The Mars orbiter magnetometer of Tianwen-1:in-flight performance and first science results

The Mars Orbiter MAGnetometer(MOMAG)is a scientific instrument onboard the orbiter of China’s first mission for Mars—Tianwen-1.Since November 13,2021,it has been recording magnetic field data from the solar wind to the magnetic pile-up region surrounding Mars.Here we present its in-flight performance and first science results,based on its first one and one-half months’data.Comparing these early MOMAG observations to the magnetic field data in the solar wind from NASA’s Mars Atmosphere and Volatile EvolutioN(MAVEN)mission,we report that the MOMAG magnetic field data are at the same level in magnitude,and describe the same magnetic structures with similar variations in three components.We recognize 158 clear bow shock(BS)crossings in these MOMAG data;their locations match well statistically with the modeled average BS.We also identify and compare five pairs of datasets collected when Tianwen-1’s orbiter and the MAVEN probe made simultaneous BS crossings.These BS crossings confirm the global shape of modeled BS,as well as the south-north asymmetry of the Martian BS.Two cases presented in this paper suggest that the BS is probably more dynamic at flank than near the nose.So far,MOMAG performs well,and provides accurate magnetic field vectors.MOMAG is continuously scanning the magnetic field surrounding Mars.Data from MOMAG’s measurements complement data from MAVEN and will undoubt edly advance our understanding of the plasma environment of Mars.

Ground-based and additional science support for SMILE

The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere ionosphere.Combining these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE mission.Here,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these efforts.Preparations include constructing an online SMILE Data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft conjunctions.We anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.

A New Method for Monitoring Scattered Stray Light of an Inner-occulted Coronagraph

The scattered stray light of a coronagraph is a type of stray light that is generated by the objective lens as its surface defects are irradiated by sunlight.The defects mainly include dust and blemishes on the lens surface,microroughness of the lens surface,and impurity and inhomogeneity of the glass.Unlike the other types of relatively stable defects introduced when the objective lens is being manufactured,the scattered stray light caused by dusts on the lens surface is difficult to quantify accurately due to the disorder and randomness of the dust accumulation.The contribution of this type of stray light to the overall stray light level is difficult to determine through simulations and experiments.This can result in continuous deterioration of the stray light level of a coronagraph and thus affect the observation capabilities of the instrument.To solve this issue,through analyzing the forming mechanism of scattered stray light and ghost image generated by the inner-occulted coronagraph,we propose a novel method to monitor the scattered stray light from dusts by utilizing different stray light correlation coefficients.In this method,we first simulate and measure the level of stray light from the ghost image of the objective lens,and then determine the flux ratio of scattered light and ghost image on the conjugate plane.Although the flux ratio varies with the accumulation of dusts on the lens surface,it remains constant on the image plane.Therefore,the level of dust scattering light on the image plane can be obtained by using this ratio together with the level of ghost image stray light.The accuracy of this method has been validated in a laboratory by applying the objective lens with numerous surface cleanliness levels.

A novel fractional case study of nonlinear dynamics via analytical approach

The present work describes the fractional view analysis of Newell-Whitehead-Segal equations,using an innovative technique.The work is carried with the help of the Caputo operator of fractional derivative.The analytical solutions of some numerical examples are presented to confirm the reliability of the proposed method.The derived results are very consistent with the actual solutions to the problems.A graphical representation has been done for the solution of the problems at various fractional-order derivatives.Moreover,the solution in series form has the desired rate of convergence and provides the closed-form solutions.It is noted that the procedure can be modified in other directions for fractional order problems.

Terahertz toroidal dipole metamaterial sensors for detection of aflatoxin B1

Terahertz metamaterial biosensors have attracted significant attention in the biological field due to their advantages of label-free,real-time and in situ detection.In this paper,a highly sensitive metamaterial sensor with semi-ring mirror symmetry based on toroidal dipole resonance is designed for a new metamaterial biosensor.It is shown that a refractive index sensitivity of 337.5 GHz per refractive index unit can be achieved under an analyte of saturated thickness near a 1.33 THz transmission dip.For biosensor samples where aflatoxin B1 is dropped on the metamaterial surface in our experiment,dip amplitudes of transmission varying from 0.1904 to 0.203 and 0.2093 are observed as aflatoxin B1 concentrations are altered from 0 to 0.001μg·ml-1 and to 0.01μg·ml-1,respectively.Furthermore,when aflatoxin B1 concentrations are 0.1μg·ml-1,1μg·ml-1,10μg·ml-1 and 100μg·ml-1,dip amplitudes of 0.2179,0.226,0.2384 and 0.2527 and dip redshifts of 10.1 GHz,20.1 GHz,27.7 GHz and 37.6 GHz are respectively observed.These results illustrate high-sensitivity,label-free detection of aflatoxin B1,enriching the applications of sensors in the terahertz domain.

GraphSTGAN:Situation understanding network of slow-fast high maneuvering targets for maritime monitor services of IoT data

With the rapid growth of the maritime Internet of Things(IoT)devices for Maritime Monitor Services(MMS),maritime traffic controllers could not handle a massive amount of data in time.For unmanned MMS,one of the key technologies is situation understanding.However,the presence of slow-fast high maneuvering targets and track breakages due to radar blind zones make modeling the dynamics of marine multi-agents difficult,and pose significant challenges to maritime situation understanding.In order to comprehend the situation accurately and thus offer unmanned MMS,it is crucial to model the complex dynamics of multi-agents using IoT big data.Nevertheless,previous methods typically rely on complex assumptions,are plagued by unstructured data,and disregard the interactions between multiple agents and the spatial-temporal correlations.A deep learning model,Graph Spatial-Temporal Generative Adversarial Network(GraphSTGAN),is proposed in this paper,which uses graph neural network to model unstructured data and uses STGAN to learn the spatial-temporal dependencies and interactions.Extensive experiments show the effectiveness and robustness of the proposed method.

A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

A patient co-infected with COVID-19 and viral hepatitis B can be atmore risk of severe complications than the one infected with a single infection.This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19.The model is fitted to real COVID-19 data from Pakistan.The proposed model incorporates logistic growth and saturated incidence functions.Rigorous analyses using the tools of stochastic calculus,are performed to study appropriate conditions for the existence of unique global solutions,stationary distribution in the sense of ergodicity and disease extinction.The stochastic threshold estimated from the data fitting is given by:R_(0)^(S)=3.0651.Numerical assessments are implemented to illustrate the impact of double-dose vaccination and saturated incidence functions on the dynamics of both diseases.The effects of stochastic white noise intensities are also highlighted.

A Novel Fractional Dengue Transmission Model in the Presence of Wolbachia Using Stochastic Based Artificial Neural Network

The purpose of this research work is to investigate the numerical solutions of the fractional dengue transmission model(FDTM)in the presence of Wolbachia using the stochastic-based Levenberg-Marquardt neural network(LM-NN)technique.The fractional dengue transmission model(FDTM)consists of 12 compartments.The human population is divided into four compartments;susceptible humans(S_(h)),exposed humans(E_(h)),infectious humans(I_(h)),and recovered humans(R_(h)).Wolbachia-infected and Wolbachia-uninfected mosquito population is also divided into four compartments:aquatic(eggs,larvae,pupae),susceptible,exposed,and infectious.We investigated three different cases of vertical transmission probability(η),namely when Wolbachia-free mosquitoes persist only(η=0.6),when both types of mosquitoes persist(η=0.8),and when Wolbachia-carrying mosquitoes persist only(η=1).The objective of this study is to investigate the effectiveness of Wolbachia in reducing dengue and presenting the numerical results by using the stochastic structure LM-NN approach with 10 hidden layers of neurons for three different cases of the fractional order derivatives(α=0.4,0.6,0.8).LM-NN approach includes a training,validation,and testing procedure to minimize the mean square error(MSE)values using the reference dataset(obtained by solving the model using the Adams-Bashforth-Moulton method(ABM).The distribution of data is 80% data for training,10% for validation,and,10% for testing purpose)results.A comprehensive investigation is accessible to observe the competence,precision,capacity,and efficiency of the suggested LM-NN approach by executing the MSE,state transitions findings,and regression analysis.The effectiveness of the LM-NN approach for solving the FDTM is demonstrated by the overlap of the findings with trustworthy measures,which achieves a precision of up to 10^(-4).

Statistical study of magnetic holes in the upstream region of Mercury’s bow shock

Magnetic holes are magnetic depression structures that exist widely in many plasma environments.The magnetic holes with durations of>1 s in the solar wind at Mercury’s orbit have drawn much attention,but the properties of the magnetic holes with shorter durations are still unclear.Here,we investigate the magnetic holes with durations of 0.1-100 s in the upstream region of Mercury’s bow shock based on observations by the MESSENGER(MErcury Surface,Space ENvironment,GEochemistry,and Ranging)spacecraft.They can be divided into two groups according to the distribution of their duration:small-duration magnetic holes(SDMHs,<0.6 s)and large-duration magnetic holes(LDMHs,>0.6 s).The duration of each group approximately obeys a log-normal distribution with a median of~0.25 s and 3 s,respectively.Approximately 1.7%(32.6%)of the SDMHs(LDMHs)reduce the magnetic field strength by more than 50%.For both groups,some structures have a linear or quasi-linear polarization,whereas others have an elliptical polarization.The magnetic hole events in both groups tend to have a higher rate of occurrence when the interplanetary magnetic field strength is weaker.Their occurrence rates are also affected by Mercury’s foreshock,which can increase(decrease)the occurrence rate of the SDMHs(LDMHs).This finding suggests that Mercury’s foreshock might be one source of the SDMHs and that the foreshock can destroy some LDMHs.These observations suggest that a new group of magnetic holes with durations of<0.6 s exist in the upstream region of Mercury’s bow shock.

Analysis of optical axis deviation caused by structural stiffness in equatorial telescopes

The impact of structural stiffness on optical axis deviation poses a significant challenge in the design of equatorial telescope structures.A comprehensive analysis during the design process can reduce the reliance of a telescope on advanced control technologies,thereby improving its economic feasibility.Although full-system finite element analyses are reliable,they are encumbered by significant time requirements and limitations in covering all possible telescope orientations.Therefore,we propose an efficient and comprehensive analytical method to evaluate the optical axis deviation of equatorial telescopes across a full range of angles.To address the challenge of ensuring that the analysis covers all possible positions of an equatorial telescope,based on a model from SiTian project,we analyze the optical axis deviations caused by the fork arm at 25 different angles and then use fitting methods to obtain results for all angles.Based on the analysis results of the optical axis deviation caused by the stiffness of the optical tube in the horizontal position,we derive the results for the tube at any position using geometric relationships.Finally,we calculate the coupling factors and combine these impacts.Furthermore,we identify six discrete feature points to reflect possible telescope orientations and conduct comprehensive finite element analyses.The results are in alignment with those acquired through a comprehensive computational approach.

An improved non-uniform fast Fourier transform method for radio imaging of coronal mass ejections

Radioheliographs can obtain solar images at high temporal and spatial resolution,with a high dynamic range.These are among the most important instruments for studying solar radio bursts,understanding solar eruption events,and conducting space weather forecasting.This study aims to explore the effective use of radioheliographs for solar observations,specifically for imaging coronal mass ejections(CME),to track their evolution and provide space weather warnings.We have developed an imaging simulation program based on the principle of aperture synthesis imaging,covering the entire data processing flow from antenna configuration to dirty map generation.For grid processing,we propose an improved non-uniform fast Fourier transform(NUFFT)method to provide superior image quality.Using simulated imaging of radio coronal mass ejections,we provide practical recommendations for the performance of radioheliographs.This study provides important support for the validation and calibration of radioheliograph data processing,and is expected to profoundly enhance our understanding of solar activities.

Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 diagnosis.However,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques.This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal cases.Texture information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering filters.Machine learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding diagnosis.The ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different pathologies.Furthermore,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased analysis.This analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered images.Notably,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

Recent advances in the magnetic reconnection,dipolarization,and auroral processes at giant planets from the perspective of comparative planetology

Magnetic reconnection and dipolarization are crucial processes driving magnetospheric dynamics,including particle energization,mass circulation,and auroral processes,among others.Recent studies have revealed that these processes at Saturn and Jupiter are fundamentally different from the ones at Earth.The reconnection and dipolarization processes are far more important than previously expected in the dayside magnetodisc of Saturn and potentially Jupiter.Dayside magnetodisc reconnection was directly identified by using Cassini measurements(Guo RL et al.,2018b)and was found to be drizzle-like and rotating in the magnetosphere of Saturn(Delamere et al.,2015b;Yao ZH et al.,2017a;Guo RL et al.,2019).Moreover,magnetic dipolarization could also exist at Saturn’s dayside(Yao ZH et al.,2018),which is fundamentally different from the terrestrial situation.These new results significantly improve our understanding of giant planetary magnetospheric dynamics and provide key insights revealing the physics of planetary aurorae.Here,we briefly review these recent advances and their potential implications for future investigations.

The ALMA-QUARKS Survey.Ⅱ.The ACA 1.3 mm Continuum Source Catalog and the Assembly of Dense Gas in Massive Star-Forming Clumps

Leveraging the high resolution,sensitivity,and wide frequency coverage of the Atacama Large Millimeter/submillimeter Array(ALMA),the QUARKS survey,standing for“Querying Underlying mechanisms of massive star formation with ALMA-Resolved gas Kinematics and Structures”,is observing 139 massive starforming clumps at ALMA Band 6(λ~1.3 mm).This paper introduces the Atacama Compact Array(ACA)7 m data of the QUARKS survey,describing the ACA observations and data reduction.Combining multiwavelength data,we provide the first edition of QUARKS atlas,offering insights into the multiscale and multiphase interstellar medium in high-mass star formation.The ACA 1.3 mm catalog includes 207 continuum sources that are called ACA sources.Their gas kinetic temperatures are estimated using three formaldehyde transitions with a non-LTE radiation transfer model,and the mass and density are derived from a dust emission model.The ACA sources are massive(16–84 percentile values of 6–160 M_(⊙)),gravity-dominated(M∝R^(1.1))fragments within massive clumps,with supersonic turbulence(M>1)and embedded star-forming protoclusters.We find a linear correlation between the masses of the fragments and the massive clumps,with a ratio of 6%between the two.When considering fragments as representative of dense gas,the ratio indicates a dense gas fraction(DGF)of 6%,although with a wide scatter ranging from 1%to 10%.If we consider the QUARKS massive clumps to be what is observed at various scales,then the size-independent DGF indicates a self-similar fragmentation or collapsing mode in protocluster formation.With the ACA data over four orders of magnitude of luminosity-to-mass ratio(L/M),we find that the DGF increases significantly with L/M,which indicates clump evolutionary stage.We observed a limited fragmentation at the subclump scale,which can be explained by a dynamic global collapse process.

In-flight calibration of the spaceborne fluxgate magnetometer in the Martian magnetosheath

In-flight calibration of the ze ro offset is crucial for ensuring high-precision measure ment of the spaceborne fluxgate magnetomete r.Tianwen-1 is China’s first Mars mission,and its orbiter will re main out of the solar wind for tens of days each year.Previous in-flight calibration methods might not be suitable for this orbiter during such a period.Recently,a new method was proposed by Wang GQ(2022 b),which we refer to as the Wang method Ⅱ for ease of description.Here,we test the performance of this method in the Martian magnetosheath by using magnetic field data measured by the Mars Atmosphere and Volatile EvolutioN(MAVEN) spacecraft.We find that the accuracy of the Wang method Ⅱ is affected by the number of magnetic field subinterval events,the eigenvalues of the minimum variance analysis for each event,and the position of the spacecraft in the magnetosheath.The estimated zero offset varies over a period of~27 days and has a 57.3% probability of accuracy within 2.0 nT.After being smoothed with a temporal window of 27 days,the ze ro offset has a 48.4%(99.3%) probability of accuracy within 1.0(2.0) nT.Our tests suggest that the Wang method Ⅱ provides an option for the Tianwen-1 orbiter to perform in-flight calibration when the orbiter remains out of the solar wind for an extended pe riod of time.

Statistical properties of kinetic-scale magnetic holes in terrestrial space

Kinetic-scale magnetic holes(KSMHs)are structures characterized by a significant magnetic depression with a length scale on the order of the proton gyroradius.These structures have been investigated in recent studies in near-Earth space,and found to be closely related to energy conversion and particle acceleration,wave-particle interactions,magnetic reconnection,and turbulence at the kineticscale.However,there are still several major issues of the KSMHs that need further study—including(a)the source of these structures(locally generated in near-Earth space,or carried by the solar wind),(b)the environmental conditions leading to their generation,and(c)their spatio-temporal characteristics.In this study,KSMHs in near-Earth space are investigated statistically using data from the Magnetospheric Multiscale mission.Approximately 200,000 events were observed from September 2015 to March 2020.Occurrence rates of such structures in the solar wind,magnetosheath,and magnetotail were obtained.We find that KSMHs occur in the magnetosheath at rates far above their occurrence in the solar wind.This indicates that most of the structures are generated locally in the magnetosheath,rather than advected with the solar wind.Moreover,KSMHs occur in the downstream region of the quasi-parallel shock at rates significantly higher than in the downstream region of the quasi-perpendicular shock,indicating a relationship with the turbulent plasma environment.Close to the magnetopause,we find that the depths of KSMHs decrease as their temporal-scale increases.We also find that the spatial-scales of the KSMHs near the subsolar magnetosheath are smaller than those in the flanks.Furthermore,their global distribution shows a significant dawn-dusk asymmetry(duskside dominating)in the magnetotail.

Stochastic Analysis for the Dynamics of a Poliovirus Epidemic Model

Most developing countries such as Afghanistan,Pakistan,India,Bangladesh,and many more are still fighting against poliovirus.According to the World Health Organization,approximately eighteen million people have been infected with poliovirus in the last two decades.In Asia,still,some countries are suffering from the virus.The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied.Some basic properties of the deterministic model are studied,equilibria,local stability around the stead states,and reproduction number.Euler Maruyama,stochastic Euler,and stochastic Runge-Kutta study the behavior of complex stochastic differential equations.The main target of this study is to develop a nonstandard computational method that restores dynamical features like positivity,boundedness,and dynamical consistency.Unfortunately,the existing methods failed to fix the actual behavior of the disease.The comparison of the proposed approach with existing methods is investigated.

2-7 Voltage Calibration and Energy Spread Measurement of 320 kV Platform at the Institute of Modern Physics

Four key reactions, 12C(, )13O, 13C(, n)16O, 25Mg(p, )26Al and 19F(p, )16O, will be studied for the first time within or near the astrophysical relevant energy regions (Gamow window) at Jinping Underground laboratory for Nuclear Astrophysics (JUNA)[1], which will take the advantage of the ultra-low background of China JinPing underground Laboratory (CJPL), high current accelerator based on ECR source and a highly sensitive detection system.

The effect of the guide field on energy conversion during collisionless magnetic reconnection

Magnetic reconnection is well known as an efficient mechanism for transferring magnetic energy into plasma energy.However,how the energy conversion and partition between different species is influenced by the shear angle of the reconnecting magnetic component(i.e.,the guide field strength)is not well understood.Using 2.5-dimensional particle-in-cell simulations,we investigated the energy conversion in reconnection with different guide fields.We found that the overall energy conversion first decreases steeply and then increases slowly when the guide field increases fromB_(g)=0 toB_(g)=4.The increase in energy conversion in the large guide field regime is due to the electron energy gain through the perpendicular channelJ_(⊥)·E_(⊥).The overall energy conversion is predominantly contributed byJ_(⊥)·E_(⊥) rather thanJ||E||.We further find that energy conversion mainly occurs within the reconnection front and the flux pileup region.However,the contribution from the fore reconnection front becomes important in large guide field regimes(3<B_(g)≤4)because of the enhanced electron energy gain.

AWeighted Average Finite Difference Scheme for the Numerical Solution of Stochastic Parabolic Partial Differential Equations

In the present paper,the numerical solution of It?type stochastic parabolic equation with a timewhite noise process is imparted based on a stochastic finite difference scheme.At the beginning,an implicit stochastic finite difference scheme is presented for this equation.Some mathematical analyses of the scheme are then discussed.Lastly,to ascertain the efficacy and accuracy of the suggested technique,the numerical results are discussed and compared with the exact solution.