Impact of initial fluctuations and nuclear deformations in isobar collisions

Relativistic isobar^(96)_(44)Ru+^(96)_(44)Ru and^(96)_(40)Zr+^(96)_(40)Zrcollisions have revealed intricate differences in their nuclear size and shape,inspiring unconventional studies of nuclear structure using relativistic heavy ion collisions.In this study,we investigate the relative differences in the mean multiplicityR_(<Nch>)and the secondR_(ε2)and third-order eccentricityR_(ε3)between isobar collisions using initial state Glauber models.It is found that initial fluctuations and nuclear deformations have negligible effects on R_(<Nch>)in most central collisions,while both are important for the R_(ε2)and R_(ε3),the degree of which is sensitive to the underlying nucleonic or sub-nucleonic degree of freedom.These features,compared to real data,may probe the particle production mechanism and the physics underlying nuclear structure.

Experimental study on temperature fluctuations on plate surface induced by coaxial-jet flow

In nuclear reactors,temperature fluctuations of fluids may cause fatigue damage to adjacent structures;this is referred to as thermal striping.Research on thermal striping in the upper plenum has mainly focused on fluid fields.Few experimental studies have been reported on solid structures in a fluid field with a coaxial jet.This study entailed an experimental study of the temperature fluctuations in the fluid and on a plate surface caused by a coaxial jet.The temperature fluctuations of the fluid and plate surfaces located at different heights were analyzed.The cause of the temperature fluctuation was analyzed using a transient temperature distribution.The results show that the mixing of the hot and cold fluids gradually becomes uniform in the positive axial direction.The average surface temperatures tended to be consistent.When the jet reaches the plate surface,the swing of the jet center,contraction and expansion of the cold jet,and changes in the jet shape result in temperature fluctuations.The intensity of the temperature fluctuation was affected by the position.More attention should be paid when the plate is located at a lower height,and between the hot and cold-fluid nozzles.

Influence of blood glucose fluctuations on chemotherapy efficacy and safety in type 2 diabetes mellitus patients complicated with lung carcinoma

BACKGROUND Patients with type 2 diabetes mellitus(T2DM)have large fluctuations in blood glucose(BG),abnormal metabolic function and low immunity to varying degrees,which increases the risk of malignant tumor diseases and affects the efficacy of tumor chemotherapy.Controlling hyperglycemia may have important therapeutic implications for cancer patients.AIM To clarify the influence of BG fluctuations on chemotherapy efficacy and safety in T2DM patients complicated with lung carcinoma(LC).METHODS The clinical data of 60 T2DM+LC patients who presented to the First Affiliated Hospital of Ningbo University between January 2019 and January 2021 were retrospectively analyzed.All patients underwent chemotherapy and were grouped as a control group(CG;normal BG fluctuation with a mean fluctuation<3.9 mmol/L)and an observation group(OG;high BG fluctuation with a mean fluctuation≥3.9 mmol/L)based on their BG fluctuations,with 30 cases each.BGrelated indices,tumor markers,serum inflammatory cytokines and adverse reactions were comparatively analyzed.Pearson correlation analysis was performed to analyze the correlation between BG fluctuations and tumor markers.RESULTS The fasting blood glucose and 2-hour postprandial blood glucose levels in the OG were notably elevated compared with those in the CG,together with markedly higher mean amplitude of glycemic excursions(MAGE),mean of daily differences,largest amplitude of glycemic excursions and standard deviation of blood glucose(P<0.05).In addition,the OG exhibited evidently higher levels of carbohydrate antigen 19-9,carbohydrate antigen 125,carcinoembryonic antigen,neuron-specific enolase,cytokeratin 19,tumor necrosis factor-α,interleukin-6,and highsensitivity C-reactive protein than the CG(P<0.05).Pearson analysis revealed a positive association of MAGE with serum tumor markers.The incidence of adverse reactions was significantly higher in the OG than in the CG(P<0.05).CONCLUSION The greater the BG fluctuation in LC patients after chemotherapy,the more unfavorable the therapeutic effect of chemotherapy;the higher the level of tumor markers and inflammatory cytokines,the more adverse reactions the patient experiences.

Dynamic grouping control of electric vehicles based on improved k-means algorithm for wind power fluctuations suppression

To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs based on an improved k-means algorithm.First,a swing door trending(SDT)algorithm based on compression result feedback was designed to extract the feature data points of wind power.The gating coefficient of the SDT was adjusted based on the compression ratio and deviation,enabling the acquisition of grid-connected wind power signals through linear interpolation.Second,a novel algorithm called IDOA-KM is proposed,which utilizes the Improved Dingo Optimization Algorithm(IDOA)to optimize the clustering centers of the k-means algorithm,aiming to address its dependence and sensitivity on the initial centers.The EVs were categorized into priority charging,standby,and priority discharging groups using the IDOA-KM.Finally,an two-layer power distribution scheme for EVs was devised.The upper layer determines the charging/discharging sequences of the three EV groups and their corresponding power signals.The lower layer allocates power signals to each EV based on the maximum charging/discharging power or SOC equalization principles.The simulation results demonstrate the effectiveness of the proposed control strategy in accurately tracking grid power signals,smoothing wind power fluctuations,mitigating EV degradation,and enhancing the SOC balance.

A new electromagnetic probe array diagnostic for analyzing electrostatic and magnetic fluctuations in EAST plasmas

A novel electromagnetic probe array(EMPA) diagnostic, which consists of a magnetic probe array and an electrostatic probe array, has recently been developed on EAST. The EMPA is fixed near the first wall at horizontal port P. The magnetic probe array of the EMPA consists of 24 identical magnetic probes, each of them capable of measuring toroidal, poloidal and radial magnetic fluctuations simultaneously, providing additional toroidal magnetic fluctuation measurements compared with the regular magnetic probes on EAST. With a higher sampling rate and self-resonant frequency, the EMPA magnetic probes can provide higher frequency magnetic fluctuation measurements. The magnetic probe array of the EMPA is composed of two parallel layers of magnetic probes with a radial distance of 63 mm, and each layer of magnetic probes is arranged in four poloidal rows and three toroidal columns. The compact arrangement of the EMPA magnetic probe array largely improves the toroidal mode number measurement ability from-8≤ n≤ 8 to-112≤ n≤ 112, and also improves the high poloidal wave number measurement ability of magnetic fluctuations compared with the regular high frequency magnetic probes on EAST. The electrostatic probe array of the EMPA consists of two sets of four-tip probes and a single-tip probe array with three poloidal rows and four toroidal columns. It complements the electrostatic parameter measurements behind the main limiter and near the first wall in EAST. The engineering details of the EMPA diagnostic, including the mechanical system, the electrical system, the acquisition and control system, and the effective area calibration, are presented. The preliminary applications of the EMPA in L-mode and H-mode discharges on EAST have demonstrated that the EMPA works well for providing information on the magnetic and electrostatic fluctuations and can contribute to deeper physical analysis in future EAST experiments.

A Cross-Seasonal Linkage between Arctic Sea Ice and Eurasian Summertime Temperature Fluctuations

This study explores the linkage between summertime temperature fluctuations over midlatitude Eurasia and the preceding Arctic sea ice concentration (SIC) by utilizing the squared norm of the temperature anomaly, the essential part of local eddy available potential energy, as a metric to quantify the temperature fluctuations with weather patterns on various timescales. By comparing groups of singular value decomposition (SVD) analysis, we suggest a significant linkage between strong (weak) August 10-to-30-day temperature fluctuations over mid-west Asia and enhanced (decreased) Barents-Kara Sea ice in the previous February. We find that when the February SIC increases in the Barents-Kara Sea, a zonal dipolar pattern of SST anomalies appears in the Atlantic subpolar region and lasts from February into the summer months. Evidence suggests that in such a background state, the atmospheric circulation changes evidently from July to August, so that the August is characterized by an amplified meridional circulation over Eurasia, weakened westerlies, and high- pressure anomalies along the Arctic coast. Moreover, the 10-to-30-day wave becomes more active in the North Atlantic-Barents-Kara Sea-Central Asia regions and manifests a more evident southward propagation from the Barents- Kara Sea into the Ural region, which is responsible for the enhanced 10-to-30-day wave activity and temperature fluctuations in the region.

UAV-Assisted FSO Communication System with Amplify-and-Forward Protocol under AOA Fluctuations:A Performance Analysis

Free space optical(FSO)communication has recently aroused great interest in academia due to its unique features,such as large transmission band,high data rates,and strong anti-electromagnetic interference.With the aim of evaluating the performance of an FSO communication system and extending the line-of-sight transmission distance,we propose an unmanned aerial vehicle(UAV)-assisted dual-hop FSO communication system equipped with amplifyand-forward protocol at the relay node.Specifically,we consider impairments of atmospheric absorption,pointing errors,atmospheric turbulence,and link interruptions due to angle-of-arrival fluctuations in the relay system.The Gamma-Gamma and Malaga distributions are used to model the influence of atmospheric turbulence on the source-to-UAV and UAVto-destination links,respectively.We derive closedform expressions of the probability density function(PDF)and cumulative distribution function(CDF)for the proposed communication system,in terms of the Meijer-G function.Based on the precise PDF and CDF,analytical expressions for the outage probability,average bit error rate,and ergodic capacity are proposed with the aid of the extended generalized bivariate Fox’s H function.Finally,we show that there is a match between the analytical results and numerical results,and we analyze the influence of the system and channel parameters on the performance.

Investigations of moiréartifacts induced by flux fluctuations in x-ray dark-field imaging

X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from the acquired phasestepping data.The retrieval process assumes a constant phase step size and a constant flux for each stepped grating position.However,stepping errors and flux fluctuations inevitably occur due to external vibrations and/or thermal drift during data acquisition.Previous studies have shown that those influences introduce errors in the acquired phase-stepping data,which cause obvious moiréartifacts in the retrieved refraction image.This work investigates moiréartifacts in x-ray dark-field imaging as a result of flux fluctuations.For the retrieved mean intensity,amplitude,visibility and dark-field images,the dependence of moiréartifacts on flux fluctuation factors is theoretically derived respectively by using a first-order Taylor series expansion.Results of synchrotron radiation experiments verify the validity of the derived analytical formulas.The spatial frequency characteristics of moiréartifacts are analyzed and compared to those induced by phase-stepping errors.It illustrates that moiréartifacts can be estimated by a weighted mean of flux fluctuation factors,with the weighting factors dependent on the moiréphase and different greatly for each retrieved image.Furthermore,moiréartifacts can even be affected by object’s features not displayed in the particular contrast.These results can be used to interpret images correctly,identify sources of moiréartifacts,and develop dedicated algorithms to remove moiréartifacts in the retrieved multi-contrast images.

Stochastic fluctuations in the rotation of the bacterial flagellar motor

The bacterial flagellar motor is a nanometer-sized rotary motor that generates the torque to drive the rotation of the flagellar filament.The output torque is an important property of the motor.The motor rotation was usually monitored by attaching aμm-sized bead to a shortened flagellar filament,and the torque was extracted by calculating the torque due to the viscous drag of the medium on the bead rotation.We sought for an independent extraction of the torque from thermal fluctuation in the motor rotation using the fluctuation theorem(FT).However,we identified an overwhelming fluctuation beyond the thermal noise that precluded the use of FT.We further characterized the timescale and the amplitude of this fluctuation,finding that it was probably due to the stepping of the motor.The amplitude of torque fluctuation we characterized here provided new information on the torque-generating interaction potential curve.

Prediction of NFT Sale Price Fluctuations on OpenSea Using Machine Learning Approaches

The rapid expansion of the non-fungible token(NFT)market has attracted many investors.However,studies on the NFT price fluctuations have been relatively limited.To date,the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction.The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea,the world’s largest NFT marketplace.We used Python programs to collect data and summarized them as:NFT information,collection information,and related account information.AdaBoost and Random Forest(RF)algorithms were employed to predict the sale price and price fluctuation of NFTs using regression and classification models,respectively.We found that the NFT related account information,especially the number of favorites and activity status of creators,confer a good predictive power to both the models.AdaBoost in the regression model had more accurate predictions,the root mean square error(RMSE)in predicting NFT sale price was 0.047.In predicting NFT sale price fluctuations,RF performed better,which the area under the curve(AUC)reached 0.956.We suggest that investors should pay more attention to the information of NFT creators.We anticipate that these prediction models will reduce the number of investment failures for the investors.

Impact of Sharp Fluctuations of Live Pig Prices on Financial Capacity of Pig Breeding Enterprises : An Analysis Based on the Data of Listed Enterprises from 2018 to 2021

Based on the general equilibrium theory of microeconomics,this study first analyzed the causes of sharp fluctuations in live pig prices,and then explored the financial capabilities of enterprises during the sharp fluctuations of live pig prices by using the financial data of 4 typical top listed enterprises from 2018 to 2021.By comparing the changes in the capabilities of enterprises,the impact of price on the financial capability of enterprises and differences were identified.The research results showed that the price of live pigs played a decisive role in enterprise profits,and there were huge differences in the fluctuation period.In the sharp increase period of price,price temptation is easy to cause enterprises to over-invest,resulting in excessive growth of enterprise assets,and increasing the business risk of enterprises.Based on the above conclusions,some policy suggestions were put forward to promote the stable development of industry from the three levels of enterprises,industries and government departments.

Vacuum Correlations, Detector Efficiency Fluctuations and Classical Dynamic Violations of CH-Inequality

We study in this paper the possible influence of vacuum fluctuations on photo detection and its background noise in Bell tests. We analyze its consequences on the standard statistical analysis of data showing that it is not fulfilled anymore the conventional hypothesis of a Poisson like probability density distribution of single photodetection events. We assume that vacuum fluctuations are due to real and measurable fluctuating fields, as recently confirmed experimentally, and that their non null correlations outside the light cone contribute to photon coincidence rates making them time dependent. We introduce a generalized Bell like correlation function which contains a new term due to supposed vacuum induced photon counting events. We deduce then a generalization of CH-inequality which takes in account the effect of these vacuum electric fields on detector efficiency. We predict an apparatus temperature fluctuations during photon detection which we suggest could be observed by looking for colored noise thermal emission of the photodetectors, generalizing the standard white noise prediction of C.S.L. models on wave function collapse postulate. We discuss an experimental test of this prediction, based on the idea of inducing a thermal wave on the whole quantum detectors, aimed to observe time dependent deviations from standard stationary statistical predictions of Quantum Mechanics.

某型航空发动机振动值波动故障诊断和排除

针对某型航空发动机试车过程中的稳态振动波动问题,开展了时域和频域分析,指出振动波动是由于低压2倍频和高压基频振动拍振所引起。推导了航空发动机拍振引起的振动响应,建立了某型航空发动机双转子动力学模型,并进行了仿真分析。仿真结果表明,当发动机两个激振力频率相近时,会产生拍振引起振动波动,仿真结果与试验结果相吻合。结合发动机结构和其工作特点,分析了发动机形成低压倍频-高压基频耦合拍振的条件,给出了拍振排除方法,并通过试验验证了方法的正确性。工程上可以通过调整高压和低压转子转差关系,将转速比调整到合理范围内即可消除拍振。

平抑风电波动的电-氢混合储能容量优化配置

针对电-氢混合系统协同平抑接入新型电力系统的新能源波动问题,提出考虑碱性电解槽运行特性的电-氢混合储能容量优化配置方案。首先,基于经验模态分解,将原始风电功率信号分解为符合波动量限值的直接并网分量和混合储能功率任务;在综合考虑电化学储能和氢储能介质充放电功率约束和存储状态约束的基础上,制定计及碱性电解槽运行特性的混合储能能量管理策略。基于此策略,以综合成本最小为目标,建立用于平抑风电波动的电-氢混合储能容量配置模型,并通过实际数据进行计算分析。算例结果表明,所提策略下的容量配置方案,在满足平抑需求的前提下,可以有效提高系统经济性。

考虑奖励机制的电动汽车充电优化引导策略

随着电动汽车(electric vehicle,EV)的大规模推广,其无序充电严重威胁电网的安全稳定运行,积极引导EV用户参与充电优化策略,对于提高电网的安全稳定性具有重要意义。为此,基于充电优化管理调度思路,提出一种考虑奖励机制的EV充电优化引导策略,在分时电价的基础上,计入用户在降低电网负荷波动中的奖励机制,考虑充电位置固定、不确定用户的出行需求,确定EV的充电时间及充电位置,达到用户满意度最高的目的;利用EV动态响应的实时优化算法,对所提的优化调度模型进行求解。仿真结果验证了所提策略的有效性和可行性,该优化调度策略不仅能有效改善负荷低谷时段集中充电形成新的负荷高峰的问题,而且可明显降低用户的充电成本及电网负荷波动。

矿产勘查市场周期性波动与我国矿产勘查趋势分析

在社会经济发展的驱动下,矿产勘查市场具有明显的周期性波动,包括长周期变化、中短周期变化和随机性变化。澳大利亚50年矿产勘查市场变化表明,经济发展的长周期变化决定了矿产资源供需关系基本面,矿产资源供需关系基本面决定了矿产勘查投入的长周期变化;经济发展中短周期变化决定了矿产品价格周期性变化,矿产品价格周期性变化决定了矿产勘查投入的中短周期变化。在国家新一轮找矿突破战略行动驱动下,我国矿产勘查活动进入新一轮增长周期,并呈现出与全球不同的变化特征。2020年以来,我国矿产勘查投入连续4年实现增长,且增速逐年扩大,2023年同比增长25.4%,矿产勘查市场内生回升动力不断增强。2016年之后,主要受国内政策环境的影响,我国矿产勘查投入变化偏离了全球勘查市场走势。综合判断,我国矿产勘查市场正处在长中短周期叠加、政策环境发生明显改善的特殊阶段。经济发展长周期变化和中短周期变化对矿产勘查投入形成较大的下行压力,而政策环境改善对市场形成了较强的上行拉力,未来2~3 a将是政策红利集中释放的时间,本轮矿产勘查增长周期可能将延续2~3 a时间。

计及SOC自恢复的混合储能平抑风电功率波动控制

混合储能系统能够较好地应对复杂的风电波动,有效地提高电网的稳定性和安全性。在混合储能平抑风电功率波动的典型应用场景下,该文首先提出一种计及荷电状态(SOC)自恢复的混合储能平抑风电功率波动控制方法,在满足风电平抑需求的情况下,通过模型预测控制快速调节储能在平抑功率过程中的荷电状态,提高储能持续稳定运行能力;然后,为提高混合储能系统协调运行能力,设计了加权滑动平均(WMA)-模糊控制策略对超级电容和蓄电池功率进行动态分配;最后,结合实际风电功率数据,通过仿真验证了所提策略能有效平衡储能寿命和平抑风电波动的矛盾,能充分考虑两种储能设备的特性差异并提高功率分配的合理性。

水电机组摆度周期性波动问题的分析和研究

本文针对某水电站机组上导轴承摆度峰峰值持续呈正弦周期性波动的问题,通过增加临时探头测量机组动态和静态时上机架支臂和基坑的间隙,以及不同方向支臂的间隙和机组运行参数等,发现支臂和基坑间隙一一对应,且间隙随环境温度的增加而增加,该间隙的变化规律符合因大部件金属构件蠕变传递至基座传感器引起的上导摆度周期波动的特征。因此可以确定机组摆度周期性波动是因为大部件金属随着温度变化而出现较大的位移蠕变,且该蠕变为非对称蠕变,以上过程量逐级传递至基座传感器位置,同时该文建议采用该结构形式的机架时应充分考虑支臂蠕变方向和限位措施。

首发与复发急性期精神分裂症患者静息态低频振幅与分数低频振幅分析

目的:分析首发和复发急性期精神分裂症患者静息态低频振幅与分数低频振幅改变情况。方法:纳入2014年6月至2020年05月在武汉大学人民医院精神卫生中心60例首发、60例复发急性期精神分裂症患者及60名健康对照者进行静息态功能磁共振扫描,采用基于体素水平的低频振幅(ALFF)及分数低频振幅(fALFF)指标分析3组间局部脑功能活动情况。结果:协方差分析显示三组间ALFF值存在显著差异的脑区位于双侧纹状体(左侧F=23.06,P<0.001;右侧F=19.31,P<0.001),而fALFF值存在显著差异的脑区位于双侧纹状体(左侧F=19.71,P<0.001;右侧F=13.53,P<0.001)和前额叶内侧皮质(F=5.46,P<0.001);事后检验显示与对照组相比,首发组和复发组双侧纹状体ALFF及fALFF值均显著升高、内侧前额叶皮质fALFF值降低;复发组内侧前额叶皮质fALFF值降低较首发组更为明显。结论:首发和复发急性期精神分裂症患者均存在双侧纹状体、内侧前额叶皮质的局部功能活动异常,而复发精神分裂症患者内侧前额叶皮质局部脑功能损害更显著。

基于贝叶斯优化LightGBM算法的主动式搜索时间调整方法

针对5G配电终端延迟波动较大导致保护闭锁的问题,提出一种基于贝叶斯优化LightGBM算法的主动式搜索时间调整方法。该方法以无线通信终端延迟波动历史数据以及温度、日期时间等特征变量为输入,对延迟进行预测并动态调整设备参数。首先,对原始特征变量进行特征工程预处理,然后同历史延迟数据一并通过LightGBM算法进行数据的拟合,在训练过程中引入贝叶斯优化算法进行参数寻优,并利用最终加权组合,结合终端实时监测延迟进行预测值的调整,最终实现5G终端延迟的高精度预测。以河北南网某5G配网试点的数据进行训练与验证,结果表明所提方法能有效实现延迟预测,较随机森林回归,XGBoost等算法有更高的预测精度。