Three-dimensional time-of-flight magnetic resonance angiography combined with high resolution T2-weighted imaging in preoperative evaluation of microvascular decompression

BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.

Wide-Area Delay-Dependent Adaptive Supervisory Control of Multi-machine Power System Based on Improve Free Weighting Matrix Approach

The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).

Patch-based vehicle logo detection with patch intensity and weight matrix

A patch-based method for detecting vehicle logos using prior knowledge is proposed.By representing the coarse region of the logo with the weight matrix of patch intensity and position,the proposed method is robust to bad and complex environmental conditions.The bounding-box of the logo is extracted by a thershloding approach.Experimental results show that 93.58% location accuracy is achieved with 1100 images under various environmental conditions,indicating that the proposed method is effective and suitable for the location of vehicle logo in practical applications.

Drawing Weighted Directed Graph from It's Adjacency Matrix

This paper proposes an algorithm for building weighted directed graph, defmes the weighted directed relationship matrix of the graph, and describes algorithm implementation using this matrix. Based on this algorithm, an effective way for building and drawing weighted directed graphs is presented, forming a foundation for visual implementation of the algorithm in the graph theory.

Syngeneic implantation of mouse hepatic progenitor cell-derived three-dimensional liver tissue with dense collagen fibrils

BACKGROUND Liver transplantation is a therapy for irreversible liver failure;however,at present,donor organs are in short supply.Cell transplantation therapy for liver failure is still at the developmental stage and is critically limited by a shortage of human primary hepatocytes.AIM To investigate the possibility that hepatic progenitor cells(HPCs)prepared from the portal branch-ligated hepatic lobe may be used in regenerative medicine,we attempted to enable the implantation of extracellular matrices containing organoids consisting of HPC-derived hepatocytes and non-parenchymal cells.METHODS In vitro liver organoid tissue has been generated by accumulating collagen fibrils,fibroblasts,and HPCs on a mesh of polylactic acid fabric using a bioreactor;this was subsequently implanted into syngeneic wild-type mice.RESULTS The in vitro liver organoid tissues generated transplantable tissues in the condensed collagen fibril matrix and were obtained from the mouse through partial hepatectomy.CONCLUSION Liver organoid tissue was produced from expanded HPCs using an originally designed bioreactor system.This tissue was comparable to liver lobules,and with fibroblasts embedded in the network collagen fibrils of this artificial tissue,it is useful for reconstructing the hepatic interstitial structure.

Three-dimensional consolidation deformation analysis of porous layered soft soils considering asymmetric effects

Long-term settlements for underground structures, such as tunnels and pipelines, are generally observed after the completion of construction in soft clay. The soil consolidation characteristic has great influences on the long-term deformation for underground structures. A three-dimensional consolidation analysis method under the asymmetric loads is developed for porous layered soil based on Biot's classical theory. Time-displacement effects can be fully considered in this work and the analytical solutions are obtained by the state space approach in the Cartesian coordinate. The Laplace and double Fourier integral transform are applied to the state variables in order to reduce the partial differential equations into algebraic differential equations and easily obtain the state space solution. Starting from the governing equations of saturated porous soil, the basic relationship of state space variables is established between the ground surface and the arbitrary depth in the integral transform domain. Based on the continuity conditions and boundary conditions of the multi-layered pore soil model, the multi-layered pore half-space solutions are obtained by means of the transfer matrix method and the inverse integral transforms. The accuracy of proposed method is demonstrated with existing classical solutions. The results indicate that the porous homogenous soils as well as the porous non-homogenous layered soils can be considered in this proposed method. When the consolidation time factor is 0.01, the value of immediate consolidation settlement coefficient calculated by the weighted homogenous solution is 27.4% bigger than the one calculated by the non-homogeneity solution. When the consolidation time factor is 0.05, the value of excess pore water pressure for the weighted homogenous solution is 27.2% bigger than the one for the non-homogeneity solution. It is shown that the material non-homogeneity has a great influence on the long-term settlements and the dissipation process of excess pore water pressure.

Spatial weight matrix in dimensionality reduction reconstruction for microelectromechanical system-based photoacoustic microscopy

A micro-electromechanical system(MEMS)scanning mirror accelerates the raster scanning of optical-resolution photoacoustic microscopy(OR-PAM).However,the nonlinear tilt angular-voltage characteristic of a MEMS mirror introduces distortion into the maximum back-projection image.Moreover,the size of the airy disk,ultrasonic sensor properties,and thermal effects decrease the resolution.Thus,in this study,we proposed a spatial weight matrix(SWM)with a dimensionality reduction for image reconstruction.The three-layer SWM contains the invariable information of the system,which includes a spatial dependent distortion correction and 3D deconvolution.We employed an ordinal-valued Markov random field and the Harris Stephen algorithm,as well as a modified delay-and-sum method during a time reversal.The results from the experiments and a quantitative analysis demonstrate that images can be effectively reconstructed using an SWM;this is also true for severely distorted images.The index of the mutual information between the reference images and registered images was 70.33 times higher than the initial index,on average.Moreover,the peak signal-to-noise ratio was increased by 17.08%after 3D deconvolution.This accomplishment offers a practical approach to image reconstruction and a promising method to achieve a real-time distortion correction for MEMS-based OR-PAM.

Research on consistency measurement and weight estimation approach of hybrid uncertain comparison matrix

The consistency measurement and weight estimation approach of the hybrid uncertain comparison matrix in the analytic hierarchy process （AHP） are studied. First, the decision-making satisfaction membership function is defined based on the decision making＇s allowable error. Then, the weight model based on the maximal satisfactory consistency idea is suggested, and the consistency index is put forward. Moreover, the weight distributing value model is developed to solve the decision making misleading problem since the multioptimization solutions in the former model. Finally, the weights are ranked based on the possibility degree approach to obtain the ultimate order.

A novel trilinear decomposition algorithm:Three-dimension non-negative matrix factorization

Non-negative matrix factorization （NMF） is a technique for dimensionality reduction by placing non-negativity constraints on the matrix. Based on the PARAFAC model, NMF was extended for three-dimension data decomposition. The three-dimension nonnegative matrix factorization （NMF3） algorithm, which was concise and easy to implement, was given in this paper. The NMF3 algorithm implementation was based on elements but not on vectors. It could decompose a data array directly without unfolding, which was not similar to that the traditional algorithms do, It has been applied to the simulated data array decomposition and obtained reasonable results. It showed that NMF3 could be introduced for curve resolution in chemometrics.

Optimal strategy of searching FPD weights scanning matrix using GA-PSO

This paper discusses a kind of optimal method used for searching flat panel display （FPD） scanning matrix. The method adopts bionic algorithm： genetic algorithm （GA） and particle swarm optimization （PSO） algorithm. The method using single GA is more time-consuming, and the search efficiency is low in later evolution; the PSO algorithm is easily falling into the local optimal solution and appears the premature convergent phenomenon. Hence, a hybrid approach of GAPSO is found to optimize the search for high grayscale weights scanning matrix. Finally in the acceptable time, it finds a weight scanning matrix （WSM） of 256 gray scales with Matlab, whose scanning efficiency reaches 94.73% and the linearity is very good.

Correction to: Spatial weight matrix in dimensionality reduction reconstruction for micro-electromechanical system-based photoacoustic microscopy

Following publication of the original article[1],the keywords are missing in the article.Keywords:Photoacoustic microscopy,Spatial weight matrix,Dimensionality reduction,Distortion correction,Mutual information The original article has been updated.

Phosphorylation and biosynthesis of high molecular weight proteins of tumor nuclear matrix

Our previous studies showed a predominance of high molecular weight protein group in tumor nuclear matrices. Contrary to normal cells, proteins of this group are preferentially phosphorylated. Phosphoproteins of hepatoma nuclear matrix are selectively subjected to rapid proteolysis. By alkali treatment and a monoclonal antibody against phosphotyrosyl residue the presence of two high molecular weight bands of phosphotyrosyl-containing proteins was detected in nuclear matrices of tumor but not of normal liver cells. High molecular weight protein group of tumor nuclear matrices revealed also a rapid turnover and preferential incorporation of labeled amino acids selectively inhibited by chloramphenicol.

A Note on the Spectral Radius of Weighted Signless Laplacian Matrix

A weighted graph is a graph that has a numeric label associated with each edge, called the weight of edge. In many applications, the edge weights are usually represented by nonnegative integers or square matrices. The weighted signless Laplacian matrix of a weighted graph is defined as the sum of adjacency matrix and degree matrix of same weighted graph. In this paper, a brief overview of the notation and concepts of weighted graphs that will be used throughout this study is given. In Section 2, the weighted signless Laplacian matrix of simple connected weighted graphs is considered, some upper bounds for the spectral radius of the weighted signless Laplacian matrix are obtained and some results on weighted and unweighted graphs are found.

New Approach of Stability for Time-Delay Takagi-Sugeno Fuzzy System Based on Fuzzy Weighting-Dependent Lyapunov Functionals

This paper deals with the stability of Takagi-Sugeno fuzzy models with time delay. Using fuzzy weighting- dependent Lyapunov-Krasovskii functionals, new sufficient stability criteria are established in terms of Linear Matrix Inequality;hence the stability bound of upper bound delay time can be easily estimated. Finally, numeric simulations are given to validate the developed approach.

基于局部-地理加权回归的时变谐波阻抗估计

现有研究中通常假定电力系统谐波阻抗恒定,但不符合真实工况中情况。实际中,系统侧谐波阻抗和背景谐波随运行工况时变,当两谐波电压样本点时间间隔较大时,对应时刻的阻抗和背景谐波的差值可能较大,难以根据时间间隔较远样本点的信息估计关注样本点的阻抗值。由此,文中提出一种基于局部-地理加权回归的时变系统侧谐波阻抗估计方法,首先依据时间间隔大小构建权重矩阵,对与关注样本点时间间隔较大的样本点赋予较小权重,并采用局部加权回归(locally weighted regression,LWR)初步估计系统侧谐波阻抗和背景谐波参考值。然后利用阻抗参考值修正回归方程以降低原回归方程的欠定程度,同时以背景谐波参考值为先验信息,筛选出与关注样本点背景谐波相似的样本点,再基于所筛选样本逐一采用地理加权回归(geographically weighted regression,GWR)求解各点的背景谐波电压和系统侧谐波阻抗。在强背景谐波波动的情况下,文中所提方法能识别阻抗的突变点、估计系统侧谐波阻抗的变化趋势。最后通过仿真分析可知,文中所提方法相对于传统恒定谐波阻抗估计方法,估计准确度提升约40%;相对于现有变阻抗估计方法,估计准确度提升约30%。

基于Weighted-slope One的用户聚类推荐算法研究

针对传统协同过滤推荐算法存在的数据稀疏性以及实时性差的问题,提出一种基于Weighted-slope One的用户聚类推荐算法。该算法首先利用Weighted-slope One算法的思想对初始的用户-评分矩阵进行有效填充,降低数据的稀疏性;然后,结合初始聚类中心优化改进的K-means方法对用户进行聚类,生成相似用户集合,以缩小目标用户搜索最近邻的范围;最后,结合目标用户所属的聚类,利用基于用户的协同过滤算法搜索最近邻居,为目标用户推荐对应的产品。仿真实验结果表明,改进算法可以显著降低数据的稀疏度,同时提升推荐的准确性和实时性。

融合SIFT特征优化初始地图的单目SLAM

针对ORB-SLAM2系统前端视觉里程计初始化的地图在相机运动变化较大时不能很好地为跟踪线程提供信息依赖的问题,提出一种融合SIFT特征的初始地图优化算法。在特征点提取部分,对传入的图像进行FAST特征和SIFT特征提取,并通过粗匹配算法得到两组特征匹配点对,提高特征点的鲁棒性以及可靠性;然后使用RANSAC算法在剔除两种特征匹配点对中的错误匹配的同时,得到对应特征的单应性矩阵估计,并按各自在FAST点对中的内点率分配权重进行融合,提升单应性矩阵估计的准确性以及鲁棒性。仿真结果表明,ORB-SLAM2在使用算法优化后的初始地图中具有更好的跟踪效果,系统定位及建图误差更小。

企业ESG表现具有同群效应吗?——基于空间计量模型的实证检验

随着“双碳”目标的提出以及绿色可持续发展的推进,ESG理念为企业决策提供了新的思路。基于此,以2015—2022年中国A股上市企业为研究样本,引入空间面板计量模型,构建地区和行业空间权重矩阵,来考察企业ESG表现的同群效应。研究结果表明:同群企业ESG表现(内生同群效应)和其特征变量(外生同群效应)对目标企业ESG表现具有正向影响,且行业同群效应强于地区同群效应,模范企业能够激励同区域和同行业企业积极履行社会责任;机制检验发现,在市场竞争越激烈的行业以及法治环境越好的地区,企业ESG表现的同群效应越显著。对同群效应的经济后果进行分析,发现地区和行业同群效应分别对企业股票收益和股票流动性具有显著正向作用。因此,中国应充分发挥标杆企业的领航作用,加强地区法治环境建设,完善ESG披露准则,重视行业协会建设,进而提升企业ESG表现以及股票市场表现。

自调节图卷积UNet的三维人体姿态估计方法

基于图卷积网络的三维人体姿态估计方法无法提取关节点的多尺度特征和未充分利用相邻节点的拓扑关系问题,提出自调节图卷积UNet的三维人体姿态估计方法M-Joint-UNet。M-Joint-UNet方法由Joint-UNet、自调节图卷积和融合损失3部分组成:Joint-UNet通过关节点池化与去池化改变特征图大小,以提取关节点的不同尺度特征;自调节图卷积通过可学习矩阵自动调节相邻节点或人体骨架结构的关系;使用L_(1)和L_(2)融合的损失缓解梯度爆炸。对比实验表明:所提方法在参数量和估计性能方面均获得了最优的结果,以Human3.6M的二维真实关节点作为输入的参数量仅为0.54×10^(6),MPJPE和P-MPJPE值分别为37.81 mm和30.21 mm。

一种用于深空网天线组阵的基于归一化权的Matrix-Free Power Method

对深空网天线组阵中的几种信号相关算法作简要介绍,重点研究无需形成矩阵的幂的方法——Matrix-Free Power Method。通过理论分析,提出一种改进算法,即基于归一化权的Matrix-Free Power Method。理论计算和软件仿真结果均表明,基于归一化权的Matrix-Free Power Method信噪比合成性能略优于原Matrix-Free Power Method。