Magnetopause properties at the dusk magnetospheric flank from global magnetohydrodynamic simulations,the kinetic Vlasov equilibrium,and in situ observations--Potential implications for SMILE

We derived the properties of the terrestrial magnetopause(MP)from two modeling approaches,one global–fluid,the other local–kinetic,and compared the results with data collected in situ by the Magnetospheric Multiscale 2(MMS2)spacecraft.We used global magnetohydrodynamic(MHD)simulations of the Earth’s magnetosphere(publicly available from the NASA-CCMC[National Aeronautics and Space Administration–Community Coordinated Modeling Center])and local Vlasov equilibrium models(based on kinetic models for tangential discontinuities)to extract spatial profiles of the plasma and field variables at the Earth’s MP.The global MHD simulations used initial solar wind conditions extracted from the OMNI database at the time epoch when the MMS2 observes the MP.The kinetic Vlasov model used asymptotic boundary conditions derived from the same in situ MMS measurements upstream or downstream of the MP.The global MHD simulations provide a three-dimensional image of the magnetosphere at the time when the MMS2 crosses the MP.The Vlasov model provides a one-dimensional local view of the MP derived from first principles of kinetic theory.The MMS2 experimental data also serve as a reference for comparing and validating the numerical simulations and modeling.We found that the MP transition layer formed in global MHD simulations was generally localized closer to the Earth(roughly by one Earth radius)from the position of the real MP observed by the MMS.We also found that the global MHD simulations overestimated the thickness of the MP transition by one order of magnitude for three analyzed variables:magnetic field,density,and tangential speed.The MP thickness derived from the local Vlasov equilibrium was consistent with observations for all three of these variables.The overestimation of density in the Vlasov equilibrium was reduced compared with the global MHD solutions.We discuss our results in the context of future SMILE(Solar wind Magnetosphere Ionosphere Link Explorer)campaigns for observing the Earth’s MP.

Dynamical Dark Energy in Light of Cosmic Distance Measurements.Ⅱ.A Study Using Current Observations

We extract key information on dark energy from current observations of BAO,OHD and H_(0),and find hints of dynamical behavior of dark energy.In particular,a dynamical dark energy model whose equation of state crosses-1 is favored by observations.We also find that the Universe has started accelerating at a lower redshift than expected.

Deep learning to estimate ocean subsurface salinity structure in the Indian Ocean using satellite observations

Accurately estimating the ocean subsurface salinity structure(OSSS)is crucial for understanding ocean dynamics and predicting climate variations.We present a convolutional neural network(CNN)model to estimate the OSSS in the Indian Ocean using satellite data and Argo observations.We evaluated the performance of the CNN model in terms of its vertical and spatial distribution,as well as seasonal variation of OSSS estimation.Results demonstrate that the CNN model accurately estimates the most significant salinity features in the Indian Ocean using sea surface data with no significant differences from Argo-derived OSSS.However,the estimation accuracy of the CNN model varies with depth,with the most challenging depth being approximately 70 m,corresponding to the halocline layer.Validations of the CNN model’s accuracy in estimating OSSS in the Indian Ocean are also conducted by comparing Argo observations and CNN model estimations along two selected sections and four selected boxes.The results show that the CNN model effectively captures the seasonal variability of salinity,demonstrating its high performance in salinity estimation using sea surface data.Our analysis reveals that sea surface salinity has the strongest correlation with OSSS in shallow layers,while sea surface height anomaly plays a more significant role in deeper layers.These preliminary results provide valuable insights into the feasibility of estimating OSSS using satellite observations and have implications for studying upper ocean dynamics using machine learning techniques.

Unprecedented JWST Observations Contest Cosmological Canons

After more than 18 months of nearly flawless operation,the James Webb Space Telescope(JWST)continues to deliver amazement,making unexpected discoveries,adding new wrinkles to known phenomena,and calling into question long-held theories of how the universe works.“The instruments are working amazingly well,in essentially all cases better than expected,”said Garth Illingworth,professor emeritus of astronomy and astrophysics at the University of California,Santa Cruz(CA,USA),and one of the three originators of the mission over three decades ago.“It has exceeded every one of its performance requirements,which is truly amazing when you think about how complex it is.”That complexity has included three decades of planning,design,and construction,followed by launch and maneuvering 1.5106 km from Earth to its second Lagrange(L2)orbit,unfolding and locking into position the 18 segments of its 6.5 m diameter main mirror,and deploying 8 motors,90 cables,and some 400 pulleys to unfurl its fragile sunshield[1,2].

Thermosphere joint observations by TM-1 constellations and Swarm-B during the April 2023 geomagnetic storm

The response of thermosphere density to geomagnetic storms is a complicated physical process.Multi-satellite joint observations at the same altitude but different local times(LTs)are important for understanding this process;however,until now such studies have hardly been done.In this report,we analyze in detail the thermosphere mass density response at 510 km during the April 23−24,2023 geomagnetic storm using data derived from the TM-1(TianMu-1)satellite constellation and Swarm-B satellites.The observations show that there were significant LT differences in the hemispheric asymmetry of the thermosphere mass density during the geomagnetic storm.Densities observed by satellite TM02 at nearly 11.3 and 23.3 LTs were larger in the northern hemisphere than in the southern.The TM04 dayside density observations appear to be almost symmetrical with respect to the equator,though southern hemisphere densities on the nightside were higher.Swarm-B data exhibit near-symmetry between the hemispheres.In addition,the mass density ratio results show that TM04 nightside observations,TM02 data,and Swarm-B data all clearly show stronger effects in the southern hemisphere,except for TM04 on the dayside,which suggest hemispheric near-symmetry.The South-North density enhancement differences in TM02 and TM04 on dayside can reach 130%,and Swarm-B data even achieve 180%difference.From the observations of all three satellites,large-scale traveling atmospheric disturbances(TADs)first appear at high latitudes and propagate to low latitudes,thereby disturbing the atmosphere above the equator and even into the opposite hemisphere.NRLMSISE00 model simulations were also performed on this geomagnetic storm.TADs are absent in the NRLMSISE00 simulations.The satellite data suggest that NRLMSISE00 significantly underestimates the magnitude of the density response of the thermosphere during geomagnetic storms,especially at high latitudes in both hemispheres.Therefore,use of the density simulation of NRLMSISE00 may lead to large errors in satellite drag calculations and orbit predictions.We suggest that the high temporal and spatial resolution of direct density observations by the TM-1 constellation satellites can provide an autonomous and reliable basis for correction and improvement of atmospheric models.

Design and analysis of an advanced thermal management system for the solar close observations and proximity experiments spacecraft

In this paper,the mission and the thermal environment of the Solar Close Observations and Proximity Experiments(SCOPE)spacecraft are analyzed,and an advanced thermal management system(ATMS)is designed for it.The relationship and functions of the integrated database,the intelligent thermal control system and the efficient liquid cooling system in the ATMS are elaborated upon.For the complex thermal field regulation system and extreme space thermal environment,a modular simulation and thermal field planning method are proposed,and the feasibility of the planning algorithm is verified by numerical simulation.A solar array liquid cooling system is developed,and the system simulation results indicate that the temperatures of the solar arrays meet the requirements as the spacecraft flies by perihelion and aphelion.The advanced thermal management study supports the development of the SCOPE program and provides a reference for the thermal management in other deep-space exploration programs.

RLS Wiener Predictor with Uncertain Observations in Linear Discrete-Time Stochastic Systems

This paper proposes recursive least-squares (RLS) l-step ahead predictor and filtering algorithms with uncertain observations in linear discrete-time stochastic systems. The observation equation is given by y(k)=y(k)z(k)+v(k), z(k)=Hx(k), where {y(k)} is a binary switching sequence with conditional probability. The estimators require the information of the system state-transition matrix Ф, the observation matrix H, the variance K(k,k) of the state vector x(k), the variance R(k) of the observation noise, the probability p(k)=p{y(k)=1} that the signal exists in the uncertain observation equation and the (2,2) element [p(k|j)]2,2 of the conditional probability of y(k), given y(j).

In-situ observations of damage-fracture evolution in surrounding rock upon unloading in 2400-m-deep tunnels

The damage-fracture evolution of deep rock mass has obvious particularity,which is revealed in 2400-mdeep tunnels by field tests.The evolution of the excavation damaged zone depth is consistent with that of the fractured zone depth.The ratio of the excavation damaged zone depth to the excavation fractured zone depth is greater than 2.0 in a rock mass with both high strength and good integrity,but less than1.5 in a rock mass with lower strength or poor integrity.Zonal disintegration in a rock mass with high strength and fair integrity is more likely to occur when it contains more than two groups of primary fractures in damaged zones.Fractures develop outward in zonal disintegration but are totally different from the single-zone fracture,in which the fractures develop inward,and it is the starting position of the fractured zone when the excavation surface of the middle pilot is 7–9 m close to the pre-set borehole and it stops after the excavation surface of the baseplate is 11–14 m away.The most intense evolution occurs around 2–4 m from the pre-set borehole in the sidewall expansion stage.The research results provide a reference for the monitoring scheme and support design of CJPL-Ⅲin its future construction.

Twenty years of ocean observations with China Argo

The international Argo program,a global observational array of nearly 4000 autonomous profiling floats initiated in the late 1990s,which measures the water temperature and salinity of the upper 2000 m of the global ocean,has revolutionized oceanography.It has been recognized one of the most successful ocean observation systems in the world.Today,the proposed decade action“OneArgo”for building an integrated global,full-depth,and multidisciplinary ocean observing array for beyond 2020 has been endorsed.In the past two decades since 2002,with more than 500 Argo deployments and 80 operational floats currently,China has become an important partner of the Argo program.Two DACs have been established to process the data reported from all Chinese floats and deliver these data to the GDACs in real time,adhering to the unified quality control procedures proposed by the Argo Data Management Team.Several Argo products have been developed and released,allowing accurate estimations of global ocean warming,sea level change and the hydrological cycle,at interannual to decadal scales.In addition,Deep and BGC-Argo floats have been deployed,and time series observations from these floats have proven to be extremely useful,particularly in the analysis of synoptic-scale to decadal-scale dynamics.The future aim of China Argo is to build and maintain a regional Argo fleet comprising approximately 400 floats in the northwestern Pacific,South China Sea,and Indian Ocean,accounting for 9%of the global fleet,in addition to maintaining 300 Deep Argo floats in the global ocean(25%of the global Deep Argo fleet).A regional BGC-Argo array in the western Pacific also needs to be established and maintained.

Dataset of Comparative Observations for Land Surface Processes over the Semi-Arid Alpine Grassland against Alpine Lakes in the Source Region of the Yellow River

Thousands of lakes on the Tibetan Plateau(TP) play a critical role in the regional water cycle, weather, and climate. In recent years, the areas of TP lakes underwent drastic changes and have become a research hotspot. However, the characteristics of the lake-atmosphere interaction over the high-altitude lakes are still unclear, which inhibits model development and the accurate simulation of lake climate effects. The source region of the Yellow River(SRYR) has the largest outflow lake and freshwater lake on the TP and is one of the most densely distributed lakes on the TP. Since 2011,three observation sites have been set up in the Ngoring Lake basin in the SRYR to monitor the lake-atmosphere interaction and the differences among water-heat exchanges over the land and lake surfaces. This study presents an eight-year(2012–19), half-hourly, observation-based dataset related to lake–atmosphere interactions composed of three sites. The three sites represent the lake surface, the lakeside, and the land. The observations contain the basic meteorological elements,surface radiation, eddy covariance system, soil temperature, and moisture(for land). Information related to the sites and instruments, the continuity and completeness of data, and the differences among the observational results at different sites are described in this study. These data have been used in the previous study to reveal a few energy and water exchange characteristics of TP lakes and to validate and improve the lake and land surface model. The dataset is available at National Cryosphere Desert Data Center and Science Data Bank.

Receding Horizon Estimation for Linear Discrete-time Systems with Multi-channel Observation Delays

This paper investigates the receding horizon state estimation for the linear discrete-time system with multi-channel observation delays. The receding horizon estimation is designed by the reorganized observation technique and the linear unbiased estimation method. The estimation gains are developed by solving a set of Riccati equations, and a stability result about the state estimation is shown. Finally, an example is given to illustrate the efficiency of the receding horizon state estimation.

Reduced-Order Observer-Based Leader-Following Formation Control for Discrete-Time Linear Multi-Agent Systems

Formation control of discrete-time linear multi-agent systems using directed switching topology is considered in this work via a reduced-order observer, in which a formation control protocol is proposed under the assumption that each directed communication topology has a directed spanning tree. By utilizing the relative outputs of neighboring agents, a reduced-order observer is designed for each following agent. A multi-step control algorithm is established based on the Lyapunov method and the modified discrete-time algebraic Riccati equation. A sufficient condition is given to ensure that the discrete-time linear multi-agent system can achieve the expected leader-following formation.Finally, numerical examples are provided so as to demonstrate the effectiveness of the obtained results.

Sampled-data Observer Design for a Class of Stochastic Nonlinear Systems Based on the Approximate Discrete-time Models

In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear systems.Euler-Maruyama approximation was investigated in this paper because it is the basis of other higher precision numerical methods,and it preserves important structures of the nonlinear systems.Also,the form of Euler-Maruyama model is simple and easy to be calculated.The results provide a reference for sampled-data observer design method for such stochastic nonlinear systems,and may be useful to many practical control applications,such as tracking control in mechanical systems.And the effectiveness of the approach is demonstrated by a simulation example.

Deterministic and Stochastic Fixed-Time Stability of Discrete-time Autonomous Systems

This paper studies deterministic and stochastic fixedtime stability of autonomous nonlinear discrete-time(DT)systems.Lyapunov conditions are first presented under which the fixed-time stability of deterministic DT systems is certified.Extensions to systems under deterministic perturbations as well as stochastic noise are then considered.For the former,sensitivity to perturbations for fixed-time stable DT systems is analyzed,and it is shown that fixed-time attractiveness results from the presented Lyapunov conditions.For the latter,sufficient Lyapunov conditions for fixed-time stability in probability of nonlinear stochastic DT systems are presented.The fixed upper bound of the settling-time function is derived for both fixed-time stable and fixed-time attractive systems,and a stochastic settling-time function fixed upper bound is derived for stochastic DT systems.Illustrative examples are given along with simulation results to verify the introduced results.

Do Observations during Patrolling Trips Detect Changes in Wildlife Presence & Diversity in National Parks?

Globally, mountains encompass spectacular landscapes and a great diversity of species. However, Savannah’s mountains in Sudan have been affected by the loss of diversity due to human activities and climate changes. Therefore, this study aims to assess changes in wildlife diversity in Jebel-Eldair Nation Park (JENP) based on only reports from patrolling activities, especially in the absence of regular wildlife monitoring programs. Reports of monthly wildlife observations during patrolling trips were used for the summer season in 2010 and 2018. Findings showed a moderate to high decline in the most important wildlife species (i.e. lion, wild dog, and crest porcupine). Six others are documented as rare species in reserve, including the civet, spotted hyena, striped hyena, jackal, seraval, and Siberian bird. Contrary and despite the diversity reduction, some species witnessed increases in their observation frequency, such as lesser kudu, caracal, monitor, and lunar bird. Moreover, human settlements, agricultural activities, and other anthropogenic factors were found to be the main drivers of biodiversity reduction in JENP. The study recommends adopting this method to detect changes in wildlife communities, especially in a situation of deficiency and lack of funding to conduct regular monitoring programs.

Stabilization of a class of discrete-time switched systems via observer-based output feedback

In this paper, observer-based static output feedback control problem for discrete-time uncertain switched systems is investigated under an arbitrary switching rule. The main method used in this note is combining switched Lyapunov function （SLF） method with Finsler＇s Lemma. Based on linear matrix inequality （LMI） a less conservative stability condition is established and this condition allows extra degree of freedom for stability analysis. Finally, a simulation example is given to illustrate the efficiency of the result.

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.

Event-Triggered Finite-Time H∞ Filtering for Discrete-Time Nonlinear Stochastic Systems

This paper addresses the problem of event-triggered finite-time H∞ filter design for a class of discrete-time nonlinear stochastic systems with exogenous disturbances. The stochastic Lyapunov-Krasoviskii functional method is adopted to design a filter such that the filtering error system is stochastic finite-time stable (SFTS) and preserves a prescribed performance level according to the pre-defined event-triggered criteria. Based on stochastic differential equations theory, some sufficient conditions for the existence of H∞ filter are obtained for the suggested system by employing linear matrix inequality technique. Finally, the desired H∞ filter gain matrices can be expressed in an explicit form.

Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks.However,when faced with a complex operation,the traditional proportional-integral-derivative(PID)control may not meet requirements for high control performance.Model-based full-state-feedback control is an effective alternative,but the states of a hydraulic manipulator are not always available and reliable in practical applications,particularly the joint angular velocity measurement.Considering that it is not suitable to obtain the velocity signal directly from differentiating of position measurement,the low-pass filtering is commonly used,but it will definitely restrict the closed-loop bandwidth of the whole system.To avoid this problem and realize better control performance,this paper proposes a novel observerbased adaptive robust controller(obARC)for a multi-joint hydraulic manipulator subjected to both parametric uncertainties and the lack of accurate velocity measurement.Specifically,a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties.Then,the adaptive robust control is developed to compensate for the dynamic uncertainties,and the close-loop system robust stability is theoretically proved under the observation and control errors.Finally,comparative experiments are carried out to show that the designed controller can achieve a performance improvement over the traditional methods,specifically yielding better control accuracy owing to the closed-loop bandwidth breakthrough,which is limited by low-pass filtering in fullstate-feedback control.

Disturbance Observer-Based Predictive Tracking Control of Uncertain HOFA Cyber-Physical Systems

Dear Editor,In this letter,an output tracking control problem of uncertain cyber-physical systems(CPSs)is considered in the perspective of high-order fully actuated(HOFA)system theory,where a lumped disturbance is used to denote the total uncertainties containing parameters perturbations and external disturbances.