The Soft X-ray Imager(SXI)on the SMILE Mission

The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.

基于知识辅助深度强化学习的巡飞弹组动态突防决策

巡飞弹组(Loitering Munition Group,LMG)突防控制决策是提高巡飞弹群组作战自主性与智能性的关键。针对存在截击拦截器和临机防空火力区的动态环境中弹组突防机动指令在线生成困难的问题,提出一种基于知识辅助强化学习方法的LMG突防控制决策算法。结合领域知识、规则知识改进状态空间和回报函数设计提高算法泛化能力与训练收敛速度。构建基于软动作-评价方法的LMG突防控制决策框架,以提高算法探索效率。利用专家经验和模仿学习方法改善多弹多威胁带来的解空间狭窄、算法初始高效训练经验匮乏的问题。实验结果表明,新算法能够在动态环境中实时生成有效的突防机动指令,相较于对比方法效果更好,验证了算法的有效性。

Tomographic reconstruction of the Earth’s magnetosheath from multiple spacecraft:a theoretical study

Following our earlier work on tomographic reconstruction of the magnetosheath soft X-ray emissions with superposed epoch analysis of many images recorded from a single spacecraft we now explore the instantaneous reconstruction of the magnetosheath and magnetopause using a few images recorded simultaneously from a few spacecraft.This work is motivated by the prospect of possibly having two or three soft X-ray imagers in space in the coming years,and that many phenomena which occur at the magnetopause boundary,such as reconnection events and pressure pulse responses,do not lend themselves as well to superposed epoch analysis.If the reconstruction is successful-which we demonstrate in this paper that it can be-this collection of imagers can be used to reconstruct the magnetosheath and magnetopause from a single image from each spacecraft,allowing for high time resolution reconstructions.In this paper we explore the reconstruction using,two,three,and four spacecraft.We show that the location of the subsolar point of the magnetopause can be determined with just two satellites,and that volume emissions of soft X-rays,and the shape of the boundary,can be reconstructed using three or more satellites.

Hybrid-Vlasov simulation of soft X-ray emissions at the Earth’s dayside magnetospheric boundaries

Solar wind charge exchange produces emissions in the soft X-ray energy range which can enable the study of near-Earth space regions such as the magnetopause,the magnetosheath and the polar cusps by remote sensing techniques.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)and Lunar Environment heliospheric X-ray Imager(LEXI)missions aim to obtain soft Xray images of near-Earth space thanks to their Soft X-ray Imager(SXI)instruments.While earlier modeling works have already simulated soft X-ray images as might be obtained by SMILE SXI during its mission,the numerical models used so far are all based on the magnetohydrodynamics description of the space plasma.To investigate the possible signatures of ion-kinetic-scale processes in soft Xray images,we use for the first time a global hybrid-Vlasov simulation of the geospace from the Vlasiator model.The simulation is driven by fast and tenuous solar wind conditions and purely southward interplanetary magnetic field.We first produce global X-ray images of the dayside near-Earth space by placing a virtual imaging satellite at two different locations,providing meridional and equatorial views.We then analyze regional features present in the images and show that they correspond to signatures in soft X-ray emissions of mirrormode wave structures in the magnetosheath and flux transfer events(FTEs)at the magnetopause.Our results suggest that,although the time scales associated with the motion of those transient phenomena will likely be significantly smaller than the integration time of the SMILE and LEXI imagers,mirror-mode structures and FTEs can cumulatively produce detectable signatures in the soft X-ray images.For instance,a local increase by 30%in the proton density at the dayside magnetopause resulting from the transit of multiple FTEs leads to a 12%enhancement in the line-of-sight-and time-integrated soft X-ray emissivity originating from this region.Likewise,a proton density increase by 14%in the magnetosheath associated with mirror-mode structures can result in an enhancement in the soft X-ray signal by 4%.These are likely conservative estimates,given that the solar wind conditions used in the Vlasiator run can be expected to generate weaker soft X-ray emissions than the more common denser solar wind.These results will contribute to the preparatory work for the SMILE and LEXI missions by providing the community with quantitative estimates of the effects of small-scale,transient phenomena occurring on the dayside.

Two methods for separating the magnetospheric solar wind charge exchange soft X-ray emission from the diffuse X-ray background

Solar wind charge exchange(SWCX)is the process of solar wind high-valence ions exchanging charges with neutral components and generating soft X-rays.Recently,detecting the SWCX emission from the magnetosphere is proposed as a new technique to study the magnetosphere using panoramic soft X-ray imaging.To better prepare for the data analysis of upcoming magnetospheric soft X-ray imaging missions,this paper compares the magnetospheric SWCX emission obtained by two methods in an XMM-Newton observation,during which the solar wind changed dramatically.The two methods differ in the data used to fit the diffuse X-ray background(DXB)parameters in spectral analysis.The method adding data from the ROSAT All-Sky Survey(RASS)is called the RASS method.The method using the quiet observation data is called the Quiet method,where quiet observations usually refer to observations made by the same satellite with the same target but under weaker solar wind conditions.Results show that the spectral compositions of magnetospheric SWCX emission obtained by the two methods are very similar,and the changes in intensity over time are highly consistent,although the intensity obtained by the RASS method is about 2.68±0.56 keV cm^(-2)s^(-1)sr^(-1)higher than that obtained by the Quiet method.Since the DXB intensity obtained by the RASS method is about 2.84±0.74 keV cm^(-2)s^(-1)sr^(-1)lower than that obtained by the Quiet method,and the linear correlation coefficient between the difference of SWCX and DXB obtained by the two methods in diffe rent energy band is close to-1,the diffe rences in magnetospheric SWCX can be fully attributed to the diffe rences in the fitted DXB.The difference between the two methods is most significant when the energy is less than 0.7 keV,which is also the main energy band of SWCX emission.In addition,the difference between the two methods is not related to the SWCX intensity and,to some extent,to solar wind conditions,because SWCX intensity typically va ries with the solar wind.In summary,both methods are robust and reliable,and should be considered based on the best available options.

Using restored two-dimensional X-ray images to reconstruct the three-dimensional magnetopause

Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)aims to capture two-dimensional(2-D)images of the Earth’s magnetosheath by using soft X-ray imaging.However,the observed 2-D images are affected by many noise factors,destroying the contained information,which is not conducive to the subsequent reconstruction of the three-dimensional(3-D)structure of the magnetopause.The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models.This makes it difficult to establish the mapping relationship between SXIsimulated observation images and target images by using mathematical models.We propose an image restoration algorithm for SXIsimulated observation images that can recover large-scale structure information on the magnetosphere.The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image,whose mapping relationship with the target image is established by the patch estimator.The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator.Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task,according to the peak signal-to-noise ratio and structural similarity.The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques,significantly improving the reconstruction results.Hence,the proposed technology may be feasible for processing SXI-simulated observation images.

Estimating the subsolar magnetopause position from soft X-ray images using a low-pass image filter

The Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)missions will image the Earth’s dayside magneto pause and cusps in soft X-rays after their respective launches in the near future,to specify glo bal magnetic reconnection modes for varying solar wind conditions.To suppo rt the success of these scientific missions,it is critical to develop techniques that extract the magnetopause locations from the observed soft X-ray images.In this research,we introduce a new geometric equation that calculates the subsolar magnetopause position(RS)from a satellite position,the look direction of the instrument,and the angle at which the X-ray emission is maximized.Two assumptions are used in this method:(1)The look direction where soft X-ray emissions are maximized lies tangent to the magnetopause,and(2)the magnetopause surface near the subsolar point is almost spherical and thus RSis nea rly equal to the radius of the magneto pause curvature.We create synthetic soft X-ray images by using the Open Geospace General Circulation Model(OpenGGCM)global magnetohydrodynamic model,the galactic background,the instrument point spread function,and Poisson noise.We then apply the fast Fourier transform and Gaussian low-pass filte rs to the synthetic images to re move noise and obtain accurate look angles for the soft X-ray pea ks.From the filte red images,we calculate RS and its accuracy for different LEXI locations,look directions,and solar wind densities by using the OpenGGCM subsolar magnetopause location as ground truth.Our method estimates RS with an accuracy of<0.3 RE when the solar wind density exceeds>10 cm-3.The accuracy improves for greater solar wind densities and during southward interplanetary magnetic fields.The method ca ptures the magnetopause motion during southwa rd interplaneta ry magnetic field turnings.Consequently,the technique will enable quantitative analysis of the magnetopause motion and help reveal the dayside reconnection modes for dynamic solar wind conditions.This technique will suppo rt the LEXI and SMILE missions in achieving their scientific o bjectives.

Mechanical properties and acoustic emission characteristics of soft rock with different water contents under dynamic disturbance

Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties and acoustic emission characteristics of soft rocks with different water contents under dynamic disturbance.The mechanical properties and acoustic emission characteristics of muddy sandstones at different water contents were analysed.Results of experimental studies show that water is a key factor in the mechanical properties of rocks,softening them,increasing their porosity,reducing their brittleness and increasing their plasticity.Under uniaxial compression,the macroscopic damage characteristics of the muddy sandstone change from mono-bevel shear damage and‘X’type conjugate bevel shear damage to a roadway bottom-drum type damage as the water content increases.Dynamic perturbation has a strengthening effect on the mechanical properties of samples with 60%and less water content,and a weakening effect on samples with 80%and more water content,but the weakening effect is not obvious.Macroscopic damage characteristics of dry samples remain unchanged,water samples from shear damage and tensile–shear composite damage gradually transformed into cleavage damage,until saturation transformation monoclinic shear damage.The evolution of acoustic emission energy and event number is mainly divided into four stages:loading stage(Ⅰ),dynamic loading stage(Ⅱ),yield failure stage(Ⅲ),and post-peak stage(Ⅳ),the acoustic emission characteristics of the stages were different for different water contents.The characteristic value of acoustic emission key point frequency gradually decreases,and the damage degree of the specimen increases,corresponding to low water content—high main frequency—low damage and high water content—low main frequency—high damage.

从中国首台紫外-可见光高光谱卫星仪器反演得到的高空间分辨率臭氧廓线

Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport,as well as when analyzing the physical and chemical properties of the atmosphere.One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations.The Environmental Trace Gases Monitoring Instrument(EMI)deployed on the Gaofen-5 satellite is the first Chinese ultraviolet-visible hyperspectral spectrometer.However,retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio.The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87%of the EMI pixels.Therefore,we developed an algorithm specific to the characteristics of the EMI.The fitting residuals are smaller than 0.3%in most regions.The retrieved ozone profiles were in good agreement with ozonesonde data,with maximum mean biases of 20%at five latitude bands.By applying EMI averaging kernels to the ozonesonde profiles,the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data,The lower layers(0-7.5 km)of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center(CNEMC).However,the upper layers(9.7-16.7 km)of the ozone profiles show different trends,with the ozone peak occurring at an altitude of 9.7-16.7 km in March,2019.A stratospheric intrusion event in central China from August 11 to 15,2019,is captured using the EMI ozone profiles,potential vorticity data,and relative humidity data.The increase in the CNEMC ozone co ncentration showed that downward transport enhanced surface ozone pollution.

SMILE soft X-ray Imager flight model CCD370 pre-flight device characterisation

Throughout the SMILE mission the satellite will be bombarded by radiation which gradually damages the focal plane devices and degrades their performance.In order to understand the changes of the CCD370s within the soft X-ray Imager,an initial characterisation of the devices has been carried out to give a baseline performance level.Three CCDs have been characterised,the two flight devices and the flight spa re.This has been carried out at the Open University in a bespo ke cleanroom measure ment facility.The results show that there is a cluster of bright pixels in the flight spa re which increases in size with tempe rature.However at the nominal ope rating tempe rature(-120℃) it is within the procure ment specifications.Overall,the devices meet the specifications when ope rating at -120℃ in 6 × 6 binned frame transfer science mode.The se rial charge transfer inefficiency degrades with temperature in full frame mode.However any charge losses are recovered when binning/frame transfer is implemented.

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection,a fundamental process that enables the transfer of mass,energy,and momentum from the solar wind into the magnetosphere.The spatial and temporal properties of the magnetopause,under varying solar and magnetospheric conditions,remain largely unknown because empirical studies using in-situ observations are challenging to interpret.Global wide field-of-view(FOV)imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and,subsequently,quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere.Two upcoming missions,ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays,an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms.High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary,the magnetopause,and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation.This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and,with this,identify the location of the magnetopause over the Sun−Earth line.To do so,we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information.Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images.Also,our proposed methodology shows that the accuracy of both three-dimensional(3-D)estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Path Planning and Tracking Control for Parking via Soft Actor-Critic Under Non-Ideal Scenarios

Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.

Simulation of the SMILE Soft X-ray Imager response to a southward interplanetary magnetic field turning

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)Soft X-ray Imager(SXI)will shine a spotlight on magnetopause dynamics during magnetic reconnection.We simulate an event with a southward interplanetary magnetic field turning and produce SXI count maps with a 5-minute integration time.By making assumptions about the magnetopause shape,we find the magnetopause standoff distance from the count maps and compare it with the one obtained directly from the magnetohydrodynamic(MHD)simulation.The root mean square deviations between the reconstructed and MHD standoff distances do not exceed 0.2 RE(Earth radius)and the maximal difference equals 0.24 RE during the 25-minute interval around the southward turning.

基于改进YOLOv7的猕猴桃果实识别优化

为了解决猕猴桃Actinidia chinensis果实识别过程中存在果实之间重叠导致的遮挡严重、检测结果易受叶片影响等问题,建立不同日照条件下的猕猴桃果实图像数据集,对YOLOv7模型做了3方面改进:将Backbone部分的卷积模块替换成GhostConv模块,在维持原有精度的程度上降低模型的参数量;针对猕猴桃果实之间存在大量重叠的情况,引入非极大值抑制NMS(Soft-NMS)策略提高检测框回归精度;融合SimAM注意力机制,增强模型对于高密度猕猴桃特征的提取能力。通过对比实验表明,优化后的模型与Faster RCNN相比,mAP值增加了12.7个百分点,检测速度提升106.8帧/s,综合性能较好,满足机器实时对于猕猴桃果实识别的需求。

Direct 4D printing of functionally graded hydrogel networks for biodegradable,untethered,and multimorphic soft robots

Recent advances in functionally graded additive manufacturing(FGAM)technology have enabled the seamless hybridization of multiple functionalities in a single structure.Soft robotics can become one of the largest beneficiaries of these advances,through the design of a facile four-dimensional(4D)FGAM process that can grant an intelligent stimuli-responsive mechanical functionality to the printed objects.Herein,we present a simple binder jetting approach for the 4D printing of functionally graded porous multi-materials(FGMM)by introducing rationally designed graded multiphase feeder beds.Compositionally graded cross-linking agents gradually form stable porous network structures within aqueous polymer particles,enabling programmable hygroscopic deformation without complex mechanical designs.Furthermore,a systematic bed design incorporating additional functional agents enables a multi-stimuli-responsive and untethered soft robot with stark stimulus selectivity.The biodegradability of the proposed 4D-printed soft robot further ensures the sustainability of our approach,with immediate degradation rates of 96.6%within 72 h.The proposed 4D printing concept for FGMMs can create new opportunities for intelligent and sustainable additive manufacturing in soft robotics.

MHz cut-off frequency and permeability mechanism of iron-based soft magnetic composites

The lack of soft magnetic composites with high power density in MHz frequency range has become an obstacle in the efficient operation of the electrical and electronic equipments.Here,a promising method to increase the cut-off frequency of iron-based soft magnetic composites to hundreds of MHz is reported.The cut-off frequency is increased from 10 MHz to 1 GHz by modulating the height of the ring,the distribution of particles,and the particle size.The mechanism of cut-off frequency and permeability is the coherent rotation of domain modulated by inhomogeneous field due to the eddy current effect.An empirical formula for the cut-off frequency in a magnetic ring composed of iron-based particles is established from experimental data.This work provides an effective approach to fabricate soft magnetic composites with a cut-off frequency in hundreds of MHz.

An Automatic Implementation of Oropharyngeal Swab Sampling for Diagnosing Respiratory Infectious Diseases via Soft Robotic End-Effectors

The most widely adopted method for diagnosing respiratory infectious diseases is to conduct polymerase chain reaction(PCR)assays on patients’respiratory specimens,which are collected through either nasal or oropharyngeal swabs.The manual swab sampling process poses a high risk to the examiner and may cause false-negative results owing to improper sampling.In this paper,we propose a pneumatically actuated soft end-effector specifically designed to achieve all of the tasks involved in swab sampling.The soft end-effector utilizes circumferential instability to ensure grasping stability,and exhibits several key properties,including high load-to-weight ratio,error tolerance,and variable swab-tip stiffness,leading to successful automatic robotic oropharyngeal swab sampling,from loosening and tightening the transport medium tube cap,holding the swab,and conducting sampling,to snapping off the swab tail and sterilizing itself.Using an industrial collaborative robotic arm,we integrated the soft end-effector,force sensor,camera,lights,and remote-control stick,and developed a robotic oropharyngeal swab sampling system.Using this swab sampling system,we conducted oropharyngeal swab-sampling tests on 20 volunteers.Our Digital PCR assay results(RNase P RNA gene absolute copy numbers for the samples)revealed that our system successfully collected sufficient numbers of cells from the pharyngeal wall for respiratory disease diagnosis.In summary,we have developed a pharyngeal swab-sampling system based on an“enveloping”soft actuator,studied the sampling process,and imple-mented whole-process robotic oropharyngeal swab-sampling.

SAC-Based Computation Offloading for Reconfigurable Intelligent Surface-Aided Mobile Edge Networks

In this paper,we concentrate on a reconfigurable intelligent surface(RIS)-aided mobile edge computing(MEC)system to improve the offload efficiency with moving user equipments(UEs).We aim to minimize the energy consumption of all UEs by jointly optimizing the discrete phase shift of RIS,UEs’transmitting power,computing resources allocation,and the UEs’task offloading strategies for local computing and offloading.The formulated problem is a sequential decision making across multiple coherent time slots.Furthermore,the mobility of UEs brings uncertainties into the decision-making process.To cope with this challenging problem,the deep reinforcement learning-based Soft Actor-Critic(SAC)algorithm is first proposed to effectively optimize the discrete phase of RIS and the UEs’task offloading strategies.Then,the transmitting power and computing resource allocation can be determined based on the action.Numerical results demonstrate that the proposed algorithm can be trained more stably and perform approximately 14%lower than the deep deterministic policy gradient benchmark in terms of energy consumption.

Characterizing structure of cross-disciplinary impact of global disciplines:A perspective of the Hierarchy of Science

Purpose:Interdisciplinary fields have become the driving force of modern science and a significant source of scientific innovation.However,there is still a paucity of analysis about the essential characteristics of disciplines’cross-disciplinary impact.Design/methodology/approach:In this study,we define cross-disciplinary impact on one discipline as its impact to other disciplines,and refer to a three-dimensional framework of variety-balance-disparity to characterize the structure of cross-disciplinary impact.The variety of cross-disciplinary impact of the discipline was defined as the proportion of the high cross-disciplinary impact publications,and the balance and disparity of cross-disciplinary impact were measured as well.To demonstrate the cross-disciplinary impact of the disciplines in science,we chose Microsoft Academic Graph(MAG)as the data source,and investigated the relationship between disciplines’cross-disciplinary impact and their positions in the Hierarchy of Science(HOS).Findings:Analytical results show that there is a significant correlation between the ranking of cross-disciplinary impact and the HOS structure,and that the discipline exerts a greater cross-disciplinary impact on its neighboring disciplines.Several bibliometric features that measure the hardness of a discipline,including the number of references,the number of cited disciplines,the citation distribution,and the Price index have a significant positive effect on the variety of cross-disciplinary impact.The number of references,the number of cited disciplines,and the citation distribution have significant positive and negative effects on balance and disparity,respectively.It is concluded that the less hard the discipline,the greater the cross-disciplinary impact,the higher balance and the lower disparity of cross-disciplinary impact.Research limitations:In the empirical analysis of HOS,we only included five broad disciplines.This study also has some biases caused by the data source and applied regression models.Practical implications:This study contributes to the formulation of discipline-specific policies and promotes the growth of interdisciplinary research,as well as offering fresh insights for predicting the cross-disciplinary impact of disciplines.Originality/value:This study provides a new perspective to properly understand the mechanisms of cross-disciplinary impact and disciplinary integration.

Applications of Soft Computing Methods in Backbreak Assessment in Surface Mines: A Comprehensive Review

Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them effectively.Soft Computing(SC)methods have gained popularity in engineering disciplines such as mining and civil engineering due to computer hardware and machine learning advancements.Unlike traditional hard computing approaches,SC models use soft values and fuzzy sets to navigate uncertain environments.This study focuses on the application of SC methods to predict backbreak,a common issue in blasting operations within mining and civil projects.Backbreak,which refers to the unintended fracturing of rock beyond the desired blast perimeter,can significantly impact project timelines and costs.This study aims to explore how SC methods can be effectively employed to anticipate and mitigate the undesirable consequences of blasting operations,specifically focusing on backbreak prediction.The research explores the complexities of backbreak prediction and highlights the potential benefits of utilizing SC methods to address this challenging issue in geo-engineering projects.