Dynamics of measurement-induced non-locality and geometric discord with initial system-environment correlations

We analyze the dynamics of geometric measure of discord （GMOD） and measurement-induced non-locality （MIN） in the presence of initial system-reservoir correlations without Born and Markov approximation. Although the initial system-environment states have the same reduced density matrices for both the system and environment, the effects of different initial system-environment correlations have been shown to fundamentally alter the time evolution of GMOD and MIN between two quantum systems in both Markovian and non-Markovian regimes. In general, both GMOD and MIN experience a sudden increase for initially quantum-correlated states, and a sudden decrease for classical-correlated states before they reach the same stationary values with initially factorized states.

Numerical simulation for the initial state of avalanche in polydisperse particle systems

Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle systems.Nucleation and propagation processes are illustrated for pentadisperse and triadisperse particle systems,respectively.In these processes,particles involved in the avalanche grow slowly in the early stage and explosively in the later stage,which is clearly different from the continuous and steady growth trend in the monodisperse system.By examining the avalanche propagation,the number growth of particles involved in the avalanche and the slope of the number growth,the initial state can be divided into three stages:T1(nucleation stage),T2(propagation stage),T3(overall avalanche stage).We focus on the characteristics of the avalanche in the T2 stage,and find that propagation distances increase almost linearly in both axial and radial directions in polydisperse systems.We also consider the distribution characteristics of the average coordination number and average velocity for the moving particles.The results support that the polydisperse particle systems are more stable in the T2 stage.

Initial-state dependence of phase behaviors in a dense active system

There are rich emergent phase behaviors in non-equilibrium active systems.Flocking and clustering are two representative dynamic phases.The relationship between both the phases is still unclear.Herein,we numerically investigate the evolution of flocking and clustering in a system consisting of self-propelled particles with active reorientation.We consider the interplay between flocking and clustering phases with different initial configurations,and observe a domain in steady state order parameter phase diagrams sensitive to the choice of initial configurations.Specifically,by tuning the initial degree of polar ordering,either a more ordered flocking or a disordered clustering state can be observed in the steady state.These results enlighten us to manipulate emergent behaviors and collective motions of an active system,and are qualitatively different from the emergence of a new bi-stable regime observed in aligned active particles due to an explicit attraction[New J.Phys.14073033(2012)].

Mg-doped,carbon-coated,and prelithiated SiO_(x) as anode materials with improved initial Coulombic efficiency for lithium-ion batteries

Silicon suboxide(SiO_(x),x≈1)is promising in serving as an anode material for lithium-ion batteries with high capacity,but it has a low initial Coulombic efficiency(ICE)due to the irreversible formation of lithium silicates during the first cycle.In this work,we modify SiO_(x) by solid-phase Mg doping reaction using low-cost Mg powder as a reducing agent.We show that Mg reduces SiO_(2) in SiO_(x) to Si and forms MgSiO_(3) or Mg_(2)SiO_(4).The MgSiO_(3) or Mg_(2)SiO_(4) are mainly distributed on the surface of SiO_(x),which suppresses the irreversible lithium-ion loss and enhances the ICE of SiO_(x).However,the formation of MgSiO_(3) or Mg_(2)SiO_(4) also sacrifices the capacity of SiO_(x).Therefore,by controlling the reaction process between Mg and SiO_(x),we can tune the phase composition,proportion,and morphology of the Mg-doped SiO_(x) and manipulate the performance.We obtain samples with a capacity of 1226 mAh g^(–1) and an ICE of 84.12%,which show significant improvement over carbon-coated SiO_(x) without Mg doping.By the synergistical modification of both Mg doping and prelithiation,the capacity of SiO_(x) is further increased to 1477 mAh g^(–1) with a minimal compromise in the ICE(83.77%).

Impact of Initial Soil Conditions on Soil Hydrothermal and Surface Energy Fluxes in the Permafrost Region of the Tibetan Plateau

Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling.This study emphasized the influence of the initial soil temperature(ST)and soil moisture(SM)conditions on a land surface energy and water simulation in the permafrost region in the Tibetan Plateau(TP)using the Community Land Model version 5.0(CLM5.0).The results indicate that the default initial schemes for ST and SM in CLM5.0 were simplistic,and inaccurately represented the soil characteristics of permafrost in the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site.Applying the long-term spin-up method to obtain initial soil conditions has only led to limited improvement in simulating soil hydrothermal and surface energy fluxes.The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost,which coexists with soil liquid water(SLW),and soil ice(SI)when the ST is below freezing temperature,effectively enhancing the accuracy of the simulated soil hydrothermal and surface energy fluxes.Consequently,the modified initial soil schemes greatly improved upon the results achieved through the long-term spin-up method.Three modified initial soil schemes experiments resulted in a 64%,88%,and 77%reduction in the average mean bias error(MBE)of ST,and a 13%,21%,and 19%reduction in the average root-mean-square error(RMSE)of SLW compared to the default simulation results.Also,the average MBE of net radiation was reduced by 7%,22%,and 21%.

Irregular initial solidification by mold thermal monitoring in the continuous casting of steels:A review

Occasional irregular initial solidification phenomena,including stickers,deep oscillation marks,depressions,and surface cracks of strand shells in continuous casting molds,are important limitations for developing the high-efficiency continuous casting of steels.The application of mold thermal monitoring(MTM) systems,which use thermocouples to detect and respond to temperature variations in molds,has become an effective method to address irregular initial solidification phenomena.Such systems are widely applied in numerous steel companies for sticker breakout prediction.However,monitoring the surface defects of strands remains immature.Hence,indepth research is necessary to utilize the potential advantages and comprehensive monitoring of MTM systems.This paper summarizes what is included in the irregular initial solidification phenomena and systematically reviews the current state of research on these phenomena by the MTM systems.Furthermore,the influences of mold slag behavior on monitoring these phenomena are analyzed.Finally,the remaining problems of the formation mechanisms and investigations of irregular initial solidification phenomena are discussed,and future research directions are proposed.

An Initial Perturbation Method for the Multiscale Singular Vector in Global Ensemble Prediction

Ensemble prediction is widely used to represent the uncertainty of single deterministic Numerical Weather Prediction(NWP) caused by errors in initial conditions(ICs). The traditional Singular Vector(SV) initial perturbation method tends only to capture synoptic scale initial uncertainty rather than mesoscale uncertainty in global ensemble prediction. To address this issue, a multiscale SV initial perturbation method based on the China Meteorological Administration Global Ensemble Prediction System(CMA-GEPS) is proposed to quantify multiscale initial uncertainty. The multiscale SV initial perturbation approach entails calculating multiscale SVs at different resolutions with multiple linearized physical processes to capture fast-growing perturbations from mesoscale to synoptic scale in target areas and combining these SVs by using a Gaussian sampling method with amplitude coefficients to generate initial perturbations. Following that, the energy norm,energy spectrum, and structure of multiscale SVs and their impact on GEPS are analyzed based on a batch experiment in different seasons. The results show that the multiscale SV initial perturbations can possess more energy and capture more mesoscale uncertainties than the traditional single-SV method. Meanwhile, multiscale SV initial perturbations can reflect the strongest dynamical instability in target areas. Their performances in global ensemble prediction when compared to single-scale SVs are shown to(i) improve the relationship between the ensemble spread and the root-mean-square error and(ii) provide a better probability forecast skill for atmospheric circulation during the late forecast period and for short-to medium-range precipitation. This study provides scientific evidence and application foundations for the design and development of a multiscale SV initial perturbation method for the GEPS.

An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous motor.However,traditional methods require a large number of filters,which leads to the deterioration of system stability and dynamic performance.In order to solve these problems,a new signal demodulation method is proposed in this paper.The proposed new method can directly obtain the amplitude of high-frequency current,thus eliminating the use of filters,improving system stability and dynamic performance and saving the work of adjusting filter parameters.In addition,a new magnetic polarity detection method is proposed,which is robust to current measurement noise.Finally,experiments verify the effectiveness of the method.

A Situational Awareness Method for Initial Insulation Fault of Distribution Network Based on Multi-Feature Index Comprehensive Evaluation

Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.

Periorbital purpura can be the only initial symptom of primary light chain amyloidosis:A case report

BACKGROUND Primary light chain amyloidosis is a rare and complex disease with complex clinical features and is highly susceptible to misdiagnosis and underdiagnosis in the early stages.CASE SUMMARY We report a case of a 47-year-old female patient whose only initial symptom was periorbital purpura,which was not taken seriously enough.As the disease progressed,pleural effusion gradually appeared,and after systematic diagnosis and treatment,she was diagnosed with“primary light chain amyloidosis”.She achieved rapid hematological remission after treatment with a daratumumab+bortezomib+cyclophosphamide+dexamethasone regimen.CONCLUSION Periorbital purpura can be the only initial symptom of primary light chain amyloidosis;we should pay attention to the cases where the initial clinical symptoms are only periorbital purpura.

Influence of initial check, information exchange, final accuracy check, reaction information nursing on the psychology of elderly with lung cancer

BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.

Drone systems for delivering defibrillators for sudden cardiac arrests

Unmanned aerial vehicles(UAVs),or drones,that were initially developed for military use during World War I[1],have evolved into highly sophisticated aircraft that can be navigated remotely using global positioning systems.With constant improvements,drones have become more efficient,and cost-effective,with longer battery life and greater loading capacity.Today,UAVs have proven to be an effective and affordable solution for enhancing healthcare accessibility for patients who face geographical or infrastructural barriers.Using drone networks can greatly reduce the time transporting life-saving equipment,such as delivering automated external defibrillators(AEDs),to cardiac arrest victims,and can provide quick assistance to reduce travel time for the patients.

Effect of Size and Initial Water Content on the Effective Diffusion Coefficient during Convective Drying of Sweet Potato Cut into Cubic and Cylindrical Shapes

In this article, we investigated the influence of size and initial water content on the effective diffusion coefficient of sweet potatoes samples cut into cubic and cylindrical shapes. The sizes of the cubic samples are 0.5, 1, 1.5, 1.75, 2, 2.5 and 3 cm edge with a respective initial water content of 2.7, 3.76, 3.48, 2.68, 3.28, 2.17 and 2.29 kg/kgms. For cylindrical samples, the radius is set at 0.5 cm and sample heights are 1, 1.5, 2, 2.5, 3, 3.5 and 4 cm with respective water contents of 2.2, 3.19, 2.85, 2.1, 2.17, 2.39 and 2.03 kg/kgms. The effective diffusion coefficients of cubic samples are of the order of 10−10 and 10−9 m2∙s−1 grew with sample edge. As for the cylindrical samples, the effective diffusion coefficients were of the order of 10−9 m2∙s−1 and there was no linear correlation between cylinder height and their effective diffusion coefficient. As for the examination of the initial water content on the effective diffusion coefficient, it turned out that the initial water content had no influence on the effective diffusion coefficient of the sweet potato samples.

Study on Multi-Scale Blending Initial Condition Perturbations for a Regional Ensemble Prediction System

An initial conditions （ICs） perturbation method was developed with the aim to improve an operational regional ensemble prediction system （REPS）. Three issues were identified and investigated： （1） the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; （2） the scale characteristic of the IC perturbations of the REPS; and （3） whether the REPS＇s skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system （GEPS） were analyzed. A ＂multi-scale blending＂ （MSB） IC perturbation scheme was developed, and the main findings can be summarized as follows： The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification.

A fast and accurate initial alignment method for strapdown inertial navigation system on stationary base

In this work,a fast and accurate stationary alignment method for strapdown inertial navigation system （SINS） is proposed. It has been demonstrated that the stationary alignment of SINS can be improved by employing the multiposition technique,but the alignment time of the azimuth error is relatively longer. Over here, the two-position alignment principle is presented. On the basis of this SINS error model, a fast estimation algorithm of the azimuth error for the initial alignment of SINS on stationary base is derived fully from the horizontal velocity outputs and the output rates, and the novel azimuth error estimation algorithm is used for the two-position alignment. Consequently, the speed and accuracy of the SINS＇ s initial alignment is enhanced greatly. The computer simulation results illustrate the efficiency of this alignment method.

Sensitivity of intrinsic mode functions of Lorenz system to initial values based on EMD method

Extreme sensitivity to initial values is an intrinsic character of chaotic systems. The evolution of a chaotic system has a spatiotemporal structure containing quasi-periodic changes of different spatiotemporal scales. This paper uses an empirical mode decomposition （EMD） method to decompose and compare the evolution of the time-dependent evolutions of the x-component of the Lorenz system. The results indicate that the sensitivity of intrinsic mode function （IMF） component is dependent on initial values, which provides some scientific evidence for the possibility of long-range climatic prediction.

Iterative Learning Control for a Class of Linear Continuous-time Switched Systems with Fixed Initial Shifts

This paper deals with the problem of iterative learning control for a class of linear continuous-time switched systems in the presence of a fixed initial shift. Here, the considered switched systems are operated during a finite time interval repetitively. According to the characteristics of the systems, a PD-type learning scheme is proposed for such switched systems with arbitrary switching rules, and the corresponding output limiting trajectories under the action of the PD-type learning scheme are given. Based on the contraction mapping method, it is shown that this scheme can guarantee the outputs of the systems converge uniformly to the output limiting trajectories of the systems over the whole time interval. Furthermore, the initial rectifying strategies are applied to the systems for eliminating the effect of the fixed initial shift. When the learning scheme is applied to the systems, the outputs of the systems can converge to the desired reference trajectories over a pre-specified interval. Finally, simulation examples illustrate the effectiveness of the proposed method.

EXISTENCE AND NONEXISTENCE FOR THE INITIAL BOUNDARY VALUE PROBLEM OF ONE CLASS OF SYSTEM OF MULTIDIMENSIONAL NONLINEAR SCHRDINGER EQUATIONS WITH OPERATOR AND THEIR SOLITON SOLUTIONS

The nonlinear interactions between the monochromatic wave have been considered by K. Matsunchi, who also proposed one class of the nonlinear Schrdinger equation system with wave operator. We also obtain the same type of equations, which are satisfied by transverse velocity of higher frequency electron, as we study soliton in plasma physics. In this paper, under some condition we study the existence and nonexistence for this equations in the cases possessing different signs in nonlinear term.

Effects of the Dicranopteris linearis root system and initial moisture content on the soil disintegration characteristics of gully erosion

Benggang erosion is caused by a special type of gully erosion in southern China that seriously endangers the local ecology and environment.In this study,typical Benggang collapsing-wall soils were used as the study area to investigate the effects of different initial moisture contents and dicranopteris linearis root weight densities,as well as their interactions on disintegration in orthogonal test method.The results showed that the rate of soil disintegration decreased as a linear function of the initial moisture content.The soil disintegration rate tended to rise and then fall as the root weight density increased,reflecting an optimum root weight density of 0.75-1.00 g/100 cm3.The incorporation of dicranopteris linearis roots was most effective for soil consolidation in the shallow layers of soil.In addition,the disintegration rate of the collapsing-wall soils increases as the soil layer deepened.The dicranopteris linearis root system and initial moisture content had an interactive effect that was more pronounced in deeper soils.However,the combined effect of these processes was always dominated by the initial moisture content.Moderate initial soil moisture content(0.20-0.24 g/g)and the addition of a high root density in dicranopteris linearis(0.75-1.00 g/100 cm3)were the optimal combinations that reduced the disintegration rate.In conclusion,maintaining a suitable natural moisture content in collapsing-wall soils and taking measures that use plants to consolidate soil can effectively prevent and control the occurrence of Benggang erosion.The results of this study provided further insight into the factors that influence soil disintegration and offered a scientific basis for soil erosion management in the southern China.

Application of a Typhoon Initialization Scheme Based on the Incremental Analysis Updates Technique in a Rapid Update Cycle System

Initialization of tropical cyclones plays an important role in typhoon numerical prediction. This study applied a typhoon initialization scheme based on the incremental analysis updates (IAU) technique in a rapid refresh system to improve the prediction of Typhoon Lekima (2019). Two numerical sensitivity experiments with or without application of the IAU technique after performing vortex relocation and wind adjustment procedures were conducted for comparison with the control experiment, which did not involve a typhoon initialization scheme. Analysis of the initial fields indicated that the relocation procedure shifted the typhoon circulation to the observed typhoon region, and the wind speeds became closer to the observations following the wind adjustment procedure. Comparison of the results of the sensitivity and control experiments revealed that the vortex relocation and wind adjustment procedures could improve the prediction of typhoon track and intensity in the first 6-h period, and that these improvements were extended throughout the first 12-h period of the prediction by the IAU technique. The new typhoon initialization scheme also improved the simulated typhoon structure in terms of not only the wind speed and warm core prediction but also the organization of the eye of Typhoon Lekima. Diagnosis of the tendencies of variables showed that use of the IAU technique in a typhoon initialization scheme is efficacious in resolving the spurious high-frequency noise problem such that the model is able to reach equilibrium as soon as possible.