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.

Stabilization of the Cascaded ODE-Schrödinger Equations Subject to Observation With Time Delay

This paper focuses on the stabilization of the cascaded Schrodinger-ODE equations subject to the observation with time delay.Both observer and predictor systems are designed to estimate the state variable on the time interval[0,t-τ]when the observation is available,and to predict the state variable on the time interval[t-τ,t]when the observation is not available,respectively.Based on the estimated state variable and the output feedback stabilizing controller using the backstepping method,it is shown that the closed-loop system is exponentially stable.

Design of RLS Wiener Smoother and Filter for Colored Observation Noise in Linear Discrete-Time Stochastic Systems

Almost estimators are designed for the white observation noise. In the estimation problems, rather than the white observation noise, there might be actual cases where the observation noise is modeled by the colored noise process. This paper examines to design a new estimation technique of recursive least-squares (RLS) Wiener fixed-point smoother and filter for colored observation noise in linear discrete-time wide-sense stationary stochastic systems. The observation y(k) is given as the sum of the signal z(k)=Hx(k) and the colored observation noise vc(k). The RLS Wiener estimators explicitly require the following information: 1) the system matrix for the state vector x(k);2) the observation matrix H;3) the variance of the state vector x(k);4) the system matrix for the colored observation noise vc(k);5) the variance of the colored observation noise;6) the input noise variance in the state equation for the colored observation noise.

Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data

On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering （EKF） and the unscented Kalman filtering （UKF）, which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network （RBFNN） prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.

Wavenumber-4 spectral component extracted from TIMED/SABER observations

The wavenumber spectral components WN4 at the mesosphere and low thermosphere(MLT)altitudes(70–10 km)and in the latitude range between±45°are obtained from temperature data(T)observed by the Sounding of the Atmosphere using Broadband Emission Radiometry(SABER)instruments on board the National Aeronautics and Space Administration(NASA)’s Thermosphere–Ionosphere–Mesosphere Energetics and Dynamics(TIMED)spacecraft during the 11-year solar period from 2002 to 2012.We analyze in detail these spectral components WNk and obtain the main properties of their vertical profiles and global structures.We report that all of the wavenumber spectral components WNk occur mainly around 100 km altitude,and that the most prominent component is the wavenumber spectral component WN4 structure.Comparing these long duration temperature data with results of previous investigations,we have found that the yearly variation of spectral component WN4 is similar to that of the eastward propagating non-migrating diurnal tide with zonal wavenumber 3(DE3)at the low latitudes,and to that of the semi-diurnal tide with zonal wavenumber 2(SE2)at the mid-latitudes:the amplitudes of the A4 are larger during boreal summer and autumn at the low-latitudes;at the mid-latitudes the amplitudes have a weak peak in March.In addition,the amplitudes of component WN4 undergo a remarkable short period variation:significant day-to-day variation of the spectral amplitudes A4 occurs primarily in July and September at the low-latitudes.In summary,we conclude that the non-migrating tides DE3 and SE2 are likely to be the origins,at the low-latitudes and the mid-latitudes in the MLT region,respectively,of the observed wavenumber spectral component WN4.

Maximum Likelihood Estimation for the Pooled Repeated Partly Interval-Censored Observations Logistic Regression Model

Often in longitudinal studies, some subjects complete their follow-up visits, but others miss their visits due to various reasons. For those who miss follow-up visits, some of them might learn that the event of interest has already happened when they come back. In this case, not only are their event times interval-censored, but also their time-dependent measurements are incomplete. This problem was motivated by a national longitudinal survey of youth data. Maximum likelihood estimation (MLE) method based on expectation-maximization (EM) algorithm is used for parameter estimation. Then missing information principle is applied to estimate the variance-covariance matrix of the MLEs. Simulation studies demonstrate that the proposed method works well in terms of bias, standard error, and power for samples of moderate size. The national longitudinal survey of youth 1997 (NLSY97) data is analyzed for illustration.

Experimental Model and Analytic Solution for Real-time Observation of Vehicle's Additional Steer Angle

The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.

The application of neural network to the analysis of earthquake precursor chaotic time series

Artificial neural network (NN) is such a model as to imitate the structure and intelligence feature of human brain. It has strong nonlinear mapping function. To introduce NN into the study of earthquake prediction is not only an extension of the application of artificial neural network model but also a new try for precursor observation to serve the earthquake prediction. In this paper, we analyzed the predictability of time series and gave a method of application of artificial neural network in forecasting earthquake precursor chaotic time series. Besides, taking the ground tilt observation of Jiangning and Xuzhou Station, the bulk strain observation of Liyang station as examples, we analyzed and forecasted their time series respectively. It is indicated that the precision of this method can meet the needs of practical task and therefore of great value in the application to the future practical earthquake analysis and prediction.

Time Series Correlated Error's Simulation Scheme with the Application to Simulate the Ephemerides Error of CHAMP

Computer simulation experiment is very important in the phase of project design, the availability of simulated result highly depends on the scheme of error simulation. Time series observations are normally correlated. This paper first discusses the formula of correlated error propagation, then derives the formula of simulating time series correlated errors. This formula is then used to simulate correlated ephemerides errors of CHAMP, then the ephemerides are used to recover the gravity vector at satellite altitude with finite differential formula. The formulae derived in this paper are verified with the difference between the recovered gravity vectors and the `true values’ which are directly computed with the same gravity model as that generating the ephemerides.

IMPULSIVE EXPONENTIAL SYNCHRONIZATION OF FRACTIONAL-ORDER COMPLEX DYNAMICAL NETWORKS WITH DERIVATIVE COUPLINGS VIA FEEDBACK CONTROL BASED ON DISCRETE TIME STATE OBSERVATIONS

This article aims to address the global exponential synchronization problem for fractional-order complex dynamical networks(FCDNs)with derivative couplings and impulse effects via designing an appropriate feedback control based on discrete time state observations.In contrast to the existing works on integer-order derivative couplings,fractional derivative couplings are introduced into FCDNs.First,a useful lemma with respect to the relationship between the discrete time observations term and a continuous term is developed.Second,by utilizing an inequality technique and auxiliary functions,the rigorous global exponential synchronization analysis is given and synchronization criterions are achieved in terms of linear matrix inequalities(LMIs).Finally,two examples are provided to illustrate the correctness of the obtained results.

Study on the Cap Rock Deformation of Hutubi Underground Gas Storage by GPS Observations

The deformation responses of surface cap rocks of Underground Gas Storage( UGS) in Hutubi,Xinjiang during gas injection and production were investigated with the GPS data recorded by the deformation monitoring network,which includes 13 observation sites. The time series of three-dimensional deformation of the surface cap rocks was obtained in the UGS operation process,and the deformation signals in different phases were identified by combining the GPS data with wellhead pressure data. The results show that the respiration response of surface cap rock deformation is obvious during gas injection and production of UGS,and the surface deformation due to a 1MPa change of wellhead pressure is 1. 02 mm in gas injection and 1. 24 mm in gas production horizontally, and- 1. 11 mm in gas injection and 0. 86 mm in gas production vertically.

Real-time observation of integrin bending/unbending conformational changes on living cells

Introduction Integrins are a large family of adhesion molecules broadly expressed on the surface of a wide variety of cells as heterodimers. Binding of integrins to ligands provides not only mechanical anchorage for the cell to another cell or

Time-Expanded Sampling for Ensemble-Based Filters:Assimilation Experiments with Real Radar Observations

By sampling perturbed state vectors from each ensemble prediction run at properly selected time levels in the vicinity of the analysis time, the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and, hence, can reduce the computational cost of an ensemble-based filter. In this study, this approach is tested for the first time with real radar data from a tornadic thunderstorm. In particular, four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemble- based filters. In these experiments, the ensemble square-root filter （EnSRF） was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs, respectively, and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances. The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis, especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation. These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data.

A seismic modeling analysis of wide and narrow 3D observation systems for channel sand bodies

The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utilize 3D physical seismic modeling experiments. A 3D channel sand body physical seismic model is constructed and two acquisition systems are designed with wide azimuth （16 lines） and narrow azimuth （8 lines） to model 3D seismic data acquisition and processing seismic work flows. From analysis of migrated time slice data with high quality and small size, we conclude that when the overlying layers are smooth and lateral velocities have little change, both wide and narrow azimuth observation systems in 3D acquisition can be used for obtaining high precision imaging and equivalent resolution of the channel sand body.

The Time and Regime Dependencies of Sensitive Areas for Tropical Cyclone Prediction Using the CNOP Method

This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optiflml perturbation （CNOP） method for forecasts of two typhoons. Typhoon Meari （2004） was weakly nonlinear and is herein referred to as the linear case, while Typhoon Matsa （2005） was strongly nonlinear and is herein referred to as the nonlinear case. In the linear case, the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times. Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times. In the nonlinear case, the similarities among the sensitive areas identified for different forecast times were more limited. The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts. For both cases, the closer the forecast time, the higher the similarities of the sensitive areas. When the forecast time was fixed, the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened, while those in the nonlinear case were always located around the initial cyclones. The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment. An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results. In general, the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.

Differential geometric guidance command with finite time convergence using extended state observer

For improving the performance of differential geometric guidance command(DGGC), a new formation of this guidance law is proposed, which can guarantee the finite time convergence(FTC) of the line of sight(LOS) rate to zero or its neighborhood against maneuvering targets in three-dimensional(3D) space. The extended state observer(ESO) is employed to estimate the target acceleration, which makes the new DGGC more applicable to practical interception scenarios. Finally, the effectiveness of this newly proposed guidance command is demonstrated by the numerical simulation results.

Actuator fault diagnosis of time-delay systems based on adaptive observer

A novel approach for the actuator fault diagnosis of time-delay systems is presented by using an adaptive observer technique. Systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system is subjected to either model uncertainty or external disturbance. An adaptive diagnostic algorithm is developed to diagnose the fault, and a modified version is proposed for general system to improve robustness. The selection of the threshold for fault detection is also discussed. Finally, a numerical example is given to illustrate the efficiency of the proposed method.

Clinical implications of doubling time of gastrointestinal submucosal tumors

AIM To evaluate the efficacy of doubling time(DT) of gastrointestinal submucosal tumors(GIST).METHODS From April 1987 through November 2012, a total of 323 patients were given a final histopathological diagnosis of GISTs on surgical resection or endoscopic ultrasound-guided fine-needle aspiration(EUS-FNA) in Kitasato University East Hospital or Kitasato University Hospital. We studied 53 of these patients(34 with resected tumors and 19 with unresected tumors) whose tumors could be measured on EUS on at least two successive occasions. The histopathological diagnosis was GIST in 34 patients, leiomyoma in 5, schwannoma in 3, ectopic pancreas in 1, hamartoma in 1, cyst in 1, Brunner's adenoma in 1, and spindle-cell tumor in 7. We retrospectively calculated the DT of GISTs on the basis of the time course of EUS findings to estimate the growth rate of such tumors.RESULTS The DT was 17.2 mo for GIST, as compared with 231.2 mo for leiomyoma, 104.7 mo for schwannoma, 274.9mo for ectopic pancreas, 61.2 mo for hamartoma, 49.0 mo for cyst, and 134.7 mo for Brunner's adenoma. The GISTs were divided into risk classes on the basis of tumor diameters and mitotic figures(Fletcher's classification). The classification was extremely low risk or low risk in 28 patients, intermediate risk in 3, and high risk in 3. DT of GIST according to risk was 24.0 mo for extremely low-risk plus low-risk GIST, 17.1 mo for intermediate-risk GIST, and 3.9 mo for high-risk GIST. DT of GIST was significantly shorter than that of leiomyoma plus schwannoma(P < 0.05), and DT of high-risk GIST was significantly shorter than that of extremely low-risk plus low-risk GIST(P < 0.05).CONCLUSION For GIST, a higher risk grade was associated with a significantly shorter DT. Small SMTs should initially be followed up within 6 mo after detection.

Observer-based multivariable fixed-time formation control of mobile robots

This paper proposes a multivariable fixed-time leaderfollower formation control method for a group of nonholonomic mobile robots, which has the ability to estimate multiple uncertainties. Firstly, based on the state space model of the leader-follower formation, a multivariable fixed-time formation kinematics controller is designed. Secondly, to overcome uncertainties existing in the nonholonomic mobile robot system, such as load change,friction, external disturbance, a multivariable fixed-time torque controller based on the fixed-time disturbance observer at the dynamic level is designed. The designed torque controller is cascaded with the formation controller and finally realizes accurate estimation of the uncertain part of the system, the follower tracking of reference velocity and the desired formation of the leader and the follower in a fixed-time. The fixed-time upper bound is completely determined by the controller parameters, which is independent of the initial state of the system. The multivariable fixed-time control theory and the Lyapunov method are adopted to ensure the system stability.Finally, the effectiveness of the proposed algorithm is verified by the experimental simulation.