High-frequency compensation for seismic data based on adaptive generalized S transform

The low-pass fi ltering eff ect of the Earth results in the absorption and attenuation of the high-frequency components of seismic signals by the stratum during propagation.Hence,seismic data have low resolution.Considering the limitations of traditional high-frequency compensation methods,this paper presents a new method based on adaptive generalized S transform.This method is based on the study of frequency spectrum attenuation law of seismic signals,and the Gauss window function of adaptive generalized S transform is used to fi t the attenuation trend of seismic signals to seek the optimal Gauss window function.The amplitude spectrum compensation function constructed using the optimal Gauss window function is used to modify the time-frequency spectrum of the adaptive generalized S transform of seismic signals and reconstruct seismic signals to compensate for high-frequency attenuation.Practical data processing results show that the method can compensate for the high-frequency components that are absorbed and attenuated by the stratum,thereby eff ectively improving the resolution and quality of seismic data.

Will high-frequency trading practices transform the financial markets in the Asia Pacific Region?

High-frequency trading(HFT)practices in the global financial markets involve the use of information and communication technologies(ICT),especially the capabilities of high-speed networks,rapid computation,and algorithmic detection of changing information and prices that create opportunities for computers to effect low-latency trades that can be accomplished in milliseconds.HFT practices exist because a variety of new technologies have made them possible,and because financial market infrastructure capabilities have also been changing so rapidly.The U.S.markets,such as the National Association for Securities Dealers Automated Quote(NASDAQ)market and the New York Stock Exchange(NYSE),have maintained relevance and centrality in financial intermediation in financial markets settings that have changed so much in the past 20 years that they are hardly recognizable.In this article,we explore the technological,institutional and market developments in leading financial markets around the world that have embraced HFT trading.From these examples,we will distill a number of common characteristics that seem to be in operation,and then assess the extent to which HFT practices have begun to be observed in Asian regional financial markets,and what will be their likely impacts.We also discuss a number of theoretical and empirical research directions of interest.

ViTAU:基于Vision transformer和面部动作单元的面瘫识别与分析

面部神经麻痹(Facial nerve paralysis,FNP),通常称为贝尔氏麻痹或面瘫,对患者的日常生活和心理健康产生显著影响,面瘫的及时识别和诊断对于患者的早期治疗和康复至关重要.随着深度学习和计算机视觉技术的快速发展,面瘫的自动识别变得可行,为诊断提供了一种更准确和客观的方式.目前的研究主要集中关注面部的整体变化,而忽略了面部细节的重要性.面部不同部位对识别结果的影响力并不相同,这些研究尚未对面部各个区域进行细致区分和分析.本项研究引入结合Vision transformer(ViT)模型和动作单元(Action unit,AU)区域检测网络的创新性方法用于面瘫的自动识别及区域分析.ViT模型通过自注意力机制精准识别是否面瘫,同时,基于AU的策略从StyleGAN2模型提取的特征图中,利用金字塔卷积神经网络分析受影响区域.这一综合方法在YouTube Facial Palsy(YFP)和经过扩展的Cohn Kanade(CK+)数据集上的实验中分别达到99.4%的面瘫识别准确率和81.36%的面瘫区域识别准确率.通过与最新方法的对比,实验结果展示了所提的自动面瘫识别方法的有效性.

Kinematic deformation and intensity assessment of the 2021 Maduo M_(S)7.4 earthquake in Qinghai revealed by high-frequency GNSS

Rapid acquisition of the kinematic deformation field and seismic intensity distribution of large earthquakes is crucial for postseismic emergency rescue,disaster assessment,and future seismic risk research.The advancement of GNSS observation and data processing makes it play an important role in this field,especially the high-frequency GNSS.We used the differential positioning method to calculate the 1 HZ GNSS data from 98 sites within 1000 km of the M_(S)7.4 Maduo earthquake epicenter.The kinematic deformation field and the distribution of the seismic intensity by using the peak ground velocity derived from displacement waveforms were obtained.The results show that:1)Horizontal coseismic response deformation levels ranging from 25 mm to 301 mm can be observed within a 1000 km radius from the epicenter.Coseismic response deformation on the east and west sides shows bilateral asymmetry,which markedly differs from the symmetry presented by surface rupture.2)The seismic intensity obtained through high-frequency GNSS and field investigations exhibits good consistency of the scope and orientation in the high seismic intensity area,although the former is generally slightly smaller than the latter.3)There may exist obstacles on the eastern side of the seismogenic fault.The Maduo earthquake induced a certain tectonic stress loading effect on the western Kunlun Pass-Jiangcuo fault(KPJF)and Maqin-Maqu segment,resulting in higher seismic risk in the future.

The relationship between the high-frequency performance of supercapacitors and the type of doped nitrogen in the carbon electrode

Nitrogen doping has been widely used to improve the performance of carbon electrodes in supercapacitors,particularly in terms of their high-frequency response.However,the charge storage and electrolyte ion response mechanisms of different nitrogen dopants at high frequencies are still unclear.In this study,melamine foam carbons with different configurations of surfacedoped N were formed by gradient carbonization,and the effects of the configurations on the high-frequency response behavior of the supercapacitors were analyzed.Using a combination of experiments and first-principle calculations,we found that pyrrolic N,characterized by a higher adsorption energy,increases the charge storage capacity of the electrode at high frequencies.On the other hand,graphitic N,with a lower adsorption energy,increases the speed of ion response.We propose the use of adsorption energy as a practical descriptor for electrode/electrolyte design in high-frequency applications,offering a more universal approach for improving the performance of N-doped carbon materials in supercapacitors.

Dynamic Response of Foundations during Startup of High-Frequency Tunnel Equipment

The specialized equipment utilized in long-line tunnel engineering is evolving towards large-scale,multifunctional,and complex orientations.The vibration caused by the high-frequency units during regular operation is supported by the foundation of the units,and the magnitude of vibration and the operating frequency fluctuate in different engineering contexts,leading to variations in the dynamic response of the foundation.The high-frequency units yield significantly diverse outcomes under different startup conditions and times,resulting in failure to meet operational requirements,influencing the normal function of the tunnel,and causing harm to the foundation structure,personnel,and property in severe cases.This article formulates a finite element numerical computation model for solid elements using three-dimensional elastic body theory and integrates field measurements to substantiate and ascertain the crucial parameter configurations of the finite element model.By proposing a comprehensive startup timing function for high-frequency dynamic machines under different startup conditions,simulating the frequency andmagnitude variations during the startup process,and suggesting functions for changes in frequency and magnitude,a simulated startup schedule function for high-frequency machines is created through coupling.Taking into account the selection of the transient dynamic analysis step length,the dynamic response results for the lower dynamic foundation during its fundamental frequency crossing process are obtained.The validation checks if the structural magnitude surpasses the safety threshold during the critical phase of unit startup traversing the structural resonance region.The design recommendations for high-frequency units’dynamic foundations are provided,taking into account the startup process of the machine and ensuring the safe operation of the tunnel.

基于贝叶斯图注意力Transformer的航空发动机剩余使用寿命概率预测

航空发动机作为飞机的心脏,其健康状态对飞机的安全飞行至关重要.深度学习强大的数据挖掘能力,为通过海量历史数据预测航空发动机的剩余使用寿命提供了新方法.然而,传统基于深度学习的方法大都关注于挖掘数据在时间上的关联,而忽略了多个传感器监测数据之间复杂的非欧氏空间关系.此外,少有研究考虑数据或者预测过程本身具有的不确定性,缺乏对预测结果可靠性的评估.为解决上述问题,本文提出了一种基于贝叶斯网络和图注意力Transformer的航空发动机剩余使用寿命概率预测方法.将图注意力机制融入Transformer的时间多头注意力模块,结合图注意力网络在空间特征提取上的优势和Transformer模型在时间特征提取的优势,实现数据特征时空关系的联合提取.同时,利用改进的贝叶斯网络度量预测不确定性,在得到剩余使用寿命预测点值的同时给出相应的置信区间.最后,通过在公开航空发动机数据集上的实验,证明了所提模型的有效性和先进性.

Review of the Analysis and Suppression for High-frequency Oscillations of the Grid-connected Wind Power Generation System

High-frequency oscillation(HFO)of gridconnected wind power generation systems(WPGS)is one of the most critical issues in recent years that threaten the safe access of WPGS to the grid.Ensuring the WPGS can damp HFO is becoming more and more vital for the development of wind power.The HFO phenomenon of wind turbines under different scenarios usually has different mechanisms.Hence,engineers need to acquire the working mechanisms of the different HFO damping technologies and select the appropriate one to ensure the effective implementation of oscillation damping in practical engineering.This paper introduces the general assumptions of WPGS when analyzing HFO,systematically summarizes the reasons for the occurrence of HFO in different scenarios,deeply analyses the key points and difficulties of HFO damping under different scenarios,and then compares the technical performances of various types of HFO suppression methods to provide adequate references for engineers in the application of technology.Finally,this paper discusses possible future research difficulties in the problem of HFO,as well as the possible future trends in the demand for HFO damping.

Efficient activation of the Co/SBA-15catalyst by high-frequency AC-DBD plasma thermal effects for toluene removal

Dielectric barrier discharge(DBD)plasma excited by a high-frequency alternating-current(AC)power supply is widely employed for the degradation of volatile organic compounds(VOCs).However,the thermal effect generated during the discharge process leads to energy waste and low energy utilization efficiency.In this work,an innovative DBD thermally-conducted catalysis(DBD-TCC)system,integrating high-frequency AC-DBD plasma and its generated thermal effects to activate the Co/SBA-15 catalyst,was employed for toluene removal.Specifically,Co/SBA-15 catalysts are closely positioned to the ground electrode of the plasma zone and can be heated and activated by the thermal effect when the voltage exceeds 10 k V.At12.4 k V,the temperature in the catalyst zone reached 261℃ in the DBD-TCC system,resulting in an increase in toluene degradation efficiency of 17%,CO_(2)selectivity of 21.2%,and energy efficiency of 27%,respectively,compared to the DBD system alone.In contrast,the DBD thermally-unconducted catalysis(DBD-TUC)system fails to enhance toluene degradation due to insufficient heat absorption and catalytic activation,highlighting the crucial role of AC-DBD generated heat in the activation of the catalyst.Furthermore,the degradation pathway and mechanism of toluene in the DBD-TCC system were hypothesized.This work is expected to provide an energy-efficient approach for high-frequency AC-DBD plasma removal of VOCs.

Effects of unilateral superimposed high-frequency jet ventilation on porcine hemodynamics and gas exchange during one-lung flooding

BACKGROUND Superimposed high-frequency jet ventilation(SHFJV)is suitable for respiratory motion reduction and essential for effective lung tumor ablation.Fluid filling of the target lung wing one-lung flooding(OLF)is necessary for therapeutic ultrasound applications.However,whether unilateral SHFJV allows adequate hemodynamics and gas exchange is unclear.AIM To compared SHFJV with pressure-controlled ventilation(PCV)during OLF by assessing hemodynamics and gas exchange in different animal positions.METHODS SHFJV or PCV was used alternatingly to ventilate the non-flooded lungs of the 12 anesthetized pigs during OLF.The animal positions were changed from left lateral position to supine position(SP)to right lateral position(RLP)every 30 min.In each position,ventilation was maintained for 15 min in both modalities.Hemodynamic variables and arterial blood gas levels were repeatedly measured.RESULTS Unilateral SHFJV led to lower carbon dioxide removal than PCV without abnormally elevated carbon dioxide levels.SHFJV slightly decreased oxygenation in SP and RLP compared with PCV;the lowest values of PaO_(2) and PaO_(2)/FiO_(2) ratio were found in SP[13.0;interquartile range(IQR):12.6-5.6 and 32.5(IQR:31.5-38.9)kPa].Conversely,during SHFJV,the shunt fraction was higher in all animal positions(highest in the RLP:0.30).CONCLUSION In porcine model,unilateral SHFJV may provide adequate ventilation in different animal positions during OLF.Lower oxygenation and CO_(2) removal rates compared to PCV did not lead to hypoxia or hypercapnia.SHFJV can be safely used for lung tumor ablation to minimize ventilation-induced lung motion.

Therapeutic efficacy of methylprednisolone sodium succinate via diverse administration routes for mid-to high-frequency sudden sensorineural hearing loss

BACKGROUND Sudden sensorineural hearing loss(SSNHL),characterized by a rapid and unexplained loss of hearing,particularly at moderate to high frequencies,presents a significant clinical challenge.The therapeutic use of methylprednisolone sodium succinate(MPSS)via different administration routes,in combination with conventional medications,remains a topic of interest.AIM To compare the therapeutic efficacy of MPSS administered via different routes in combination with conventional drugs for the treatment of mid-to high-frequency SSNHL.METHODS The medical records of 109 patients with mid-to high-frequency SSNHL were analyzed.The patients were divided into three groups based on the route of administration:Group A[intratympanic(IT)injection of MPSS combined with mecobalamin and Ginkgo biloba leaf extract injection],Group B(intravenous injection of MPSS combined with mecobalamin and Ginkgo biloba leaf extract injection),and Group C(single IT injection of MPSS).The intervention effects were compared and analyzed.RESULTS The posttreatment auditory thresholds in Group A(21.23±3.34)were significantly lower than those in Groups B(28.52±3.36)and C(30.23±4.21;P<0.05).Group A also exhibited a significantly greater speech recognition rate(92.23±5.34)than Groups B and C.The disappearance time of tinnitus,time to hearing recovery,and disappearance time of vertigo in Group A were significantly shorter than those in Groups B and C(P<0.05).The total effective rate in Group A(97.56%)was significantly greater than that in Groups B and C(77.14%and 78.79%,χ^(2)=7.898,P=0.019).Moreover,the incidence of adverse reactions in Groups A and C was significantly lower than that in Group B(4.88%,3.03%vs 2.57%,χ^(2)=11.443,P=0.003),and the recurrence rate in Group A was significantly lower than that in Groups B and C(2.44%vs 20.00%vs 21.21%,χ^(2)=7.120,P=0.028).CONCLUSION IT injection of MPSS combined with conventional treatment demonstrates superior efficacy and safety compared to systemic administration via intravenous infusion and a single IT injection of MPSS.This approach effectively improves patients'hearing and reduces the risk of disease recurrence.

Stage IV malignant transformation of mature cystic teratoma palliatively treated with concurrent chemoradiotherapy:A case report

BACKGROUND Malignant transformation(MT)of mature cystic teratoma(MCT)has a poor prognosis,especially in advanced cases.Concurrent chemoradiotherapy(CCRT)has an inhibitory effect on MT.CASE SUMMARY Herein,we present a case in which CCRT had a reduction effect preoperatively.A 73-year-old woman with pyelonephritis was referred to our hospital.Computed tomography revealed right hydronephrosis and a 6-cm pelvic mass.Endoscopic ultrasound-guided fine-needle biopsy(EUS-FNB)revealed squamous cell carci-noma.The patient was diagnosed with MT of MCT.Due to her poor general con-dition and renal malfunction,we selected CCRT,expecting fewer adverse effects.After CCRT,her performance status improved,and the tumor size was reduced;surgery was performed.Five months postoperatively,the patient developed dis-semination and lymph node metastases.Palliative chemotherapy was ineffective.She died 18 months after treatment initiation.CONCLUSION EUS-FNB was useful in the diagnosis of MT of MCT;CCRT suppressed the disea-se and improved quality of life.

Transforming growth factor-beta 1 enhances discharge activity of cortical neurons

Transforming growth factor-beta 1(TGF-β1)has been extensively studied for its pleiotropic effects on central nervous system diseases.The neuroprotective or neurotoxic effects of TGF-β1 in specific brain areas may depend on the pathological process and cell types involved.Voltage-gated sodium channels(VGSCs)are essential ion channels for the generation of action potentials in neurons,and are involved in various neuroexcitation-related diseases.However,the effects of TGF-β1 on the functional properties of VGSCs and firing properties in cortical neurons remain unclear.In this study,we investigated the effects of TGF-β1 on VGSC function and firing properties in primary cortical neurons from mice.We found that TGF-β1 increased VGSC current density in a dose-and time-dependent manner,which was attributable to the upregulation of Nav1.3 expression.Increased VGSC current density and Nav1.3 expression were significantly abolished by preincubation with inhibitors of mitogen-activated protein kinase kinase(PD98059),p38 mitogen-activated protein kinase(SB203580),and Jun NH2-terminal kinase 1/2 inhibitor(SP600125).Interestingly,TGF-β1 significantly increased the firing threshold of action potentials but did not change their firing rate in cortical neurons.These findings suggest that TGF-β1 can increase Nav1.3 expression through activation of the ERK1/2-JNK-MAPK pathway,which leads to a decrease in the firing threshold of action potentials in cortical neurons under pathological conditions.Thus,this contributes to the occurrence and progression of neuroexcitatory-related diseases of the central nervous system.

基于Depth-wise卷积和视觉Transformer的图像分类模型

图像分类作为一种常见的视觉识别任务,有着广阔的应用场景。在处理图像分类问题时,传统的方法通常使用卷积神经网络,然而,卷积网络的感受野有限,难以建模图像的全局关系表示,导致分类精度低,难以处理复杂多样的图像数据。为了对全局关系进行建模,一些研究者将Transformer应用于图像分类任务,但为了满足Transformer的序列化和并行化要求,需要将图像分割成大小相等、互不重叠的图像块,破坏了相邻图像数据块之间的局部信息。此外,由于Transformer具有较少的先验知识,模型往往需要在大规模数据集上进行预训练,因此计算复杂度较高。为了同时建模图像相邻块之间的局部信息并充分利用图像的全局信息,提出了一种基于Depth-wise卷积的视觉Transformer(Efficient Pyramid Vision Transformer,EPVT)模型。EPVT模型可以实现以较低的计算成本提取相邻图像块之间的局部和全局信息。EPVT模型主要包含3个关键组件:局部感知模块(Local Perceptron Module,LPM)、空间信息融合模块(Spatial Information Fusion,SIF)和“+卷积前馈神经网络(Convolution Feed-forward Network,CFFN)。LPM模块用于捕获图像的局部相关性;SIF模块用于融合相邻图像块之间的局部信息,并利用不同图像块之间的远距离依赖关系,提升模型的特征表达能力,使模型学习到输出特征在不同维度下的语义信息;CFFN模块用于编码位置信息和重塑张量。在图像分类数据集ImageNet-1K上,所提模型优于现有的同等规模的视觉Transformer分类模型,取得了82.6%的分类准确度,证明了该模型在大规模数据集上具有竞争力。

CNN-Transformer特征融合多目标跟踪算法

在卷积神经网络(CNN)中,卷积运算能高效地提取目标的局部特征,却难以捕获全局表示;而在视觉Transformer中,注意力机制可以捕获长距离的特征依赖,但会忽略局部特征细节。针对以上问题,提出一种基于CNN-Transformer双分支主干网络进行特征提取和融合的多目标跟踪算法CTMOT(CNN-transformer multi-object tracking)。使用基于CNN和Transformer双分支并行的主干网络分别提取图像的局部和全局特征。使用双向桥接模块(two-way braidge module,TBM)对两种特征进行充分融合。将融合后的特征输入两组并行的解码器进行处理。将解码器输出的检测框和跟踪框进行匹配,完成多目标跟踪任务。在多目标跟踪数据集MOT17、MOT20、KITTI以及UADETRAC上进行评估,CTMOT算法的MOTP和IDs指标在四个数据集上均达到了SOTA效果,MOTA指标分别达到了76.4%、66.3%、92.36%和88.57%,在MOT数据集上与SOTA方法效果相当,在KITTI数据集上达到SOTA效果。由于同时完成目标检测和关联,能够端到端进行目标跟踪,跟踪速度可达35 FPS,表明CTMOT算法在跟踪的实时性和准确性上达到了较好的平衡,具有较大潜力。

基于RoBERTa和图增强Transformer的序列推荐方法

自推荐系统出现以来,有限的数据信息就一直制约着推荐算法的进一步发展。为降低数据稀疏性的影响,增强非评分数据的利用率,基于神经网络的文本推荐模型相继被提出,但主流的卷积或循环神经网络在文本语义理解和长距离关系捕捉方面存在明显劣势。为了更好地挖掘用户与商品之间的深层潜在特征,进一步提高推荐质量,提出一种基于Ro BERTa和图增强Transformer的序列推荐(RGT)模型。引入评论文本数据,首先利用预训练的Ro BERTa模型捕获评论文本中的字词语义特征,初步建模用户的个性化兴趣,然后根据用户与商品的历史交互信息,构建具有时序特性的商品关联图注意力机制网络模型,通过图增强Transformer的方法将图模型学习到的各个商品的特征表示以序列的形式输入Transformer编码层,最后将得到的输出向量与之前捕获的语义表征以及计算得到的商品关联图的全图表征输入全连接层,以捕获用户全局的兴趣偏好,实现用户对商品的预测评分。在3组真实亚马逊公开数据集上的实验结果表明,与Deep FM、Conv MF等经典文本推荐模型相比,RGT模型在均方根误差(RMSE)和平均绝对误差(MAE)2种指标上有显著提升,相较于最优对比模型最高分别提升4.7%和5.3%。

基于Transformer和自适应特征融合的矿井低照度图像亮度提升和细节增强方法

高质量矿井影像为矿山安全生产提供保障,也有利于提高后续图像分析技术的性能。矿井影像受低照度环境的影响,易出现亮度低,照度不均,颜色失真,细节信息丢失严重等问题。针对上述问题,提出一种基于Transformer和自适应特征融合的矿井低照度图像亮度提升和细节增强方法。基于生成对抗思想搭建生成对抗式主体模型框架,使用目标图像域而非单一参考图像驱动判别器监督生成器的训练,实现对低照度图像的充分增强;基于特征表示学习理论搭建特征编码器,将图像解耦为亮度分量和反射分量,避免图像增强过程中亮度与颜色特征相互影响从而导致颜色失真问题;设计CEM-Transformer Encoder通过捕获全局上下文关系和提取局部区域特征,能够充分提升整体图像亮度并消除局部区域照度不均;在反射分量增强过程中,使用结合CEM-Cross-Transformer Encoder的跳跃连接将低级特征与深层网络处特征进行自适应融合,能够有效避免细节特征丢失,并在编码网络中添加ECA-Net,提高浅层网络的特征提取效率。制作矿井低照度图像数据集为矿井低照度图像增强任务提供数据资源。试验显示,在矿井低照度图像数据集和公共数据集中,与5种先进的低照度图像增强算法相比,该算法增强图像的质量指标PSNR、SSIM、VIF平均提高了16.564%,10.998%,16.226%和14.438%,10.888%,14.948%,证明该算法能够有效提升整体图像亮度,消除照度不均,避免颜色失真和细节丢失,实现矿井低照度图像增强。

Magnetic flux leakage analysis and compensation of high-frequency planar insulated core transformer

A novel high-frequency and high power density planar insulated core transformer(PICT) applied to high voltage DC generator is introduced. PICT's operating principle and fundamental configuration are described,and preliminary experimental results in self-designed PICT apparatus are presented. Emphatically, magnetic leakage flux(MFL) giving rise to the output voltage drop is analyzed in detail both theoretically and by finite element method(FEM). Showing good consistency with experimental result, FEM simulation is considered to be practicable in physical design of PICT. To cancel out leakage inductance and improve the voltage uniformity,compensation capacitor is adopted and experimental verification is also presented. All shows satisfactory results.

基于残差U-Net和自注意力Transformer编码器的磁场预测方法

利用有限元方法对几何结构复杂的电机和变压器进行磁场分析,存在仿真时间长且无法复用的问题。因此,该文提出一种基于残差U-Net和自注意力Transformer编码器的磁场预测方法。首先建立永磁同步电机(PMSM)和非晶合金变压器(AMT)有限元模型,得到深度学习训练所需的数据集;然后将Transformer模块与U-Net模型结合,并引入短残差机制建立ResUnet-Transformer模型,通过预测图像的像素实现磁场预测;最后通过Targeted Dropout算法和动态学习率调整策略对模型进行优化,解决拟合问题并提高预测精度。计算实例证明,ResUnet-Transformer模型在PMSM和AMT数据集上测试集的平均绝对百分比误差(MAPE)均小于1%,且仅需500组样本。该文提出的磁场预测方法能减少实际工况和多工况下精细模拟和拓扑优化的时间和资源消耗,亦是虚拟传感器乃至数字孪生的关键实现方法之一。

融合卷积注意力和Transformer架构的行人重识别方法

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