An embedded electron current layer observed at the edge of the plasma sheet in the Earth’s magnetotail

The formation of an embedded electron current sheet within the magnetotail plasma sheet has been poorly understood.In this article,we present an electron current layer detected at the edge of the magnetotail plasma sheet.The ions were demagnetized inside the electron current layer,but the electrons were still frozen in with the magnetic field line.Thus,this decoupling of ions and electrons gave rise to a strong Hall electric field,which could be the reason for the formation of the embedded thin current layer.The magnetized electrons,the absence of the nongyrotropic electron distribution,and negligible energy dissipation in the layer indicate that magnetic reconnection had not been triggered within the embedded thin current layer.The highly asymmetric plasma on the two sides of the current layer and low magnetic shear across it could suppress magnetic reconnection.The observations indicate that the embedded electric current layer,probably generated by the Hall electric field,even down to electron scale,is not a sufficient condition for magnetic reconnection.

Global hybrid simulations of soft X-ray emissions in the Earth’s magnetosheath

Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas,and it is also the boundary of the solar wind energy transport to the magnetosphere.Soft X-ray imaging allows investigation of the large-scale magnetopause by providing a two-dimensional(2-D)global view from a satellite.By performing 3-D global hybrid-particle-in-cell(hybrid-PIC)simulations,we obtain soft X-ray images of Earth’s magnetopause under different solar wind conditions,such as different plasma densities and directions of the southward interplanetary magnetic field.In all cases,magnetic reconnection occurs at low latitude magnetopause.The soft X-ray images observed by a hypothetical satellite are shown,with all of the following identified:the boundary of the magnetopause,the cusps,and the magnetosheath.Local X-ray emissivity in the magnetosheath is characterized by large amplitude fluctuations(up to 160%);however,the maximum line-of-sight-integrated X-ray intensity matches the tangent directions of the magnetopause well,indicating that these fluctuations have limited impact on identifying the magnetopause boundary in the X-ray images.Moreover,the magnetopause boundary can be identified using multiple viewing geometries.We also find that solar wind conditions have little effect on the magnetopause identification.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will provide X-ray images of the magnetopause for the first time,and our global hybrid-PIC simulation results can help better understand the 2-D X-ray images of the magnetopause from a 3-D perspective,with particle kinetic effects considered.

Ion and electron motions in the outer electron diffusion region of collisionless magnetic reconnection

Two-dimensional particle-in-cell simulations are performed to study the coupling between ion and electron motions in collisionless magnetic reconnection.The electron diffusion region(EDR),where the electron motions are demagnetized,is found to have a two-layer structure:an inner EDR near the reconnection site and an outer EDR that is elongated to nearly 10 ion inertial lengths in the outflow direction.In the inner EDR,the speed of the electron outflow increases when the electrons move away from the X line.In the outer EDR,the speed of the electron outflow first increases and then decreases until the electrons reach the boundary of the outer EDR.In the boundary of the outer EDR,the magnetic field piles up and forms a depolarization front.From the perspective of the fluid,a force analysis on the formation of electron and ion outflows has also been investigated.Around the X line,the electrons are accelerated by the reconnection electric field in the out-of-plane direction.When the electrons move away from the X line,we find that the Lorentz force converts the direction of the accelerated electrons to the x direction,forming an electron outflow.Both electric field forces and electron gradient forces tend to drag the electron outflow.Ion acceleration along the x direction is caused by the Lorentz force,whereas the pressure gradient force tends to decelerate the ion outflow.Although these two terms are important,their effects on ions are almost offset.The Hall electric field force does positive work on ions and is not negligible.The ions are continuously accelerated,and the ion and electron outflow velocities are almost the same near the depolarization front.

Short-term train arrival delay prediction:a data-driven approach

Purpose-To optimize train operations,dispatchers currently rely on experience for quick adjustments when delays occur.However,delay predictions often involve imprecise shifts based on known delay times.Real-time and accurate train delay predictions,facilitated by data-driven neural network models,can significantly reduce dispatcher stress and improve adjustment plans.Leveraging current train operation data,these models enable swift and precise predictions,addressing challenges posed by train delays in high-speed rail networks during unforeseen events.Design/methodology/approach-This paper proposes CBLA-net,a neural network architecture for predicting late arrival times.It combines CNN,Bi-LSTM,and attention mechanisms to extract features,handle time series data,and enhance information utilization.Trained on operational data from the Beijing-Tianjin line,it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.Findings-This study evaluates our model’s predictive performance using two data approaches:one considering full data and another focusing only on late arrivals.Results show precise and rapid predictions.Training with full data achieves aMAEof approximately 0.54 minutes and a RMSEof 0.65 minutes,surpassing the model trained solely on delay data(MAE:is about 1.02 min,RMSE:is about 1.52 min).Despite superior overall performance with full data,the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals.For enhanced adaptability to real-world train operations,training with full data is recommended.Originality/value-This paper introduces a novel neural network model,CBLA-net,for predicting train delay times.It innovatively compares and analyzes the model’s performance using both full data and delay data formats.Additionally,the evaluation of the network’s predictive capabilities considers different scenarios,providing a comprehensive demonstration of the model’s predictive performance.

In situ evidence of resonant interactions between energetic electrons and whistler waves in magnetopause reconnection

In this paper,we analyze one reconnection event observed by the Magnetospheric Multiscale(MMS)mission at the earth’s magnetopause.In this event,the spacecraft crossed the reconnection current sheet from the magnetospheric side to the magnetosheath side,and whistler waves were observed on both the magnetospheric and magnetosheath sides.On the magnetospheric side,the whistler waves propagated quasi-parallel to the magnetic field and toward the X-line,while on the magnetosheath side they propagated almost anti-parallel to the magnetic field and away from the X-line.Associated with the enhancement of the whistler waves,we find that the fluxes of energetic electrons are concentrated around the pitch angle 90°when their energies are higher than the minimum energy that is necessary for the resonant interactions between the energetic electrons and whistler waves.This observation provides in situ observational evidence of resonant interactions between energetic electrons and whistler waves in the magnetic reconnection.

Collisionless magnetic reconnection in the magnetosphere

Magnetic reconnection underlies the physical mechanism of explosive phenomena in the solar atmosphere and planetary magnetospheres, where plasma is usually collisionless. In the standard model of collisionless magnetic reconnection,the diffusion region consists of two substructures: an electron diffusion region is embedded in an ion diffusion region,in which their scales are based on the electron and ion inertial lengths. In the ion diffusion region, ions are unfrozen in the magnetic fields while electrons are magnetized. The resulted Hall effect from the different motions between ions and electrons leads to the production of the in-plane currents, and then generates the quadrupolar structure of out-of-plane magnetic field. In the electron diffusion region, even electrons become unfrozen in the magnetic fields, and the reconnection electric field is contributed by the off-diagonal electron pressure terms in the generalized Ohm’s law. The reconnection rate is insensitive to the specific mechanism to break the frozen-in condition, and is on the order of 0.1. In recent years, the launching of Cluster, THEMIS, MMS, and other spacecraft has provided us opportunities to study collisionless magnetic reconnection in the Earth’s magnetosphere, and to verify and extend more insights on the standard model of collisionless magnetic reconnection. In this paper, we will review what we have learned beyond the standard model with the help of observations from these spacecraft as well as kinetic simulations.

On the ion distributions at the separatrices during symmetric magnetic reconnection

A particle-in-cell simulation of symmetric reconnection with zero guide field is carried out to understand the dynamics of ions along the separatrices.Through the investigation of ion velocity distributions at different moments and locations along the separatrices,a typical distribution is found:two counter-streaming populations in the perpendicular direction,with another two populations accelerated into distinct energy levels in the parallel direction.Backward tracing of ions reveals that the counter-streaming cores are mostly composed of ions initially located at the same side of the separatrix,while the other two accelerated populations in the parallel direction are composed of ions crossing through the neutral sheet.Through analysis of energy conversion of these populations,it is found that the ion energization along the separatrix is attributable primarily to the Hall electric field,while that in the region between the two separatrices is caused primarily by the induced reconnection electric field.For the counter-streaming population,the low-energy ions that cross the separatrix twice are affected by both Hall and reconnection electric fields,while the high-energy ions that directly enter the separatrix from the unperturbed plasma are energized mainly by the Hall electric field.For the two energized populations in the parallel direction,the ions with lower-energy are accelerated mainly by the in-plane electric field and the Hall electric field on the opposite side of the separatrix,whereas the ions with higher-energy not only experience the same energization process but also are constantly accelerated by the reconnection electric field.

Focus-RCNet:a lightweight recyclable waste classification algorithm based on focus and knowledge distillation

Waste pollution is a significant environmental problem worldwide.With the continuous improvement in the living standards of the population and increasing richness of the consumption structure,the amount of domestic waste generated has increased dramatically,and there is an urgent need for further treatment.The rapid development of artificial intelligence has provided an effective solution for automated waste classification.However,the high computational power and complexity of algorithms make convolutional neural networks unsuitable for real-time embedded applications.In this paper,we propose a lightweight network architecture called Focus-RCNet,designed with reference to the sandglass structure of MobileNetV2,which uses deeply separable convolution to extract features from images.The Focus module is introduced to the field of recyclable waste image classification to reduce the dimensionality of features while retaining relevant information.To make the model focus more on waste image features while keeping the number of parameters small,we introduce the SimAM attention mechanism.In addition,knowledge distillation was used to further compress the number of parameters in the model.By training and testing on the TrashNet dataset,the Focus-RCNet model not only achieved an accuracy of 92%but also showed high deployment mobility.

High intensity focused ultrasound in combination with chemotherapy by the regime of PFC: a clinical study for advanced gastric carcinoma

Objective： To evaluate the recent curative efficacy and security of High intensity focused ultrasound （HIFU） in combination with chemotherapy（PFC） in patients with advanced gastric carcinoma. Method： Sixty patients with measurable advanced gastric carcinoma, proved pathologically, were divided into Group A and Group B. Group A： Patients were treated by HIFU（FEP-BY01） in combination with chemotherapy（PFC, paclitaxel, cisplatin and 5-fluorouracil）. Group B： Patients were treated with the single regime of PFC. Results： All cases could be evaluated, ha group A, 5 patients achieved complete response, 17 patients achieved partial response,and a response rate was 73.3%. The stable disease（SD） and the inefficiency all were 13.3% （4/30） respectively, and msurvival time（MST） was 13.9 months. In group B, 2 patients achieved complete response, 14 patients achieved partial response, and a response rate was 53.3%. The stable disease（SD） was 23.3%（7/30）. The inefficiency all were 23.3%（7/30） respectively, and median survival time was 9.6 months. There was significant difference between two groups MST（ P 〈 0.05）. Major toxicities included bone marrow depression, nausea, vomiting and alopecia, without significant differences between two groups（ P 〉 0.05）. Conclusion： This study shows that HIFU in combination with chemotherapy（PFC） was a new efficent and secure therapy for the patients with advanced gastric carcinoma. It was observed that the MST was prolonged. Prospective trials should be warranted to determine the result.

A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways

Purpose–This paper aims to propose a train timetable rescheduling(TTR)approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.Design/methodology/approach–Firstly,a single-train trajectory optimization(STTO)model is constructed based on train dynamics and operating conditions.The train kinematics parameters,including acceleration,speed and time at each position,are calculated to predict the arrival times in the train timetable.A STTO algorithm is developed to optimize a single-train time-efficient driving strategy.Then,a TTR approach based on multi-train tracking optimization(TTR-MTTO)is proposed with mutual information.The constraints of temporary speed restriction(TSR)and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train.The multi-train trajectories at each position are optimized to generate a timeefficient train timetable.Findings–The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF.The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay(TTD).As for the TSR scenario,the proposed TTR-MTTO can reduce TTD by 60.60%compared with the traditional TTR approach with dispatchers’experience.Moreover,TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.Originality/value–With the cooperative relationship and mutual information between train rescheduling and control,the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

车站封锁下基于问题知识的高速铁路列车运行实时调整方法

针对突发事件导致的车站封锁情况,本文以列车运行图为问题对象,以进化计算框架为基础,提出基于问题知识的运行图实时调整方法,通过减小列车总晚点时间,保证高铁运营的安全高效和旅客的满意舒适.首先,基于调整列车发车次序的运行图调整策略提出排列编码方法,用于减少解空间的无效搜索.之后,根据“紧追踪”的列车运行追踪方式,设计启发式解码方法消除所有行车作业约束,提升算法求解效率.最后,将调度员调整运行图的经验作为问题知识,用于初始化进化计算的初始种群,由此提出基于问题知识的启发式种群初始化方法,加快算法前期的收敛速度并提高求解方案质量.以京津高速线为例,在北京南站设置车站封锁下20~150 min不同封锁时长的9个典型场景,选择加强精英保留遗传算法和差分进化算法,分别应用实整数编码和排列编码,与随机种群初始化和启发式种群初始化的不同组合进行仿真实验.仿真结果表明,相较于实整数编码难以获取可行解,2种进化算法应用排列编码方法后,能在9 s的平均时间内给出列车总晚点时间最小的调整方案.在启发式种群初始化的改进下,2种进化算法能更快地收敛于近似最优解.选取加强精英保留遗传算法应用排列编码和启发式种群初始化的改进变体,作为本文最优改进进化算法.针对CPLEX无法在10 min获得最优解的7个场景,该改进进化算法都能在20 s内给出近似最优解.

The Ghd7 transcription factor represses ARE1 expression to enhance nitrogen utilization and grain yield in rice

The genetic improvement of nitrogen use efficiency(NUE)of crops is vital for grain productivity and sustainable agriculture.However,the regulatory mechanism of NUE remains largely elusive.Here,we report that the rice Grain number,plant height,and heading date7(Ghd7)gene genetically acts upstream of ABC1 REPRESSOR1(ARE1),a negative regulator of NUE,to positively regulate nitrogen utilization.As a transcriptional repressor,Ghd7 directly binds to two Evening Element-like motifs in the promoter and intron 1 of ARE1,likely in a cooperative manner,to repress its expression.Ghd7 and ARE1 display diurnal expression patterns in an inverse oscillation manner,mirroring a regulatory scheme based on these two loci.Analysis of a panel of 2656 rice varieties suggests that the elite alleles of Ghd7 and ARE1 have undergone diversifying selection during breeding.Moreover,the allelic distribution of Ghd7 and ARE1 is associated with the soil nitrogen deposition rate in East Asia and South Asia.Remarkably,the combination of the Ghd7 and ARE1 elite alleles substantially improves NUE and yield performance under nitrogen-limiting conditions.Collectively,these results define a Ghd7–ARE1-based regulatory mechanism of nitrogen utilization,providing useful targets for genetic improvement of rice NUE.