (GBE) of nickel-based alloy 825 tubes was carried out with different cold drawing deformations by using a draw-bench on a factory production line and subsequent annealing at various temperatures. The microstructure evolution of alloy 825 during thermal-mechanical processing (TMP) was characterized by means of the electron backscatter diffraction (EBSD) technique to study the TMP effects on the grain boundary network and the evolution of grain boundary character distributions during high temperature annealing. The results showed that the proportion of ∑ 3 n coincidence site lattice (CSL) boundaries of alloy 825 tubes could be increased to > 75% by the TMP of 5% cold drawing and subsequent annealing at 1050 °C for 10 min. The microstructures of the partially recrystallized samples and the fully recrystallized samples suggested that the proportion of low ∑ CSL grain boundaries depended on the annealing time. The frequency of low ∑ CSL grain boundaries increases rapidly with increasing annealing time associating with the formation of large-size highly-twinned grains-cluster microstructure during recrystallization. However, upon further increasing annealing time, the frequency of low ∑ CSL grain boundaries decreased markedly during grain growth. So it is concluded that grain boundary engineering is achieved through recrystallization rather than grain growth.

In this paper we consider the steady two dimensional flow of micro polar fluids on a flat plate. The flow under discussion is the modified Hiemenz flow for a micro polar fluid which occurs in the hjkns + skms boundary layer near an orthogonal stagnation point. The full governing equation reduced to a modified Hiemenz flow. The solution to the boundary value problem is governed by two non dimensional parameters, the material parameter K and the ratio of the micro rotation to skin friction parameter n. The obtained nonlinear coupled ordinary differential equations are solved by using the Homotopy perturbation method. Comparison between numerical and analytical solutions of the problem is shown in tables form for different values of the governing parameters K and n. Effects of the material parameter K on the velocity profile and microrotation profiles for different cases of n are discussed graphically as well as numerically. Velocity profile decreases as the material parameter K increases and the microrotation profile increases as the material parameter K increases for different cases of n.

Large grain-cluster or so-called twin-related domain is a typical characteristic of the grain boundary (GB) engineered microstructure. Grain-cluster is formed via numerous twinning operations starting from single nucleus, and the process is referred to as multiple-twinning. This work investigated the orientation diversity within grain-clusters and the twinning ordering of multiple-twinning based on the statistics of grain-orientations in 30 large-sized grain-clusters from GB-engineered Ni-based alloy 690. The statistics show that the grain-cluster apparently has several dominant orientations. A few dominant orientations occupy most area and most grains in a grain-cluster. Moreover most misorientations between these dominant orientations are of low-order ∑3n-type (n = 1, 2), and the 4 sub-dominant orientations are twinning variants of the first-dominant orientation in most cases. These statistical characteristics of grain-clusters reflect the general behavior of multiple-twinning: back-and-forth pattern and preferential orientations. The twinning operations produce not only higher (forward) but also lower (backward) generation orientations, and the backward probability is higher than the forward. The multiple-twinning shows a propensity to form or access to a few preferential orientations, and results in the formation of dominant orientations of the formed grain-cluster. Keywords: EBSD, Grain boundary engineering, Multiple-twinning, Grain-cluster, Grain orientation

Background The large family of pentatricopeptide repeat (PPR) proteins is widely distributed among land plants. Such proteins play vital roles in intron splicing, RNA editing, RNA processing, RNA stability and RNA translation. However, only a small number of PPR genes have been identified in rice. Results In this study, we raised a mutant from tissue-culture-derived plants of Oryza sativa subsp. japonica ‘Zhonghua 11’, which exhibited a lethal chlorosis phenotype from germination to the third-leaf stage. The mutant was designated seedling-lethal chlorosis 1 (slc1). The slc1 mutant leaves showed extremely low contents of photosynthetic pigments and abnormal chloroplast development, and were severely defective in photosynthesis. Map-based cloning of OsSLC1 revealed that a single base (G) deletion was detected in the first exon of Os06g0710800 in the slc1 mutant, which caused a premature stop codon. Knockout and complementation experiments further confirmed that OsSLC1 is responsible for the seedling-lethal chlorosis phenotype in the slc1 mutant. OsSLC1 was preferentially expressed in green leaves, and encoded a chloroplast-localized PPR protein harboring 12 PPR motifs. Loss-of-function of OsSLC1 affected the intron splicing of multiple group II introns, and especially precluded the intron splicing of rps16, and resulted in significant increase in the transcript levels of 3 chloroplast ribosomal RNAs and 16 chloroplast development-related and photosynthesis-related genes, and in significant reduction in the transcript levels of 1 chloroplast ribosomal RNAs and 2 chloroplast development-related and photosynthesis-related genes. Conclusion We characterized a novel chloroplast-localized PPR protein, OsSLC1, which plays a vital role in the intron splicing of multiple group II introns, especially the rps16 intron, and is essential for early chloroplast development and seedling survival in rice.

For understanding the improvement of intergranular stress corrosion cracking (IGSCC) propagation in grain boundary engineering (GBE)-processed metals exposed to a simulated pressurized water reactor (PWR) environment, characteristics of the grain boundary network of 316L stainless steel before and after GBE were investigated and compared, including proportions both in length and in number of ∑3n boundaries, sizes, and topology of grain clusters (or twin-related domains), and connectivity of random boundaries. The term through-view random boundary path (TRBP) was proposed to evaluate the random boundary connectivity. A TRBP is a chain of end-to-end connected crack-susceptible boundaries that passes through the entire mapped microstructure. The work provides the following key findings: (I) the length fraction of ∑3n boundaries was increased to approximately 75% after GBE, but the number fraction was only approximately 50%; (II) a connected non-twin boundary network still existed in the GBE sample due to the formation of grain clusters; (III) the GBE sample exhibited a higher resistance to IGSCC; and (IV) as the twin boundary fraction increased, the number of TRBPs decreased and the normalized length of the minimum TRBP increased monotonically, leading to a higher resistance to IGSCC.

Recently, an effective improvement of linear discriminant analysis (LDA) called L2-norm linear discriminant analysis via the Bhattacharyya error bound estimation (L2BLDA) was proposed in its adaptability and nonsingularity. However, L2BLDA assumes all samples from the same class are independently identically distributed (i.i.d.). In real world, this assumption sometimes fails. To solve this problem, in this paper, reverse nearest neighbor (RNN) technique is imbedded into L2BLDA and a novel linear discriminant analysis named RNNL2BLDA is proposed. Rather than using classes to construct within-class and between-class scatters, RNNL2BLDA divides each class into subclasses by using RNN technique, and then defines the scatter matrices on these classes that may contain several subclasses. This makes RNNL2BLDA get rid of the i.i.d.assumption in L2BLDA and applicable to multimodal data, which have mixture of Gaussian distributions. In addition, by setting a threshold in RNN, RNNL2BLDA achieves robustness. RNNL2BLDA can be solved through a simple standard generalized eigenvalue problem. Experimental results on an artificial data set, some benchmark data sets as well as two human face databases demonstrate the effectiveness of the proposed method.

This paper proposed a power allocation mechanism and mode switching strategy for the series-parallel hybrid electric vehicles. A test-data based simulation platform for series-parallel plug-in hybrid electric vehicles is established and developed for theoretical verification. The results indicate that the proposed control strategy realized a more reasonable power distribution in the combined power system under various working modes, which means a remarkable improvement in vehicle fuel economy.

Two axles four wheel drive electric vehicle is an important development tendency of electric vehicle. However, how to coordinate the torque distribution between front and rear axles thus ensuring vehicle stability while maximizing motor’s efficiency still confronts great challenges. In this paper, we propose a three-layer hierarchical control method, which not only incorporates prior engineering knowledge into the control policy so as to relieve computational burden for real-time usage, but also properly deals with the priority between safety and system efficiency. Simulations are conducted to verify the effectiveness of the proposed method. Results show that the derived control policy can ensure high system efficiency when safety is guarenteed. Simultaneously, it can actively decrease the motor torque to improve vehicle stability when wheel slip occurs.

The effects of surface chemical treatment (ST), which is a combination of acid and alkaline cleaning to remove surface impurities, on the corrosion behavior of an Al-B4C metal matrix composite (MMC) in boric acid solutions at 40 ℃ and 90 ℃ were investigated. SEM and TEM analysis revealed duplex-layer surface scales, consisting an outer layer of blade-like strips and a continuous amorphous inner layer. The outer layers have similar thicknesses, while the impurity-containing samples (without ST) have thicker inner layers, in which the interfaces between the impurities and surrounding oxide scale were acted as fast inward diffusion channels of oxygen.

Background The aim of the present study was to investigate the synergistic effects and interactive mechanisms of Shufeng Jiedu Capsule (SFJDC) combined with oseltamivir in the treatment of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) induced by the influenza A virus (IAV). Methods The extraction of SFJDC was analyzed by UHPLC/ESI Q-Orbitrap Mass Spectrometry. Human bronchial epithelial cells were isolated from COPD (DHBE) bronchial tissues, co-cultured with IAV for 24 h, and were subsequently treated with SFJDC and/or oseltamivir. Cell viability was detected by MTT assay. A rat model of COPD with IAV infection was established and treated with SFJDC and/or oseltamivir. Interleukin (IL)-1β and IL-18 in serum and bronchoalveolar lavage fluid (BALF) were measured by ELISA. Additionally, mRNA and protein levels of NLRP3 inflammasome pathway were measured by quantitative real-time PCR and Western blotting, respectively. Results SFJDC and/or oseltamivir, at their optimal concentrations, had no significant cytotoxicity against DHBEs. The levels of NLRP3-inflammasome-associated components were significantly elevated after cells were inoculated with IAV, whereas the mRNA and protein levels of these components were significantly decreased after treatment with SFJDC and/or oseltamivir in vitro. Moreover, in vivo, the combination of SFJDC and oseltamivir improved survival rates, attenuated clinical symptoms, induced weight gain, alleviated lung damage, and significantly reduced IL-1β and IL-18 levels in serum and BALF, as well as reduced the expression levels of NLRP3-associated components and viral titers in lung homogenates. Conclusion SFJDC combined with oseltamivir treatment significantly attenuated IAV-induced airway inflammation and lung viral titers. Hence, our findings may provide a novel therapeutic strategy for IAV-induced respiratory infection.

Subspace segmentation is a fundamental issue in computer vision and machine learning, which segments a collection of high-dimensional data points into their respective low-dimensional subspaces. In this paper, we first propose a model for segmenting the data points from incomplete and noisy observations. Then, we develop an inexact splitting method for solving the resulted model. Moreover, we prove the global convergence of the proposed method. Finally, the inexact splitting method is implemented on the clustering problems in synthetic and benchmark data, respectively. Numerical results demonstrate that the proposed method is computationally efficient, robust as well as more accurate compared with the state-of-the-art algorithms.