A Sharding Scheme Based on Graph Partitioning Algorithm for Public Blockchain

Blockchain technology,with its attributes of decentralization,immutability,and traceability,has emerged as a powerful catalyst for enhancing traditional industries in terms of optimizing business processes.However,transaction performance and scalability has become the main challenges hindering the widespread adoption of blockchain.Due to its inability to meet the demands of high-frequency trading,blockchain cannot be adopted in many scenarios.To improve the transaction capacity,researchers have proposed some on-chain scaling technologies,including lightning networks,directed acyclic graph technology,state channels,and shardingmechanisms,inwhich sharding emerges as a potential scaling technology.Nevertheless,excessive cross-shard transactions and uneven shard workloads prevent the sharding mechanism from achieving the expected aim.This paper proposes a graphbased sharding scheme for public blockchain to efficiently balance the transaction distribution.Bymitigating crossshard transactions and evening-out workloads among shards,the scheme reduces transaction confirmation latency and enhances the transaction capacity of the blockchain.Therefore,the scheme can achieve a high-frequency transaction as well as a better blockchain scalability.Experiments results show that the scheme effectively reduces the cross-shard transaction ratio to a range of 35%-56%and significantly decreases the transaction confirmation latency to 6 s in a blockchain with no more than 25 shards.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Partitioning Calculation Method of Short-Circuit Current for High Proportion DG Access to Distribution Network

Aiming at the problemthat the traditional short-circuit current calculationmethod is not applicable to Distributed Generation(DG)accessing the distribution network,the paper proposes a short-circuit current partitioning calculation method considering the degree of voltage drop at the grid-connected point of DG.Firstly,the output characteristics of DG in the process of low voltage ride through are analyzed,and the equivalent output model of DG in the fault state is obtained.Secondly,by studying the network voltage distribution law after fault in distribution networks under different DG penetration rates,the degree of voltage drop at the grid-connected point of DG is used as a partition index to partition the distribution network.Then,iterative computation is performed within each partition,and data are transferred between partitions through split nodes to realize the fast partition calculation of short-circuit current for high proportion DG access to distribution network,which solves the problems of long iteration time and large calculation error of traditional short-circuit current.Finally,a 62-node real distribution network model containing a high proportion of DG access is constructed onMATLAB/Simulink,and the simulation verifies the effectiveness of the short-circuit current partitioning calculation method proposed in the paper,and its calculation speed is improved by 48.35%compared with the global iteration method.

Effects of Spin Transition and Cation Substitution on the Optical Properties and Iron Partitioning in Carbonate Minerals

The high-pressure behavior of deep carbonate dictates the state and dynamics of oxidized carbon in the Earth's mantle,playing a vital role in the global carbon cycle and potentially influencing long-term climate change.Optical absorption and Raman spectroscopic measurements were carried out on two natural carbonate samples in diamond-anvil cells up to 60 GPa.Mg-substitution in high-spin siderite FeCO_(3)increases the crystal field absorption band position by approximately 1000 cm^(-1),but such an effect is marginal at>40 GPa when entering the low-spin state.The crystal field absorption band of dolomite cannot be recognized upon compression to 45.8 GPa at room temperature but,in contrast,the high-pressure polymorph of dolomite exhibits a strong absorption band at frequencies higher than(Mg,Fe)CO_(3)in the lowspin state by 2000–2500 cm^(-1).Additionally,these carbonate minerals show more complicated features for the absorption edge,decreasing with pressure and undergoing a dramatic change through the spin crossover.The optical and vibrational properties of carbonate minerals are highly correlated with iron content and spin transition,indicating that iron is preferentially partitioned into low-spin carbonates.These results shed new light on how carbonate minerals evolve in the mantle,which is crucial to decode the deep carbon cycle.

Slope deformation partitioning and monitoring points optimization based on cluster analysis

The scientific and fair positioning of monitoring locations for surface displacement on slopes is a prerequisite for early warning and forecasting.However,there is no specific provision on how to effectively determine the number and location of monitoring points according to the actual deformation characteristics of the slope.There are still some defects in the layout of monitoring points.To this end,based on displacement data series and spatial location information of surface displacement monitoring points,by combining displacement series correlation and spatial distance influence factors,a spatial deformation correlation calculation model of slope based on clustering analysis was proposed to calculate the correlation between different monitoring points,based on which the deformation area of the slope was divided.The redundant monitoring points in each partition were eliminated based on the partition's outcome,and the overall optimal arrangement of slope monitoring points was then achieved.This method scientifically addresses the issues of slope deformation zoning and data gathering overlap.It not only eliminates human subjectivity from slope deformation zoning but also increases the efficiency and accuracy of slope monitoring.In order to verify the effectiveness of the method,a sand-mudstone interbedded CounterTilt excavation slope in the Chongqing city of China was used as the research object.Twenty-four monitoring points deployed on this slope were monitored for surface displacement for 13 months.The spatial location of the monitoring points was discussed.The results show that the proposed method of slope deformation zoning and the optimized placement of monitoring points are feasible.

Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm

Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of alternatives.Accordingly,assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems.Three methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated methods.In this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on decision-making.The SPC methodology is systematically presented and supported by detailed calculations related to an artificial example.To validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC methods.Comparative analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of criteria.Additionally,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning algorithm.The main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning algorithm.The research demonstrates that the SPC method can be applied to solving different multi-criteria problems.

2D Minimum Compliance Topology Optimization Based on a Region Partitioning Strategy

This paper presents an extended sequential element rejection and admission(SERA)topology optimizationmethod with a region partitioning strategy.Based on the partitioning of a design domain into solid regions and weak regions,the proposed optimizationmethod sequentially implements finite element analysis(FEA)in these regions.After standard FEA in the solid regions,the boundary displacement of the weak regions is constrained using the numerical solution of the solid regions as Dirichlet boundary conditions.This treatment can alleviate the negative effect of the material interpolation model of the topology optimization method in the weak regions,such as the condition number of the structural global stiffness matrix.For optimization,in which the forward problem requires nonlinear structural analysis,a linear solver can be applied in weak regions to avoid numerical singularities caused by the over-deformedmesh.To enhance the robustness of the proposedmethod,the nonmanifold point and island are identified and handled separately.The performance of the proposed method is verified by three 2D minimum compliance examples.

Hybrid Graph Partitioning with OLB Approach in Distributed Transactions

Online Transaction Processing(OLTP)gets support from data partitioning to achieve better performance and scalability.The primary objective of database and application developers is to provide scalable and reliable database systems.This research presents a novel method for data partitioning and load balancing for scalable transactions.Data is efficiently partitioned using the hybrid graph partitioning method.Optimized load balancing(OLB)approach is applied to calculate the weight factor,average workload,and partition efficiency.The presented approach is appropriate for various online data transaction applications.The quality of the proposed approach is examined using OLTP database benchmark.The performance of the proposed methodology significantly outperformed with respect to metrics like throughput,response time,and CPU utilization.

Purification of Moringa oleifera Leaves Protease by Three-Phase Partitioning and Investigation of Its Potential Antibacterial Activity

One of plant-based products for dental care is plant-based proteolytic enzymes which are principally proteases. In order not to damage the protein and bioactive content, an efficient method should be employed for their purifications. As such, three-phase partitioning (TPP) was used to purify protease from moringa (Moringa oleifera). TPP is an emerging, promising, non-chromatographic and economical technology which is simple, quick, efficient and often one-step process for the separation and purification of bioactive molecules from natural sources. It involves the addition of salt (ammonium sulphate) to the crude extract followed by the addition of an organic solvent (butanol). The protein appears as an interfacial precipitate between upper organic solvent and lower aqueous phases. The various conditions such as ammonium sulphate, ratio of crude extract to t-butanol and pH which are required for attaining efficient purification of the protease fractions were optimized. Under optimized conditions, it was seen that, 35% of ammonium sulphate saturation with 1:0.75 ratio of crude extract to t-butanol at pH 7 gave 4.94-fold purification with 96.20% activity yield of protease in the middle phase of the TPP system. The purified enzyme from Moringa oleifera has no antimicrobial effect on the pathogenic bacteria tested. However, this purified enzyme, can be considered as a promising agent, cheap, and safe source which is suitable for using in various industries.

考虑恐慌行人和多救援人员分区引导的疏散研究

为了探究紧急情况下多救援人员对恐慌行人疏散的影响,建立了一个考虑恐慌行人和多救援人员分区引导的元胞自动机扩展模型。首先,在模型中引入了恐慌因子Pm(t)定量反应恐慌情绪对行人疏散的影响;然后,考虑当多个救援人员存在时,协作开展分区救援的行为;最后,通过仿真重点分析了恐慌情绪阈值、救援人员数量及危险源位置对疏散动力学的影响。结果表明:恐慌情绪阈值和危险源位置显著影响人群的恐慌传播过程和疏散过程;救援人员的引导提高了疏散效率;当多名救援人员存在时,实行分区引导更有利于疏散;出现救援人数不足时,根据危险源的位置和恐慌传播过程对疏散的影响合理地分配救援人员能够提高疏散效率。

基于遗传算法的划分序乘积空间问题求解层选择

划分序乘积空间作为一种新的粒计算模型,可以从多个视角和多个层次对问题进行描述和求解.其解空间是由多个问题求解层组成的格结构,其中每个问题求解层由多个单层次视角构成.如何在划分序乘积空间中选择问题求解层是一个NP难问题.为此,提出一种两阶段自适应遗传算法TSAGA(two stage adaptive genetic algorithm)来寻找问题求解层.首先,采用实数编码对问题求解层进行编码,然后根据问题求解层的分类精度和粒度定义适应度函数.算法第1阶段基于经典遗传算法,预选出一些优秀问题求解层作为第2阶段初始种群的一部分,从而优化解空间.算法第2阶段,提出随当前种群进化迭代次数动态变化的自适应选择算子、自适应交叉算子以及自适应大变异算子,从而在优化的解空间中进一步选择问题求解层.实验结果证明了所提方法的有效性.

基于CatBoost算法的配电网分区拓扑辨识

含多分布式电源配电网的拓扑结构具有多样性与多变性,影响拓扑辨识的实时性和准确性。提出一种基于CatBoost算法的配电网分区拓扑辨识方法。构建结合拓扑分区的配电网拓扑辨识框架,采用区域开关状态矩阵描述拓扑结构,以进行物理上的辨识降维;提出基于CatBoost算法的特征选择与拓扑辨识方法,通过分区并行离线训练得到历史拓扑和未知拓扑的区域拓扑辨识CatBoost模型,通过在线应用得到实时的区域开关状态矩阵标签,形成配电网开关状态矩阵,实现系统拓扑辨识。配电网算例系统测试结果验证了所提方法的有效性。

融合内外部特征水印的模型保护方案

针对经典模型水印技术在保护模型所有权过程中存在鲁棒性差、提取率低等问题,融合白、黑盒水印优势,提出了一种特征嵌入的模型保护方案。按照香农熵大小进行数据集样本划分的策略,将数据集样本划分为良性样本、风格迁移样本、关键密钥样本;利用风格迁移样本集对模型嵌入外部特征,将关键密钥样本标签嵌入模型内部特征;通过训练二元分类器并利用掩码梯度下降方法修改极少量参数让模型产生特定输出来综合判断模型是否被窃取。实验结果表明,所提方案用较小开销保证了水印的高保真度,在标签查询、知识蒸馏等攻击下仍具有较高稳定性,且能规避恶意检测风险。

玉米干物质分配与发育进程关系的干旱响应

为深入了解玉米干物质分配(DMP)随发育进程(DVS)的变化及其对干旱的响应机理,并完善玉米DMP参数化方案,基于锦州地区开展4a的玉米营养(VP)和生殖(RP)生长期干旱试验,研究‘丹玉405’和‘先玉335’两个品种玉米地上各器官干物质积累和分配随玉米发育进程的变化及其对干旱的响应特征。结果表明:正常生长情况下,玉米的果穗干重与地上总干重随DVS递增的趋势相似,叶和茎干重随DVS都表现出先增后减趋势;玉米叶干物质分配系数(DMPR)随DVS线性或指数减小,茎DMPR随DVS先增大后减小,最大值出现在开花吐丝期,果穗DMPR随DVS线性增大;叶干物质增长量分配系数(IDMPR)随DVS减小,在乳熟期发生干物质再分配,茎和果穗IDMPR与DVS都呈先增后减的变化特征,茎干物质再分配略晚于叶。土壤干旱情况下,各器官干重随干旱加重而减小;各器官DMPR比干重对干旱的响应偏小且偏晚,其中‘丹玉405’的叶和茎DMPR在玉米生长后期随干旱的加重及发生时间的延后而增大,果穗DMPR的响应与之相反,‘先玉335’各器官DMPR对干旱的响应弱于‘丹玉405’。不同时期干旱使叶、茎和果穗IDMPR较正常值分别偏小、偏大和偏小,叶干物质再分配时间提前。高温和干旱叠加可导致玉米果穗生长停滞,使叶和茎的干物质再分配受到严重抑制,导致DMPR和干重比正常值明显偏大。综合4a试验结果,玉米的干物质积累和DMP随DVS变化及对干旱的响应都表现出明显的种间差异,干旱响应与干旱程度及其发生阶段关系密切。

基于计算机视觉的公路边坡裂缝监测方法

为及时发现裂缝问题并减少潜在的危害,提出一种公路边坡裂缝的自动监测方法。以公路边坡裂缝为研究对象,针对裂缝图像形态不规则、周边环境干扰大的特点,设计了公路边坡裂缝分割网络(slope cracks segmentation network,SCSNet)和公路边坡裂缝几何参数计算方法。该网络首先采用编码器逐渐捕获更高层次的语义特征,其次采用解码器通过逐渐恢复空间信息并结合跳跃连接融合不同尺度间的信息,然后利用通道注意力机制,学习每个通道间的特征,增强裂缝的特征表达。另外,提出参数计算方法,基于连通域分析得到裂缝连通域,并计算裂缝长度、宽度、面积几何参数。实验结果表明:裂缝分割网络的平均交并比达87.86%,该网络能较好地提取公路边坡裂缝特征;裂缝几何参数计算方法能较准确地测算裂缝的当前状态。

面向乳腺超声分类的低尺度形态特征重校准方法

针对乳腺超声图像具有类内差异大、类间差异小以及结节形状复杂多变等问题,提出一种形状特征重校准的乳腺超声图像算法,实现乳腺超声的自动化诊断.首先,构建端到端的网络模型,采用渐进训练方式,充分学习图像中更具辨别力的区域,获取更细粒度的特征信息;其次,提出分区打乱机制,降低网络中打乱图像时破坏结节区域所产生的噪声;然后,将模型底层提取的特征与通过掩膜图像获得的形状特征进行重校准,提出低尺度重校准损失函数;最后,构建一个包含1550张乳腺超声图像数据集LSRD(low-scale recalibration database),验证所提方法的有效性.实验结果表明:本文模型在LSRD上准确率94.3%、敏感性91.2%、特异性93.6%、ROC(receiver operator characteristic curve)与坐标围成的面积(area under curve,AUC)为0.941,均优于对比模型;在BUSI(breast ultrasound image)数据集上,相较于对比模型,其分类精度提升3.3%.

基于系统聚类法的含新能源电力系统分区策略

为实现含新能源电力系统的惯量分布特性的有效评估,提出一种基于系统聚类法的含新能源电力系统分区策略。首先分析新能源机组惯量与同步机组惯量之间的差异;其次构建节点惯量响应模型,分析节点惯量相关因素的特性;然后通过主成分分析对影响节点惯量的主导变量进行降维,将降维后的变量应用系统聚类法对节点进行聚类分区;最后通过系统辨识得到区域惯量,评判出整个系统惯量的空间分布。在仿真软件中搭建改进的IEEE 10机39节点模型验证了分区策略的合理性。

基于高低温分区热管网络的高轨通信卫星散热能力提升方法

针对我国高轨通信卫星不断提升的散热需求,提出采用基于高低温分区热管网络的热设计方法。在分析热管网络散热能力的基础上,进行设备分区布局设计、分区热管网络散热面设计和分区热管网络布局设计。该方法可在保证卫星仪器设备工作温度、不降低热设计可靠性、不增加分系统重量及功率需求的前提下,将卫星散热能力提升15%~20%。文章还结合近些年通信卫星研制中的经验和教训,归纳给出高低温分区热管网络设计中的注意事项,以期为相关工程设计提供有效指导。

替雷利珠单抗较索拉非尼作为晚期不可切除肝细胞癌一线治疗的成本-效用分析

目的对比替雷利珠单抗与索拉非尼用于治疗一线治疗晚期不可切除肝细胞癌的成本-效用,从药物经济学的角度为治疗方案选择提供参考。方法采用分区生存模型,模拟10年内患者使用替雷利珠单抗或者索拉非尼的生存状态,分别计算成本和健康产出,获得增量成本效用比(ICUR)。以3倍的2022年我国人均国内生产总值(GDP)为意愿支付阈值(WTP)。结果在模拟期限内,替雷利珠单抗与索拉非尼方案ICUR为280691.4元/质量调整生命年(QALY),显著高于索拉非尼组,具有明显的经济性。单因素敏感性分析显示,替雷利珠单抗组三级以上不良反应发生率、替雷利珠单抗费用,索拉非尼组三级以上不良反应发生率是影响ICUR的重要因素。概率敏感性分析显示,在WTP为3倍GDP时,替雷利珠单抗有显著成本-效用优势,经济概率为81.4%,结果稳健。结论对于一线治疗晚期不可切除肝细胞癌,替雷利珠单抗比索拉非尼具有显著成本-效用优势。

量子近似优化算法在数字分区问题中的应用

量子近似优化算法(QAOA)是一种近似求解组合优化问题的方法,它通过反复调整电路参数,以获取问题哈密顿量的最大期望值为目的来解决问题,在组合优化问题领域具有广阔的应用前景。将QAOA应用于数字分区问题(二分区问题),通过将问题函数转换成对应的哈密顿量,构造了量子线路,采用线性近似约束优化(COBYLA)方法对电路参数进行了优化,并使用IBMQ模拟平台进行了模拟实验。研究发现量子近似优化算法在数字分区问题中有着良好的性能表现,可在多项式时间内给出问题的解,并且降低了问题的时间复杂度。