Diffusion tensor imaging reveals brain structure changes in dogs after spinal cord injury

Based on the Wallerian degeneration in the spinal cord pathways,the changes in synaptic connections,and the spinal cord-related cellular responses that alter the cellular structure of the brain,we presumed that brain diffusion tensor imaging(DTI)parameters may change after spinal cord injury.However,the dynamic changes in DTI parameters remain unclear.We established a Beagle dog model of T10 spinal cord contusion and performed DTI of the injured spinal cord.We found dynamic changes in DTI parameters in the cerebral peduncle,posterior limb of the internal capsule,pre-and postcentral gyri of the brain within 12 weeks after spinal cord injury.We then performed immunohistochemistry to detect the expression of neurofilament heavy polypeptide(axonal marker),glial fibrillary acidic protein(glial cell marker),and NeuN(neuronal marker).We found that these pathological changes were consistent with DTI parameter changes.These findings suggest that DTI can display brain structure changes after spinal cord injury.

Discussion on moment tensor solution and seismogenic structure of Ruichang-Yangxin earthquake on 10 September 2011

Ruichang-Yangxin earthquake is another moderate earthquake in Yangxin-Jiujiang area since 2005 Jiujiang-Ruichang M5.7 earthquake. In order to more understand the seismic activities in this area, we study the moment tensor solution and the seismogenic structure of the Ruichang-Yangxin earthquake. Precise earthquake relocation shows that the mainshock occurred on the southwestern part of the NE-trending fault and aftershocks are distributed not only along the NE-trending fault but also along its conjugated NW-trending fault. By comprehensive analysis on the earthquake distribution, characteristics of isoseismal curve, focal mechanism, and regional structure characteristics, it is inferred that this earthquake is caused by the NE-trending Tanlu fault. In addition, it has close relationship with the conjugated NW-trending fault as well. Many researches have shown that the junction area is the earthquake-prone area, and should be paid more attention to. And our study also proves this viewpoint.

Combination of structure tensor and tilt angle in the edge detection of potential field data

Edge detection is a commonly requested task in the interpretation of potential field data. Different methods have different results for varied depths and shapes of geological bodies. In this paper,we propose using the combination of structure tensor and tilt angle to detect the edges of the sources,which can display the edges of shallow and deep bodies simultaneously. Through tests on synthetic potential field data,it is obvious that the proposed edge detection methods can display the sources edges more clearly and precisely,compared with other commonly used methods. The application on real potential field data shows similar result,obtaining the edges of layers and faults clearly. In addition,another advantage of the new method is its insensitivity to noise.

Edge detection of gravity anomaly with an improved 3D structure tensor

Edge detection plays an important role in geological interpretation of potential field data,which can indicate the subsurface faults,contact,and other tectonic features.A variety of methods have been proposed to detect and enhance the edges.3 D structure tensor can well delineate the edges of geological bodies,however,it is sensitive to noise and additional false edges need to be removed artificially.In order to overcome these disadvantages,this paper redefines the 3 D structure tensor with a Gaussian envelop and proposes a new normalized edge detector,which can remove the additional false edges and reduce the influence of noise effectively,and balance the edges of different amplitude anomalies completely.This method has been tested on the synthetic and measured gravity data,showing that the new improved method achievesbetter results and reveals more details.

Contour tracking using weighted structure tensor based variational level set

A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite symmetric covariance matrix for each pixel.Then,a level set method is employed to represent object contour implicitly which separates the image domain into two areas each modeled by tensor field based Gaussian mixture model separately.By solving agradient flow equation of energy functional with respect to the level set,the object contour will converge to its real profile in the newly arrived frame.Experimental results on several video sequences demonstrate the better performance of our method than the other two contour tracking algorithms.

How to Determine Initial Starting Time Step with an Initial Hubble Parameter H = 0 after Formation of Causal Structure Leading to Investigation of the Penrose Weyl Tensor Conjecture

We start where we use an inflaton value due to use of a scale factor . Also we use as the variation of the time component of the metric tensor ?in Pre-Planckian Space-time. In doing so, what we lead up to using the Huang Superfluid universe model, which is by the modified superfluid cosmology model leading to examining within the Pre Planckian regime, Curvature, small but non zero, and energy density . The Potential energy is given by what it would be if leading to a relationship of , where we will isolate conditions for the initial time and compare them against a root finder procedure given in another paper written by the author. Then, afterwards, assuming a modified Hubble parameter, with an initial Hubble parameter after the Causal surface with, right after a quantum bounce, determined by , is then . And is an initial degree of freedom value of about 110. Then, the graviton production rate is a function of time leading to a temperature T dependence, with M here is a chosen Mass scale, M of about 30 TeV, with d greater than or equal to zero, representing the Kaluza Klein dimensions assumed with the number of gravitons produced after the onset of Causal structure given by . This?? ?by Infinite quantum statistics is proportional to entropy. We close with a caveat as far as the implications of all this to the Penrose Conjecture about the vanishing of the Weyl tensor, in the neighborhood of a cosmological initial singularity. And what we think should be put in place instead of the Penrose Weyl tensor hypothesis near a “cosmological” singularity. And we close with a comment about the Weyl curvature tensor, in Pre Planckian to Planckian physics, and also a final appendix on the Mach’s principle as written by Sciama, in defining the initial space-time non-singular “bubble”.

Influence of particle packing structure on sound velocity

The anisotropy in the particle systems of different packing structures affects the sound velocity. The acoustic propagation process in four kinds of packing structures（denoted as S45, H60, S90, and D） of two-dimensional granular system is simulated by the discrete element method. The velocity vtof obtained by the time of flight method and the velocity vc obtained from the stiffness tensor of the system are compared. Different sound velocities reflect various packing structures and force distributions within the system. The compression wave velocities of H60 and S90 are nearly the same, and transmit faster than that of D packing structure, while the sound velocity of S45 is the smallest. The shear wave velocities of S45 and H60 are nearly the same, and transmit faster than that of D packing structure. The compression wave velocity is sensitive to the volume fraction of the structure, however, the shear wave velocity is more sensitive to the geometrical structure itself. As the normal stress p is larger than 1 MPa, vtof and vc are almost equal, and the stiffness tensors of various structures explain the difference of sound velocities. When the normal stress is less than 1 MPa, with the coordination number unchanged, the law vtof ∝ p^1/4 still exists. This demonstrates that apart from different power laws between force and deformation as well as the change of the coordination number under different stresses, there are other complicated causes of vtof∝ p^1/4, and an explanation of the deviation from vtof ∝ p^1/6 is given from the perspective of dissipation.

On Quaternionic 3 CR-Structure and Pseudo-Riemannian Metric

A CR-structure on a 2n +1-manifold gives a conformal class of Lorentz metrics on the Fefferman S1-bundle. This analogy is carried out to the quarternionic conformal 3-CR structure (a generalization of quaternionic CR- structure) on a 4n + 3 -manifold M. This structure produces a conformal class [g] of a pseudo-Riemannian metric g of type (4n + 3,3) on M × S3. Let (PSp(n +1,1), S4n+3) be the geometric model obtained from the projective boundary of the complete simply connected quaternionic hyperbolic manifold. We shall prove that M is locally modeled on (PSp(n +1,1), S4n+3) if and only if (M × S3 ,[g]) is conformally flat (i.e. the Weyl conformal curvature tensor vanishes).

Commuting Structure Jacobi Operator for Real Hypersurfaces in Complex Space Forms

Let M be a real hypersurface of a complex space form with almost contact metric structure (φ,ξ,η,g). In this paper, we prove that if the structure Jacobi operator Rξ=(·,ξ) ξ is φ▽ξξ-parallel and Rξ commute with the shape operator, then M is a Hopf hypersurface. Further, if Rξ is φ▽ξξ-parallel and Rξ commute with the Ricci tensor, then M is also a Hopf hypersurface provided that TrRξ is constant.

基于自动纤维定量技术研究卒中后抑郁的纤维束改变

目的通过自动纤维定量(automated fiber quantification,AFQ)技术研究卒中后抑郁(post-stroke depression,PSD)神经纤维束的结构改变,并探索与抑郁程度相关的纤维节段。方法纳入单部位前循环脑梗死患者,分为PSD组和卒中后非抑郁(non-PSD)组,收集发病1个月时的汉密尔顿抑郁量表(Hamilton depression scale,HAMD)和MRI数据,采用AFQ提取神经纤维束节段的部分各项异性(fractional anisotropy,FA),评估纤维束节段FA组间差异,以及差异纤维束节段FA与HAMD的相关性。结果共收集8例PSD和18例non-PSD患者。与non-PSD组相比,PSD组胼胝体、左侧下纵束和钩状束的节段FA降低(P<0.05)。所有患者胼胝体小钳(r=-0.418,P=0.047)和左侧钩状束(r=-0.467,P=0.029)部分节段FA与其HAMD呈负相关。结论AFQ精确地揭示了PSD患者的神经纤维束存在节段性的微结构损害,且胼胝体小钳和钩状束节段性微结构损害与抑郁严重程度有关。

基于结构张量的走滑断裂破碎带地震识别——以富满油田超深层碳酸盐岩为例

塔里木盆地超深层奥陶系碳酸盐岩走滑断裂破碎带发现了丰富的油气资源,但由于超深层地震资料分辨率低,难以精准刻画走滑断裂破碎带,制约了走滑断控油气藏的高效评价与目标优选。根据富满油田走滑断裂破碎带的地震响应特征,在构造导向滤波基础上,利用结构张量方法计算特征值和特征向量,通过时窗选取与纵向厚度叠加加强反映沿断裂方向的投影能量,突出走滑断裂破碎带,刻画其边界与强度。结果表明:该方法更清晰地刻画了走滑断裂的分布,可以识别更小规模的走滑断裂;实现了超深层碳酸盐岩走滑断裂破碎带宽度与强度的刻画,可以用来评价走滑断裂破碎带的发育程度;将该方法应用于圈闭评价、井位部署、井轨迹设计、钻井监测等,大幅提高了钻探成功率与单井油气产量。

碳酸盐岩强非均质储层相控反演方法研究

岩溶缝洞体是碳酸盐岩主要储层类型,具有强非均质性特征,量化预测难度大。常规地震反演方法虽然可实现储层的量化预测,但满足不了岩溶缝洞体中多类型储层的量化及高精度研究需求。针对这一问题,在相控约束反演技术思路的基础上,提出了基于梯度结构张量属性约束的确定性相控反演方法。该方法可概述为3步:首先,基于梯度结构张量属性,划分出反映碳酸盐岩缝洞体轮廓的储层相与非储层相;其次,以地震相为约束条件,建立低频模型;最后,将低频模型应用于地震反演过程,得到储层敏感属性,进而实现碳酸盐岩强非均质储层的量化预测。模型试算结果和塔里木盆地M工区实际应用结果均表明,该方法能有效识别岩溶缝洞体中多类型储层的分布范围,与实钻结果及开发动态特征吻合,为碳酸盐岩缝洞型油藏的整体量化研究奠定了基础。

2022年四川马尔康6.0级震群序列震源机制特征分析

采用近震全波形矩张量方法反演了2022年四川马尔康6.0级震群序列22次地震的震源机制解,结果显示:这22次地震全部为走滑型,断层面走向呈NNW和NE两个优势方向,断层面倾角近似直立,滑动角分布在0°和180°附近,P轴优势方位为NWW-SEE向,倾伏角接近水平,表明此次地震事件主要受区域NWW-SEE向水平挤压应力场控制。3次5级以上地震震源机制均与序列其他地震的总体震源机制差异较小,说明序列震源机制较为一致。结合精定位结果综合分析认为:马尔康震群属于多断层面触发性震群,3次5级以上地震是不同断裂的破裂事件,其中5.8级和6.0级地震发震断层面走向为NNW,为左旋走滑破裂事件;5.2级地震发震断层面走向为NE,为右旋走滑破裂事件,3个发震断层均以走滑错动为主,断层面近似直立。

改进非凸估计与非对称时空正则化的红外小目标检测方法

针对复杂背景下的红外小目标检测,在非对称时空正则化约束的非凸张量低秩估计算法基础上,提出了一种新的核范数估计方法代替原算法中的估计方法。提出基于结构张量与多结构元顶帽(Top-Hat)滤波的自适应权重张量对目标张量进行约束,增强目标张量稀疏性的同时抑制其中残存的强边缘结构。实验结果表明,所提改进算法能够更好地消除图像中强边缘结构对检测结果的影响,在保证检测率的情况下,较原算法具有更低的虚警率。

糖尿病周围神经病变多模态MRI研究进展

糖尿病周围神经病变(diabetes peripheral neuropathy,DPN)是较常见的糖尿病慢性并发症,严重影响患者生活质量。DPN发病机制比较复杂,目前研究表明与神经病理性改变关系密切。近些年多模态MRI获得长足进展,MRI以软组织分辨率高、无创、无辐射等优点著称,成为探索DPN中枢神经及周围神经发病机制的重要方法。本文应用基于体素的形态学测量(voxel-based morphometry,VBM)、弥散张量成像(diffusion tensor imaging,DTI)、功能MRI(functional MRI,fMRI)等技术,对研究DPN脑结构、脑功能改变以及周围神经结构异常的文献进行综述,为临床早期诊断和制订精准治疗方案提供依据。

面向弱纹理空间目标的特征点匹配方法

特征点提取与匹配是遥感图像处理中关键的一环,目前成熟的算法大多面向对地成像类型的遥感图像,对于空间目标的遥感图像,没有考虑成像条件与探测平台的影响因素,特征点匹配质量较差。针对空间目标的匹配精度不高这一问题,文章提出了一种基于聚类的特征点匹配算法。首先,根据空间目标的重复弱纹理进行特征点提取与描述,再利用特征点的空间位置进行聚类,并对特征点簇进行匹配;之后将特征点的主方向减去目标整体方向,利用特征点主方向对每一个点簇进行再分组,并完成特征点匹配;最后利用最近邻次近邻比率方法和随机样本一致算法(RANSAC)剔除外点。采用该特征点匹配方法进行的模拟成像数据实验结果表明,对于空间目标图像,基于聚类的特征点匹配较直接匹配,匹配数量的提升最高可达50%,重投影误差优于1/4个像元。文章提出的这一方法使用目前通用的各种特征描述子,能够大幅度提高空间目标图像特征点匹配的数量与精度。

2023年10月24日甘肃肃北Ms5.5地震震源机制及发震构造

收集到青海和甘肃区域地震台网记录的宽频带地震波形和震相观测数据,利用ISOLA近震全波形方法对2023年10月24日甘肃肃北Ms5.5地震进行矩张量反演,得到震源机制解和矩心深度;通过双差定位方法获得地震序列精定位结果和时空分布特征,并结合该地区构造背景对发震构造进行分析。获得肃北Ms5.5地震震源机制解参数为:节面Ⅰ的走向、倾角和滑动角为170°、73°和108°,节面Ⅱ的走向、倾角和滑动角为300°、24°和42°,震源矩心深度为4km;重定位后,此次地震序列震中集中分布在长约22km、宽约10km的区域内,地震丛集的优势方向为NNW-SSE向。通过对震源机制解、定位结果、区域构造背景等进行分析,推测震源机制解节面Ⅰ为发震断层面,此次地震为发生在隐伏断层上的一次逆冲兼有走滑型地震事件,发震断裂与周边主要断裂的性质一致。

磁共振扩散张量成像在青少年抑郁症中的研究进展

抑郁症是致残的主要原因之一,通常始于青春期。青少年抑郁症常导致学业失败、同伴关系不佳、行为问题、家庭及社会关系冲突,甚至自杀等不良后果,早期预防和积极有效的治疗至关重要。磁共振扩散张量成像技术能定量评价脑白质微结构,构建结构网络,可用于分析青少年抑郁症患者脑白质异常与症状、年龄、性别等临床变量的相关性。青少年抑郁症扩散张量成像研究显示,青少年抑郁症患者存在胼胝体、扣带束及钩状束等多个白质纤维束微结构异常,前额叶-纹状体环路、前额叶-边缘系统神经环路受损,且与记忆、情绪调节、奖励处理、认知加工等密切相关,与成人抑郁症中的发现一致。本研究对扩散张量成像的成像原理、数据处理方法及在青少年抑郁症中的应用进展进行简要综述,为今后的研究提供新思路。

面向弱纹理图像的自适应多邻域特征点描述子

针对弱纹理场景中特征提取困难、特征匹配准确率低等问题,提出一种自适应多邻域结构张量(adaptive multi-neighborhood structure tensor,AMST)特征点描述子。基于多个图像邻域及其结构张量,多层次地表达图像结构信息,解决弱纹理图像的特征提取与匹配等问题;通过特征点密度自适应邻域数量,提高计算效率,利用海森矩阵,剔除不稳定特征点,增强算法实时性以及稳定性。实验结果表明,AMST算法在弱纹理图像上的匹配准确率达到99.90%以上,同时具有良好地旋转不变性,能够适应遮挡、截断等复杂场景,具备良好的鲁棒性。

Multi-functional Hollow Structures for Intelligent Drug Delivery

Multi-fountional hollow structures have emerged as promising platforms for intelligent drug delivery due to their unique properties,such as high loading capacities and programmed drug release.In particular,hollow multishell structures(HoMSs)with multilevel shell and space can regulate the molecular-level interaction between drugs and materials,so as to achieve the temporal-spatial order and sequential release of drugs.The anisotropic hollow structures can control the drug diffusion process by inducing the macroscopic interface flow through autonomous movement,realizing the targeted drug transport and release.In this paper,a key focus will be HoMSs with their temporal-ordered architectures and anisotropic hollow carriers with directional movement.Their synthesis mechanisms,structure-property relationships,smartly programmed drug delivery and biomedical applications will be discussed,providing insights into designing next-generation intelligent drug carriers.