Highly Aligned Ternary Nanofiber Matrices Loaded with MXene Expedite Regeneration of Volumetric Muscle Loss

Current therapeutic approaches for volumetric muscle loss(VML)face challenges due to limited graft availability and insufficient bioactivities.To overcome these limitations,tissue-engineered scaffolds have emerged as a promising alternative.In this study,we developed aligned ternary nanofibrous matrices comprised of poly(lactide-co-ε-caprolactone)integrated with collagen and Ti_(3)C_(2)T_(x)MXene nanoparticles(NPs)(PCM matrices),and explored their myogenic potential for skeletal muscle tissue regeneration.The PCM matrices demonstrated favorable physicochemical properties,including structural uniformity,alignment,microporosity,and hydrophilicity.In vitro assays revealed that the PCM matrices promoted cellular behaviors and myogenic differentiation of C2C12 myoblasts.Moreover,in vivo experiments demonstrated enhanced muscle remodeling and recovery in mice treated with PCM matrices following VML injury.Mechanistic insights from next-generation sequencing revealed that MXene NPs facilitated protein and ion availability within PCM matrices,leading to elevated intracellular Ca^(2+)levels in myoblasts through the activation of inducible nitric oxide synthase(i NOS)and serum/glucocorticoid regulated kinase 1(SGK1),ultimately promoting myogenic differentiation via the m TOR-AKT pathway.Additionally,upregulated i NOS and increased NO–contributed to myoblast proliferation and fiber fusion,thereby facilitating overall myoblast maturation.These findings underscore the potential of MXene NPs loaded within highly aligned matrices as therapeutic agents to promote skeletal muscle tissue recovery.

THE LOGARITHMIC SOBOLEV INEQUALITY FOR A SUBMANIFOLD IN MANIFOLDS WITH ASYMPTOTICALLY NONNEGATIVE SECTIONAL CURVATURE

In this note,we prove a logarithmic Sobolev inequality which holds for compact submanifolds without a boundary in manifolds with asymptotically nonnegative sectional curvature.Like the Michale-Simon Sobolev inequality,this inequality contains a term involving the mean curvature.

The“depict”strategy for discovering new compounds in complex matrices:Lycibarbarspermidines as a case

The comprehensive detection and identification of active ingredients in complex matrices is a crucial challenge.Liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS)is the most prominent analytical platform for the exploration of novel active compounds from complex matrices.However,the LC-HRMS-based analysis workflow suffers from several bottleneck issues,such as trace content of target compounds,limited acquisition for fragment information,and uncertainty in interpreting relevant MS2 spectra.Lycibarbarspermidines are vital antioxidant active ingredients in Lycii Fructus,while the reported structures are merely focused on dicaffeoylspermidines due to their low content.To comprehensively detect the new structures of lycibarbarspermidine derivatives,a“depict”strategy was developed in this study.First,potential new lycibarbarspermidine derivatives were designed according to the biosynthetic pathway,and a comprehensive database was established,which enlarged the coverage of lycibarbarspermidine derivatives.Second,the polarity-oriented sample preparation of potential new compounds increased the concentration of the target compounds.Third,the construction of the molecular network based on the fragmentation pathway of lycibarbarspermidine derivatives broadened the comprehensiveness of identification.Finally,the weak response signals were captured by data-dependent scanning(DDA)followed by parallel reaction monitoring(PRM),and the efficiency of acquiring MS2 fragment ions of target compounds was significantly improved.Based on the integrated strategy above,210 lycibarbarspermidine derivatives were detected and identified from Lycii Fructus,and in particular,170 potential new compounds were structurally characterized.The integrated strategy improved the sensitivity of detection and the coverage of low-response components,and it is expected to be a promising pipeline for discovering new compounds.

Acellular dermal matrices in reconstructive surgery;history,current implications and future perspectives for surgeons

Large-scale defects of body in the reconstructive surgical practice,and the help-lessness of their repair with autologous tissues,have been an important factor in the development of artificial biological products for the temporary,definitive,or staged repair of these defects.A major advance in the field of plastic and other reconstructive surgery in this regard has been the introduction and successful use of acellular dermal matrices(ADMs).In recent years,not only the type of tissue from which ADMs are produced,product range,diversity and areas of use have increased,but their use in reconstructive fields,especially in post oncologic breast surgery,has become highly regarded and this has favored ADMs to be a potential cornerstone in specific and well-defined surgical fields in future.It is essential that reconstructive surgeons become familiar with some of the ADM’s as well as the advantages and limitations to their use.This review not only provides basic science and clinical evidence of the current use of ADMs in wide range of surgical fields but also targets to keep them as an important backdrop in the arma-mentarium of reconstructive surgeons.Brief considerations of possible future directions for ADMs are also conducted in the end.

Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Criteria Condition for Generalized Diagonally Dominant Matrices

In this paper, we provide some new necessary and sufficient conditions for generalized diagonally dominant matrices and also obtain some criteria for nongeneralized dominant matrices.

The Monotonicity Problems for Generalized Inverses of Matrices in H (n, ≥)

On the basis of the paoers[3—7],this paper study the monotonicity problems for the positive semidefinite generalized inverses of the positive semidefinite self-conjugate matrices of quaternions in the Lowner partial order,give the explicit formulations of the monotonicity solution sets A{1;≥,T_1;≤B^(1)}and B{1;≥,T_2≥A^(1)}for the(1)-inverse,and two results of the monotonicity charac teriaztion for the(1,2)-inverse.

基于Nonnegative Garrote的ARX和ARMA模型定阶方法

针对传统ARX和ARMA模型定阶方法计算量大和稳定性不强的缺点,提出采用非负绞杀法对ARX和ARMA模型进行定阶。通过分析ARX和ARMA模型的特点,对常规非负绞杀方法进行了改进,使其更适用于动态系统辨识问题,进而给出了相应的求解算法。仿真实验的结果表明了该方法的有效性,且在稳定性上优于传统的信息量准则法。

BEST APPROXIMATION BY NORMAL MATRICES WITH SPECTRAL CONSTRAINTS

The problem of best approximating, a given square complex matrix in the Frobenius norm by normal matrices under a given spectral restriction is considered. The ne cessary and sufficient condition for the solvability of the problem is given. A numerical algorithm for solving the problem is provided and a numerical example is presented.

NECESSARY AND SUFFICIENT CONDITIONS FOR THE EXISTENCE OF NONNEGATIVE SOLUTIONS OF INHOMOGENEOUS p-LAPLACE EQUATION

Let Ω be a smooth bounded domain in R^n. In this article, we consider the homogeneous boundary Dirichlet problem of inhomogeneous p-Laplace equation --△pu = ｜u｜^q-1 u ＋ λf（x） on Ω, and identify necessary and sufficient conditions on Ω and f（x） which ensure the existence, or multiplicities of nonnegative solutions for the problem under consideration.

Formulation and evaluation the bioadhesive properties of drug delivery system based on PEGylated mucin matrices

Objective:To formulate and evaluate the application of PEGylated mucin in oral bioadhesive drug(OBD) delivery system.Methods:The bioadhesive strength of different formulation ratios of polyethylene glycol(PEG) and mucin was evaluated by tensiometry.Co polymer matrices containing mucin and PEG(PEGylated mucin) in the following ratios of 1:1(A),2:1(B),1:2(C), 0:1(D) and 1:0(E) were prepared by co-precipitation.Microparticles were prepared from the matrices using a size reduction technique.Five different samples were prepared using direct mixtures in the appropriate solvenfs having mucin and PEG ratios of 1:1,2:1,1:2,0:1, 1:0 and labeled as(A-E).The matrices were evaluated for their flow properties and the in vitro bioadhesion characteristics of the samples were examined.Results:The range of flow rates of the matrices was 1.35-2.23 g/sec.The angle of repose was in the range of 37.3-39.9 degree.The bulk and tapped densities were within the ranges of 0.41- 0.49.The Hausner’s quotient(HQ) were 1.12, 1.24,1.14,1.25 and 1.2 for matrix batches A-E respectively,The bioadhesive strength of polymer matrices appeared to be directly related to amount of mucin.The order of bioadhesive strength is 2:1】1:1】1:0】1:2】0:1 of PEG:mucin in both simulated intestine fluid(SEP) and simulated gastrointestinal fluid(SGF).The physical properties of the micrometrics properties of the matrices were within the accepted values.Conclusions:OBD preparation containing PEGylated mucin can be prepared by direct compression and be used in drug delivery to the oral cavity.

Generalized Drazin spectrum of operator matrices

Let A ∈ B（X） and B ∈ B（Y）, Me be an operator on Banach space X ＋ Y given by Mc =（A C 0 B）A generalized Drazin spectrum defined by σgD（T） = {λ∈C ： T-λI is not generalized Drazin invertible} is considered in this paper. It is shown that

Real-time origin-destination matrices estimation for urban rail transit network based on structural state-space model

The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from automatic fare collection(AFC) system as the real time observed passenger flow counts. For lacking of measurable passenger flow information, the proposed model employs priori O-D matrices and travel time distribution from historical travel records in AFC system to establish the dynamic system equations. An arriving rate based on travel time distribution is defined to identify the dynamic interrelations between time-varying O-D flows and observed flows, which greatly decreases the computational complexity and improve the model's applicability for large-scale network. This methodology is tested in a real transit network from Beijing subway network in China through comparing the predicted matrices with the true matrices. Case study results indicate that the proposed model is effective and applicative for estimating dynamic O-D matrices for large-scale rail transit network.

Bispectrum Feature Extraction of Gearbox Faults Based on Nonnegative Tucker3 Decomposition with 3D Calculations

Nonnegative Tucker3 decomposition（NTD） has attracted lots of attentions for its good performance in 3D data array analysis. However, further research is still necessary to solve the problems of overfitting and slow convergence under the anharmonic vibration circumstance occurred in the field of mechanical fault diagnosis. To decompose a large-scale tensor and extract available bispectrum feature, a method of conjugating Choi-Williams kernel function with Gauss-Newton Cartesian product based on nonnegative Tucker3 decomposition（NTD_EDF） is investigated. The complexity of the proposed method is reduced from o（nNlgn） in 3D spaces to o（RiR2nlgn） in 1D vectors due to its low rank form of the Tucker-product convolution. Meanwhile, a simultaneously updating algorithm is given to overcome the overfitting, slow convergence and low efficiency existing in the conventional one-by-one updating algorithm. Furthermore, the technique of spectral phase analysis for quadratic coupling estimation is used to explain the feature spectrum extracted from the gearbox fault data by the proposed method in detail. The simulated and experimental results show that the sparser and more inerratic feature distribution of basis images can be obtained with core tensor by the NTD EDF method compared with the one by the other methods in bispectrum feature extraction, and a legible fault expression can also be performed by power spectral density（PSD） function. Besides, the deviations of successive relative error（DSRE） of NTD_EDF achieves 81.66 dB against 15.17 dB by beta-divergences based on NTD（NTD_Beta） and the time-cost of NTD EDF is only 129.3 s, which is far less than 1 747.9 s by hierarchical alternative least square based on NTD （NTD_HALS）. The NTD_EDF method proposed not only avoids the data overfitting and improves the computation efficiency but also can be used to extract more inerratic and sparser bispectrum features of the gearbox fault.

Sparse recovery in probability via l_q-minimization with Weibull random matrices for 0 < q ≤ 1

Although Gaussian random matrices play an important role of measurement matrices in compressed sensing, one hopes that there exist other random matrices which can also be used to serve as the measurement matrices. Hence, Weibull random matrices induce extensive interest. In this paper, we first propose the lrobust null space property that can weaken the D-RIP, and show that Weibull random matrices satisfy the lrobust null space property with high probability. Besides, we prove that Weibull random matrices also possess the lquotient property with high probability. Finally, with the combination of the above mentioned properties,we give two important approximation characteristics of the solutions to the l-minimization with Weibull random matrices, one is on the stability estimate when the measurement noise e ∈ R~n needs a priori ‖e‖≤ε, the other is on the robustness estimate without needing to estimate the bound of ‖e‖. The results indicate that the performance of Weibull random matrices is similar to that of Gaussian random matrices in sparse recovery.

Synchronization of complex switched delay dynamical networks with simultaneously diagonalizable coupling matrices

This paper studies local exponential synchronization of complex delayed networks with switching topology via switched system stability theory. First, by a common unitary matrix, the problem of synchronization is transformed into the stability analysis of some linear switched delay systems. Then, when all subnetworks are synchronizable, a delay-dependent sufficient condition is given in terms of linear matrix inequalities （LMIs） which guarantees the solvability of the synchronization problem under an average dwell time scheme. We extend this result to the case that not all subnetworks are synchronizable. It is shown that in addition to average dwell time, if the ratio of the total activation time of synchronizable and non-synchronizable subnetworks satisfy an extra condition, then the problem is also solvable. Two numerical examples of delayed dynamical networks with switching topology are given, which demonstrate the effectiveness of obtained results.

Inverse Eigenvalue Problem for Generalized Arrow-Like Matrices

This paper researches the following inverse eigenvalue problem for arrow-like matrices. Give two characteristic pairs, get a generalized arrow-like matrix, let the two characteristic pairs are the characteristic pairs of this generalized arrow-like matrix. The expression and an algorithm of the solution of the problem is given, and a numerical example is provided.

Development of damage probability matrices based on Greek earthquake damage data

A comprehensive study is presented for empirical seismic vulnerability assessment of typical structural types, representative of the building stock of Southern Europe, based on a large set of damage statistics. The observational database was obtained from post-earthquake surveys carried out in the area struck by the September 7, 1999 Athens earthquake. After analysis of the collected observational data, a unified damage database has been created which comprises 180,945 damaged buildings from/after the near-field area of the earthquake. The damaged buildings are classified in specific structural types, according to the materials, seismic codes and construction techniques in Southern Europe. The seismic demand is described in terms of both the regional macroseismic intensity and the ratio αg/ao, where αg is the maximum peak ground acceleration （PGA） of the earthquake event and ao is the unique value PGA that characterizes each municipality shown on the Greek hazard map. The relative and cumulative frequencies of the different damage states for each structural type and each intensity level are computed in terms of damage ratio. Damage probability matrices （DPMs） and vulnerability curves are obtained for specific structural types. A comparison analysis is fulfilled between the produced and the existing vulnerability models.

Construction of protograph LDPC codes with circular generator matrices

The application of protograph low density parity check （LDPC） codes involves the encoding complexity problem. Since the generator matrices are dense, and if the positions of ＂1＂ s are irregularity, the encoder needs to store every ＂1＂ of the generator matrices by using huge chip area. In order to solve this problem, we need to design the protograph LDPC codes with circular generator matrices. A theorem concerning the circulating property of generator matrices of nonsingular protograph LDPC codes is proposed. The circulating property of generator matrix of nonsingular protograph LDPC codes can be obtained from the corresponding quasi-cyclic parity check matrix. This paper gives a scheme of constructing protograph LDPC codes with circulating generator matrices, and it reveals that the fast encoding algorithm of protograph LDPC codes has lower encoding complexity under the condition of the proposed theorem. Simulation results in ad- ditive white Gaussian noise （AWGN） channels show that the bit error rate （BER） performance of the designed codes based on the proposed theorem is much better than that of GB20600 LDPC codes and Tanner LDPC codes.

Compressed data separation via dual frames based split-analysis with Weibull matrices

In this paper, we consider data separation problem, where the original signal is composed of two distinct subcomponents, via dual frames based Split-analysis approach. We show that the two distinct subcomponents, which are sparse in two diff erent general frames respectively, can be exactly recovered with high probability, when the measurement matrix is a Weibull random matrix （not Gaussian） and the two frames satisfy a mutual coherence property. Our result may be significant for analysing Split-analysis model for data separation.