丙泊酚调节MPP+诱导的SH-SY5Y细胞线粒体氧化应激和凋亡

目的探讨不同浓度的丙泊酚(propofol,PPF)对1-甲基-4-苯基吡啶离子(1-Methyl-4-phenylpyridinium,MPP+)诱导的帕金森(Parkinson’s disease,PD)模型细胞氧化应激和凋亡的作用。方法利用1 mM MPP+诱导人神经母细胞瘤细胞SH-SY5Y构建PD细胞模型。PPF处理组分别用10、20、40、80μM PPF在MPP+诱导前刺激SH-SY5Y细胞4 h。细胞计数法(cell counting kit-8,CCK-8)评估细胞增殖活力。2′,7′-二氯二氢荧光素二乙酸酯(H2DCF-DA)荧光探针用于检测细胞中活性氧(reactive oxygen species,ROS)。试剂盒分别检测丙二醛(malondialdehyde,MDA)和还原型烟酰胺腺嘌呤二核苷酸磷酸(reduced nicotinamide adenine dinucleotide phosphate oxidase,NADPH)氧化酶的水平。Western blot用于检测线粒体和细胞质中细胞色素c的蛋白表达以及细胞中Bcl-2、Bax和Cleaved caspase-3蛋白表达。流式细胞术分析细胞凋亡率。结果MPP+诱导明显抑制SH-SY5Y细胞的增殖(P<0.001),促进细胞中ROS(P<0.001)、MDA(P<0.001)、NADPH氧化酶(P<0.01)、细胞质中细胞色素c的表达(P<0.01)并诱导细胞凋亡(P<0.001)以及促凋亡蛋白Bax和Cleaved caspase-3的表达(P<0.01),减少线粒体中细胞色素c的蛋白表达(P<0.01)和抗凋亡蛋白Bcl-2的表达(P<0.01)。PPF预处理可缓解MPP+诱导引起的SH-SY5Y细胞增殖抑制以及氧化应激和凋亡的促进作用(P<0.001),且40μM和80μM对细胞的作用更为显著。结论PPF预处理可缓解MMP+诱导的SH-SY5Y细胞氧化应激,减少细胞凋亡。

基于MPP数据库的多源异构数据分布式集成平台构建

对多源异构数据进行集成,是实现数据共享、打破“信息孤岛”的关键。运用分布式并行计算技术,对基于 MPP 数据库的多源异构数据分布式集成平台的构建进行分析研究,文章分析了多源异构数据集成的发展动态,阐述了 MPP 数据库基本架构及运行机制,分四个层次设计了基于 MPP 数据库的多源异构数据分布式集成平台的框架结构,并对数据规划进行了分析。为多源异构数据分布式集成的实践应用提供了方法和思路上的借鉴。

基于MPPT控制的两级式直流孤岛检测方法研究

针对主动式孤岛检测方法存在扰动同步注入、影响电网供电质量等问题,提出了一种基于最大功率点跟踪(MPPT)控制的两级式直流孤岛检测方法。该方法通过检测并网变换器直流侧电流来判断疑似孤岛,然后利用疑似孤岛信号触发电压扰动的注入使得孤岛后的公共耦合点(PCC)电压出现特定频率的波动。由于扰动信号的注入受疑似孤岛信号控制,减少了正常状态下扰动的注入时长,有效降低对系统电能质量的影响。此外建立小信号模型分析了耦合点电压对扰动分量的频域特性,选取扰动信号的最优频率。最后通过仿真与实验验证了所提方法在单机与多机工况下的有效性。

基于SSA-ELM神经网络控制器的光伏MPPT方法

光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该文提出了一种基于麻雀搜索算法优化的极限学习机(sparrow search algorithm-extreme learning machine,SSA-ELM)神经网络控制器的MPPT方法。与传统技术相比,该MPPT方法在稳定性、速度、超调和MPP的振荡等方面的效果均较好。使用MATLAB/Simulink平台进行仿真实验,验证了所提控制策略及理论分析的正确性。

基于改进布谷鸟搜索算法的光伏MPPT控制

复杂阴影情况下,光伏阵列的P-V特性曲线会出现多个峰值,传统的MPPT算法因不能准确识别局部峰值和全局峰值,而无法进行复杂阴影情况下的最大功率点跟踪。针对传统布谷鸟搜索(Cuckoo Search,CS)算法因鸟窝之间缺乏交流能力导致可能陷入局部最优的问题,提出了一种多策略改进布谷鸟搜索(EGICS)算法。将传统CS算法中发现概率值的选择自适应变化,提高算法的搜索能力;将步长因子自适应化,提高算法的收敛速度;引入高斯扰动和精英反向学习策略,增加种群多样性,避免算法陷入局部最优。对EGICS算法在单峰和多峰函数中进行性能测试,并将其应用于光伏系统MPPT控制中进行仿真验证。仿真结果表明,EGICS算法在收敛速度、跟踪精度以及动态稳定三个方面有更好的效果。

基于混合算法的多峰值MPPT控制

针对光照不均匀时光伏阵列输出呈现非线性、多峰值的问题,提出一种基于自然选择粒子群(SelPSO)算法结合电导增量法(INC)的多峰值最大功率点追踪(MPPT)算法。SelPSO算法通过淘汰和替换迭代过程中适应度低的粒子,更快、更准确地完成对全局最大值点的搜索;使用INC进行局部跟踪,有效减少寻优过程中的功率振荡,达到最大功率点跟踪的目的。利用MATLAB/Simulink进行仿真试验。结果表明:与INC相比,SelPSO算法的功率振荡由12 W降至0.05 W;与PSO算法相比,跟踪时间由0.15 s缩短至0.07 s。该混合算法在复杂环境下具有较优的跟踪速度、收敛精度以及较低的功率波动。

基于改进黏菌算法的光伏多峰值MPPT控制

针对传统最大功率点跟踪技术在局部遮阴等天气条件下存在无法追踪到全局最大功率点的问题,提出一种基于改进黏菌算法的MPPT控制。首先,对太阳电池模型及多峰值特性进行分析;其次,在黏菌算法中引入领导者策略和基于最优个体的凸透镜反向学习策略,在提高算法计算精度、收敛速度的同时克服了算法易“早熟”现象;最后,根据光伏阵列最大功率输出特性分别确定算法优化模型、初始化位置及重启机制。仿真与实验结果表明:基于改进黏菌算法的MPPT控制能快速、准确地跟踪到全局最大功率点,有效规避陷入局部最优问题,提高了光伏系统的转换效率。

副猪嗜血杆菌OmpP2基因分子特征及重组乳酸菌的构建与鉴定

猪格拉瑟病是由副猪嗜血杆菌引起的猪的主要细菌性传染病。构建安全、有效的新型疫苗是防控该病的研究热点。本研究对OmpP2基因编码的蛋白质进行生物信息学预测分析后,应用无缝克隆技术把PCR扩增获得的OmpP2基因连接到pNZ8148载体,构建出pNZ8148-OmpP2重组载体,转入乳酸乳球菌感受态细胞,获得pNZ8148-OmpP2重组乳酸乳球菌;再进行蛋白表达与鉴定。结果表明:生物信息学预测到OmpP2蛋白具备优势B细胞和T细胞表位,是具有潜力的候选抗原;经重组乳酸乳球菌蛋白表达与鉴定,检测到大小约为38.5kD的目的条带,与预期大小相符。说明乳酸乳球菌能作为递送载体成功表达G.parasuis异源蛋白。本实验为后续G.parasuis乳酸菌活载体疫苗的研制奠定了基础。

基于改进SCSO算法的光伏MPPT研究

在解决光伏阵列在局部遮挡时发电效率降低的问题时,传统最大功率点追踪(MPPT)方法容易追踪失败。为此,提出一种改进沙猫群优化算法的最大功率点追踪方法。该算法在标准沙猫群算法的基础上,引入了精英反向学习和自适应t分布,同时优化沙猫群算法(SCSO)的局部搜索并融合Jaya算法。通过对4种典型单峰、多峰函数的测试,证明该算法具有极高的收敛速度,容易跳出局部最优值。将算法应用于MPPT控制中,仿真结果表明:在静态遮荫情况下,所提方法的搜索最大功率点的时间更少;在动态遮荫条件下,重新搜寻到最大功率点的响应时间平均为0.2 s。实验表明所提算法可以适应动态变化的天气,解决了传统算法收敛速度和防止陷入局部最优等问题。

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.

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.

Prediction of collapse process and tipping points for mutualistic and competitive networks with k-core method

Ecosystems generally have the self-adapting ability to resist various external pressures or disturbances,which is always called resilience.However,once the external disturbances exceed the tipping points of the system resilience,the consequences would be catastrophic,and eventually lead the ecosystem to complete collapse.We capture the collapse process of ecosystems represented by plant-pollinator networks with the k-core nested structural method,and find that a sufficiently weak interaction strength or a sufficiently large competition weight can cause the structure of the ecosystem to collapse from its smallest k-core towards its largest k-core.Then we give the tipping points of structure and dynamic collapse of the entire system from the one-dimensional dynamic function of the ecosystem.Our work provides an intuitive and precise description of the dynamic process of ecosystem collapse under multiple interactions,and provides theoretical insights into further avoiding the occurrence of ecosystem collapse.

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.

Triple points and phase transitions of D-dimensional dyonic Ad S black holes with quasitopological electromagnetism in Einstein–Gauss–Bonnet gravity

By considering the negative cosmological constant Λ as a thermodynamic pressure, we study the thermodynamics and phase transitions of the D-dimensional dyonic Ad S black holes(BHs) with quasitopological electromagnetism in Einstein–Gauss–Bonnet(EGB) gravity. The results indicate that the small/large BH phase transition that is similar to the van der Waals(vdW) liquid/gas phase transition always exists for any spacetime dimensions. Interestingly, we then find that this BH system exhibits a more complex phase structure in 6-dimensional case that is missed in other dimensions.Specifically, it shows for D = 6 that we observed the small/intermediate/large BH phase transitions in a specific parameter region with the triple point naturally appeared. Moreover, when the magnetic charge turned off, we still observed the small/intermediate/large BH phase transitions and triple point only in 6-dimensional spacetime, which is consistent with the previous results. However, for the dyonic Ad S BHs with quasitopological electromagnetism in Einstein–Born–Infeld(EBI) gravity, the novel phase structure composed of two separate coexistence curves observed by Li et al. [Phys. Rev. D105 104048(2022)] disappeared in EGB gravity. This implies that this novel phase structure is closely related to gravity theories, and seems to have nothing to do with the effect of quasitopological electromagnetism. In addition, it is also true that the critical exponents calculated near the critical points possess identical values as mean field theory. Finally, we conclude that these findings shall provide some deep insights into the intriguing thermodynamic properties of the dyonic Ad S BHs with quasitopological electromagnetism in EGB gravity.

Petrophysical Evaluation of Cape Three Points Reservoirs

The findings of a study to ascertain and assess the petrophysical characteristics of Cape Three Points reservoirs in the Western basin with a view to describe the reservoir quantitatively using Well Logs, Petrel and Techlog. The investigated characteristics, which were all deduced from geophysical wire-line logs, include lithology, porosity, permeability, fluid saturation, and net to gross thickness. To characterise the reservoir on the field, a suite of wire-line logs including gamma ray, resistivity, spontaneous potential, and density logs for three wells (WELL_1X, WELL_2X, and WELL_3X) from the Tano Cape Three Point basin were studied. The analyses that were done included lithology delineation, reservoir identification, and petrophysical parameter determination for the identified reservoirs. The tops and bases of the three wells analysed were marked at a depth of 1203.06 - 2015.64 m, 3863.03 - 4253.85 m and 2497.38 - 2560.32 m respectively. There were no hydrocarbons in the reservoirs from the studies. The petrophysical parameters computed for each reservoir provided porosities of 13%, 3% and 11% respectively. The water saturation also determined for these three wells (WELL_1X, WELL_2X and WELL_3X) were 94%, 95% and 89% respectively. These results together with the behaviour of the density and neutron logs suggested that these wells are wildcat wells.

A hybrid contact approach for modeling soil-structure interaction using the material point method

The grid-based multi-velocity field technique has become increasingly popular for simulating the Material Point Method(MPM)in contact problems.However,this traditional technique has some shortcomings,such as(1)early contact and contact penetration can occur when the contact conditions are unsuitable,and(2)the method is not available for contact problems involving rigid-nonrigid materials,which can cause numerical instability.This study presents a new hybrid contact approach for the MPM to address these limitations to simulate the soil and structure interactions.The approach combines the advantages of point-point and point-segment contacts to implement contact detection,satisfying the impenetrability condition and smoothing the corner contact problem.The proposed approach is first validated through a disk test on an inclined slope.Then,several typical cases,such as granular collapse,bearing capacity,and deformation of a flexible retaining wall,are simulated to demonstrate the robustness of the proposed approach compared with FEM or analytical solutions.Finally,the proposed method is used to simulate the impact of sand flow on a deformable structure.The results show that the proposed contact approach can well describe the phenomenon of soil-structure interaction problems.

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.

FPSblo:A Blockchain Network Transmission Model Utilizing Farthest Point Sampling

Peer-to-peer(P2P)overlay networks provide message transmission capabilities for blockchain systems.Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems.However,traditional blockchain P2P networks face a common challenge where there is often a mismatch between the upper-layer traffic requirements and the underlying physical network topology.This mismatch results in redundant data transmission and inefficient routing,severely constraining the scalability of blockchain systems.To address these pressing issues,we propose FPSblo,an efficient transmission method for blockchain networks.Our inspiration for FPSblo stems from the Farthest Point Sampling(FPS)algorithm,a well-established technique widely utilized in point cloud image processing.In this work,we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritize message forwarding so that messages reach the network edge quickly and are evenly distributed.Moreover,we compare our model with the Kadcast transmission model,which is a classic improvement model for blockchain P2P transmission networks,the experimental findings show that the FPSblo model reduces 34.8%of transmission redundancy and reduces the overload rate by 37.6%.By conducting experimental analysis,the FPS-BT model enhances the transmission capabilities of the P2P network in blockchain.