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.

Regularity analysis of resilient modulus for hot-mix asphalt with large temperature fluctuations

To evaluate the regularity of resilient modulus for hot-mix asphalt(HMA)under large temperature fluctuations,back propagation(BP)neural network technology was used to analyze the continuous change of HMA resilient modulus.Firstly,based on the abundant data,the training model of HMA resilient modulus was established by using BP neural network technology.Subsequently,BP neural network prediction and regression analysis were performed,and the prediction model of HMA resilient modulus at different temperatures(50C to 60C)was obtained,which fully considered multi-factor and nonlinearity.Finally,the fitted theoretical model can be used to evaluate the HMA performance under the condition of large temperature fluctuations,and the rationality of theoretical model was verified by taking Harbin region as an example.It was found that the relationship between HMA resilient modulus and temperatures can be described by inverse tangent function.And the key parameters of theoretical model can be used to evaluate the continuous change characteristics of HMA resilient modulus with large temperature fluctuations.The results can further improve the HMA performance evaluation system and have certain theoretical value.

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.

Altered spontaneous brain activity patterns in hypertensive retinopathy using fractional amplitude of low-frequency fluctuations:a functional magnetic resonance imaging study

AIM:To study functional brain abnormalities in patients with hypertensive retinopathy(HR)and to discuss the pathophysiological mechanisms of HR by fractional amplitude of low-frequency fluctuations(fALFFs)method.METHODS:Twenty HR patients and 20 healthy controls(HCs)were respectively recruited.The age,gender,and educational background characteristics of the two groups were similar.After functional magnetic resonance imaging(fMRI)scanning,the subjects’spontaneous brain activity was evaluated with the fALFF method.Receiver operating characteristic(ROC)curve analysis was used to classify the data.Further,we used Pearson’s correlation analysis to explore the relationship between fALFF values in specific brain regions and clinical behaviors in patients with HR.RESULTS:The brain areas of the HR group with lower fALFF values than HCs were the right orbital part of the middle frontal gyrus(RO-MFG)and right lingual gyrus.In contrast,the values of fALFFs in the left middle temporal gyrus(MTG),left superior temporal pole(STP),left middle frontal gyrus(MFG),left superior marginal gyrus(SMG),left superior parietal lobule(SPL),and right supplementary motor area(SMA)were higher in the HR group.The results of a t-test showed that the average values of fALFFs were statistically significantly different in the HR group and HC group(P<0.001).The fALFF values of the left middle frontal gyrus in HR patients were positively correlated with anxiety scores(r=0.9232;P<0.0001)and depression scores(r=0.9682;P<0.0001).CONCLUSION:fALFF values in multiple brain regions of HR patients are abnormal,suggesting that these brain regions in HR patients may be dysfunctional,which may help to reveal the pathophysiological mechanisms of HR.

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.

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.

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.

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.

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.

A Statistical Method for Characterizing CMOS Process Fluctuations in Subthreshold Current Mirrors

A novel method to characterize CMOS process fluctuations in subthreshold current mirrors （SCM） is reported. The proposed model is succinct in methodology and calculation complexity compared with previous statistical models. However,it provides favorable estimations of CMOS process fluctuations on the SCM circuit, which makes it promising for engineering applications. The model statistically abstracts physical parameters, which depend on the IC process, into random variables with certain mean values and standard deviations, while aggregating all the random impacts into a discrete martingale. The correctness of the proposed method is experimentally verified on an SCM circuit implemented in an SMIC 0.18μm CMOS 1P6M mixed signal process with a conversion factor of 100 in an input range from 100pA to lμA. The pro- posed theory successfully predicts - 10% of die-to-die fluctuation measured in the experiment, and also suggests the -lmV of threshold voltage standard deviation over a single die,which meets the process parameters suggested by the design kit from the foundry. The deviations between calculated probabilities and measured data are less than 8%. Meanwhile, pertinent suggestions concerning high fluctuation tolerance subthreshold analog circuit design are also made and discussed.

An Interpretation on Jig's Psychological Fluctuations in Hills like White Elephants

Hills like White Elephants is one of the masterpieces of Ernest Hemingway. The story bears an open ending. This paper attempts to analyze the heroine-Jig's psychological fluctuations, and her three emotional stages to support the author's interpretation on the end of the story—the heroine's final decision is to have the baby born.

Trends in Temperature Extremes in Association with Weather-Intraseasonal Fluctuations in Eastern China

Trends in the frequencies of four temperature extremes （the occurrence of warm days, cold days, warm nights and cold nights） with respect to a modulated annual cycle （MAC）, and those associated exclusively with weather-intraseasonal fluctuations （WIF） in eastern China were investigated based on an updated homogenized daily maximum and minimum temperature dataset for 1960–2008. The Ensemble Empirical Mode Decomposition （EEMD） method was used to isolate the WIF, MAC, and longer-term components from the temperature series. The annual, winter and summer occurrences of warm （cold） nights were found to have increased （decreased） significantly almost everywhere, while those of warm （cold） days have increased （decreased） in northern China （north of 40°N）. However, the four temperature extremes associated exclusively with WIF for winter have decreased almost everywhere, while those for summer have decreased in the north but increased in the south. These characteristics agree with changes in the amplitude of WIF. In particular, winter WIF of maximum temperature tended to weaken almost everywhere, especially in eastern coastal areas （by 10%–20%）; summer WIF tended to intensify in southern China by 10%–20%. It is notable that in northern China, the occurrence of warm days has increased, even where that associated with WIF has decreased significantly. This suggests that the recent increasing frequency of warm extremes is due to a considerable rise in the mean temperature level, which surpasses the effect of the weakening weather fluctuations in northern China.

Model test of the influence of cyclic water level fluctuations on a landslide

Many landslides in reservoir areas continuously deform under cyclic water level fluctuations due to reservoir operations. In this paper,a landslide model, developed for a typical colluvial landslide in the Three Gorges Reservoir area, is used to study the effect of cyclic water level fluctuations on the landslide. Five cyclic water level fluctuations were implemented in the test, and the fluctuation rate in the last two fluctuations doubled over the first three fluctuations. The pore water pressure and lateral landslide profiles were obtained during the test. A measurement of the landslide soil loss was proposed to quantitatively evaluate the influence of water level fluctuations. The test results show that the first water level rising is most negative to the landslide among the five cycles. The fourth drawdown with a higher drawdown rate caused further large landslide deformation. An increase of the water level drawdown rate is much more unfavorable to the landslide than an increase of the water level rising rate. In addition, the landslide was found to have an adaptive ability to resist subsequent water level fluctuations after undergoing large deformation during a water level fluctuation. The landslide deformation and observations in the field were found to support the test results well.

Functional Integrals and Quantum Fluctuations on Two-Dimensional Noncommutative Space-Time

The generalized Thirring model with impurity coupling is defined on two-dimensional noncommutativespace-time,a modified propagator and free energy are derived by means of functional integrals method.Moreover,quantum fluctuations and excitation energies are calculated on two-dimensional black hole and soliton background.

Effect of water level fluctuations on temporal-spatial patterns of foraging activities by the wintering Hooded Crane(Grus monacha)

Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temporal-spatial patterns of foraging activities.It is of considerable importance to investigate the effect of these fluctuations on food availability for wintering Hooded Cranes and their foraging response to these changes.Understanding their behavior patterns is beneficial in protecting the wintering crane population and restoring their wintering habitats.Methods:A field survey of the winter behavior of cranes was carried out at Shengjin Lake from November in 2013 to April in 2014.Habitat variables,as well as the spatial distribution and behavior patterns of wintering cranes at their foraging sites during five stages of water level fluctuation were collected.Based on this data we analyzed the relationship of foraging behavior relative to water level fluctuations and habitat types.Results:The foraging habitats used by Hooded Cranes varied at the different water level stages.As the water level decreased,the use of meadows and mudflats increased.When the water dropped to its lowest level,the use by the Hooded Crane in the mudflats reached a peak.There were statistically significant differences in time budget in the three types of habitats over the five stages of the water level.In the mudflats,the foraging behavior and maintenance behavior varied significantly with the water level,while the alert behavior showed little variation.Analysis of a generalized linear model showed that the five water level stages and three habitat types had a significant effect on foraging behavior,while the combined effect of these two variables was significant on the foraging time budget and the length of foraging activity of the Hooded Crane.Conclusions:With the decrease in the water level,the use of mudflats by Hooded Cranes increased correspondingly.Food availability in different habitats was affected by changes in the water level.The Hooded Crane adjusted its foraging patterns and made full use of the three available types of habitat in order to acquire enough food in response to fluctuations in the water level.