Observation of Arctic surface currents using data from a surface drifting buoy

During the 10th Chinese Arctic scientific expedition carried out in the summer of 2019,the surface current in the high-latitude areas of the Arctic Ocean was observed using a self-developed surface drifting buoy,which was initially deployed in the Chukchi Sea.The buoy traversed the Chukchi Sea,Chukchi Abyssal Plain,Mendeleev Ridge,Makarov Basin,and Canada Basin over a period of 632 d.After returning to the Mendeleev Ridge,it continued to drift toward the pole.Overall,the track of the buoy reflected the characteristics of the transpolar drift and Chukchi Slope Current,as well as the inertial flow,cross-ridge surface flow,and even the surface disorganized flow for some time intervals.The results showed that:(1)the transpolar drift mainly occurs in the Chukchi Abyssal Plain,Mendeleev Ridge,and western Canada Basin to the east of the ridge where sea ice concentration is high,and the average northward flow velocity in the region between 79.41°N and 86.32°N was 5.1 cm/s;(2)the average surface velocity of the Chukchi Slope Current was 13.5 cm/s,and while this current moves westward along the continental slope,it also extends northwestward across the continental slope and flows to the deep sea;and(3)when sea ice concentration was less than 50%,the inertial flow was more significant(the maximum observed inertial flow was 26 cm/s,and the radius of the inertia circle was 3.6 km).

Simulation and reconstruction of particle trajectories in the CEPC drift chamber

The circular electron-positron collider(CEPC)is designed to precisely measure the properties of the Higgs boson,study electroweak interactions at the Z-boson peak,and search for new physics beyond the Standard Model.As a component of the 4th conceptual CEPC detector,the drift chamber facilitates the measurement of charged particles.This study implemented a Geant4-based simulation and track reconstruction for the drift chamber.For the simulation,detector construction and response were implemented and added to the CEPC simulation chain.The development of track reconstruction involves track finding using the combinatorial Kalman filter method and track fitting using the tool of GenFit.Using the simulated data,the tracking performance was studied.The results showed that both the reconstruction resolution and tracking efficiency satisfied the requirements of the CEPC experiment.

Role of Stokes Drift in Ocean Dynamics Under Typhoon Conditions in the Bohai Sea

The effect of Stokes drift production(SDP),which includes Coriolis-Stokes forcing,Langmuir circulation,and Craik-Lei-bovich vortexes,on the upper ocean during typhoon passage in the Bohai Sea(BS),China,is investigated by using a coupled wave-current model.The role of SDP in turbulent mixing and the further dynamics during the entire typhoon period are comprehensively stud-ied.Experimental results show that SDP greatly increases turbulent mixing at all depths under typhoon conditions by up to seven times that under normal weather conditions.SDP generally strengthens sea surface cooling by more than 0.4℃,with the maximum reduction in sea surface temperature(SST)at the during-typhoon stage exceeding 2℃,which is approximately seven times larger than that under normal weather conditions.The SDP-induced decrease in current speed can exceed 0.2ms^(-1),and the change in current direction is generally opposite the wind direction.These results suggest that Stokes drift depresses the effect of strong winds on currents by intensifying turbulent mixing.Mixed layer depth(MLD)is distinctly increased by O(1)during typhoons due to SDP and can deepen by more than 5m.In addition,the continuous effects of SDP on SST,current,and MLD at the after-typhoon stage indi-cate a hysteretic response between SDP and typhoon actions.

Typhoon-Induced Ocean Waves and Stokes Drift:A Case Study of Typhoon Mangkhut(2018)

Ocean waves and Stokes drift are generated by typhoons.This study investigated the characteristics of ocean waves and wave-induced Stokes drift and their effects during Typhoon Mangkhut using European Centre for MediumRange Weather Forecasts(ECMWF)ERA5 datasets and observational data.The results revealed that the typhoon generated intense cyclones and huge typhoon waves with a maximum wind speed of 45 m/s,a minimum pressure of955 h Pa,and a maximum significant wave height of 12 m.The Stokes drift caused by typhoon waves exceeded 0.6m/s,the Stokes depth scale exceeded 18 m,and the maximum Stokes transport reached 6 m^(2)/s.The spatial distribution of 10-m wind speed,typhoon wave height,Stokes drift,Stokes depth,and Stokes transport during the typhoon was highly correlated with the typhoon track.The distribution along the typhoon track showed significant zonal asymmetry,with greater intensity on the right side of the typhoon track than on the left side.These findings provide important insights into the impact of typhoons on ocean waves and Stokes drift,thus improving our understanding of the interactions between typhoons and the ocean environment.This study also investigated the contribution of Stokes transport to the total net transport during typhoons using Ekman-Stokes Numbers as a comparative measure.The results indicated that the ratio of Stokes transport to the total net transport reached up to 50%within the typhoon radius,while it was approximately 30%outside the radius.Strong Stokes transport induced by typhoon waves led to divergence in the transport direction,which resulted in upwelling of the lower ocean as a compensation current.Thus,Stokes transport played a crucial role in the vertical mixing of the ocean during typhoons.The findings suggested that Stokes transport should be paid more attention to,particularly in high latitude ocean regions,where strong winds can amplify its effects.

Hand Cooling Enhances the Proprioceptive Drift during Rubber Hand Illusion

Background: The neural representation of the body is easily altered by integrating multiple sensory signals in the brain. The “Rubber Hand Illusion” (RHI) is one of the most popular experimental paradigms to investigate this phenomenon. During this illusion, ownership of a rubber hand is temporarily induced. It was shown that external and continuous cooling of the palm enhanced the RHI, suggesting an association between altered the autonomic nervous system regulation and altered the sense of ownership of a specific limb. Purpose: To investigate whether artificially cooling the entire hand for a short period affects the magnitude of the illusion. Methods: Participants immersed their entire hand in cool, cold, or warm water for 1 min before the RHI procedure. Results: We found that cooling the entire hand enhanced the proprioceptive drift during the RHI but not the subjective feeling of ownership. In contrast, warming and intense cooling of the entire hand did not affect the RHI strength. Conclusion: Our results suggest that transient and moderate cooling of the entire hand was sufficient in enhancing the illusory disembodiment of one’s own hand.

Coordination of distinctive pesticide adjuvants and atomization nozzles on droplet spectrum evolution for spatial drift reduction

Pesticide adjuvants,as crop protection products,have been widely used to reduce drift loss and improve utilization efficiency by regulating droplet spectrum.However,the coordinated regulation mechanisms of adjuvants and nozzles on droplet spectrum remain unclear.Here,we established the relationship between droplet spectrum evolution and liquid atomization by investigating the typical characteristics of droplet diameter distribution near the nozzle.Based on this,the regulation mechanisms of distinctive pesticide adjuvants on droplet spectrum were clarified,and the corresponding drift reduction performances were quantitively evaluated by wind tunnel experiments.It shows that the droplet diameter firstly shifts to the smaller due to the liquid sheet breakup and then prefers to increase caused by droplet interactions.Reducing the surface tension of sprayed liquid facilitates the uniform liquid breakup and increasing the viscosity inhibits the liquid deformation,which prolong the atomization process and effectively improve the droplet spectrum.As a result,the drift losses of flat-fan and hollow cone nozzles are reduced by about 50%after adding organosilicon and vegetable oil adjuvants.By contrast,the air induction nozzle shows a superior anti-drift ability,regardless of distinctive adjuvants.Our findings provide insights into rational adjuvant design and nozzle selection in the field application.

Dual-phase coexistence enables to alleviate resistance drift in phase-change films

The amorphous phase-change materials with spontaneous structural relaxation leads to the resistance drift with the time for phase-change neuron synaptic devices. Here, we modify the phase change properties of the conventional Ge_2Sb_2Te_5(GST) material by introducing an SnS phase. It is found that the resistance drift coefficient of SnS-doped GST was decreased from 0.06 to 0.01. It can be proposed that the origin originates from the precipitation of GST nanocrystals accompanied by the precipitation of SnS crystals compared to single-phase GST compound systems. We also found that the decrease in resistance drift can be attributed to the narrowed bandgap from 0.65 to 0.43 eV after SnS-doping. Thus, this study reveals the quantitative relationship between the resistance drift and the band gap and proposes a new idea for alleviating the resistance drift by composition optimization, which is of great significance for finding a promising phase change material.

Data Quality Control Method of a New Drifting Observation Technology Named Drifting Air-Sea Interface Buoy

An integral quality control(QC)procedure that integrates various QC methods and considers the design indexes and operational status of the instruments for the observations of drifting air-sea interface buoy was developed in the order of basic in-spection followed by targeted QC.The innovative method of combining a moving Hampel filter and local anomaly detection com-plies with statistical laws and physical processes,which guarantees the QC performance of meteorological variables.Two sets of observation data were used to verify the applicability and effectiveness of the QC procedure,and the effect was evaluated using the observations of the Kuroshio Extension Observatory buoy as the reference.The results showed that the outliers in the time series can be correctly identified and processed,and the quality of data improved significantly.The linear correlation between the quality-controlled observations and the reference increased,and the difference decreased.The correlation coefficient of wind speed before and after QC increased from 0.77 to 0.82,and the maximum absolute error decreased by approximately 2.8ms^(-1).In addition,air pressure and relative humidity were optimized by 10^(-3)–10^(-2) orders of magnitude.For the sea surface temperature,the weight of coefficients of the continuity test algorithm was optimized based on the sea area of data acquisition,which effectively expanded the applicability of the algorithm.

Growth mechanism and characteristics of electron drift instability in Hall thruster with different propellant types

The existence of a significant electron drift instability(EDI) in the Hall thruster is considered as one of the possible causes of the abnormal increase in axial electron mobility near the outlet of the channel. In recent years, extensive simulation research on the characteristics of EDI has been conducted, but the excitation mechanism and growth mechanism of EDI in linear stage and nonlinear stage remain unclear. In this work, a one-dimensional PIC model in the azimuthal direction of the thruster near-exit region is established to gain further insights into the mechanism of the EDI in detail, and the effects of different types of propellants on EDI characteristics are discussed. The changes in axial electron transport caused by EDI under different types of propellants and electromagnetic field strengths are also examined. The results indicate that EDI undergoes a short linear growth phase before transitioning to the nonlinear phase and finally reaching saturation through the ion Landau damping. The EDI drives a significant ion heating in the azimuthal direction through electron–ion friction before entering the quasi-steady state, which increases the axial mobility of the electrons. Using lighter atomic weight propellant can effectively suppress the oscillation amplitude of EDI, but it will increase the linear growth rate, frequency, and phase velocity of EDI. Compared with the classical mobility, the axial electron mobility under the EDI increases by three orders of magnitude, which is consistent with experimental phenomena. The change of propellant type is insufficient to significantly change the axial electron mobility. It is also found that the collisions between electrons and neutral gasescan significantly affect the axial electron mobility under the influence of EDI, and lead the strength of the electric field to increase and the strength of the magnetic field to decrease, thereby both effectively suppressing the axial transport of electrons.

Strong Feller Property for SDEs with Super-linear Drift and Hölder Diffusion Coefficients

In this paper,we investigate the strong Feller property of stochastic differential equations(SDEs)with super-linear drift and Hölder diffusion coefficients.By utilizing the Girsanov theorem,coupling method,truncation method and the Yamada-Watanabe approximation technique,we derived the strong Feller property of the solution.

High-precision nonisothermal transient wellbore drift flow model suitable for the full flow pattern domain and full dip range

A reliable multiphase flow simulator is an important tool to improve wellbore integrity and production decision-making.To develop a multiphase flow model with high adaptability and high accuracy,we first build a multiphase flow database with 3561 groups of data and developed a drift closure relationship with stable continuity and high adaptability.Second,a high-order numerical scheme with strong fault capture ability is constructed by effectively combining MUSCL technology,van Albada slope limiter and AUSMV numerical scheme.Finally,the energy equation is coupled into the AUSMV numerical scheme of the drift flow model in the form of finite difference.A transient non-isothermal wellbore multiphase flow model with wide applicability is formed by integrating the three technologies,and the effects of various factors on the calculation accuracy are studied.The accuracy of the simulator is verified by comparing the measurement results with the blowout experiment of a full-scale experimental well.

Evaluating and correcting short-term clock drift in data from temporary seismic deployments

Temporary seismic network deployments often suffer from incorrect timing records and thus pose a challenge to fully utilize the valuable data.To inspect and fix such time problems,the ambient noise cross-correlation function(NCCF)has been widely adopted by using daily waveforms.However,it is still challenging to detect the shortterm clock drift and overcome the influence of local noise on NCCF.To address these challenges,we conduct a study on two temporary datasets,including an ocean-bottom-seismometer(OBS)dataset from the southern Mariana subduction zone and a dataset from a temporary dense network from the Weiyuan shale gas field,Sichuan,China.We first inspect the teleseismic and local event waveforms to evaluate the overall clock drift and data quality for both datasets.For the OBS dataset,NCCF using different time segments(3,6,and 12-h)beside daily waveforms data is computed to select the data length with optimal detection capability.Eventually,the 6-h segment is the preferred choice with high detection efficiency and low noise level.For the land dataset,higher drift detection is achieved by NCCF using the daily long waveforms.Meanwhile,we find that NCCF symmetry on the dense array is highly influenced by localized intense noise for large interstation distances(>1 km)but is well preserved for short interstation distances.The results have shown that the use of different segments of daily waveform data in the OBS dataset,and the careful selection of interstation distances in the land dataset substantially improved the NCCF results.All the clock drifts in both datasets are successfully corrected and verified with waveforms and NCCF.The newly developed strategies using short-segment NCCF help to overcome the existing issues to correct the clock drift of seismic data.

A multi-module with a two-way feedback method for Ulva drift-diffusion

The outbreak of Ulva in the Yellow Sea has seriously affected marine ecology and economic activities.Therefore,effective prediction of the distribution of Ulva is of great significance for disaster prevention and reduction.However,the prediction method of Ulva is mainly based on numerical simulation.There are two problems with these methods.First is that the initial distribution of Ulva is simulated using independent pixel-level particles.Besides,the influence of Ulva growth and diffusion on the drift is not considered.Therefore,this paper proposes a multi-module with a two-way feedback method(MTF)to solve the above problems.The main contributions of our approach are summarized as follows.First,the initialization module,the generation and elimination module,and the drive module are composed in our way.Second,we proposed an initialization method using rectangle objects to simulate the Ulva distribution extracted from remote sensing images.Thirdly,the drift and diffusion mechanism of the Ulva is considered to realize the two-way feedback between the generation and elimination module and the drive module.The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of Ulva.The code is already publicly available at https://github.com/UPCGIT/A-multi-module-with-a-two-way-feedback-method-for-Ulva-drift-diffusion.

Concept Drift Analysis and Malware Attack Detection System Using Secure Adaptive Windowing

Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning(ML)models.Due to attackers’(and/or benign equivalents’)dynamic behavior changes,testing data distribution frequently diverges from original training data over time,resulting in substantial model failures.Due to their dispersed and dynamic nature,distributed denial-of-service attacks pose a danger to cybersecurity,resulting in attacks with serious consequences for users and businesses.This paper proposes a novel design for concept drift analysis and detection of malware attacks like Distributed Denial of Service(DDOS)in the network.The goal of this architecture combination is to accurately represent data and create an effective cyber security prediction agent.The intrusion detection system and concept drift of the network has been analyzed using secure adaptive windowing with website data authentication protocol(SAW_WDA).The network has been analyzed by authentication protocol to avoid malware attacks.The data of network users will be collected and classified using multilayer perceptron gradient decision tree(MLPGDT)classifiers.Based on the classification output,the decision for the detection of attackers and authorized users will be identified.The experimental results show output based on intrusion detection and concept drift analysis systems in terms of throughput,end-end delay,network security,network concept drift,and results based on classification with regard to accuracy,memory,and precision and F-1 score.

SOLPS-ITER drift modeling of neon impurity seeded plasmas in EAST with favorable and unfavorable toroidal magnetic field direction

To better understand divertor detachment and asymmetry in the Experimental Advanced Superconducting Tokamak(EAST),drift modeling via the comprehensive edge plasma code SOLPS-ITER of neon impurity seeded plasmas in favorable/unfavorable toroidal magnetic field(BT)has been performed.Firstly,electrostatic potential/field(f/E)distribution has been analyzed,to make sure that f and E are correctly described and to better understand drift-driven processes.After that,drift effects on divertor detachment and asymmetry have been focused on.In accordance with the corresponding experimental observations,simulation results demonstrate that in favorable BTthe onset of detachment is highly asymmetric between the inner and outer divertors;and reversing BT can significantly decrease the magnitude of in-out asymmetry in the onset of detachment,physics reasons for which have been explored.It is found that,apart from the well-known E×B drift particle flow from one divertor to the other through the private flux region,scrape-off layer(SOL)heat flow,which is much more asymmetrically distributed between the high field side and low field side for favorable BTthan that for unfavorable B_T,is also a critical parameter affecting divertor detachment and asymmetry.During detachment,upstream pressure(P_u)reduction occurs and tends to be more dramatical in the colder side than that in the hotter side.The convective SOL heat flow,emerging due to in-out asymmetry in P_u reduction,is found to be critical for understanding divertor detachment and asymmetry observed in EAST.To better understand the calculated drastic power radiation in the core and upstream SOL,drift effects on divertor leakage/retention of neon in EAST with both BTdirections have been addressed for the first time,by analyzing profile of poloidal neon velocity and that of neon ionization source from atoms.This work can be a reference for future numeric simulations performed more closely related to experimental regimes.

Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more complex.The existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s performance.We analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream classification.Precision, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority classes.The study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

A drift-kinetic perturbed Lagrangian for low-frequency nonideal MHD applications

We find that the perturbed Lagrangian derived from the drift-kinetic equation in[Porcelli F et al 1994 Phys.Plasmas 1470]is inconsistent with the ordering for the low-frequency large-scale magnetohydrodynamic(MHD).Here,we rederive the expression for the perturbed Lagrangian within the framework of nonideal MHD using the ordering system for the low-frequency largescale MHD in a low-beta plasma.The obtained perturbed Lagrangian is consistent with Chen's gyrokinetic theory[Chen L and Zonca F 2016 Rev.Mod.Phys.88015008],where the terms related to the field curvature and gradient are small quantities of higher order and thus negligible.As the perturbed Lagrangian has been widely used in the literature to calculate the plasma nonadiabatic response in low-frequency MHD applications,this finding may have a significant impact on the understanding of the kinetic driving and dissipative mechanisms of MHD instabilities and the plasma response to electromagnetic perturbations in fusion plasmas.

Drift characteristics and the multi-field coupling stress mechanism of the pantograph-catenary arc under low air pressure

The fault caused by a pantograph-catenary arc is the main factor that threatens the stability of high-speed railway energy transmission.Pantograph-catenary arc vertical drift is more severe than the case under normal pressure,as it is easy to develop the rigid busbar,which may lead to the flashover occurring around the support insulators.We establish a pantograph-catenary arc experiment and diagnosis platform to simulate low pressure and strong airflow environment.Meanwhile,the variation law of arc drift height with time under different air pressures and airflow velocities is analyzed.Moreover,arc drift characteristics and influencing factors are explored.The physical process of the arc column drifting to the rigid busbar with the jumping mechanism of the arc root on the rigid busbar is summarized.In order to further explore the mechanism of the above physical process,a multi-field stress coupling model is built,as the multi-stress variation law of arc is quantitatively evaluated.The dynamic action mechanism of multi-field stress on arc drifting characteristics is explored,as the physical mechanism of arc drifting under low pressure is theoretically explained.The research results provide theoretical support for arc suppression in high-altitude areas.

A Review on the Study of Continental Drift and Numerical Simulation Associated with the Early Earth Core-Magma Angular Momentum Exchange

According to the drive of planetary-scale upper magma fluid motions associated with the core-magma angular momentum exchange in the early Earth’s interior, this paper reviewed the results of continental drift studied over the last three decades. The theoretical speculation is in good fit to the traces of geological events left on the Earth’s surface. A northeastward drift directionality of the Australian, African, and South American continents relative to the Antarctica Continent in the Southern Hemisphere is reanalyzed according to the slowing down of the early Earth’s rotation. Six traces of significant back-and-forth drifts of the Australian and Asian continents left respectively on the Southwest and Northwest Pacific seafloors are reidentified according to the gradually decreasing amplitude of core-magma angular momentum exchange during early geological evolution. Finally, the thickening and shortening of different continents during the early drift processes are re-simulated by using a simple magma fluid dynamical model.

Drift DetectionMethod Using DistanceMeasures and Windowing Schemes for Sentiment Classification

Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products.Due to changes in data distribution,commonly referred to as concept drift,mining this data stream is a challenging problem for researchers.The majority of the existing drift detection techniques are based on classification errors,which have higher probabilities of false-positive or missed detections.To improve classification accuracy,there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data streams.This paper presents an adaptive unsupervised learning technique,an ensemble classifier based on drift detection for opinion mining and sentiment classification.To improve classification performance,this approach uses four different dissimilarity measures to determine the degree of concept drifts in the data stream.Whenever a drift is detected,the proposed method builds and adds a new classifier to the ensemble.To add a new classifier,the total number of classifiers in the ensemble is first checked if the limit is exceeded before the classifier with the least weight is removed from the ensemble.To this end,a weighting mechanism is used to calculate the weight of each classifier,which decides the contribution of each classifier in the final classification results.Several experiments were conducted on real-world datasets and the resultswere evaluated on the false positive rate,miss detection rate,and accuracy measures.The proposed method is also compared with the state-of-the-art methods,which include DDM,EDDM,and PageHinkley with support vector machine(SVM)and Naive Bayes classifiers that are frequently used in concept drift detection studies.In all cases,the results show the efficiency of our proposed method.