Clinical observation of electroacupuncture"Tongmin Point"combined with heat-sensitive moxibustion on knee osteoarthritis and its influence on blood lipid level and ADAMTS-4

Objective:To observe the clinical effect of electroacupuncture"Tongmin point"combined with heat-sensitive moxibustion on knee osteoarthritis and its effect on blood lipid level,polyprotein polysaccharide enzyme-4(a disintegrin and metalloprotease with thrombospondin motifs,ADAMTS-4,matrix metalloproteinase-3(matrix metalloproteinase-3,);and MMPs-3)Impact.Methods:80 patients were randomly divided into two groups,40 cases per group,Treatment and control groups,The treatment group was given electroacupuncture combined with heat-sensitive moxibustion,Six times a week,Continuous treatment for 4 weeks;The control group was given intraarticular sodium hyaluronate,Once a week,continuous treatment for 4 weeks.Results:During the treatment period,Visual analogue scale visual analogue scale,VAS)show a downward trend,Intra-group comparisons,Differences were statistically significant(P<0.05);After 2 weeks of treatment,4 weeks of treatment and 2 weeks of follow-up,All the scores in the treatment group were lower than those in the control group(P<0.05).After treatment in two groups(The Western Ontario and Mc Master Universities Osteoarthritis Index,)of osteoarthritis index,University of Western Ontario WOMAC)The scores of each item decreased significantly,treatment group was better than the control group(P<0.05).After four weeks of treatment,(Total cholesterol,)Total cholesterol TC,triglycerides(Triglyceride,);and TG,LDL(Low density lipoprotein,);and LDL-C)A decrease in content,High density lipoprotein High density lipoprotein,HDL-C)Increased content,and the improvement was better than that of the control group(P<0.05).After treatment,the ADAMTS-4,MMPs-3 content decreased,Intergroup comparisons,Differences were statistically significant(P<0.05);The effective rate in the treatment group was 87.5%,The control rate was 60%,treatment group was more effective(P<0.05).Conclusions:Electroacupuncture"Tongmin point"combined with heat-sensitive moxibustion can obviously improve the symptoms of knee osteoarthritis patients,Regulate blood lipids,High security,It is worth popularizing in clinic.

基于轻量化PointNet网络的林果园喷雾作业靶标实时识别方法

为了进一步提高喷雾机器人靶标检测的精准性、实时性和应用部署的实用性,该研究提出一种基于轻量化PointNet网络的林果园喷雾作业靶标实时识别方法。首先通过区域提取降采样、地面分割和改进DBSCAN聚类等点云预处理方法提取原始点云中的靶标;然后通过移动最小二乘上采样将靶标点云转化为满足点云识别网络输入要求的点云数据;最终通过在PointNet网络中引入残差模块和改进循环剪枝算法轻量化PointNet网络,完成林果树靶标的实时识别。试验结果表明,在ModelNet40数据集上,轻量化PointNet网络可达89.7%的准确率;在实际苗圃环境的试验中,该研究方法对靶标的识别准确率可达92.49%,同时误识率与拒识率分别为13.4%和6.47%,相较PointNet网络识别准确率提升了4.38个百分点,误识率和拒识率分别降低了7.2和4.07个百分点;轻量化PointNet网络识别准确率仅比PointNet++网络低1.14个百分点,误识率和拒识率分别高了0.9和1.12个百分点。但是轻量化PointNet网络的模型参数量较PointNet网络和PointNet++网络的模型参数量显著减少,仅为PointNet网络的11.5%,PointNet++网络的27.02%;运算量相较PointNet网络、PointNet++网络分别减少13.3和76.79个百分点。该研究提出的轻量化PointNet网络具有较高的实时性、精确性和鲁棒性,能够满足林果园喷雾作业的靶标识别需求,可为林果园喷雾作业靶标实时识别提供参考。

Heat-sensitive moxibustion attenuates the inflammation after focal cerebral ischemia/ reperfusion injury

Heat-sensitive moxibustion has neuroprotective effects against focal cerebral ischemia/reperfusion injury, however its mechanism of action remains unclear. In this study, rat models of focal cerebral ischemia/reperfusion injury were treated with suspended moxibustion at acupoint Dazhui （DU14） for 35 minutes. Results showed that suspended moxibustion decreased infarct volume, reduced cortical myeloperoxidase activity, and suppressed serum levels of proinflammatory cytokines in rats with focal cerebral ischemia/reperfusion injury. Our experimental findings indicated that heat-sensitive moxibustion can attenuate inflammation and promote repair after focal cerebral ischemia/reperfusion injury.

Thermal Effect of a Revolving Gaussian Beam on Activating Heat-Sensitive Nociceptors in Skin

We consider the problem of inducing withdrawal reflex on a test subject by exposing the subject’s skin to an electromagnetic beam. Heat-sensitive nociceptors in the skin are activated wherever the temperature is above the activation temperature. Withdrawal reflex occurs when the activated volume reaches a threshold. Previously we studied static beams with 3 types of power density distribution: Gaussian, super-Gaussian, and flat-top. We found that the flaptop is the best and the Gaussian is the worst in their performance with regard to 1) minimizing the time to withdrawal reflex, 2) minimizing the energy consumption and 3) minimizing the maximum temperature increase. The less-than-desirable performance of Gaussian beams is attributed to the uneven distribution of power density resulting in low energy efficiency: near the beam center the high power density does not contribute proportionally to increasing the activated volume;outside the beam effective radius the low power density fails to activate nociceptors. To overcome the drawbacks of Gaussian beams, in this study, we revolve a Gaussian beam around a fixed point to make the power density more uniformly distributed. We optimize the performance over two parameters: the spot size of static beam and the radius of beam revolution. We find that in comparison with a static Gaussian beam, a revolving Gaussian beam can reduce the energy consumption, and at the same time lower the maximum temperature.

基于PointNet++的邻域特征增强点云语义分割方法

随着智能驾驶、机器人导航等以点云为基础的应用蓬勃发展,点云语义分割逐渐成为研究热点。然而,现有的点云语义分割方法存在局部特征提取不充分、特征融合不完整的缺陷。针对这些不足,提出了对应的解决方案。对于局部特征提取不充分的现象,通过嵌入邻域点的坐标、方向、距离等相关信息去关联邻域点的显式特征。对于特征融合不完整的现象,提出了一种最大池化与自注意力池化相结合的混合池化方法。网络架构基于PointNet++,并结合提出的局部特征提取和融合方法,在S3DIS数据集上的实验结果表明,与基线方法PointNet++相比,各评价指标都有不同程度的提高,证实了新方法的有效性和优越性。

基于Point Transformer v2的点云枝叶分离方法研究

准确高效的点云枝叶分离对精确计算森林树木的垂直参数至关重要。然而,当前的研究方法计算成本高,且依赖先验知识导致泛化能力不足。针对以上问题,文章提出利用基于点特征的Transformer网络进行自动化的森林场景三维点云的枝叶分离研究。该方法使用Point Transformer v2网络,首先利用网格编码模块提取可学习的局部结构关系,保留点云的几何拓扑结构;其次使用分组注意力实现多通道联合学习,降低特征的冗余度,提高计算的效率;最后构建了基于点的Transformer网络实现高精度森林树木三维点云语义分割,降低了对于先验知识的需求。使用地基激光扫描仪获取的加拿大和芬兰7个不同树种样地的三维点云数据,进行枝叶分离实验和精度评价。实验结果表明,网络整体精度(OA)为94.42%,mIoU为78.89%,能够适应不同树种、不同点云密度的森林场景的枝叶分离。

Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://github.com/yahuiliu99/PointC onT.

Material point method simulation of hydro-mechanical behaviour in twophase porous geomaterials: A state-of-the-art review

The material point method(MPM)has been gaining increasing popularity as an appropriate approach to the solution of coupled hydro-mechanical problems involving large deformation.In this paper,we survey the current state-of-the-art in the MPM simulation of hydro-mechanical behaviour in two-phase porous geomaterials.The review covers the recent advances and developments in the MPM and their extensions to capture the coupled hydro-mechanical problems involving large deformations.The focus of this review is aiming at providing a clear picture of what has or has not been developed or implemented for simulating two-phase coupled large deformation problems,which will provide some direct reference for both practitioners and researchers.

Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

Automatic Extraction Method of 3D Feature Guidelines for Complex Cultural Relic Surfaces Based on Point Cloud

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation,which is a simple and intuitive product with low cost of displaying compared with 3D models.Dimensionality reduction is undoubtedly necessary for line drawings.However,most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex.Therefore,conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection.Based on the given criteria for assessing surface complexity,this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces.A 2D and 3D combined factor that measured the importance of points on describing surface features,vertex weight,was designed.Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions.The feasibility and stability were verified through experiments conducted on real cultural relic surface data.Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces.The extraction method and the obtained results will be useful for line graphic drawing,displaying and propaganda of cultural relics.

基于改进PointNet++的输电线路关键部位点云语义分割研究

输电线路的关键部位包括塔身、导线、绝缘子、避雷线以及引流线,无人机精细化导航的首要任务是构造输电线路的点云地图并从中分割出上述部位。为解决现有算法在输电线路的绝缘子、引流线等精细结构分割时精度低的问题,通过改进PointNet++算法,提出了一种面向输电线路精细结构的点云分割方法。首先,基于无人机机载激光雷达在现场采集的点云数据,构造了输电线路点云分割数据集;其次,通过对比实验,筛选出在本输电线路场景下合理的数据增强方法,并对数据集进行了数据增强;最后,将自注意力机制以及倒置残差结构和PointNet++相结合,设计了输电线路关键部位点云语义分割算法。实验结果表明:该改进PointNet++算法在全场景输电线路现场点云数据作为输入的前提下,首次实现了对引流线、绝缘子等输电线路中精细结构和导线、杆塔塔身以及输电线路无关背景点的同时分割,平均交并比(mean intersection over union,mIoU)达80.79%,所有类别分割的平均F_(1)值(F1 score)达88.99%。

Coexistence of Dirac and Weyl points in non-centrosymmetric semimetal NbIrTe_(4)

Using angle-resolved photoemission spectroscopy and density functional theory calculations methods,we investigate the electronic structures and topological properties of ternary tellurides NbIrTe_(4),a candidate for type-II Weyl semimetal.We demonstrate the presence of several Fermi arcs connecting their corresponding Weyl points on both termination surfaces of the topological material.Our analysis reveals the existence of Dirac points,in addition to Weyl points,giving both theoretical and experimental evidences of the coexistence of Dirac and Weyl points in a single material.These findings not only confirm NbIrTe_(4) as a unique topological semimetal but also open avenues for exploring novel electronic devices based on its coexisting Dirac and Weyl fermions.

PCT和PointMLP融合的三维点云分类算法研究

为了提高三维点云数据的分类准确率,对注意力机制的PCT与残差点MLP的PointMLP的融合算法进行研究。首先,加入几何仿射模块对输入点云进行正态分布以解决点云的密度不均匀和几何结构不确定性;其次,在编码模块首先使用注意力机制对上层特征进行全局表达,之后加入残差点MLP模块对注意力模块的输出特征进行深度特征表示以充分提取点云特征;最后是分类模块,完成下游点云分类任务。实验结果表明,改进后的算法在ModelNet40数据集上的分类准确率达到95.6%,相比PCT模型准确率提高了2.4%,且对点云数量的变化具有鲁棒性。

基于知识蒸馏和定位引导的Pointpillars点云检测网络

激光雷达数据由于其几何特性,被广泛应用于三维目标检测任务中。由于点云数据的稀疏性和不规则性,难以实现特征提取的质量和推理速度间的平衡。本文提出一种基于体柱特征编码的三维目标检测算法,以Pointpillars网络为基础,设计Teacher-Student模型框架对回归框尺度进行蒸馏,增加蒸馏损失,优化训练网络模型,提升特征提取的质量。为进一步提高模型检测效果,设计定位引导分类项,增加分类预测和回归预测之间的相关性,提高物体识别准确率。本网络所做改进没有引入额外的网络嵌入。算法在KITTI数据集上的实验结果表明,相比于基准网络,在三维模式下的平均精度值从60.65%提升到了64.69%,鸟瞰图模式下的平均精度值从67.74%提升到70.24%。模型推理速度为45 FPS,在提升检测精度的同时满足了实时性要求。

Enhanced Mechanism for Link Failure Rerouting in Software-Defined Exchange Point Networks

Internet Exchange Point(IXP)is a system that increases network bandwidth performance.Internet exchange points facilitate interconnection among network providers,including Internet Service Providers(ISPs)andContent Delivery Providers(CDNs).To improve service management,Internet exchange point providers have adopted the Software Defined Network(SDN)paradigm.This implementation is known as a Software-Defined Exchange Point(SDX).It improves network providers’operations and management.However,performance issues still exist,particularly with multi-hop topologies.These issues include switch memory costs,packet processing latency,and link failure recovery delays.The paper proposes Enhanced Link Failure Rerouting(ELFR),an improved mechanism for rerouting link failures in software-defined exchange point networks.The proposed mechanism aims to minimize packet processing time for fast link failure recovery and enhance path calculation efficiency while reducing switch storage overhead by exploiting the Programming Protocol-independent Packet Processors(P4)features.The paper presents the proposed mechanisms’efficiency by utilizing advanced algorithms and demonstrating improved performance in packet processing speed,path calculation effectiveness,and switch storage management compared to current mechanisms.The proposed mechanism shows significant improvements,leading to a 37.5%decrease in Recovery Time(RT)and a 33.33%decrease in both Calculation Time(CT)and Computational Overhead(CO)when compared to current mechanisms.The study highlights the effectiveness and resource efficiency of the proposed mechanism in effectively resolving crucial issues inmulti-hop software-defined exchange point networks.

The molecular mechanism of meridian qi sensory transmission by heat-sensitive moxibustion in the treatment of cerebral infarction

Background:To explore the potential mechanism of thermal moxibustion in the treatment of i schemic strok e by using the method of network pharmacology and to partially explain the mechanism of acupoint meridian qi sense transmission.Methods:In this project,a training set was formed by researching the intersection of the reported components of M ugwort leaves that entered the blood after combustion and obtained the targets of heat-sensitive moxibustion meridian qi sensing and thermal effect by querying the literature.The Encyclopedia of Tr ad itional Chinese Medicine is used to search and screen the highly active chemical constituents of Artemisia argyi to predict potential targets;search i schemic strok e-related targets through GeneCards,O nline Mendelian Inheritance in Man,Drugbank databases.Gene Oncology functional analysis and Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment analysis were performed on the potential targets of the blood components of Artemisia argyi and molecular docking simulated the binding activity of key candidate active components and core genes.Results:192 ischemic stroke disease targets with r elevance score greater than 10 were screened out for analysis.Through the database Encyclopedia of Tr ad itional Chinese Medicine query of the action targets(243)of Mugwort leaves and the intersection of heat-sensitive moxibustion effect targets and ischemic stroke-related targets,a Venn diagram was drawn and a total of 17 were obtained.Finally,the effective components of Mugwort leaves into the blood were screened out.Five main volatile components were molecularly docked with 17 targets and 9 targets of acupoint meridian gas sensing/thermal effect.The docking results showed that the main volatile components showed good affinities for binding to key targets,respectively.Conclusion:Using the characteristics of“multi-component-multi-target-multi-pathway”of traditional Chinese medicine,the potential mechanism of action of Artemisia argyi in the treatment of i schemic strok e is explored,which provides a certain basis for the follow-up scientific research and clinical application of Artemisia argyi in the treatment of IS.

Diagnosis of indirectly driven double shell targets with point-projection hard x-ray radiography

We present an application of short-pulse laser-generated hard x rays for the diagnosis of indirectly driven double shell targets. Coneinserted double shell targets were imploded through an indirect drive approach on the upgraded SG-II laser facility. Then, based on thepoint-projection hard x-ray radiography technique, time-resolved radiography of the double shell targets, including that of their near-peakcompression, were obtained. The backlighter source was created by the interactions of a high-intensity short pulsed laser with a metalmicrowire target. Images of the target near peak compression were obtained with an Au microwire. In addition, radiation hydrodynamicsimulations were performed, and the target evolution obtained agrees well with the experimental results. Using the radiographic images, arealdensities of the targets were evaluated.

Exceptional points and quantum dynamics in a non-Hermitian two-qubit system

We study the exceptional-point(EP) structure and the associated quantum dynamics in a system consisting of a non-Hermitian qubit and a Hermitian qubit. We find that the system possesses two sets of EPs, which divide the systemparameter space into PT-symmetry unbroken, partially broken and fully broken regimes, each with distinct quantumdynamics characteristics. Particularly, in the partially broken regime, while the PT-symmetry is generally broken in the whole four-dimensional Hilbert space, it is preserved in a two-dimensional subspace such that the quantum dynamics in the subspace are similar to those in the PT-symmetry unbroken regime. In addition, we reveal that the competition between the inter-qubit coupling and the intra-qubit driving gives rise to a complex pattern in the EP variation with system parameters.

Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation

This paper focuses on the task of few-shot 3D point cloud semantic segmentation.Despite some progress,this task still encounters many issues due to the insufficient samples given,e.g.,incomplete object segmentation and inaccurate semantic discrimination.To tackle these issues,we first leverage part-whole relationships into the task of 3D point cloud semantic segmentation to capture semantic integrity,which is empowered by the dynamic capsule routing with the module of 3D Capsule Networks(CapsNets)in the embedding network.Concretely,the dynamic routing amalgamates geometric information of the 3D point cloud data to construct higher-level feature representations,which capture the relationships between object parts and their wholes.Secondly,we designed a multi-prototype enhancement module to enhance the prototype discriminability.Specifically,the single-prototype enhancement mechanism is expanded to the multi-prototype enhancement version for capturing rich semantics.Besides,the shot-correlation within the category is calculated via the interaction of different samples to enhance the intra-category similarity.Ablation studies prove that the involved part-whole relations and proposed multi-prototype enhancement module help to achieve complete object segmentation and improve semantic discrimination.Moreover,under the integration of these two modules,quantitative and qualitative experiments on two public benchmarks,including S3DIS and ScanNet,indicate the superior performance of the proposed framework on the task of 3D point cloud semantic segmentation,compared to some state-of-the-art methods.

Anti-inflammatory Effect of Heat-sensitive Moxibustion via the NF-κB Signaling Pathway on Cerebral Ischemia/Reperfusion Injury in Rats

Ischemic stroke is universally acknowledged as a common cause of long-term disability or even death. Suspended moxibustion, an indirect form of moxibustion, is when moxibustion is placed superficially over the skin without being in contact with it. Some researchers have used this method to treat stroke patients, but strong evidence of its therapeutic effectiveness is lacking. However, the effect of traditional suspended moxibustion has recently been improved with the development of heat-sensitive suspended moxibustion. Our previous studies showed that moxibustion for 35 min provided a more effective treatment strategy than moxibustion for 15 min, and moxibustion by 35 min with tail temperature increase had a better outcome than that without, however, the mechanism underlying the effect is not clear. In this study, we treated the stroke rats with moxibustion by 35min and divided them into non-heat sensitive moxibustion(NHSM) group and heat sensitive moxibustion (HSM) group according to difference in the tail temperature increase, then we compared the effect and investigated the mechanisms between NHSM and HSM. We found that HSM significantly decreased tail-flick latency, increased neurological function score, decreased infarct volume, reduced inflammatory cells, decreased the expression of inflammatory factor ICAM-1 and reduced the expression of NF-κB p65 and p-IKKα/β in rats with focal cerebral ischemia/reperfusion injury. Our experimental findings revealed that HSM exerted its anti-inflammatory and neuroprotective effects from MCAO-induced injury by decreasing the expression of the NF-κB signaling pathway.