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.

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.

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.

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.

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。

考虑次生故障差异化影响下韧性主动提升的输电系统网架重构策略

近年来,我国能源电力加速转型,极端自然灾害频发,国际形势不稳定,使得常规安全风险与非常规安全风险交织,大停电风险有增加的趋势。稳健可靠的网架重构方案对防止恢复中再次发生系统崩溃具有重要意义,针对当前研究中未有效计及恢复中次生故障的不足,该文提出一种考虑次生故障差异化影响下系统韧性主动提升的网架重构策略。首先,讨论在网架重构恢复方案中考虑次生故障影响的必要性;然后,基于分割多目标风险分析方法提出一种系统韧性指标,旨在差异化处理次生故障并突出高风险故障对恢复过程的影响;进一步建立考虑韧性主动提升的网架重构全局优化模型,以增强系统对高风险故障的抵御能力。为提高模型的求解效率,提出一种基于窗口滚动机制的求解策略,可给出兼顾快速性与稳健性的网架重构方案。最后,采用新英格兰10机39节点系统和IEEE 118节点系统验证所提出方法的有效性。

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。

岩体结构面对爆破块度的影响机制研究

结构面对爆破块度形成的影响一直是爆破工程中的热点问题,与工程的长期运行安全和经济效益关系密切。首先基于玉龙喀什水利枢纽开展级配料爆破原位试验,通过对比岩体天然块度与爆破块度的对应关系研究了结构面对爆破块度形成的影响特性,结果表明对于5 mm以下的小粒径块度,爆破荷载与岩石本身的动抗压强度起主要作用;对于中大粒径块度,应力波的扰动和结构面对原始岩体的切割是最重要的影响因素,试验结果表明结构面对级配形成影响具有明显的分区特性;进而采用LS-DYNA的二次开发技术开展爆破块度数值仿真,结果表明由于粉碎区的冲击波峰值大,结构面对小粒径块度的形成影响并不明显,但结构面的存在改变了应力波传播过程,对于中大粒径块度则有明显影响;数值仿真与原位试验相互印证。最后在传统的KUZ-RAM模型基础上,引入修正的小粒径级配预测方法,采用自学习的方式修正岩体参数项,提出了基于分区机制的岩体爆破块度预测模型,结合工程数据与已有的爆破块度预测模型进行验证,结果表明本文所提的爆破级配分区预测模型在预测精度方面有所提高。

筋材布设方式对加筋土挡墙动力响应的影响

针对目前加筋土挡墙设计和施工中筋材布设方式大多为等长形的问题,提出一种倒梯形的筋材布设方式,并基于挡墙位移分区理论和有限差分Flac^(3D)数值模拟,建立加筋土挡墙三维分析模型,探讨不同峰值加速度下3种加筋土挡墙对位移、水平土压力、筋材拉应力及潜在破裂面的影响。结果表明,随峰值加速度增大,挡墙位移逐渐增大,同一荷载作用下,改变筋材布设方式,侧向水平位移减少9.3%,竖向沉降减少5.3%;3种形式挡墙水平土压力相差不大,最大水平土压力分布在挡墙的中下部;筋材拉应力随峰值加速度的增大,沿墙高从单峰型转化为双峰型分布,最大值位于挡墙中下部;潜在破裂面填土区破裂带的形状与筋材的布设方式有关。所提出的倒梯形筋材布设方式对加筋土挡墙的抗震效果更好,可为施工设计中加筋土挡墙筋材布设提供参考。

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.

基于背部受压分区的小学生书包背板设计研究

针对小学生书包背板设计不合理引起的背部疼痛和脊柱侧弯的问题,提出了基于背部受压分区的小学生书包背板三维造型设计。首先,通过对人体背部主要受压区域进行分区,记录受试者背部各区域肌肉群在受压前后完成相应动作的表面肌电信号,分析目标肌肉群的适能性;然后,运用人体测量学方法采集用户的标准背部数据(n=240),结合背部各区域肌肉群的适能性设计书包背板的三维造型并制作样机;最后,召集受试者通过体压分布实验及主观评价对样机与竞品进行验证。实验结果表明:斜方肌和背阔肌区域受压能力较好,竖脊肌区域受压能力较差。样机书包能够把背负压力合理分配到背部分区上,有效避免因压力集中引起的不适和肌肉损伤等危害。

利用伯努利滤波的多目标机动雷达误差配准方法

传统的组网雷达多目标误差配准方法通常假设数据关联关系已知,但在平台机动的情况下,系统同时存在雷达测量偏差和平台姿态角偏差,且雷达观测过程中会受到杂波干扰,导致数据关联尤为困难。针对这一问题,该文提出一种基于伯努利滤波的多目标机动雷达误差配准方法。首先建立系统偏差的量测与状态方程,然后将系统偏差建模成伯努利随机有限集,利用公共坐标系下的原始量测可实现系统偏差在伯努利滤波框架下的递推估计,有效避免了数据关联问题。同时,为了充分利用多目标量测信息,提出一种修正的贪婪量测划分方法,在每个滤波时刻挑选出系统偏差对应的最优量测子集,利用量测子集中的多量测信息实现系统偏差的集中式融合估计,提高了系统偏差的估计精度和收敛速度。仿真实验表明,所提方法能够在数据关联未知的多目标多杂波场景下对雷达测量偏差和平台姿态角偏差进行有效估计,在平台姿态角变化率较低时,所提方法具有较强的适应性。

面向负载均衡的动态均衡分区策略

针对MapReduce计算框架处理倾斜数据集时造成Reduce端出现负载不均衡现象,提出一种动态均衡分区策略。在mapper阶段提出基于分治法的数据切分原则处理任务传入的数据组;结合最佳适应算法思想设计动态分配原则逐步将切分后的数据块均衡分配到预分区链表中;根据分区索引分配到各Reduce节点上实现负载均衡。实验结果显示,动态均衡分区策略与两个基准模型相比任务执行时长平均降低了7.7%,表明动态均衡分区策略更好地解决了数据倾斜问题,降低了任务执行时间,验证了模型的有效性。

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。