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To ensure the high reliability of the pipeline system, it is necessary to take group maintenance actions. This work proposes an optimal group maintenance approach based on a heuristically genetic algorithm to attain the system-performing goal while minimizing overall costs with assured system reliability. Multi-stage corrosion defects and multi-level risk areas are considered in this novel approach. The proposed method can sufficiently avoid pipeline failures by considering the multi-level probability of failure constraints. The methodology is illustrated by taking the 60-segment pipelines with multiple corrosion defects as an example. Numerical studies show that the proposed methodology can find an optimized maintenance strategy with a lower cost compared with the unified batch maintenance strategy. In addition, an optimal dynamic maintenance model is proposed and compared with the static model when the environment of the pipelines varies. Sensitivity analyses of the physical parameters of the phenomenon and the tuning parameters of the data-driven model show that the method has good effectiveness, compatibility, and universality. [ABSTRACT FROM AUTHOR]

In recent years, attention mechanisms have gained popularity in sequential recommender systems (SRSs) due to obtaining dynamic user preferences efficiently. However, over-parameterization of these models often increases the risk of overfitting. To address this challenge, we propose a Transformer model based on tensor train networks. Initially, we propose a tensor train layer (TTL) to accommodate the original weight matrix, thus reducing the space complexity of the mapping layer. Based on the TTL, we reconfigure the multi-head attention module and the position-wise feed-forward network. Finally, a tensor train layer replaces the output layer to complete the overall compression. According to the experimental results, the proposed model compresses SRSs parameters effectively, achieving compression rates of 76. 2 % − 85. 0 % , while maintaining or enhancing sequence recommendation performance. To our knowledge, the Tensor Train Transformer is the first model compression approach for Transformer-based SRSs, and the model is broadly applicable. • A novel model as a remedy for parameter redundancy in SRSs is proposed. • A tensor train layer has lower space complexity than the original linear layer. • The proposed model compresses SRSs parameters effectively. • Tensor Train Transformer model is broadly applicable. [ABSTRACT FROM AUTHOR]

Reasonable maintenance of pipeline systems is essential for ensuring energy transportation and achieving a trade-off between safe operation and maintenance costs. However, previous studies have barely considered the system structure, system availability, and multi-stage corrosion. To fill this gap, a multi-objective optimization framework was established. This framework can balance the cost and downtime caused by maintenance to achieve the desired trade-off between the maintenance cost and transportation continuity of a system with multi-stage corrosion defects and multi-level reliability constraints. By combining the NSGA-II algorithm with the general structure of pipeline systems, chromosome coding was designed to improve the efficiency of the evolutionary algorithm, and a series of preventive maintenance strategies were proposed, including decisions regarding repaired segments, time point for maintenance, and the type of maintenance mode. The effectiveness and accuracy of the methodology were illustrated by considering the pipeline systems with different structures and parameters as examples. A comparison of multi-objective programming with empirical decision and single-objective decisions demonstrates the rationality and universality of the methodology. The proposed methodology can help adjust the corresponding maintenance strategies for diverse requirements and provide reasonable maintenance schemes for corroded pipeline systems. • Multiple states and diversified maintenance modes are considered. • Cost and availability are optimized under multi-level PoF constraints. • NSGA-II is improved to complete multi-objective management framework. • The methodology can be applied to the general structure of pipeline systems. • The methodology is demonstrated by comparing with single-objective optimization. [ABSTRACT FROM AUTHOR]

Abstract The recommendation algorithm is attracting increasing attention in analyzing big data. Matrix factorization (MF) is one of the recommendation methods and Singular Value Decomposition (SVD) is the most popular matrix factorization method. However, the existing SVD methods usually initialize user and item feature randomly, not fully utilize the information of the data, so require plenty of experiments to determine feature matrix dimension, with low convergence efficiency and low accuracy. This paper presents a hybrid initialization method based on attribute mapping and autoencoder neural network to solve these problems, which consists of three parts: (1) use the number of item attribute types to determine feature matrix dimension in order to avoid multiple experiments to select the optimal dimension value; (2) use items' attributes to initialize the item feature matrix in SVD＋＋, and use an attribute mapping mechanism to get an item feature vector by fitting the rating matrix to accelerate the convergence; (3) adopt the autoencoder neural network to reduce feature dimension and obtain item latent features for initializing SVD＋＋. The experimental results show that our methods achieve better performance than SVD＋＋ random initialization and also be adopted to other matrix factorization methods. [ABSTRACT FROM AUTHOR]

This paper considers the problem of extended dissipativity analysis and synthesis for network control systems under an event-triggered scheme, where the extended dissipativity analysis unifies the H ∞ , passivity, dissipativity, and L 2 − L ∞ performance in one framework. Firstly, the proposed system is modeled as a network control system with an suitable event-triggered scheme. Then, by using the improved integral inequality and reciprocally convex inequality technique, sufficient condition to guarantee the extended dissipativity of the network control systems is given in terms of linear matrix inequalities ( LMIs ). Furthermore, the design of the state feedback controller is also proposed. Finally, numerical examples are given to illustrate the efficiency of the addressed method. [ABSTRACT FROM AUTHOR]

To provide preferable operating conditions for biomass carbonization, the carbonization properties of maize straw, cotton stalk and poplar wood were investigated in nitrogen atmosphere by segmented heating process at different final temperatures of 300–800 °C for 1 h. Segmented heating carbonization contributes to higher ratio of mass and energy yields than a constant temperature/linear heating process with final temperature of around 300 °C. The fuel properties and characteristics of raw and carbonized biomass were analysed systematically. Increasing carbonization temperature, the fuel ratios of the obtained chars rise exponentially, and the profile of atomic H/C ratio versus atomic O/C ratio approximately decreases linearly. There are small changes of sulphur and nitrogen content in the chars. To provide an estimation method for higher heating value for torrefied/carbonized biomass, a new correlation is proposed based on ultimate analysis. The correlation is H H V = 19.9579 + 0.1284 C + 0.3355 H − 0.1209 O − 1.3836 N − 5.4680 S , which is validated through experimental data. The correlation has a low level of errors, that the correlation efficient, mean absolute error, average absolute error and average bias error are 0.971, − 6.75 × 10 − 6 MJ, 1.2% and 0.02% respectively. This work will make a contribution to the biomass pretreatment process. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the problem of context-aware recommendation using tensor factorization. Traditional tensor-based models in context-aware recommendation scenario only consider user-item-context interactions. In this paper, we argue that rating can't be totally explained by the interactions and the rating also influenced by the combined impact of overall mean, user bias, item bias and context bias. Based on this hypothesis, we propose a novel context-aware recommendation model named Bias Tensor Factorization, which take all this factors into account. Additionally, traditional context-aware recommenders with tensor factorization still have three main drawbacks: (1) the model complexity of those models increase exponentially with the number of context features, (2) those models can only handle context features with categorical values and (3) the models fail to select effective features from available context features. To address those problems, we propose a context features auto-encoding algorithm based on regression tree which can both handle numerical features and select effective features. Then we integrate this algorithm with Bias Tensor Factorization. Experiments on a real world contextual dataset and Movielens show that our proposed algorithms outperform the state-of-art context-aware recommendation algorithms, namely tensor factorization and factorization machine. [ABSTRACT FROM AUTHOR]

• A property in the iterative process of FPC is discovered. • A novel initialization method of FPC is proposed. • A strategy to improve the efficiency of FPC is given. • The method makes the recommendation algorithm have a high convergence speed. In recent years, the problem of matrix completion based on rank minimization has received widespread attention in machine learning. The tightest convex relaxation of this problem is the linearly constrained nuclear norm minimization. Fixed point continuation (FPC), as a representative nuclear norm relaxation matrix completion algorithm, has been proven to perform well in theories and experiments. However, the traditional FPC algorithm initializes the matrix to be completed by zero, which does not make full use of the shrinkage characteristics of the singular value shrinkage operator on the matrix elements and the known field data information, then will lead to slow convergence and poor accuracy. Aiming at this problem, this paper analyzes the shrinkage properties of matrix elements in the iterative process of the FPC algorithm. Combined with the known rating information in the recommendation systems, a new initialization method of overestimation based on FPC is proposed, and it is applied to the rating prediction in the recommendation systems. The experimental results show that the initialization method proposed in this paper greatly improves the algorithm efficiency and prediction accuracy. [ABSTRACT FROM AUTHOR]

• A fast weighted CP decomposition model for context-aware recommendation. • Unifying explicit and implicit feedback by assigning non-uniform weights. • Reducing computation time by element-wise alternating least squares. • A simple and effective multi-threaded computing scheme for above model. As an effective method for high-dimensional information processing, tensor factorization has been widely used in context-aware recommendation. However, the multi-dimensional processing of tensor factorization usually leads to more serious data sparsity. Making full use of the data in recommendation systems, including a small amount of explicit rating data and a large amount of implicit feedback data such as clicks, plays, and purchases, can effectively alleviate this problem. Meanwhile, the processing of sparse explicit data and huge implicit feedback data makes tensor factorization face a severe challenge of computational efficiency. Therefore, this study proposes a fast tensor factorization model named FWCP that unifies explicit and implicit feedback information, which mainly studies as follows: (1) Assigning non-uniform weights to observed and unobserved values to unify explicit and implicit feedback information; (2) Memorizing intermediate data which generated by element-wise alternating least squares(ALS), and implementing parallel optimization of FWCP, which can reduce the training time of tensor factorization based on whole-data. The evaluation results on two real datasets showed that FWCP proposed in this study is superior to other context-aware recommendation algorithms. [ABSTRACT FROM AUTHOR]

• A novel GCN-based traffic prediction model is proposed. • The model enables dynamic spatial–temporal modeling of traffic data. • This model has superior long-term forecasting capability. • Hidden spatial relationships in traffic data were captured. In recent years, spatial–temporal graph modeling based on graph convolutional neural networks (GCN) has become an effective method for mining spatial–temporal dependencies in traffic forecasting research. However, existing studies lack the capability of dynamic spatial–temporal modeling of traffic speeds. Furthermore, long-term forecasting is difficult because of the diversity of traffic conditions. In addition, traditional studies capture only the features of fixed graph structures, which do not reflect real spatial dependence. To address these challenges, this study proposes a novel attention-based dynamic spatial–temporal graph convolutional network (ADSTGCN) model. ADSTGCN mainly consists of multiple dynamic spatial–temporal blocks, each of which contains three modules: 1) a dynamic adjustment module to model the dynamic spatial–temporal correlations of traffic speed, 2) a gated dilated convolution module to mine long-term dependencies, and 3) a spatial convolution module to capture hidden spatial dependencies. Experiments on three public traffic datasets demonstrated the good performance of the model. [ABSTRACT FROM AUTHOR]

Abstract: Background: In vitro experiments demonstrate that adiponectin, a cardioprotective cytokine, is inhibited by tumor necrosis factor-alpha (TNFα). However, the role of TNFα in post-myocardial infarction (post-MI) adiponectin reduction remains unclear. More importantly, the TNF receptor type (TNFR1 or TNFR2) responsible for TNFα-mediated suppression of adiponectin production is unknown. The current study determined the role of TNFα in post-myocardial infarction (post-MI) adiponectin reduction, and identified the receptor type responsible for TNFα-mediated suppression of adiponectin production. Methods and results: Adult male wild type (WT) and three knockout variety (TNFα−/−, TNFR1−/−, and TNFR2−/−) mice were subjected to MI via coronary artery occlusion. Histological and biochemical analyses were performed 3 and 7days post-MI. In WT mice, MI significantly increased plasma TNFα, reduced adipocyte adiponectin mRNA, and decreased plasma adiponectin levels. TNFα deletion had no significant effect upon basal adiponectin level, and partially restored adiponectin expression/production post-MI (P<0.01 vs. WT). Basal adiponectin levels were significantly increased in TNFR1−/− (P<0.05 vs. WT), and unchanged in TNFR2−/− mice. Importantly, suppressed adiponectin expression/production by MI or TNFα administration was markedly decreased by TNFR1 deletion (P<0.01 vs. WT), but exacerbated by TNFR2 deletion (P<0.05 vs. WT). Mechanistically, TNFR1 knockout significantly inhibited, whereas TNFR2 knockout further enhanced TNFα-induced mRNA and protein expression of ATF3, a transcriptional factor known to significantly inhibit adiponectin expression. Conclusion: Our study demonstrates that TNFα overproduction is responsible for reduced adiponectin expression/production following MI. Furthermore, we show that TNFR1/TNFR2 exerts opposite effects upon adiponectin expression/production via differential regulation of ATF3. [Copyright &y& Elsevier]

Abstract: By means of complex representation of a quaternion matrix, we study the relationship between the solutions of the quaternion equality constrained least squares problem and that of complex equality constrained least squares problem, and obtain a new technique of finding a solution of the quaternion equality constrained least squares problem. [Copyright &y& Elsevier]

SiC/Cu/Gr composites with a boundary of SiO 2 –Cu 2 O glass phase (GP) were manufactured through the hot pressing sintering process at a temperature of 950 °C. The influence of graphite (Gr) on the mechanical properties and tribological behavior under high-temperature were purposefully investigated. The microhardness of 1.37 ± 0.02 GPa is achieved by SiC/Cu/Gr composites with a graphite content of 1 vol%. The friction coefficient decreases significantly to 0.64 ± 0.02, while the average wear rate is as low as 2.2 × 10−3±0.02 mm3/(N·m) at a friction temperature of 500 °C. The results indicate that the excellent lubrication effect of graphite is utilized in the SiC/Cu/Gr composites, leading to a significant improvement in its high-temperature wear resistance performance. This behavior is attributed to the molten state of GP at high temperatures, which acts as a "binder" promoting high interface bonding strength between particles, coupled with the solid-phase lubrication provided by graphite. This research work provides a direction for developing and applying materials conducive to high-temperature contact conductivity. [ABSTRACT FROM AUTHOR]

In recent years, context information has been widely used in recommender systems. Tensor factorization is an effective method to process high-dimensional information. However, data sparsity is more serious in tensor factorization, and it is difficult to build a more accurate recommender system only based on user–item–context interaction information. Making full use of user's social information and implicit feedback can alleviate this problem. In this paper, we propose a new tensor factorization model named TrustTF, which mainly works as follows: (1) Using user's social trust information and implicit feedback to extend the bias tensor factorization (BiasTF), effectively alleviate data sparsity problem and improve the recommendation accuracy; (2) Dividing user's trust relationship into unilateral trust and mutual trust, which makes better use of user's social information. To our knowledge, this is the first work to consider the effects of both user trust and implicit feedback on the basis of the BiasTF model. The experimental results in two real-world data sets demonstrate that the TrustTF proposed in this paper can achieve higher accuracy than BiasTF and other social recommendation methods. [ABSTRACT FROM AUTHOR]

Recently, the artificial intelligence technologies have been widely used in the field of pipeline integrity management. When crossing mountains, pipelines would inevitably encounter rockfall impact, which will potentially affect the growth of crack. However, previous research barely investigated the effect of sudden rockfall impact on health management of pipelines with fatigue cracks. To overcome this limitation, a novel crack propagation prediction algorithm based is proposed for pipelines subjected to rockfall impact. The stress intensity factor (SIF) rockfall impact ratio is introduced to describe the interaction effect of rockfall on the fatigue crack of pipelines. And the dynamic SIF values are acquired by finite element modeling (FEM) where 354 models with different parameters are analyzed. To more accurately forecast the crack growth under the rockfall impact, a method integrates multilayer perceptron (MLP) with Paris' law is proposed based on the above reliable database. Two parameters impacting the performance of the network including the number of neurons in the hidden layer and the hidden layer's activation function are evaluated and network with the most precise prediction results is selected. Quantitative analyses are performed for key factors including rockfall mass, impact velocity, impact position and crack size. The prediction results using dynamic SIF values are compared with the static ones to indicate the effect of rockfall on the crack propagation. The proposed method is valuable to support decision-making in pipeline reliability assessment and integrity management. [ABSTRACT FROM AUTHOR]

• The low-cycle fatigue (LCF) design rule of pipelines in ASME B31 code is studied. • The structural strain method generalizes ASME B31 design rule for welded pipelines. • The structural strain method can analyze LCF behavior of irregular pipe tee joint. • Different aspects of the structural strain method are discussed in detail. The welded pipe components are prone to low-cycle fatigue (LCF) at welds, especially under extreme loadings. ASME B31.8 specifies the fatigue design rules of the welded pipelines. In this work, the LCF fatigue analysis approach stipulated in the ASME B31 code is revisited to figure out its underlying mechanism, limitations, and scope, by analyzing two sets of LCF fatigue data of piping structures using different strain information. A structural strain method is proposed to generalize the pseudo-stress idea implied in the ASME code, which correlates large amounts of high- and low-cycle fatigue data of weldments into the master E-N curve. [ABSTRACT FROM AUTHOR]

• Circ_0128846 expression was increased in cartilage tissues of OA patients. • IL-1β treatment increased circ_0128846 expression in chondrocytes. • Circ_0128846 depletion assuaged IL-1β-caused chondrocyte dysfunction. • Circ_0128846 targeted miR-940. • MiR-940 combined with PTPN12. Previous evidence has suggested that circular RNA (circRNA) is abnormally expressed in osteoarthritis (OA). However, the underlying mechanism of circRNA in OA progression remains unclear. The study aims to reveal the mechanism of circ_0128846 regulating OA. Human chondrocytes (C28/I2 cells) were treated with interleukin-1β (IL-1β) to mimic an OA cell model. The expression levels of circ_0128846, miR-940 and protein tyrosine phosphatase 12 (PTPN12) were detected by qRT-PCR. Protein expression was checked by Western blotting. Cell viability, proliferation, and apoptosis were analyzed by a cell counting kit-8 assay, 5-Ethynyl-2′-deoxyuridine (EdU) assay and flow cytometry analysis, respectively. The production of tumor necrosis factor-α (TNF-α) and IL-6 was determined by an enzyme-linked immunosorbent assay (ELISA). The binding relationship between miR-940 and circ_0128846 or PTPN12 was identified by dual-luciferase reporter assay and RNA immunoprecipitation assay. Circ_0128846 and PTPN12 expression were significantly upregulated, whereas miR-940 was downregulated in the cartilage tissues of OA patients and IL-1β-treated C28/I2 cells compared with controls. IL-1β treatment inhibited C28/I2 cell proliferation and induced cell apoptosis and the production of inflammatory factors, TNF-α and IL-6; however, these effects were partly reversed after circ_0128846 depletion. In terms of mechanism, circ_0128846 acted as a miR-940 sponge, and miR-940 combined with PTPN12. Also, circ_0128846 depletion partly ameliorated IL-1β-induced C28/I2 cell disorders through miR-940. PTPN12 overexpression also partly relieved miR-940-mediated effects in IL-1β-treated C28/I2 cells. Further, circ_0128846 induced PTPN12 expression by interacting with miR-940. Circ_0128846 regulated human chondrocyte proliferation, apoptosis and inflammation through the miR-940/PTPN12 pathway in OA. [ABSTRACT FROM AUTHOR]

Lime enhanced gasification (LEGS) process based on calcium looping in which CaO is employed as CO2 sorbent is an emerging technology for hydrogen production and CO2 capture. In this work, carbide slag which was an industrial solid waste was utilized as CO2 sorbent in hydrogen production process. Modification of carbide slag by propionic acid was proposed to improve its reactivity. The CO2 capture behavior of raw and modified carbide slags was investigated in a dual fixed-bed reactor (DFR) and a thermo-gravimetric analyzer (TGA). The results show that modification of carbide slag by propionic acid enhances its CO2 capture capacity in the multiple calcination/carbonation cycles. The favorable carbonation temperature and calcination temperature for modified carbide slag are 680–700 °C and 850–950 °C, respectively. Prolonged carbonation treatment is beneficial to CO2 capture of raw and modified carbide slags. The prolonged carbonation for 9 h in the 21st cycle increases the conversions of raw and modified carbide slags in this cycle. And then the carbonation conversions of the two sorbents were also improved in the subsequent cycles. Calcined modified carbide slag shows more porous microstructure compared with calcined raw one for the same number of cycles. Modification of carbide slag by propionic acid increases the surface area, pore volume and pore area. In addition, the volume and area of the pores in 20–100 nm in diameter were improved, which had been proved to be more effective to capture CO2. The microstructure of calcined modified carbide slag favors its higher CO2 capture capacity in the multiple calcination/carbonation cycles. [ABSTRACT FROM AUTHOR]

Atherosclerotic vascular disease remains the principal cause of death and disability among patients with type 2 diabetes. Unfortunately, the problem is not adequately resolved by therapeutic strategies with currently available drugs or approaches that solely focus on optimal glycemic control. To identify the key contributors and better understand the mechanism of diabetic atherosclerotic vascular disease, we aimed to elucidate the key genetic characteristics and pathological pathways in atherosclerotic vascular disease through nonbiased bioinformatics analysis and subsequent experimental demonstration and exploration in diabetic atherosclerotic vascular disease. Sixty-eight upregulated and 23 downregulated genes were identified from the analysis of gene expression profiles (GSE30169 and GSE6584). A comprehensive bioinformatic assay further identified that ferroptosis, a new type of programmed cell death and HMOX1 (a gene that encodes heme oxygenase), were vital factors in atherosclerotic vascular disease. We further demonstrated that diabetes significantly increased ferroptosis and HMOX1 levels compared to normal controls. Importantly, the ferroptosis inhibitor ferrostatin-1 (Fer-1) effectively attenuated diabetic atherosclerosis, suggesting the causative role of ferroptosis in diabetic atherosclerosis development. At the cellular level, Fer-1 ameliorated high glucose high lipid-induced lipid peroxidation and downregulated ROS production. More importantly, HMOX1 knockdown attenuated Fe2+ overload, reduced iron content and ROS, and alleviated lipid peroxidation, which led to a reduction in ferroptosis in diabetic human endothelial cells. We demonstrated that HMOX1 upregulation is responsible for the increased ferroptosis in diabetic atherosclerosis development, suggesting that HMOX1 may serve as a potential therapeutic or drug development target for diabetic atherosclerosis. [ABSTRACT FROM AUTHOR]

The fluidized bed reactor has been recognized for large-scale CaO/Ca(OH) 2 heat storage system. In this work, the effects of critical factors such as particle size, fluidization number, steam concentration in hydration, initial temperature, cycle number and type of carrier gas on heat release performance of CaO in the fluidized bed reactor were experimentally investigated. CaO under fluidization state exhibits excellent cyclic stability on the heat release performance. The decay in heat release temperature of CaO under fluidization state is less 10% of that under static state. With increasing the cycle number, the heat release temperature of CaO using N 2 as carrier gas decreases because of the rapid expansion of particles. After 20 cycles with N 2 as carrier gas, the average particle size of CaO increases by 46.2% and the hydration conversion of CaO reaches above 95%. The hydration conversion of CaO experienced 20 cycles using air as carrier gas is 20% lower than that using N 2 as carrier gas due to the presence of CO 2 in air. The experimental investigation of CaO/Ca(OH) 2 heat storage provides an important reference for the development of CaO/Ca(OH) 2 system using the fluidized bed reactor. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we give some closed-form formulas for calculating maximal and minimal ranks and inertias of with respect to , where is given, is common Hermitian least squares solutions to matrix equations and . As application, we derive necessary and sufficient conditions for in the Löwner partial ordering. In addition, we give identifying conditions for the existence of definite common Hermitian least squares solutions to matrix equations and . [Copyright &y& Elsevier]

Abstract: Performances of calcium propionate (CP) on nitric oxide (NO) reduction are experimentally investigated on a drop tube furnace system from basic reburning (BR), Thermal De-NO x and advanced reburning (AR) and it is demonstrated to be feasible of using CP as reburning fuel. BR could supply about 80% efficiency with reburning fuel fraction (Rff) and residence time (τ) kept 20–25% and 0.7 s, respectively. Also, oxygen concentration is required to be less than 4%. However, initial NO concentration is not important to reduction. Characteristics of Thermal De-NO x are also studied. The maximum efficiency of 85.34% could be achieved at 1273 K with mole ratio of ammonia to nitric oxide (β) equaling to 1.75. The corresponding “temperature window” is 1215–1341 K. From 2% to 6% of oxygen concentration, the efficiency of Thermal De-NO x is constantly depressed by 16.17%. The performances of advanced reburning are greatly optimized and higher efficiency could be achieved using less calcium propionate and ammonia. At 1273 K, efficiency of 93.37% is supplied by AR with Rff = 19.83% and β = 0.8. Also, the corresponding “temperature window” is broadened to 1195–1355 K which is 1.27 times of the one in Thermal De-NO x at β = 1.75. Meanwhile, the impact of oxygen concentration on NO reduction is weakened in AR. [Copyright &y& Elsevier]

Abstract: In this paper, we first present a class of structure-oriented hybrid two-stage iteration methods for solving the large and sparse blocked system of linear equations, as well as the saddle point problem as a special case. And the new methods converge to the solution under suitable restrictions, for instance, when the coefficient matrix is positive stable matrix generally. Numerical experiments for a model generalized saddle point problem are given, and the results show that our new methods are feasible and efficient, and converge faster than the Classical Uzawa Method. [Copyright &y& Elsevier]

This work reported the one-pot synthesis of the promising, cheap and green heterogeneous nanocatalyst for biodiesel production. The halloysite nanotube (HNT) was impregnated with 40 wt % NaAlO 2 (SA) and the assistance of ultrasonic helped to achieve a better and more stable modification. The resulting 0.4SA/HNTs-UI catalyst was applied in catalyzing the transesterification of palm oil with methanol, using a GA_BP neural network to train and predict the optimal values of reaction parameters. The test results proved the prediction accuracy of the model with R 2 = 0.989. The catalyst possessed excellent performance, and the maximum biodiesel yield of 99.15% was achieved with the catalyst loaded amount of 8.82 wt %, methanol to oil molar ratio of 16.79 and transesterification temperature of 65.12 °C. Besides, the physicochemical properties of the purified transesterification product were in accordance with the ASTM D 6751 standard of biodiesel. [Display omitted] [ABSTRACT FROM AUTHOR]

• A simultaneous SO 2 /NO removal technology has been proposed. • Pellets made of carbide slag and coal char was prepared by extrusion-spheronization. • The pellets possess efficient simultaneous SO 2 and NO removal property. • Carbide slag provides a significant catalytic effect on NO reduction. • Addition of supporter highly enhances mechanical strength of the pellets. In this work, a simultaneous SO 2 /NO removal method using pellets made of carbide slag and coal char by extrusion-spheronization process was proposed. The effects of char type, reaction temperature, O 2 concentration, initial NO/SO 2 concentration and the addition of supporters on the simultaneous SO 2 /NO removal performance of the pellets made of carbide slag and coal char were investigated in a bubbling fluidized-bed reactor. CaO derived from carbide slag not only acts as an excellent desulfurizer but also catalyzes the reduction of NO by coal char. The results show that the pellets made of carbide slag and coal char possess better simultaneous SO 2 /NO removal performance than the pellets made of carbide slag and bio-char. The optimal reaction temperature range for SO 2 /NO removal by the pellets made of carbide slag and coal char is 850−875 °C. The addition of the supporters such as Al 2 O 3 and high alumina cement enhances the mechanical strength of the pellets. The pellets made of carbide slag and coal char seems promising for efficient simultaneous SO 2 /NO removal in the circulating fluidized bed decoupling combustion. [ABSTRACT FROM AUTHOR]

• We introduce and compare six typically fusion strategies for saliency detection. • Overall, the non-linear fusion strategies outperform the linear-based strategies. • The devised non-linear fusion strategy based on least square method is optimum. Saliency detection is a hot topic in the field of computer vision and pattern recognition, thus plenty of saliency models have been exploited and extended to various visual correspondence applications. Currently, it's still confronted with a variety of obstacles and challenges, although it has been studied for decades. With the progress of saliency detection, different computational models and salient features have been proposed and some of them improve and compensate the deficiencies of the others. In this paper, we focus on investigating the salient feature fusion strategies in human visual attention mechanism for saliency detection (e.g., linear and non-linear), in order to efficiently incorporate various salient cues for achieving a better result. Based on the complementary principle, we firstly construct a saliency map based on the information of the image background. Then, we generate a supplemental saliency map from the compactness saliency features. Finally, we evaluate the performance of six individual fusion strategies including both linear and non-linear models in terms of three publicly available image datasets. Experimental results show that our designed non-linear fusion strategy based on least-square method outperforms the other fusion strategies in saliency detection. [ABSTRACT FROM AUTHOR]

• The adsorption of CO 2 and H 2 O by CaO/Ca 12 Al 14 O 33 was studied by DFT calculations. • The chemical adsorption of CO 2 and H 2 O on Ca 12 Al 14 O 33 -supported CaO is competitive. • The adsorption of CO 2 on Ca 12 Al 14 O 33 -supported CaO is stronger than that of H 2 O. • The adsorbed H 2 O activates adjacent O atoms of CaO, which benefits CO 2 adsorption. • The DFT can predict the CO 2 adsorption performance of different CaO-based sorbents. The synthetic CaO/Ca 12 Al 14 O 33 sorbent has been regarded as an efficient CO 2 sorbent during the calcium looping cycles. In this work, the CO 2 adsorption performance of the synthetic CaO/Ca 12 Al 14 O 33 sorbent in the presence of H 2 O was investigated by density functional theory (DFT) calculations. DFT was used to analyze the adsorption of CO 2 and H 2 O on the synthetic sorbent. Both structural parameters (atomic layout and electronic configuration) and the adsorption parameters (energy, bond lengths, angles, bond population and charge transfer) of CO 2 and H 2 O on the synthetic sorbent were determined. To confirm the feasibility of DFT analysis, the CO 2 capture performance of the synthetic sorbent in the presence of steam was examined in a dual fixed bed reactor. The results indicate strong interactions between the C atom and the O atom in CaO and interactions between the H atom and the O atom in CaO. The higher adsorption energy of CO 2 than H 2 O on pristine CaO and Ca 12 Al 14 O 33 -supported CaO suggests that the adsorptions of CO 2 and H 2 O are competitive and that the adsorption of CO 2 is stronger than that of H 2 O. The adsorption of H 2 O leads to the activation of adjacent O atoms of CaO and thus stronger CO 2 adsorption on the O atom with H 2 O adsorbed. The electrons in the p orbital of the O atom near the Fermi level play important roles in CO 2 adsorption by CaO. The presence of Ca 12 Al 14 O 33 hinders CO 2 adsorption by CaO. A low Ca 12 Al 14 O 33 content in synthetic sorbents should be maintained to ensure high CO 2 capture capacity and sintering resistance of synthetic sorbents. DFT calculations can predict the CO 2 adsorption performance of CaO-based sorbents with additives under different reaction atmospheres. [ABSTRACT FROM AUTHOR]

Highlights • Synthetic CaO-based CO 2 sorbent was prepared using paper fibre as a biotemplate. • Synthetic sorbent is mainly composed of CaO and Ca 12 Al 14 O 33. • Synthetic sorbents possess microtube-like structure with superior CO 2 uptake. • Synthetic sorbent has improved sintering resistance in severe calcination condition. Abstract Calcium looping is regarded as an effective and viable way to address CO 2 emissions. To overcome the loss-in-capacity problems of calcium-based sorbents with the number of calcium looping cycles, a novel CaO/Ca 12 Al 14 O 33 sorbent with a microtube-like structure was prepared from carbide slag and Al(NO 3) 3 ·9H 2 O using paper fibre as a biotemplate. The CO 2 capture performance and microstructure of the novel synthetic sorbent under calcium looping conditions were investigated. The results show that the utilization of the biotemplate is good to retain the high cyclic CO 2 capture reactivity of the synthetic sorbent. Due to the unique hollow porous structure, the CO 2 capture capacity of the synthetic sorbent containing 7.5 wt% Al 2 O 3 retains 0.56 and 0.33 g/g after 30 cycles under mild and severe calcination conditions, respectively, which are 2.56 and 2.11 times higher than those of carbide slag under the same respective calcination conditions. With the presence of 10% steam in the carbonation atmosphere, the CO 2 capture capacity of the synthetic sorbent retains 0.55 g/g under the severe calcination conditions after 10 cycles. The native hierarchical biostructure of paper fibre is preserved in the synthetic sorbent. CaO and Ca 12 Al 14 O 33 are uniformly distributed in the synthetic sorbent, resulting in a high sintering resistance during multiple CO 2 capture cycles. CO 2 can penetrate through the microtube-like structure of the synthetic sorbent from two directions, i.e., from the outer surface and inner surface. This phenomenon effectively enlarges the contact area between CO 2 and CaO. The CaO/Ca 12 Al 14 O 33 sorbent with a hollow porous structure by means of a biotemplate appears promising in the calcium looping technology for CO 2 capture. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we study the power method of the right eigenvalue problem of a quaternion matrix A. If A is Hermitian, we propose the power method that is a direct generalization of that of complex Hermitian matrix. When A is non-Hermitian, by applying the properties of quaternion right eigenvalues, we propose the power method for computing the standard right eigenvalue with the maximum norm and the associated eigenvector. We also briefly discuss the inverse power method and shift inverse power method for the both cases. The real structure-preserving algorithm of the power method in the two cases are also proposed, and numerical examples are provided to illustrate the efficiency of the proposed power method and inverse power method. [ABSTRACT FROM AUTHOR]

Abstract Carbide slag pellets fabricated by bagasse templating using extrusion-spheronization were proposed to simultaneously remove SO 2 /NO from flue gas. The effects of the reaction temperature, O 2 concentration, mass ratio of bagasse to carbide slag and particle size on the simultaneous SO 2 /NO removal performance of carbide slag pellets were investigated in a bubbling fluidized bed reactor. CaO in the carbide slag pellets has a significant promotion effect on NO reduction by CO. SO 2 and NO are completely removed by the carbide slag pellets at 825–875 °C. The presence of O 2 in the reaction gas results in an adverse effect on NO removal by carbide slag pellets, while it leads to a positive effect on SO 2 removal. With an increase in the mass of bagasse in the pellets, the duration for the complete NO removal becomes longer and the porosity of the pellets appears higher. Carbide slag pellets with a smaller particle size possess a higher NO removal capacity. The higher mass ratio of bagasse to carbide slag leads to a larger surface area and pore volume of the pellets during SO 2 /NO removal process but results in a slight decrease in the attrition resistance. Carbide slag pellets by bagasse templating for simultaneous SO 2 /NO removal seems promising in the industrial application. Highlights • Bagasse templated carbide slag pellets are fabricated by extrusion-spheronization. • Carbide slag provides a significant promotion effect on NO reduction by CO. • Bagasse template improves SO 2 sorption capacity of carbide slag pellets. • Carbide slag pellets achieve efficient simultaneous SO 2 and NO removal. [ABSTRACT FROM AUTHOR]

Abstract Withaferin A (WFA), a withanolide derived from medicinal plant Withania somnifera , possesses anti-tumorigenic and immunomodulatory activities against various cancer cells. However, the role of WFA in myocardial ischemia reperfusion (MI/R) injury remains unclear. In the present study, we determined whether WFA may regulate cardiac ischemia reperfusion injury and elucidate the underlying mechanisms. We demonstrated that WFA enhanced H9c2 cells survival ability against simulated ischemia/reperfusion (SI/R) or hydrogen peroxide (H 2 O 2)-induced cell apoptosis. In addition, the enhanced oxidative stress induced by SI/R was inhibited by WFA. Among the multiple antioxidant molecules determined, antioxidants SOD2, SOD3, Prdx-1 was obviously upregulated by WFA. When Akt inhibitor IV was administrated, WFA's suppression effect on oxidative stress was obviously abolished. Additional experiments demonstrated that WFA successfully inhibited H 2 O 2 induced upregulation of SOD2, SOD3, and Prdx-1, ameliorated cardiomyocyte caspase-3 activity via an Akt dependent manner. Collectively, these results support the therapeutic potential of WFA against cardiac ischemia reperfusion injury and highlight the application of WFA in cardiovascular diseases holding great promise for the future. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A bifunctional system integrating with CO 2 capture and heat storage is proposed. • Original carbide slag can be used in CaO/Ca(OH) 2 thermochemical heat storage process. • High Cl content results in low cyclic CO 2 capture capacity of carbide slag. • Hydration performance of carbide slag with Cl is improved after CO 2 capture cycles. • CaO after CO 2 capture cycles is promising to be used for heat storage. Abstract Carbide slag is an industrial waste generated from ethylene gas production in chlor-alkali plants. Here, a novel system coupling calcium looping and CaO/Ca(OH) 2 thermochemical heat storage using carbide slag were proposed to simultaneously capture CO 2 and store heat. For CaO/Ca(OH) 2 thermochemical heat storage, the hydration/dehydration performance of original carbide slag and carbide slag that experienced calcium looping cycles for CO 2 capture was investigated. The performances of the two types of carbide slag with and without chlorine were compared. The dehydration conversions of carbide slag improved with the increase of dehydration temperature. The chlorine content has no apparent effect on the hydration/dehydration performance of original carbide slag. However, for CO 2 capture, carbide slag with high chlorine content shows lower carbonation conversion than that of carbide slag without chlorine. The hydration/dehydration conversions of carbide slag that experienced CO 2 capture cycles are lower than those of original carbide slag. For carbide slag with chlorine, the hydration conversion can be improved by more than one CO 2 capture cycle. Therefore, carbide slag that experienced various CO 2 capture cycles is still suitable to be used in CaO/Ca(OH) 2 thermochemical heat storage although calcium looping has an adverse effect on the hydration/dehydration performance of carbide slag. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we propose an efficient method for special least squares solution of the complex matrix equation (A X B , C X D) = (E , F). By using the real representation matrices of complex matrices, the particular structure of the real representation matrices, the Moore–Penrose generalized inverse and the Kronecker product, we obtain the explicit expression of the minimal norm least squares Hermitian solution of the complex matrix equation (A X B , C X D) = (E , F) , which was studied by a product of matrices and vectors in Wang et al. (2016). Our resulting formulas only involve real matrices, and the corresponding algorithm only performs real arithmetic. Therefore our proposed method is more effective and portable. Finally, we give three numerical examples to illustrate the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

• We propose a Tensor Ring decomposition framework for context-aware recommendation. • Our framework can achieve a better balance between performance and computational. • We analyze the advantages of formulating recommendation as Tensor Ring. • Experiments show the superiority of the proposed framework. As a powerful tool for processing high-dimensional data, tensor decomposition has been widely used in context-aware recommendation. Most of the current tensor decomposition-based recommendation models use CP decomposition or Tucker decomposition. In practical recommendation applications, fewer parameters limit the performance of CP decomposition, and the high-order tensor kernel makes the computational complexity of Tucker decomposition exponential. In order to improve the performance of recommendation while maintaining high computational efficiency, we propose a bias Tensor Ring decomposition framework for context-aware recommendation, which employs Tensor Ring decomposition to extract user-item-context latent factors. Comparing to current tensor decomposition-based recommendation models, our framework achieves a better balance between recommendation performance and computational complexity by Tensor Ring decomposition. This is a highly scalable recommendation framework that can easily further integrate additional information such as social trust and implicit feedback, thus used for more complex recommendation tasks. To the best of our knowledge, this work is the first to formulate context-aware recommendation as Tensor Ring decomposition process. Our in-depth analyses confirm that Tensor Ring decomposition has certain advantages over CP decomposition and Tucker decomposition. Multiple experiments on three real datasets also show that the proposed framework helps to improve the recommendation performance. [ABSTRACT FROM AUTHOR]

In this paper, we survey three different forms of Householder based transformations for quaternion matrices in the literature, and propose a new form of quaternion Householder based transformation. We propose real structure-preserving algorithms of these Householder based transformations, which make the procedure computationally more flexible and efficient. We compare the computation counts and assignment numbers of these algorithms. We also compare the effectiveness of these real structure-preserving algorithms applying to the quaternion QRD and the quaternion SVD. All these four real structure-preserving algorithms are more efficient, comparing to the algorithms which apply Quaternion Toolbox using quaternion arithmetics, or algorithms which directly performs real Householder transformations on the real representation of a quaternion matrix. Among these four real structure-preserving algorithms, the most efficient ones are based on quaternion Householder reflection, and new proposed Householder based transformation. [ABSTRACT FROM AUTHOR]

In this paper, by using the real representations of quaternion matrices, the particular structure of the real representations of quaternion matrices, the Kronecker product of matrices and the Moore–Penrose generalized inverse, we obtain the expressions of the minimal norm least squares solution, the pure imaginary least squares solution, and the real least squares solution for the quaternion matrix equation A X B + C X D = E , respectively. Our resulting formulas only involve real matrices, and therefore are simpler than those reported in Yuan (2014). The corresponding algorithms only perform real arithmetic which also consider the particular structure of the real representations of quaternion matrices, and therefore are very efficient and portable. Numerical examples are provided to illustrate the efficiency of our algorithms. [ABSTRACT FROM AUTHOR]

• In-situ conversion mechanism of captured CO 2 by CaO in H 2 was studied by DFT theory. • Detailed reaction paths of direct reduction of CaCO 3 to form CO and CaO by H 2. • The presence of H 2 reduces a 0.35 eV in the energy barrier for CaO generation. • H 2 addition leads to reduced C O orbital overlap and electron cloud disturbances. In-situ conversion of the captured CO 2 by CaO to CO is realized by using renewable H 2 in the calcination stage of calcium looping process, which effectively reduces the decomposition temperature of CaCO 3 and alleviates the sintering of CaO. However, the mechanism for this reaction is unclear which is difficult to determine just by experimental methods. In this work, the reaction mechanism for in-situ conversion of captured CO 2 by CaO to CO in presence of H 2 during calcium looping process was investigated by density function theory (DFT) analysis. The CaCO 3 direct decomposition was compared to clarify the effect of H 2 on CaO regeneration. The electron differential densities (EDD) and partial density of states (PDOS) for HCO 3 * and CO 3 * models were also compared. The results show the detailed reaction pathway for in-situ conversion of the capture CO 2 by CaO in presence of H 2 in the calcination stage of CaCO 3. H 2 is adsorbed on the CaCO 3 surface to form OH*, CO 2 *and HCO 3 *. CO 2 * further is decomposed into CO and O*. HCO 3 * is decomposed into CO 2 and OH*. Then, two OH* are attracted to each other to form H 2 O and O*. The CO 3 * hydrogenation is the rate control step in this reaction with energy barrier of 3.12 eV. The presence of H 2 causes a 0.35 eV reduction in the energy barrier for CaO generation on CaCO 3 surface. The overlap of C O orbitals and the disturbance of electron clouds around O atom all confirm that the addition of H 2 makes C and O atoms in HCO 3 * have small interaction energy. The DFT calculations reinforce the possible mechanism of in-situ conversion of the captured CO 2 by CaO in presence of H 2 during calcium looping process. [ABSTRACT FROM AUTHOR]

CaO/CaCO 3 thermochemical energy storage has been considered as a promising technology in the concentrated solar power plants. In this work, the high-alumina granule stabilized soda residue, which contains CaO, MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4 , was manufactured by wet-mixing method, and explored for thermochemical energy storage via CaO/CaCO 3 cycles. The effects of the addition amount of high-alumina granule, carbonation pressure, and number of cycles on the energy storage capacity of the stabilized soda residue were investigated. MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4 inhibit the growth and agglomeration of CaO grains and enhance the sintering resistance of soda residue; besides, the addition of high-alumina granule increases the basicity of soda residue. Moreover, the increase of carbonation pressure improves the energy storage performance of the stabilized soda residue. Hence, the stabilized soda residue with the mass ratio of high-alumina granule to CaO = 10:100 exhibits the excellent energy storage capacity and cyclic stability in the CaO/CaCO 3 cycles. The energy storage density and effective conversion of the stabilized soda residue are approximately 2394 kJ·kg−1 and 75% after 30 cycles at 1.1 MPa. The stabilized soda residue is an efficient material for CaO/CaCO 3 energy storage system. [Display omitted] • High-alumina granule stabilized soda residue is used for CaO/CaCO 3 energy storage. • The stabilized soda residue contains CaO, MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4. • MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4 inhibit the growth and sintering of CaO grains. • The stabilized soda residue has high energy storage capacity and cyclic stability. • The stabilized soda residue retains porous and stable structure in CaO/CaCO 3 cycles. [ABSTRACT FROM AUTHOR]

CaO/CaCO 3 thermochemical heat storage has been considered as a competitive technology in concentrated solar power plants. Carbide slag and red mud are solid wastes from the chlor-alkali industry and aluminum industry, respectively. In this work, the red mud/Mn co-doped high alumina cement-stabilized carbide slag was synthesized for CaO/CaCO 3 heat storage. The effects of the addition of high alumina cement and red mud/Mn on the heat storage capacity, cyclic stability, and optical absorption of the modified carbide slag were investigated. The modified carbide slag exhibits excellent heat storage capacity and optical absorption. The Ca 3 Al 2 O 6 and CaMnO 3 inhibit the growth of CaO grains. FeMnO 3 and Ca 2 Fe 2 O 5 possess high optical absorption properties. The additions of Mn and red mud enhance the heat storage rate and basicity of the carbide slag. The effective conversion of the modified carbide slag is 0.62 after 30 cycles, which is 3.1 times as high as that of the untreated carbide slag. The modified carbide slag reaches the optical absorptance of ~58%, which is 6.5 times as high as that of the untreated one. Thus, the red mud/Mn co-doped high alumina cement-stabilized carbide slag is a potential candidate for the CaO/CaCO 3 heat storage system. • A red mud/Mn co-doped high alumina cement-stabilized carbide slag was fabricated. • The composite was proposed to use in CaO/CaCO 3 heat storage cycles. • High alumina cement improves cyclic stability due to formation of Ca 3 Al 2 O 6 in cycles. • The composite shows excellent heat storage capacity and optical absorption in cycles. • Red mud and Mn both enhance optical absorption of the composites in cycles. [ABSTRACT FROM AUTHOR]

Herein, a hollow microtubular Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 bi-functional material was prepared by the bio-template method and used for H 2 production from sorption enhanced water gas shift (SEWGS). The microtubular Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 exhibits excellent CO 2 capture and H 2 production performance in SEWGS/regeneration cycles. The stable hollow microtubular structure improves available adsorption and catalytic sites in Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 for CO 2 capture and H 2 production. Mn addition improves CO 2 affinity capacity of the microtubular material. The Fe-Mn interaction increases redox ability of Fe3+/Fe3+, 2+, which promotes CO conversion. Moreover, the formed Ca 2 Fe 2 O 5 and Ca 2 MnO 4 both increase oxygen vacancies to promote catalytic activity of the microtubular material for WGS and its CO 2 capture capacity. The CO conversions for the microtubular material with the Fe/Mn/Al/Ca molar ratio= 10/2/10/100 are 98.7% and 94.0% after 20 cycles under the mild and severe calcination conditions, respectively. The hollow microtubular bi-functional material shows good prospect for efficient H 2 production from SEWGS. [Display omitted] • Microtubular Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 bi-functional material was prepared. • Microtubular material is good for H 2 production by sorption enhanced water gas shift. • Porous and hollow microtubular structure of the material keeps stable in cycles. • Synergistic effect of Fe/Mn in the material promotes CO 2 capture and H 2 production. • High and stable H 2 production from SEWGS using microtubular material is achieved. [ABSTRACT FROM AUTHOR]

Reduced levels of adiponectin (APN) contribute to cardiovascular injury in the diabetic population. Recent studies demonstrate elevated circulating APN levels are associated with endothelial dysfunction during pre-diabetes, suggesting the development of APN resistance. However, mechanisms leading to, and the role of, vascular APN resistance in endothelial dysfunction remain unidentified. The current study determined whether diabetes cause endothelial APN resistance, and by what mechanisms. Under high glucose/high lipids (HG/HL), APN-stimulated nitric oxide production by HUVEC was decreased, phosphorylation of eNOS, AMPK, and Akt was attenuated (P<0.01), and APN's anti-TNFα effect was blunted (P<0.01). APN receptor expression remained normal, whereas Cav1 expression was reduced in HG/HL cells (P<0.01). The AdipoR1/Cav1 signaling complex was dissociated in HG/HL cells. Knock-down of Cav1 inhibited APN's anti-oxidative and anti-inflammatory actions. Conversely, preventing HG/HL-induced Cav1 downregulation by Cav1 overexpression preserved APN signaling in HG/HL cells. Knock-in of a wild type Cav1 in Cav1 knock-down cells restored caveolae structure and rescued APN signaling. In contrast, knock-in of a mutated Cav1 scaffolding domain restored caveolae structure, but failed to rescue APN signaling in Cav1 knock-down cells. Finally, AdipoR1/Cav1 interaction was significantly reduced in diabetic vascular tissue, and the vasorelaxative response to APN was impaired in diabetic animals. The current study demonstrates for the first time the interaction between AdipoR1 and Cav1 is critical for adiponectin-mediated vascular signaling. The AdipoR1/Cav1 interaction is adversely affected by HG/HL, due largely to reduced Cav1 expression, supporting a potential mechanism for the development of APN resistance, contributing to diabetic endothelial dysfunction. [ABSTRACT FROM AUTHOR]

In this paper, by applying particular structure of the real representations of quaternion matrices and the Moore–Penrose generalized inverse, we derive the expressions of the minimal norm least squares solution, the pure imaginary least squares solution, and the real least squares solution for the quaternion matrix equation A X = B . The resulting formulas only involve real matrices, which are simpler than those reported in (Yuan et al., 2013). The corresponding algorithms only perform real arithmetic which also consider particular structure of the real representations of quaternion matrices, therefore are very efficient and easily understood. Numerical examples are provided to illustrate the efficiency of our algorithms. [ABSTRACT FROM AUTHOR]

Abstract: The nonhomogeneous Yakubovich-transpose matrix equation , which contains the well-known Kalman–Yakubovich-transpose matrix equation and general discrete Lyapunov-transpose matrix equation as special cases, has many important applications in control system theory. This study presents two methods to obtain the closed-form solutions of the nonhomogeneous Yakubovich-transpose matrix equation. Moreover, the equivalent forms of the solutions are provided and one of the solutions is established with the controllability matrix, the observability matrix and symmetric operator matrix. [Copyright &y& Elsevier]