Ascertaining the influences of auxiliary qubits on the Einstein–Podolsky–Rosen steering and its directions

Einstein–Podolsky–Rosen(EPR) steering is an example of nontrivial quantum nonlocality and characteristic in the non-classical world.The directivity(or asymmetry) is a fascinating trait of EPR steering,and it is different from other quantum nonlocalities.Here,we consider the strategy in which two atoms compose a two-qubit X state,and the two atoms are owned by Alice and Bob,respectively.The atom of Alice suffers from a reservoir,and the atom of Bob couples with a bit flip channel.The influences of auxiliary qubits on EPR steering and its directions are revealed by means of the entropy uncertainty relation.The results indicate that EPR steering declines with growing time t when adding fewer auxiliary qubits.The EPR steering behaves as damped oscillation when introducing more auxiliary qubits in the strong coupling regime.In the weak coupling regime,the EPR steering monotonously decreases as t increases when coupling auxiliary qubits.The increases in auxiliary qubits are responsible for the fact that the steerability from Alice to Bob(or from Bob to Alice) can be more effectively revealed.Notably,the introductions of more auxiliary qubits can change the situation that steerability from Alice to Bob is certain to a situation in which steerability from Bob to Alice is certain.

A GENERALIZED SCALAR AUXILIARY VARIABLE METHOD FOR THE TIME-DEPENDENT GINZBURG-LANDAU EQUATIONS

This paper develops a generalized scalar auxiliary variable(SAV)method for the time-dependent Ginzburg-Landau equations.The backward Euler method is used for discretizing the temporal derivative of the time-dependent Ginzburg-Landau equations.In this method,the system is decoupled and linearized to avoid solving the non-linear equation at each step.The theoretical analysis proves that the generalized SAV method can preserve the maximum bound principle and energy stability,and this is confirmed by the numerical result,and also shows that the numerical algorithm is stable.

Research on uninterruptable power supply technology for auxiliary winding of electric locomotive while passing the neutral section

Purpose–Auxiliary power system is an indispensable part of the train;the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways,which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters.Powered by DC-link voltage of traction converters,the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking.Meanwhile,powered by traction transformers,the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.Design/methodology/approach–Uninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied.Failure reasons why previous solutions cannot be realized are analyzed.An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper.The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive.This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.Findings–This scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid.Control objectives of uninterrupted power supply technology are proposed,which are no overvoltage,no overcurrent and uninterrupted power supply.Originality/value–The control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section.Furthermore,this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

Effect of endoscopic full-thickness resection assisted by distal serosal turnover with floss traction for gastric submucosal masses

BACKGROUND Complex and high-risk surgical complications pose pressing challenges in the clinical implementation and advancement of endoscopic full-thickness resection(EFTR).Successful perforation repair under endoscopy,thereby avoiding surgical intervention and postoperative complications such as peritonitis,are pivotal for effective EFTR.AIM To investigate the effectiveness and safety of EFTR assisted by distal serosal inversion under floss traction in gastric submucosal tumors.METHODS A retrospective analysis of patients with gastric and duodenal submucosal tumors treated with EFTR assisted by the distal serosa inversion under dental floss traction from January 2023 to January 2024 was conducted.The total operation time,tumor dissection time,wound closure time,intraoperative bleeding volume,length of hospital stay and incidence of complications were analyzed.RESULTS There were 93 patients,aged 55.1±12.1 years.Complete tumor resection was achieved in all cases,resulting in a 100% success rate.The average total operation time was 67.4±27.0 min,with tumor dissection taking 43.6±20.4 min.Wound closure times varied,with gastric body closure time of 24.5±14.1 min and gastric fundus closure time of 16.6±8.7 min,showing a significant difference(P<0.05).Intraoperative blood loss was 2.3±4.0 mL,and average length of hospital stay was 5.7±1.9 d.There was no secondary perforation after suturing in all cases.The incidence of delayed bleeding was 2.2%,and the incidence of abdominal infection was 3.2%.No patient required other surgical intervention during and after the operation.CONCLUSION Distal serosal inversion under dental-floss-assisted EFTR significantly reduced wound closure time and intraoperative blood loss,making it a viable approach for gastric submucosal tumors.

Auxiliary Software for Defining the Parameters of the Structural Organization of a Complex System

The developed auxiliary software serves to simplify, standardize and facilitate the software loading of the structural organization of a complex technological system, as well as its further manipulation within the process of solving the considered technological system. Its help can be especially useful in the case of a complex structural organization of a technological system with a large number of different functional elements grouped into several technological subsystems. This paper presents the results of its application for a special complex technological system related to the reference steam block for the combined production of heat and electricity.

Roles of HIV-1 auxiliary proteins in viral pathogenesis and host-pathogen interactions

Active host-pathogen interactions take place during infection of human immunodeficiency virus type 1 (HIV-1). Outcomes of these interactions determine the efficiency of viral infection and subsequent disease progression. HIV- infected cells respond to viral invasion with various defensive strategies such as innate, cellular and humoral immune antiviral mechanisms. On the other hand, the virus has also developed various offensive tactics to suppress these host cellular responses. Among many of the viral offensive strategies, HIV-1 viral auxiliary proteins (Tat, Rev, Nef, Vif, Vpr and Vpu) play important roles in the host-pathogen interaction and thus have significant impacts on the outcome of HIV infection. One of the best examples is the interaction of Vif with a host cytidine deaminase APOBEC3G. Although specific roles of other auxiliary proteins are not as well described as Vif-APOBEC3G interaction, it is the goal of this brief review to summarize some of the preliminary findings with the hope to stimulate further discussion and investiga- tion in this exhilarating area of research.

Evolutionary Multitasking With Global and Local Auxiliary Tasks for Constrained Multi-Objective Optimization

Constrained multi-objective optimization problems(CMOPs) include the optimization of objective functions and the satisfaction of constraint conditions, which challenge the solvers.To solve CMOPs, constrained multi-objective evolutionary algorithms(CMOEAs) have been developed. However, most of them tend to converge into local areas due to the loss of diversity. Evolutionary multitasking(EMT) is new model of solving complex optimization problems, through the knowledge transfer between the source task and other related tasks. Inspired by EMT, this paper develops a new EMT-based CMOEA to solve CMOPs, in which the main task, a global auxiliary task, and a local auxiliary task are created and optimized by one specific population respectively. The main task focuses on finding the feasible Pareto front(PF), and global and local auxiliary tasks are used to respectively enhance global and local diversity. Moreover, the global auxiliary task is used to implement the global search by ignoring constraints, so as to help the population of the main task pass through infeasible obstacles. The local auxiliary task is used to provide local diversity around the population of the main task, so as to exploit promising regions. Through the knowledge transfer among the three tasks, the search ability of the population of the main task will be significantly improved. Compared with other state-of-the-art CMOEAs, the experimental results on three benchmark test suites demonstrate the superior or competitive performance of the proposed CMOEA.

Auxiliary guidance manufacture and revealing potential mechanism of perovskite solar cell using machine learning

To promote the development of global carbon neutrality,perovskite solar cells(PSCs)have become a research hotspot in related fields.How to obtain PSCs with expected performance and explore the potential factors affecting device performance are the research priorities in related fields.Although some classical computational methods can facilitate material development,they typically require complex mathematical approximations and manual feature screening processes,which have certain subjectivity and one-sidedness,limiting the performance of the model.In order to alleviate the above challenges,this paper proposes a machine learning(ML)model based on neural networks.The model can assist both PSCs design and analysis of their potential mechanism,demonstrating enhanced and comprehensive auxiliary capabilities.To make the model have higher feasibility and fit the real experimental process more closely,this paper collects the corresponding real experimental data from numerous research papers to develop the model.Compared with other classical ML methods,the proposed model achieved better overall performance.Regarding analysis of underlying mechanism,the relevant laws explored by the model are consistent with the actual experiment results of existing articles.The model exhibits great potential to discover complex laws that are difficult for humans to discover directly.In addition,we also fabricated PSCs to verify the guidance ability of the model in this paper for real experiments.Eventually,the model achieved acceptable results.This work provides new insights into integrating ML methods and PSC design techniques,as well as bridging photovoltaic power generation technology and other fields.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

Multi-Objective Optimization Analysis of Auxiliary Flux Modulator Magnetic Gear with Unequal Magnetic Poles

To enhance the output torque and minimize the torque ripple of coaxial magnetic gear(CMG),a novel auxiliary flux modulator CMG with unequal magnetic poles is proposed.This design incorporates an inner rotor with an asymmetric sector and a trapezoidal combined N-S pole structure,featuring Halbach arrays for the arrangement of permanent magnets(PMs).The outer rotor PMs adopt a Spoke-type configuration.To optimize the CMG for high output torque and low torque ripple,a sensitivity analysis is conducted to identify key size parameters that significantly influence the optimization objectives.Based on the sensitivity hierarchy of these parameters,a multi-objective optimization analysis is performed using a genetic algorithm(GA)to determine the optimal structural parameter values of the CMG.In addition,a coaxial magnetic gear(CMG)topology with 4 inner and 17 outer pole pairs is adopted,and the parametric model is established.Finally,the electromagnetic properties of the CMG are evaluated using the finite element method.The results indicate a remarkable reduction in torque ripple,specifically by 46.15%.

Auxiliary Classifier of Generative Adversarial Network for Lung Cancer Diagnosis

The classification of lung nodules is a challenging problem as the visual analysis of the nodules and non-nodules revealed homogenous textural patterns.In this work,an Auxiliary Classifier(AC)-Generative Adversarial Network(GAN)based Lung Cancer Classification(LCC)system is developed.The pro-posed AC-GAN-LCC system consists of three modules;preprocessing,Lungs Region Detection(LRD),and AC-GAN classification.A Wienerfilter is employed in the preprocessing module to remove the Gaussian noise.In the LRD module,only the lung regions(left and right lungs)are detected using itera-tive thresholding and morphological operations.In order to extract the lung region only,floodfilling and background subtraction.The detected lung regions are fed to the AC-GAN classifier to detect the nodules.It classifies the nodules into one of the two classes,i.e.,binary classification(such as nodules or non-nodules).The AC-GAN is the extended version of the conditional GAN that predicts the label of a given image.Three different optimization techniques,adaptive gradient optimi-zation,root mean square propagation optimization,and Adam optimization are employed for optimizing the AC-GAN architecture.The proposed AC-GAN-LCC system is evaluated on the Lung Image Database Consortium(LIDC)data-base Computed Tomography(CT)scan images.The proposed AC-GAN-LCC system classifies∼15000 CT slices(7310 non-nodules and 7685 nodules).It pro-vides an overall accuracy of 98.8%on the LIDC database using Adam optimiza-tion by a 10-fold cross-validation approach.

国医大师熊继柏治疗失眠的方药规律分析

目的对国医大师熊继柏教授治疗失眠的病案进行数据挖掘,分析熊继柏教授诊治失眠的用方、用药经验。方法基于中医传承辅助平台软件(V3.5),归纳和分析熊继柏教授在湖南中医药大学第一附属医院治疗失眠患者的门诊病历数据,利用该平台软件的关联规则、复杂系统熵聚类等统计方法进行数据挖掘和分析,总结药物的性味、归经、应用频次、药对组合及合方,对“证-症-方”“证-症-药”“证-方-药”进行关联,结合熊继柏教授对失眠病因病机、治则治法的认识,明确核心用药,探索其对失眠的诊治规律及遣方用药心得。结果通过总结分析,共纳入病历276份,处方中用药频次较多的有酸枣仁、龙齿、茯神、甘草,重在补虚安神;黄连、陈皮、竹茹、半夏、珍珠母、远志,重在清热化痰安神。用药性味偏甘、苦、辛,归经多为心、脾经。并归纳出虚证治疗常用合方为酸枣仁汤、枕中丹和甘麦大枣汤;因痰所致失眠治疗的主方为温胆汤及温胆汤类方(枣仁温胆汤、黄连温胆汤及十味温胆汤)。结论国医大师熊继柏治疗失眠以“补脾化痰清热,养血补肝宁心”为治疗原则,以温胆汤为基础进行加减化裁。

三电平辅助变流器寿命优化控制

辅助变流系统是动车组车辆上关键的电气组成部分,主要为空调机组、风机、照明等交流负载提供稳定的三相电源。结温是影响动车组三电平辅助变流器IGBT(Insulated-gate Bipolar Transistor)模块寿命的主要因素。为了提高动车组三电平中点钳位(Neutral-Point Clamped,NPC)型辅助变流器寿命,提出一种降低结温的模型预测电流控制(Model Predictive Current Control,MPCC)策略。首先,考虑传统MPCC在每个采样周期需要代入27个电压矢量循环计算,计算量较大,因此将三电平基本电压矢量划分在间隔60°的6个扇区中,通过计算电压矢量在两相静止坐标下的相角,进而判断参考电压矢量所处扇区,将备选矢量数目从27缩减至10,减少了计算量;其次,传统MPCC直接应用于动车组辅助变流器会使IGBT模块的结温较高,老化速度加快,对变流器安全稳定运行产生不可预测的损害,本文对IGBT模块的开关损耗和导通损耗进行近似等效,得到了和集射极电压、集电极电流相关的功率损耗因子。通过预测每相电流的方向,进而预测IGBT模块的开关和导通情况,动态加入功率损耗因子,并在代价函数中约束每相IGBT及其续流二极管(Free Wheeling Diode,FWD)的功率损耗,使得最优电压矢量在降低功率损耗的同时保证一定的控制性能。通过仿真与实验验证,本文所提方法相比传统MPCC策略降低了功率器件的结温,提高了变流器寿命。

MATLAB在“张量分析”课程教学中的应用

张量分析是一种重要的数学工具,它在相对论、电磁场论和连续介质力学等诸多学科都有着广泛的应用。掌握这种数学工具,已成为从事相关科学研究的必备基础。然而,张量分析中非欧几里得空间局部切标架的存在,增加了张量计算和分析的复杂性。学生在学习“张量分析”课程时面临着抽象概念和复杂公式的理解上的困难。本文提出利用MATLAB工具在绘图、脚本编程和符号推导等方面的强大功能,从旋度分析、坐标变换和定理辅助证明这三个方面,并结合MATLAB脚本代码,展示MATLAB工具辅助于该课程教学的重要作用。教师借助该工具开展课程教学,将帮助学生有效提高对张量分析知识的理解。学生掌握了该课程的基础知识后,便能进一步使用MATLAB的张量工具箱或Pytorch深度学习库进行张量运算操作。

滤波辨识(10):多变量Box-Jenkins系统的滤波辅助模型递阶广义增广参数辨识

针对多变量Box-Jenkins模型,即多变量输出误差自回归滑动平均(M-OEARMA)系统,利用滤波辨识理念和辅助模型辨识思想,研究和提出了滤波辅助模型递阶广义增广随机梯度辨识方法、滤波辅助模型递阶多新息广义增广随机梯度辨识方法、滤波辅助模型递阶广义增广递推梯度辨识方法、滤波辅助模型递阶多新息广义增广递推梯度辨识方法、滤波辅助模型递阶广义增广最小二乘辨识方法、滤波辅助模型递阶多新息广义增广最小二乘辨识方法。这些滤波辅助模型递阶广义增广辨识方法可以推广到其他有色噪声干扰下的线性和非线性多变量随机系统中。

砻谷机转子系统结构参数辅助计算系统的设计与实现

[目的]提高胶辊砻谷机转子系统机械工作效率。[方法]基于VB与Matlab平台开发可在Windows系统下独立安装运行的胶辊砻谷机转子系统结构参数辅助计算系统(RRHRSPD)。根据等效设计方法和传统机械设计方法建立了砻谷机的工艺参数、动力参数、结构参数间的耦联关系,探明了转子系统结构参数的设计计算原理;采用VB开发系统操作界面并实时调用Matlab动态链接库,形成系统的核心运算机制,并对系统进行封装发布。[结果]开发了一套胶辊砻谷机转子系统结构参数辅助计算系统。[结论]该系统的计算结果准确、可靠,不仅可用于砻谷机转子系统机械结构的设计计算,也可用于砻谷机性能分析的虚拟试验平台。

基于新能源发电改进型移相全桥变换器研究

新能源发电中需要广泛使用移相全桥变换器,以实现软开关技术从而减小系统的开关损耗。而传统移相全桥直流变换器滞后臂在轻载时难以实现ZVS,导致系统大功率输出时效率降低以及系统换路时容易产生尖峰电压、电流等现象,针对这一问题,提出了一种改进的有源软开关移相全桥DC-DC变换器拓扑。系统首先提出了改进变换器的拓扑结构,在此基础上对其工作模态进行了研究分析,并合理优化相关器件的选型,最后通过系统仿真及试验平台进行了系统仿真和试验测试,结果表明,所设计的加入辅助电路改进型移相全桥直流变换器在轻载情况下,能够使变换器滞后臂达到软开关效果,同时,在大功率输出情况下,对器件发热、电压波形振荡均有较好的抑制作用,系统整体效率变高,同时可靠性、稳定性变强。

薄壁结构件的正向吸附辅助支撑钻削工艺研究

航空航天领域中薄壁结构件的连接装配要求加工高精度的连接孔,但此类结构件钻削加工时变形大、易振动,严重影响制孔精度和表面质量,传统装夹方法存在装夹跨距大、难以充分有效支撑等问题。本文提出通过正向吸附辅助支撑,提高薄壁结构件加工时的局部刚度,进而提高薄壁结构件的加工质量,并通过仿真和试验相结合的方式研究了正向吸附辅助支撑对薄壁结构件钻削加工的影响。结果表明,在本文仿真和试验条件下,正向吸附辅助支撑可使钻削位置刚度提升40倍以上,孔壁粗糙度值降低67%以上,圆度公差降低60%以上,孔径偏差降低50%以上,同一孔的靠近出口、入口位置的孔径偏差降低90%以上。可见,正向吸附辅助支撑可显著提高薄壁结构件的制孔精度和质量。

基于多尺度细节增强的脑瘤图像分割研究

针对脑瘤图像分割网络的跳跃连接引起的语义特征传递不平衡,以及多尺度特征关联不足,导致细节特征丢失,从而造成对细小目标肿瘤的分割精度不佳的问题,提出一种改进的Res-Unet框架的分割模型。该模型引入多尺度注意力融合模块,通过混合多尺度特征使模型更好地适应不同尺寸的肿瘤;该模型在跳跃连接中引入空间注意力模块,增强特征表达同时避免无用信息的干扰,保留特征图空间细节特征;最后通过辅助分类器模块,在解码器部分对不同尺度特征图进行特征预测。使用BraTS2020数据集进行实验和评估,使用Dice系数来评估模型分割效果。结果显示,改进的网络在全肿瘤区域、肿瘤核心区域和增强肿瘤区域的Dice系数分别为0.8877、0.8229、0.8027,相比于通道注意力模型增强肿瘤区域和肿瘤核心区域的系数分别提升2.6%和0.14%,证明改进模型在脑瘤核磁共振图像分割的有效性和精确性。

血压变异性对移植物动静脉内瘘功能的影响

目的探讨血液透析患者血压变异性对移植物动静脉内瘘(arteriovenous graft,AVG)功能的影响。方法回顾性收集2020年12月用AVG为血管通路的患者作为研究对象,分析其连续4周血液透析时血压变异性,根据血压变异性中位数分为对照组(血压变异性>17.3,n=40)和观察组(血压变异性≤17.3,n=40),观察其血栓发生率及辅助初级通畅率,探讨其相关性。结果共纳入80例患者,观察1年内临床数据。对照组和观察组AVG血栓形成率分别为77.5%(31/40)和22.5%(9/40),2组比较差异有统计学意义(χ^(2)=24.200,P<0.001);对照组12个月辅助初级通畅率低于观察组(Log-rank χ^(2)=63.870,P<0.001)。结论血压变异性越高,血流动力学变化越大,移植物动静脉内瘘血栓形成的风险越高,建议临床上定期评估患者透析中血压变异性,并采取针对性的干预措施,降低血栓形成,提高辅助初级通畅率。