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This paper considers model order reduction based on low-rank decomposition of the cross Gramian for linear systems. The proposed approach uses the low-rank factors of the cross Gramian to generate approximate balanced model for the large-scale system. Then, the reduced-order model is obtained by truncating the states corresponding to the small approximate Hankel singular values. The low-rank factors are directly constructed from the expansion coefficients of impulse responses in the space spanned by Legendre polynomials by solving block tridiagonal linear systems. In contrast to balanced truncation related approaches which require to solve Sylvester equation to compute the full cross Gramian, the proposed method needs to solve sparse linear equations, and only one singular value decomposition is applied to a low-dimensional matrix. The stability preservation of the reduced model is briefly discussed. And in combination with the dominant subspace projection method, the reduction procedure is modified to alleviate the shortcoming, which may unexpectedly lead to unstable systems even though the original one is stable. Finally, numerical experiments are given to demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the topic of model order reduction (MOR) for coupled systems. At first, an approximation via Laguerre polynomials expansions to controllability and observability gramians for such systems are presented, which provides a low-rank decomposition form whose factors are constructed from a recurrence formula instead of Lyapunov equations. Then, in combination of balanced truncation and dominant subspace projection method, a series of MOR algorithms are proposed that preserve the coupled structures. What's more, some main properties of reduced-order models, such as stability preservation, are well discussed. Finally, three numerical simulations are provided to illustrate the effectiveness of our algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a series of structure-preserving model order reduction algorithms for K-power bilinear systems via Laguerre functions. The method first aims to rewritten the K-power bilinear system as a general bilinear system and calculate the approximate low-rank factors of the cross Gramian of the bilinear system by combining the idea of Laguerre functions expansion of the matrix exponential function. After that, the approximate balanced system of the K-power bilinear system is constructed by the corresponding projection transformation of each subsystem. In order to achieve the purpose of model order reduction, the states with smaller singular values are then truncated, so as to further obtain the reduced order model. For this approach, there is a disadvantage that unstable systems may be generated although the original one is stable. To alleviate the inadequacies of this approach, we have improved the model reduction procedure, which is based upon the dominant subspace projection method. In addition, we also carried out a correlation analysis on the stability of improved algorithms. Finally, numerical experiments are employed to substantiate the effectiveness of the presented algorithms. [ABSTRACT FROM AUTHOR]

Poly (lactic acid) (PLA) is a biodegradable and environmentally friendly material. And the spent coffee grounds (SCG) are huge waste all over the world. Therefore, the issue that how to convert the low‐value wastes SCG into more valuable products is attracting more research attention. In this work, we compounded PLA with SCG. Firstly, the efficiency of oil extraction from SCG was compared by different methods and solvents. Then, the biocomposites specimens of different SCG contents (0, 5, 10, and 15 wt%) were prepared by extrusion and injection molding. The effects of SCG particle size and content on the thermal and mechanical properties were investigated. Next, the effect of coupling agent (4,4‐methylene diphenyl diisocyanate [MDI]) on the biocomposites properties at 10 wt% SCG was examined by Field emission‐scanning electron microscope and Fourier transform infrared spectroscopy. The results show that the tensile strength and elongation at break of the PLA composites with the optimal contents are increased by about 50% and 120%, respectively, compared with untreated SCG. [ABSTRACT FROM AUTHOR]

The cross Gramian is a useful tool in model order reduction but only applicable to square dynamical systems. Throughout this paper, time-limited cross Gramians is firstly extended to square bilinear systems that satisfies a generalized Sylvester equation, and then concepts from decentralized control are used to approximate a cross Gramian for non-square bilinear systems. In order to illustrate these cross Gramians, they are calculated efficiently based on shifted Legendre polynomials and applied to dimension reduction, which leads to a lower dimensional model by truncating the states that are associated with smaller approximate generalized Hankel singular values. In combination of the dominant subspace projection method, our reduction procedure is modified to produce a bounded-input bounded-output stable-preserved reduced model under some certain conditions. At last, the performance of numerical experiments indicates the validity of our reduction methods. [ABSTRACT FROM AUTHOR]

A new structure-preserving model order reduction technique based on Laguerre-Gramian for second-order form systems is presented in this article. The main task of the proposed approach is to use the Laguerre polynomial expansion of the matrix exponential function to obtain the approximate low-rank decomposition of the Gramians for the equivalent first-order representation of the original second-order form system. The approximate balanced system is generated by a balancing transformation which is directly computed from the expansion coefficients of impulse responses in the space spanned by Laguerre polynomials, without computing the full Gramians for the first-order representation. Then, the reduced second-order model is constructed by truncating the states with small approximate Hankel singular values (HSVs). The above method has a disadvantage that it may unexpectedly result in unstable systems although the original one is stable. Therefore, modified reduction procedure combined with the dominant subspace projection method is presented to alleviate the limitation. Finally, two numerical experiments are provided to demonstrate the effectiveness of the algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a dimension reduction method via general orthogonal polynomials and multiorder Arnoldi algorithm is proposed, which focuses on the topic of structure-preserving for k-power bilinear systems. The main procedure is using a series of expansion coefficient vectors of each state variables in the space spanned by general orthogonal polynomials that satisfy a recurrence formula to generate a projection based on multiorder Arnoldi algorithm. The resulting reduced-order model not only matches a desired number of expansion coefficients of the original output but also retains the topology structure. Meanwhile, the stability is well preserved under some certain conditions and the error bound is also given. Finally, two numerical simulations are provided to illustrate the effectiveness of our proposed algorithm in the views of accuracy and computational cost. [ABSTRACT FROM AUTHOR]

Colon cancer side population (SP) cells are a small subset of cancer cells that have cancer stemness capacity and enhanced drug resistance. ABCG2 is a multidrug resistance-related protein in SP cells and has been demonstrated to be regulated by Notch signalling pathway. Recently, microRNAs are reported to play a critical role in SP cell fate. However, their role in ABCG2-mediated drug resistance in colon cancer SP cells remains unclear. In the current study, the different expressions of miR-552, miR-611, miR-34a and miR-5000-3p were compared within SP and non-SP cells, which were separated from human colon cancer cell lines (SW480 and LoVo). We found that miR-34a was significantly down-regulated in SP cells and that overexpressing miR-34a overcame drug resistance to 5-fluorouracil (5-FU). The luciferase reporter assay indicated that miR-34a negatively regulated DLL1, a ligand of Notch signalling pathway, via binding with 3′-untranslated region of its messenger RNA. In addition, overexpressing miR-34a overcame ABCG2-mediated resistance to 5-FU via DLL1/Notch pathway in vitro , and suppressed tumour growth under 5-FU treatment in vivo. In conclusion, our findings suggest that miR-34a acts as a tumour suppressor via enhancing chemosensitivity to 5-FU in SP cells, which provides a novel therapeutic target in chemotherapy-resistant colon cancer. [ABSTRACT FROM AUTHOR]

Activation of hepatic stellate cells (HSCs) is a prominent driver of liver fibrogenesis, including alcoholic liver fibrosis (ALF). Furthermore, autophagy contributes to HSCs activation. This study aims to investigate the role and the mechanisms of long noncoding RNA XIST in regulating HSCs autophagy and activation. Human HSC cells (LX‐2) were treated with 100 mmol/L ethanol to mimic HSCs activation. The HSCs activation was evaluated by determining cell viability and protein levels of fibrosis markers α‐smooth muscle actin (α‐SMA) and collagen type 1 α1 (CoL1A1). The autophagy was evaluated by measuring autophagy markers Beclin‐1 and LC3‐II. The interaction among XIST, miR‐29b, and high‐mobility group box‐1 (HMGB1) were analyzed using luciferase reporter assay, qRT‐PCR, and western blot. Lentiviruses targeting sh‐XIST (LV‐sh‐XIST) were injected into ALF model mice via tail vein to elucidate the in vivo role of XIST in ALF injury. XIST was upregulated in ethanol‐activated LX‐2 cells. Furthermore, XIST served as a competitive endogenous RNA of miR‐29b to facilitate HMGB1 expression, and thus enhanced ethanol‐induced HSCs autophagy and activation. Further in vivo assay showed that downregulation of XIST by LV‐sh‐XIST alleviated ALF injury in ALF model mice. Collectively, XIST enhances ethanol‐induced HSCs autophagy and activation via miR‐29b/HMGB1 axis. [ABSTRACT FROM AUTHOR]

This study focuses on the topic of model order reduction (MOR) for coupled systems with inhomogeneous initial conditions and presents an MOR method by general orthogonal polynomials with Arnoldi algorithm. The main procedure is to use a series of expansion coefficients vectors in the space spanned by orthogonal polynomials that satisfy a recursive formula to generate a projection based on the multiorder Arnoldi algorithm. The resulting model not only match desired number of expansion coefficients but also has the same coupled structure as the original system. Moreover, the stability is preserved as well. The error bound between the outputs is well‐discussed. Finally, numerical results show that the authors' method can deal well with those systems with inhomogeneous initial conditions in the views of accuracy and computational cost. [ABSTRACT FROM AUTHOR]

This study considers structure preserving balanced proper orthogonal decomposition for second‐order form systems via shifted Legendre polynomials. The proposed approach is to use time interval empirical Gramians of the first‐order representation, which are constructed from impulse responses by solving block tridiagonal linear systems, to generate approximate balanced system for the large‐scale second‐order form system. The balancing transformation is directly computed from the expansion coefficients of impulse responses in the space spanned by shifted Legendre polynomials, without computing the full Gramians for the first‐order representation. Then, the reduced second‐order model is constructed by truncating the states corresponding to the small approximate singular values. Furthermore, in combination with the dominant subspace projection method, the authors modify the reduction procedure to alleviate the shortcoming of the above method, which may unexpectedly lead to unstable systems even though the original one is stable. The stability preservation of the reduced model is briefly discussed. Finally, the effectiveness of the proposed methods is demonstrated by two numerical experiments. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the Krylov subspace-based model order reduction methods of second-order systems with time delays, and present two structure-preserving methods for model order reduction of these second-order systems, which avoid to convert the second-order systems into first-order ones. One method is based on a Krylov subspace by using the Taylor series expansion, the other method is based on the Laguerre series expansion. These two methods are used in the multi-order Arnoldi algorithm to construct the projection matrices. The resulting reduced models can not only preserve the structure of the original systems, but also can match a certain number of approximate moments or Laguerre expansion coefficients. The effectiveness of the proposed methods is demonstrated by two numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, we propose a model order reduction (MOR) method based on general orthogonal polynomials for K-power bilinear systems in the time domain. Constructing proper projection matrices by solving a series of linear equations, a reduced K-power bilinear system is produced, which preserves the original coupled structure. It can match several expansion coefficients of the original output. Then the error bound of our algorithm is also investigated. Moreover, the stability of the reduced system is discussed as well. Finally, two numerical examples are provided to illustrate the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we present a model order reduction (MOR) method based on Laguerre polynomials and singular value decomposition (SVD) for coupled systems in the frequency domain. By constructing projection matrices from the global perspective and then blockdiagonalizing them, the reduced system is produced, which not only retains the structure of the original system, but also matches the first several Laguerre coefficients. In addition, the connection between our algorithm and the moment matching approximation is also discussed. The error estimation of our method is given as well. Besides, the stability of the reduced system is also studied. Finally, two numerical examples are provided to verify the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the Arnoldi-based model reduction methods are employed to fractional order linear time-invariant systems. The resulting model has a smaller dimension, while its fractional order is the same as that of the original system. The error and stability of the reduced model are discussed. And to overcome the local convergence of Padé approximation, the multi-point Arnoldi algorithm, which can recursively generate a reduced-order orthonormal basis from the corresponding Krylov subspace, is used. Numerical examples are given to illustrate the accuracy and efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

In this article, we discuss the time-domain dimension reduction methods for second-order systems by general orthogonal polynomials, and present a structure-preserving dimension reduction method for second-order systems. The resulting reduced systems not only preserve the second-order structure but also guarantee the stability under certain conditions. The error estimate of the reduced models is also given. The effectiveness of the proposed methods is demonstrated by three test examples. [ABSTRACT FROM AUTHOR]

In this study, the combustion behaviors of sludge–biomass mixed pellets with different sludge ratios in air atmosphere were investigated by thermogravimetric analysis. The pellets consisted of sludge and Chinese fir or rice straw with sludge ratios of 0%, 25%, 50%, 75% and 100%, respectively. The thermogravimetric data were applied for kinetic analysis using the Coats and Redfern (CR) equation. Results showed that there were four main stages such as dehydration, volatile oxidation, char burning and burnout during thermal decomposition of pellets. The reactivities of sludge–biomass pellets were improved by the increment of the mixing ratio of biomass. In addition, the potential slagging behaviors of the resultant ashes were evaluated by X-ray fluorescence (XRF). The suitable sludge to biomass ratio should consider the combustion properties and ash slagging deposition of pellets. It is inappropriate for the production of sludge–straw pellet in the present state due to the high ash slagging potential. [ABSTRACT FROM AUTHOR]

Presently, most pellets are made of lignocellulose biomass. However, the rocketing development of demands and fierce competition of feedstock between biomass industries have resulted in local biomass supply insufficiency and rising prices of the raw material. Therefore, other kinds of raw materials should be involved in the production of pellets to improve the stable supply of feedstock. In this study, the pelletization of biomass materials mixed with sewage sludge (SS) was investigated. The effects of process parameters on energy consumption and pellet properties were studied. It was shown that the compression energy consumption was affected by applied pressure, die temperature and water content. Both temperature and water content had an influence on the above pellet properties to a different extent, which was found to be independent of pressure. Optimal parameters (55 MPa for pressure, 90 °C for temperature and 10–15% for water content) were recommended for co-pelletization. [ABSTRACT FROM AUTHOR]

Reverse micelles have drawn attention of many research workers. However, most of the early efforts were focused on the single-phase reverse micelles. In this study, rhamnolipid, a kind of biosurfactant, was firstly tested to form a mixed reversed micellar systems with tween 80. The pseudo-ternary phase diagrams and the properties of this formed reverse micellar systems were investigated, and the catalytic activity of lignin peroxidase was explored. The results show that the phase diagram was sensitive to some critical factors, such as pH and ionic concentration. The properties electrical conductivity of mixed reverse micelles indicated that electrical conductivity increased with the increase of water concentration, and viscosity varied as function of water content in a non-monotonic way giving two peaked plot. The highest activity of lignin peroxidase was up to 350% in the appropriate conditions. The findings further provide theoretical knowledge that the pseudo-ternary systems can increase the potential of lignin peroxidase as catalysts for various oxidations. [ABSTRACT FROM AUTHOR]