考虑衬砌截面协调变形约束的既有隧道受盾构下穿施工影响的Fourier能量变分解

目前关于新建盾构开挖诱发既有地铁隧道变形的理论研究,大多将既有隧道简化为不含接头的Euler-Bernoulli梁,而忽视了衬砌截面的剪切变形与管片接头的局部刚度削弱。此外,既有地基模型理论较少考虑衬砌管片与接触土体的协调变形约束。首先,采用Loganathan-Polous公式计算盾构开挖诱发的土体自由位移场,并将既有隧道视为考虑剪切变形的Timoshenko梁,基于沿轴线变化的抗弯与剪切刚度函数来描述管片接头的局部削弱作用;然后,结合能量变分原理与连续弹性体Mindlin解,建立考虑衬砌截面协同变形约束的隧道位移控制方程,将盾构开挖诱发的附加荷载施加于既有隧道,并使用Fourier级数方法求解既有隧道纵向变形;最后,将Fourier能量变分解与3组工程实测数据进行对比验证,取得了较好的一致性。此外,考虑隧道抗弯刚度、剪切刚度、接头刚度削弱作用、土体参数与隧道空间位置等因素的共同影响,使用抗弯系数、剪切系数及接头系数进行敏感性分析。结果表明,考虑截面变形协调约束的理论解更为符合实际,不考虑变形协调约束所得隧道位移结果偏大;衬砌接头局部刚度的削弱作用将造成隧道弯矩沿轴线在接头处发生明显锯齿状突变;抗弯系数与剪切系数的增长均导致隧道结构所受弯矩降低;剪切系数由低到高的增长将导致隧道变形模式发生“弯曲控制-弯剪混合-剪切控制”三阶段变化;隧道变形模式进入“剪切控制”阶段的过程中,抗弯刚度的变化对隧道内力影响逐渐降低;接头系数的增长将造成隧道所受弯矩降低,但隧道抗弯刚度较大时其影响逐渐减弱。

基于Doehlert Matrix的全贯流泵装置定转子进出流间隙优化设计

全贯流泵是一种新型的机电-水泵一体式贯流泵,然而其在运行时存在定转子间隙回流,扰乱了叶轮内的流场分布,导致泵装置产生能量损失、压力波动和噪声等问题,影响泵站的正常运行。通过数值模拟和模型试验研究全贯流泵装置定转子间隙流的水力特性,结合Doehlert Matrix设计-响应面优化法对其定转子进、出流间隙结构进行优化设计,揭示全贯流泵装置定转子进、出流间隙结构对泵装置性能的影响机理,并得到最终优化的折角式定转子进、出流间隙结构方案为:外侧延伸段长度t1为4.921r,外侧收缩段长度x1为0.624r,内侧延伸段长度t2为3.655r,内侧收缩段长度x2为1.6r(r为定转子间隙宽度),使得全贯流泵装置扬程和效率分别提升约10.3%和5.2%。

基于Fourier变换红外光谱分析咖啡豆成分

采用Fourier变换红外光谱对不同产区、不同海拔的5组浅中烘焙的咖啡豆样品进行分析,根据官能团的红外光谱特征峰分析样品主要成分;为进一步分析5组样品的成分差异,对原始光谱进行二阶导数处理,结合聚类分析理论建立平均偏离分析方法,计算出5组样品间的平均偏离大小并进行分析.结果表明:5组样品的红外光谱特征峰峰形相似,即主要成分相同;根据红外光谱得到平均偏离大小与产区海拔差值呈正相关.研究结果为分析咖啡豆产区和海拔提供鉴别依据,并对红外光谱研究提供一定参考.

分数阶Fourier变换的测不准原理

该文参考Fourier变换的性质研究了离散分数阶Fourier变换的测不准原理以及连续分数阶Fourier变换在Lebesgue测度下的测不准原理,使得分数阶Fourier变换的测不准原理性质更一般化.

High quality repair of osteochondral defects in rats using the extracellular matrix of antler stem cells

BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown that decellularized extracellular matrix(ECM)derived from autologous,allogenic,or xenogeneic mesenchymal stromal cells(MSCs)can effectively restore osteochondral integrity.AIM To determine whether the decellularized ECM of antler reserve mesenchymal cells(RMCs),a xenogeneic material from antler stem cells,is superior to the currently available treatments for osteochondral defects.METHODS We isolated the RMCs from a 60-d-old sika deer antler and cultured them in vitro to 70%confluence;50 mg/mL L-ascorbic acid was then added to the medium to stimulate ECM deposition.Decellularized sheets of adipocyte-derived MSCs(aMSCs)and antlerogenic periosteal cells(another type of antler stem cells)were used as the controls.Three weeks after ascorbic acid stimulation,the ECM sheets were harvested and applied to the osteochondral defects in rat knee joints.RESULTS The defects were successfully repaired by applying the ECM-sheets.The highest quality of repair was achieved in the RMC-ECM group both in vitro(including cell attachment and proliferation),and in vivo(including the simultaneous regeneration of well-vascularized subchondral bone and avascular articular hyaline cartilage integrated with surrounding native tissues).Notably,the antler-stem-cell-derived ECM(xenogeneic)performed better than the aMSC-ECM(allogenic),while the ECM of the active antler stem cells was superior to that of the quiescent antler stem cells.CONCLUSION Decellularized xenogeneic ECM derived from the antler stem cell,particularly the active form(RMC-ECM),can achieve high quality repair/reconstruction of osteochondral defects,suggesting that selection of decellularized ECM for such repair should be focused more on bioactivity rather than kinship.

周期边界条件下四阶特征值问题的一种有效的Fourier谱逼近

文章提出了周期边界条件下四阶特征值问题的一种有效的Fourier谱逼近方法.首先,根据周期边界条件引入了适当的Sobolev空间和相应的逼近空间,建立了原问题的一种弱形式及其离散格式,并推导了等价的算子形式.其次,定义了正交投影算子,并证明了其逼近性质,结合紧算子的谱理论证明了逼近特征值的误差估计.另外,构造了逼近空间中的一组基函数,推导了离散格式基于张量积的矩阵形式.最后,文章给出了一些数值算例,数值结果表明其算法是有效的和谱精度的.

Fourier正则化同时反演热传导方程的初值和源项

研究边值问题中从已知的给定数据中同时识别初始条件和未知源的问题。用Fourier变换求出问题的精确解,发现该反问题是严重不适定的。为了解决所提出的问题,本文中用Fourier正则化方法构造出正则化解近似解,并在边界条件的假设下,得到先验参数选取下的精确解与其正则化近似解之间的对数型误差估计。

Neurocircuit regeneration by extracellular matrix reprogramming

The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.

Matrix Riccati Equations in Optimal Control

In this paper, the matrix Riccati equation is considered. There is no general way for solving the matrix Riccati equation despite the many fields to which it applies. While scalar Riccati equation has been studied thoroughly, matrix Riccati equation of which scalar Riccati equations is a particular case, is much less investigated. This article proposes a change of variable that allows to find explicit solution of the Matrix Riccati equation. We then apply this solution to Optimal Control.

Efficient Clustering Network Based on Matrix Factorization

Contrastive learning is a significant research direction in the field of deep learning.However,existing data augmentation methods often lead to issues such as semantic drift in generated views while the complexity of model pre-training limits further improvement in the performance of existing methods.To address these challenges,we propose the Efficient Clustering Network based on Matrix Factorization(ECN-MF).Specifically,we design a batched low-rank Singular Value Decomposition(SVD)algorithm for data augmentation to eliminate redundant information and uncover major patterns of variation and key information in the data.Additionally,we design a Mutual Information-Enhanced Clustering Module(MI-ECM)to accelerate the training process by leveraging a simple architecture to bring samples from the same cluster closer while pushing samples from other clusters apart.Extensive experiments on six datasets demonstrate that ECN-MF exhibits more effective performance compared to state-of-the-art algorithms.

Factors influencing Frey syndrome after parotidectomy with acellular dermal matrix

BACKGROUND Frey syndrome,also known as ototemporal nerve syndrome or gustatory sweating syndrome,is one of the most common complications of parotid gland surgery.This condition is characterized by abnormal sensations in the facial skin accompanied by episodes of flushing and sweating triggered by cognitive processes,visual stimuli,or eating.AIM To investigate the preventive effect of acellular dermal matrix(ADM)on Frey syndrome after parotid tumor resection and analyzed the effects of Frey syndrome across various surgical methods and other factors involved in parotid tumor resection.METHODS Retrospective data from 82 patients were analyzed to assess the correlation between sex,age,resection sample size,operation time,operation mode,ADM usage,and occurrence of postoperative Frey syndrome.RESULTS Among the 82 patients,the incidence of Frey syndrome was 56.1%.There were no significant differences in sex,age,or operation time between the two groups(P>0.05).However,there was a significant difference between ADM implantation and occurrence of Frey syndrome(P<0.05).ADM application could reduce the variation in the incidence of Frey syndrome across different operation modes.CONCLUSION ADM can effectively prevent Frey syndrome and delay its onset.

Biofabrication of nanocomposite-based scaffolds containing human bone extracellularmatrix for the differentiation of skeletal stem and progenitor cells

Autograft or metal implants are routinely used in skeletal repair.However,they fail to provide long-term clinical resolution,necessitating a functional biomimetic tissue engineering alternative.The use of native human bone tissue for synthesizing a biomimeticmaterial inkfor three-dimensional(3D)bioprintingof skeletal tissueis anattractivestrategyfor tissueregeneration.Thus,human bone extracellular matrix(bone-ECM)offers an exciting potential for the development of an appropriate microenvironment for human bone marrow stromal cells(HBMSCs)to proliferate and differentiate along the osteogenic lineage.In this study,we engineered a novel material ink(LAB)by blending human bone-ECM(B)with nanoclay(L,Laponite®)and alginate(A)polymers using extrusion-based deposition.The inclusion of the nanofiller and polymeric material increased the rheology,printability,and drug retention properties and,critically,the preservation of HBMSCs viability upon printing.The composite of human bone-ECM-based 3D constructs containing vascular endothelial growth factor(VEGF)enhanced vascularization after implantation in an ex vivo chick chorioallantoic membrane(CAM)model.The inclusion of bone morphogenetic protein-2(BMP-2)with the HBMSCs further enhanced vascularization and mineralization after only seven days.This study demonstrates the synergistic combination of nanoclay with biomimetic materials(alginate and bone-ECM)to support the formation of osteogenic tissue both in vitro and ex vivo and offers a promising novel 3D bioprinting approach to personalized skeletal tissue repair.

Reinforced tissue matrix to strengthen the abdominal wall following reversal of temporary ostomies or to treat incisional hernias

BACKGROUND Abdominal wall deficiencies or weakness are a common complication of tem-porary ostomies,and incisional hernias frequently develop after colostomy or ileostomy takedown.The use of synthetic meshes to reinforce the abdominal wall has reduced hernia occurrence.Biologic meshes have also been used to enhance healing,particularly in contaminated conditions.Reinforced tissue matrices(R-TMs),which include a biologic scaffold of native extracellular matrix and a syn-thetic component for added strength/durability,are designed to take advantage of aspects of both synthetic and biologic materials.To date,RTMs have not been reported to reinforce the abdominal wall following stoma reversal.METHODS Twenty-eight patients were selected with a parastomal and/or incisional hernia who had received a temporary ileostomy or colostomy for fecal diversion after rectal cancer treatment or trauma.Following hernia repair and proximal stoma closure,RTM(OviTex®1S permanent or OviTex®LPR)was placed to reinforce the abdominal wall using a laparoscopic,robotic,or open surgical approach.Post-operative follow-up was performed at 1 month and 1 year.Hernia recurrence was determined by physical examination and,when necessary,via computed tomo-graphy scan.Secondary endpoints included length of hospital stay,time to return to work,and hospital readmissions.Evaluated complications of the wound/repair site included presence of surgical site infection,seroma,hematoma,wound dehiscence,or fistula formation.RESULTS The observational study cohort included 16 male and 12 female patients with average age of 58.5 years±16.3 years and average body mass index of 26.2 kg/m^(2)±4.1 kg/m^(2).Patients presented with a parastomal hernia(75.0%),in-cisional hernia(14.3%),or combined parastomal/incisional hernia(10.7%).Using a laparoscopic(53.6%),robotic(35.7%),or open(10.7%)technique,RTMs(OviTex®LPR:82.1%,OviTex®1S:17.9%)were placed using sublay(82.1%)or intraperitoneal onlay(IPOM;17.9%)mesh positioning.At 1-month and 1-year follow-ups,there were no hernia recurrences(0%).Average hospital stays were 2.1 d±1.2 d and return to work occurred at 8.3 post-operative days±3.0 post-operative days.Three patients(10.7%)were readmitted before the 1-month follow up due to mesh infection and/or gastrointestinal issues.Fistula and mesh infection were observed in two patients each(7.1%),leading to partial mesh removal in one patient(3.6%).There were no complications between 1 month and 1 year(0%).CONCLUSION RTMs were used successfully to treat parastomal and incisional hernias at ileostomy reversal,with no hernia recurrences and favorable outcomes after 1-month and 1-year.

An approximate analytical model for unconventional reservoir considering variable matrix blocks and simultaneous matrix depletion

In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate production evaluations because of the absence of matrix-macrofracture communication.In addition,most of the existing models are solved analytically based on Laplace transform and numerical inversion.Hence,an approximate analytical solution is derived directly in real-time space considering variable matrix blocks and simultaneous matrix depletion.To simplify the derivation,the simultaneous matrix depletion is divided into two parts:one part feeding the macrofractures and the other part feeding the microfractures.Then,a series of partial differential equations(PDEs)describing the transient flow and boundary conditions are constructed and solved analytically by integration.Finally,a relationship between oil rate and production time in real-time space is obtained.The new model is verified against classical analytical models.When the microfracture system and matrix-macrofracture communication is neglected,the result of the new model agrees with those obtained with the dual-porosity and triple-porosity model,respectively.Certainly,the new model also has an excellent agreement with the numerical model.The model is then applied to two actual tight oil wells completed in western Canada sedimentary basin.After identifying the flow regime,the solution suitably matches the field production data,and the model parameters are determined.Through these output parameters,we can accurately forecast the production and even estimate the petrophysical properties.

Super-Fast Approximation Algorithms Using Classical Fourier Tools

In the author’s recent publications, a parametric system biorthogonal to the corresponding segment of the exponential Fourier system was unusually effective. On its basis, it was discovered that knowledge of a finite number of Fourier coefficients of function f from an infinite-dimensional set of elementary functions allows f to be accurately restored (the phenomenon of over-convergence). Below, parametric biorthogonal systems are constructed for classical trigonometric Fourier series, and the corresponding phenomena of over-convergence are discovered. The decisive role here was played by representing the space L2 as an orthogonal sum of two corresponding subspaces. As a result, fast parallel algorithms for reconstructing a function from its truncated trigonometric Fourier series are proposed. The presented numerical experiments confirm the high efficiency of these convergence accelerations for smooth functions. In conclusion, the main results of the work are summarized, and some prospects for the development and generalization of the proposed approaches are discussed.

Research and design of matrix operation accelerator based on reconfigurable array

In the case of massive data,matrix operations are very computationally intensive,and the memory limitation in standalone mode leads to the system inefficiencies.At the same time,it is difficult for matrix operations to achieve flexible switching between different requirements when implemented in hardware.To address this problem,this paper proposes a matrix operation accelerator based on reconfigurable arrays in the context of the application of recommender systems(RS).Based on the reconfigurable array processor(APR-16)with reconfiguration,a parallelized design of matrix operations on processing element(PE)array is realized with flexibility.The experimental results show that,compared with the proposed central processing unit(CPU)and graphics processing unit(GPU)hybrid implementation matrix multiplication framework,the energy efficiency ratio of the accelerator proposed in this paper is improved by about 35×.Compared with blocked alternating least squares(BALS),its the energy efficiency ratio has been accelerated by about 1×,and the switching of matrix factorization(MF)schemes suitable for different sparsity can be realized.

Enhanced Fourier Transform Using Wavelet Packet Decomposition

Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properties, it has limits. The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks. In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation. The choice of Daubechies level 4 was motivated by several reasons. Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization. By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal. Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal. The findings demonstrated that the suggested method offered a more accurate representation of non-stationary and transient signals in the frequency domain. Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.

Maillard reaction affecting immunobinding activity and digestibility of tropomyosin in Alectryonella plicatula food matrix

In recent years,the allergy rate of oysters has surged,and daily food processing methods make it hard to reduce heat resistance and digestive allergy such as tropomyosin(TM).In this study,the Maillard reaction with xylose significantly reduced the IgE binding capacity of Alectryonella plicatula food matrix(AFM),that reduced by(77.81±2.68)%.The study found the Maillard reaction changes the structure of the AFM,in which the content ofα-helix decreased by(24.64±1.46)%.Structural transformation further explains why the Maillard reaction alters the immunobinding activity of AFM.In addition,the Maillard reaction reduces the digestive stability of the AFM and makes TM in the A.plicatula food matrix Maillard reaction products(AFM-MRPs)more easily digested.Based on the above research,10 amino acids on the 7 IgE epitopes of TM were modified.This result indicates that the Maillard reaction reduces the immunobinding activity of the AFM by changing the structure and modifying the amino acids on the epitope.

基于Fourier拟合的光伏跟踪系统设计

[目的]为提高光伏支架的发电效率,以基于Fourier拟合算法的视日运动轨迹光伏跟踪器为研究设计对象。[方法]借助MATLAB分析了传统视日运动轨迹算法的跟踪精度情况,更进一步地在此基础上提出了精度更优的8阶傅里叶拟合视日运动轨迹跟踪算法,并结合GNSS定位技术,得出太阳实时运行轨迹。系统设计以STM32单片机作为微处理器,采用6轴加速度传感器,通过重力矢量在其轴上的投影确定光伏跟踪支架的实时倾斜度,以此二者建立跟踪支架三维运行模型,通过分析太阳光线在支架上的余弦效应即可得到电机需要运行的动作角。同时为解决晨昏时刻光伏组件间的阴影遮挡问题,系统增加逆跟踪算法。并考虑到大规模机组的应用,提出主从电机同步控制策略。[结果]傅-2里叶拟合算法拥有更高的跟踪精度,精度可达到10数量级,高于传统算法一个数量级。同时采用逆跟踪技术可节约24.3%光伏阵列用地面积,大幅提高了土地利用率。[结论]本研究采用更为精准的视日运动轨迹跟踪模型,较好地解决了太阳辐射利用的余弦效应,提升了电站的发电效率,实现了安全高效绿色能源体系的建设,促进了我国“双碳”目标的推进与达成。

A Deepfake Detection Algorithm Based on Fourier Transform of Biological Signal

Deepfake-generated fake faces,commonly utilized in identity-related activities such as political propaganda,celebrity impersonations,evidence forgery,and familiar fraud,pose new societal threats.Although current deepfake generators strive for high realism in visual effects,they do not replicate biometric signals indicative of cardiac activity.Addressing this gap,many researchers have developed detection methods focusing on biometric characteristics.These methods utilize classification networks to analyze both temporal and spectral domain features of the remote photoplethysmography(rPPG)signal,resulting in high detection accuracy.However,in the spectral analysis,existing approaches often only consider the power spectral density and neglect the amplitude spectrum—both crucial for assessing cardiac activity.We introduce a novel method that extracts rPPG signals from multiple regions of interest through remote photoplethysmography and processes them using Fast Fourier Transform(FFT).The resultant time-frequency domain signal samples are organized into matrices to create Matrix Visualization Heatmaps(MVHM),which are then utilized to train an image classification network.Additionally,we explored various combinations of time-frequency domain representations of rPPG signals and the impact of attention mechanisms.Our experimental results show that our algorithm achieves a remarkable detection accuracy of 99.22%in identifying fake videos,significantly outperforming mainstream algorithms and demonstrating the effectiveness of Fourier Transform and attention mechanisms in detecting fake faces.