Impact of extended nursing model after multi-disciplinary treatment on young patient with post-stroke

BACKGROUND Stroke has become one of the most serious life-threatening diseases due to its high morbidity,disability,recurrence and mortality rates.AIM To explore the intervention effect of multi-disciplinary treatment(MDT)extended nursing model on negative emotions and quality of life of young patients with post-stroke.METHODS A total of 60 young stroke patients who were hospitalized in the neurology department of our hospital from January 2020 to December 2021 were selected and randomly divided into a control group and an experimental group,with 30 patients in each group.The control group used the conventional care model and the experimental group used the MDT extended nursing model.After the inhospital and 3-mo post-discharge interventions,the differences in negative emotions and quality of life scores between the two groups were evaluated and analyzed at the time of admission,at the time of discharge and after discharge,respectively.RESULTS There are no statistically significant differences in the negative emotions scores between the two groups at admission,while there are statistically significant differences in the negative emotions scores within each group at admission and discharge,at discharge and post-discharge,and at discharge and post-discharge.In addition,the negative emotions scores were all statistically significant at discharge and after discharge when compared between the two groups.There was no statistically significant difference in quality of life scores at the time of admission between the two groups,and the difference between quality of life scores at the time of admission and discharge,at the time of discharge and post-discharge,and at the time of admission and post-discharge for each group of patients was statistically significant.CONCLUSION The MDT extended nursing mode can improve the negative emotion of patients and improve their quality of life.Therefore,it can be applied in future clinical practice and is worthy of promotion.

Notes on Convergence and Modeling for the Extended Kalman Filter

The goal of this work is to provide an understanding of estimation technology for both linear and nonlinear dynamical systems.A critical analysis of both the Kalman filter(KF)and the extended Kalman filter(EKF)will be provided,along with examples to illustrate some important issues related to filtering convergence due to system modeling.A conceptual explanation of the topic with illustrative examples provided in the paper can help the readers capture the essential principles and avoid making mistakes while implementing the algorithms.Adding fictitious process noise to the system model assumed by the filter designers for convergence assurance is being investigated.A comparison of estimation accuracy with linear and nonlinear measurements is made.Parameter identification by the state estimation method through the augmentation of the state vector is also discussed.The intended readers of this article may include researchers,working engineers,or engineering students.This article can serve as a better understanding of the topic as well as a further connection to probability,stochastic process,and system theory.The lesson learned enables the readers to interpret the theory and algorithms appropriately and precisely implement the computer codes that nicely match the estimation algorithms related to the mathematical equations.This is especially helpful for those readers with less experience or background in optimal estimation theory,as it provides a solid foundation for further study on the theory and applications of the topic.

Entanglement and thermalization in the extended Bose–Hubbard model after a quantum quench: A correlation analysis

Exploring the role of entanglement in quantum nonequilibrium dynamics is important to understand the mechanism of thermalization in an isolated system. We study the relaxation dynamics in a one-dimensional extended Bose–Hubbard model after a global interaction quench by considering several observables: the local Boson numbers, the nonlocal entanglement entropy, and the momentum distribution functions. We calculate the thermalization fidelity for different quench parameters and different sizes of subsystems, and the results show that the degree of thermalization is affected by the distance from the integrable point and the size of the subsystem. We employ the Pearson coefficient as the measurement of the correlation between the entanglement entropy and thermalization fidelity, and a strong correlation is demonstrated for the quenched system.

Trend Autoregressive Model Exact Run Length Evaluation on a Two-Sided Extended EWMA Chart

The Extended Exponentially Weighted Moving Average(extended EWMA)control chart is one of the control charts and can be used to quickly detect a small shift.The performance of control charts can be evaluated with the average run length(ARL).Due to the deriving explicit formulas for the ARL on a two-sided extended EWMA control chart for trend autoregressive or trend AR(p)model has not been reported previously.The aim of this study is to derive the explicit formulas for the ARL on a two-sided extended EWMA con-trol chart for the trend AR(p)model as well as the trend AR(1)and trend AR(2)models with exponential white noise.The analytical solution accuracy was obtained with the extended EWMA control chart and was compared to the numer-ical integral equation(NIE)method.The results show that the ARL obtained by the explicit formula and the NIE method is hardly different,but the explicit for-mula can help decrease the computational(CPU)time.Furthermore,this is also expanded to comparative performance with the Exponentially Weighted Moving Average(EWMA)control chart.The performance of the extended EWMA control chart is better than the EWMA control chart for all situations,both the trend AR(1)and trend AR(2)models.Finally,the analytical solution of ARL is applied to real-world data in the healthfield,such as COVID-19 data in the United Kingdom and Sweden,to demonstrate the efficacy of the proposed method.

Backstepping Sliding Mode Control Based on Extended State Observer for Hydraulic Servo System

Hydraulic servo system plays an important role in industrial fields due to the advantages of high response,small size-to-power ratio and large driving force.However,inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking perfor-mance.To deal with these difficulties,this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interfer-ence ability.For this purpose,the nonlinear dynamic model is firstly established,where the nonlinear behaviors and modeling uncertainties are lumped as one term.Then,the extended state observer is introduced to estimate the lumped distur-bance.The system stability is proved by using the Lyapunov stability theorem.Finally,comparative simulation and experimental are conducted on a hydraulic servo system platform to verify the efficiency of the proposed control scheme.

Inverse Calculation of Wave-Absorbing Structure Dimensions Based on Extended ANFIS Model

A new wave energy dissipation structure is proposed, aiming to optimize the dimensions of the structure and make the reflection of the structure maintain a low level within the scope of the known frequency band. An optimal extended ANFIS model combined with the wave reflection coefficient analysis for the estimation of the structure dimensions is established. In the premise of lower wave reflection coefficient, the specific sizes of the structure are obtained inversely, and the contribution of each related parameter on the structural reflection performance is analyzed. The main influencing factors are determined. It is found that the optimal dimensions of the proposed structure exist, which make the wave absorbing performance of the structure reach a perfect status under a wide wave frequency band.

Extended Generalized Riccati Equation Mapping for Thermal Traveling-Wave Distribution in Biological Tissues through a Bio-Heat Transfer Model with Linear/Quadratic Temperature-Dependent Blood Perfusion

Analytical thermal traveling-wave distribution in biological tissues through a bio-heat transfer (BHT) model with linear/quadratic temperature-dependent blood perfusion is discussed in this paper. Using the extended generalized Riccati equation mapping method, we find analytical traveling wave solutions of the considered BHT equation. All the travelling wave solutions obtained have been used to explicitly investigate the effect of linear and quadratic coefficients of temperature dependence on temperature distribution in tissues. We found that the parameter of the nonlinear superposition formula for Riccati can be used to control the temperature of living tissues. Our results prove that the extended generalized Riccati equation mapping method is a powerful tool for investigating thermal traveling-wave distribution in biological tissues.

Analysis of SDEs Applied to SEIR Epidemic Models by Extended Kalman Filter Method

A disease transmission model of SEIR type is discussed in a stochastic point of view. We start by formulating the SEIR epidemic model in form of a system of nonlinear differential equations and then change it to a system of nonlinear stochastic differential equations (SDEs). The numerical simulation of the resulting SDEs is done by Euler-Maruyama scheme and the parameters are estimated by adaptive Markov chain Monte Carlo and extended Kalman filter methods. The stochastic results are discussed and it is observed that with the SDE type of modeling, the parameters are also identifiable.

Hierarchical Modeling by Recursive Unsupervised Spectral Clustering and Network Extended Importance Measures to Analyze the Reliability Characteristics of Complex Network Systems

The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.

An Extended Enterprise Modeling Approach to Enterprise-based Integration

The paradigm of extended enterprise is the core competency focused. An extended enterprise expands its scope from bounding a single enterprise to including additional processes performed by other enterprises. The integration of processes is enterprise based. This paper proposes a recursive enterprises interconnected chain model for the extended enterprise, and presents an enterprise-based integration framework for the extended enterprise. The case study is based on a motorcycle group corporation.

eXtended Pom-Pom黏弹性流体的改进光滑粒子动力学模拟

黏弹性流体广泛存在于自然界和工业生产中,对其复杂流变特性的研究具有重要的学术价值和应用意义.本文提出一种改进的光滑粒子动力学方法,对基于eXtended Pom-Pom模型的黏弹性流动进行了数值模拟.为了提高计算精度,采用一种不含核导数计算的核梯度修正离散格式.为了防止粒子穿透固壁,提出一种增强型的边界处理技术.为了消除张力不稳定性,将人工应力耦合到动量守恒方程中.运用改进光滑粒子动力学方法数值模拟了基于eXtended Pom-Pom模型的黏弹性Poiseuille流和黏弹性液滴撞击固壁问题,通过与解析解或有限差分方法解的比较以及对数值收敛性的评价,验证了改进光滑粒子动力学方法的有效性和优势,并在此基础上,深入分析了Reyonlds数、Weissenberg数、溶剂黏度比、各向异性参数、松弛时间比和分子链臂数等流变参数对流动过程的影响.

Noether's theorem for non-conservative Hamilton system based on El-Nabulsi dynamical model extended by periodic laws

This paper focuses on the Noether symmetries and the conserved quantities for both holonomic and nonholonomic systems based on a new non-conservative dynamical model introduced by El-Nabulsi. First, the El-Nabulsi dynamical model which is based on a fractional integral extended by periodic laws is introduced, and El-Nabulsi–Hamilton's canonical equations for non-conservative Hamilton system with holonomic or nonholonomic constraints are established. Second,the definitions and criteria of El-Nabulsi–Noether symmetrical transformations and quasi-symmetrical transformations are presented in terms of the invariance of El-Nabulsi–Hamilton action under the infinitesimal transformations of the group. Finally, Noether's theorems for the non-conservative Hamilton system under the El-Nabulsi dynamical system are established,which reveal the relationship between the Noether symmetry and the conserved quantity of the system.

SHARP H?LDER CONTINUITY OF THE INTEGRATED DENSITY OF STATES FOR EXTENDED HARPER’S MODEL WITH A LIOUVILLE FREQUENCY

In this article, the non-self dual extended Harper's model with a Liouville frequency is considered. It is shown that the corresponding integrated density of states is 1/2-Holder continuous. As an application, the homogeneity of the spectrum is proven.

An Examination of Extended a-Rescaling Model

The extended x-rescaling model can explain the quark's nuclear effect very well. Weather it can also explain the gluon's nuclear effect should be investigated further. Associated J/ψ and γ production with large PT is a very clean channel to probe the gluon distribution in proton or nucleus. In this paper, using the extended x-rescaling model, the PT distribution of the nuclear effect factors of p + Fe → J/Ψ + γ+ X process is calculated and discussed. Comparing our theoretical results with the future experimental data, the extended x-rescaling model can be examined.

Adaptive Random Effects/Coefficients Modeling

Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.

Ionospheric time delay corrections based on the extended single layer model over low latitude region

Ionospheric delay error is considered to be one of the most prominent factors impacting the Global Navigation Satellite Systems(GNSS) positioning and navigation accuracies. Due to dispersive nature and anisotropic of the ionosphere above certain regions, the positioning accuracy is seriously affected when using a precision-limited model. In this paper, an attempt has been taken to estimate ionosphere-delays based on Planar Fit(PF) and Spherical Harmonic Function(SHF) models by applying the commonly used single layer Model(SLM) and an extended single layer model(ESLM) which has been explored sparsely over the region. The results show that ESLM of PF and SHF techniques performed better in estimating ionospheric delay compared to the existing SLM model. Although the performance of the ESLM approach is almost comparable to the SLM results during the quiet ionospheric conditions, the ESLM-PF and ESLMSHF models led to respective improvements of 4.66% and 7.14% over the classically used SLM model under the disturbed ionospheric conditions. In view of the uneven variability of equatorial/low latitude ionosphere above the Indian subcontinental region, the suitability of ESLM-PF and ESLM-SHF models has been emphasized and suggested for assessing its completeness and reliableness across other parts of the globe. The output of this work may be useful for high precession GNSS positioning through mitigating the ionospheric delays under quiet as well as varied ionospheric conditions across the low/equatorial latitude regions.

Reliability Modelling and Analysis of Satellite Propulsion System Based on Reliability Block Diagram and Extended Object-Oriented Petri Net

Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.

An extended improved global structure model for influential node identification in complex networks

Accurate identification of influential nodes facilitates the control of rumor propagation and interrupts the spread of computer viruses.Many classical approaches have been proposed by researchers regarding different aspects.To explore the impact of location information in depth,this paper proposes an improved global structure model to characterize the influence of nodes.The method considers both the node’s self-information and the role of the location information of neighboring nodes.First,degree centrality of each node is calculated,and then degree value of each node is used to represent self-influence,and degree values of the neighbor layer nodes are divided by the power of the path length,which is path attenuation used to represent global influence.Finally,an extended improved global structure model that considers the nearest neighbor information after combining self-influence and global influence is proposed to identify influential nodes.In this paper,the propagation process of a real network is obtained by simulation with the SIR model,and the effectiveness of the proposed method is verified from two aspects of discrimination and accuracy.The experimental results show that the proposed method is more accurate in identifying influential nodes than other comparative methods with multiple networks.

Testing and Evaluation for Web Usability Based on Extended Markov Chain Model

As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can be utilized in the latter stages, which is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (EMM) is to present the error type vector which is treated as a part of page node. This paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented.

Metadata Extended Model Based On Geological Domain Ontology

The current metadata modeling techniques can not meet the needs of knowledge conception expression, knowledge organization, and metadata semantic consistency in geological domain. This paper introduces ontology and integrates this theory to geological domain metadata modeling. It adopts the first order logic equivalent algorithm and defines the metadata extended model as a quaternion group which is consists of geological term set, geological term definition set, attribute definition set and instance set. It also provides the formal description of each set. Finally the five steps for building geological domain metadata extended model are given. The result presents that this model not only provides the content standards for geological domain knowledge representation and knowledge organization, but also provides the basis for geological domain multi-source data and historical data integration and application in semantic consistency.