Analysis of the Effect of Integrated Extended Care Model in Improving the Quality of Life of Elderly Patients with Type 2 Diabetes Mellitus

Objective: To analyze the impact of an integrated extended care model on improving the quality of life of elderly patients with Type 2 Diabetes Mellitus (T2DM). Methods: A total of 176 patients admitted to the hospital from March 2015 to February 2018 were selected and randomly assigned to an observation group and a control group, with 88 patients each. The control group implemented conventional nursing interventions, and the observation group carried out an integrated extended-care model. The level of glycemic control, quality of life, and daily medication adherence between both groups were compared. Results: The observation group showed significant improvement in the level of glycemic control, and their fasting blood glucose, 2-hour postprandial blood glucose, and glycated hemoglobin levels were significantly lower as compared with those in the study group (P < 0.05). The quality of life of the patients in the observation group was higher than that of the control group (P < 0.05). The observation group had a higher compliance score (95.48 ± 7.45) than the control group (81.31 ± 8.72) (t = 8.909, P < 0.05). Conclusion: The integrated extended care model allows patients to receive comprehensive and individualized nursing services after discharge, which improves the effect of drug therapy and the quality of life of patients.

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.

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.

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 E1-Nabulsi. First, the E1-Nabulsi dynamical model which is based on a fractional integral extended by periodic laws is introduced, and E1-Nabulsi-Hamilton＇s canoni- cal equations for non-conservative Hamilton system with holonomic or nonholonomic constraints are established. Second, the definitions and criteria of E1-Nabulsi-Noether symmetrical transformations and quasi-symmetrical transformations are presented in terms of the invariance of E1-Nabulsi-Hamilton action under the infinitesimal transformations of the group. Fi- nally, Noether＇s theorems for the non-conservative Hamilton system under the E1-Nabulsi dynamical system are established, which reveal the relationship between the Noether symmetry and the conserved quantity of the system.

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.

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. Key words statistical testing - evaluation for Web usability - extended Markov chain model (EMM) - Web log mining - reliability evaluation CLC number TP311. 5 Foundation item: Supported by the National Defence Research Project (No. 41315. 9. 2) and National Science and Technology Plan (2001BA102A04-02-03)Biography: MAO Cheng-ying (1978-), male, Ph.D. candidate, research direction: software testing. Research direction: advanced database system, software testing, component technology and data mining.

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.

The ‘Two oceans and one sea' extended range numerical prediction system with an ultra-high resolution atmosphere-ocean-land regional coupled model

The‘Two Oceans and One Sea’area(West Pacific,Indian Ocean,and South China Sea;15°S–60°N,39°–178°E)is a core strategic area for the‘21st Century Maritime Silk Road’project,as well as national defense.With the increasing demand for disaster prevention and mitigation,the importance of 10–30-day extended range prediction,between the conventional short-term(around seven days)and the climate scale(longer than one month),is apparent.However,marine extended range prediction is still a‘blank point’in China,making the early warning of marine disasters almost impossible.Here,the authors introduce a recently launched Chinese national project on a numerical forecasting system for extended range prediction in the‘Two Oceans and One Sea’area based on a regional ultra-high resolution multi-layer coupled model,including the scientific aims,technical scheme,innovation,and expected achievements.The completion of this prediction system is of considerable significance for the economic development and national security of China.

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.

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.

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.

Simulation on model predictive control for PMSM drive system based on double extended state observer

A novel double extended state observer(DESO)based on model predictive torque control(MPTC)strategy is developed for three-phase permanent magnet synchronous motor(PMSM)drive system without current sensor.In general,to achieve high-precision control,two-phase current sensors are necessary for successful implementation of MPTC.For this purpose,two ESOs are used to estimate q-axis current and stator resistance respectively,and then based on this,d-axis current is estimated.Moreover,to reduce torque and flux ripple and to improve the performance of the torque and speed,MPTC strategy is designed.The simulation results validate the feasibility and effectiveness of the proposed scheme.

Extended activated sludge model no. 1 (ASM1) for simulating biodegradation process using bacterial technology

Phosphorus is one of the most important nutrients required to support various kinds of biodegradation processes. As this particular nutrient is not included in the activated sludge model no. 1 （ASM1）, this study extended this model in order to determine the fate of phosphorus during the biodegradation processes. When some of the kinetics parameters are modified using observed data from the restoration project of the Xuxi River in Wuxi City, China, from August 25 to 31 in 2009, the extended model shows excellent results. In order to obtain optimum values of coefficients of nitrogen and phosphorus, the mass fraction method was used to ensure that the final results were reasonable and practically relevant. The temporal distribution of the data calculated with the extended ASM1 approximates that of the observed data.

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.

Regression Modeling of Individual-Patient Correlated Discrete Outcomes with Applications to Cancer Pain Ratings

Purpose: To formulate and demonstrate methods for regression modeling of probabilities and dispersions for individual-patient longitudinal outcomes taking on discrete numeric values. Methods: Three alternatives for modeling of outcome probabilities are considered. Multinomial probabilities are based on different intercepts and slopes for probabilities of different outcome values. Ordinal probabilities are based on different intercepts and the same slope for probabilities of different outcome values. Censored Poisson probabilities are based on the same intercept and slope for probabilities of different outcome values. Parameters are estimated with extended linear mixed modeling maximizing a likelihood-like function based on the multivariate normal density that accounts for within-patient correlation. Formulas are provided for gradient vectors and Hessian matrices for estimating model parameters. The likelihood-like function is also used to compute cross-validation scores for alternative models and to control an adaptive modeling process for identifying possibly nonlinear functional relationships in predictors for probabilities and dispersions. Example analyses are provided of daily pain ratings for a cancer patient over a period of 97 days. Results: The censored Poisson approach is preferable for modeling these data, and presumably other data sets of this kind, because it generates a competitive model with fewer parameters in less time than the other two approaches. The generated probabilities for this model are distinctly nonlinear in time while the dispersions are distinctly nonconstant over time, demonstrating the need for adaptive modeling of such data. The analyses also address the dependence of these daily pain ratings on time and the daily numbers of pain flares. Probabilities and dispersions change differently over time for different numbers of pain flares. Conclusions: Adaptive modeling of daily pain ratings for individual cancer patients is an effective way to identify nonlinear relationships in time as well as in other predictors such as the number of pain flares.

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.

Experimental Research on the Erosion Pattern and Protection Using the Extended Modelling Method

In the paper the extended modelling method with serial sands is used in an experimental research on the erosion patterns at the discharge outlet of a beach Hua-Neng power plant. The theoretical basis for the extended modelling method with serial sands is systematically presented in the paper and the method has been successfully employed in the sediment experiment of coastal works. According to the Froude Law, the model is designed to be a normal one with movable bed, the geometric scale lambda(L) = lambda(H) = 15, and three scales of sediment grain size are chosen, i.e., lambda(d1) = 0.207; lambda(d2) = 0.393; and lambda(d3) = 0.656. The median particle diameter of sea beach prototype sand d(50p) = 0.059 mm and the dis-changed water flow of the power plant is 21.7 m(3) / s. Three types of natural sea sands have been chosen as the serial modelling sands to extend the simulation of the prototype, thus replacing the conventional test in which artificial lightweight sands are used. As a result, this method can not only reduce the cost significantly, but also it is an advanced technique easy to use. Upon a series of tests, satisfactory results have been obtained.

Extended intrinsic mean spin tensor for turbulence modelling in non-inertial frame of reference

We investigate the role of extended intrinsic mean spin tensor introduced in this work for turbulence modelling in a non-inertial frame of reference. It is described by the Euclidean group of transformations and, in particular, its significance and importance in the approach of the algebraic Reynolds stress modelling, such as in a nonlinear K-ε model. To this end and for illustration of the effect of extended intrinsic spin tensor on turbulence modelling, we examine several recently developed nonlinear K-ε models and compare their performance in predicting the homogeneous turbulent shear flow in a rotating frame of reference with LES data. Our results and analysis indicate that, only if the deficiencies of these models and the like be well understood and properly corrected, may in the near future, more sophisticated nonlinear K-ε models be developed to better predict complex turbulent flows in a non-inertial frame of reference.

Evaluation of flow regime of turbidity currents entering Dez Reservoir using extended shallow water model

In this study, the performance of the extended shallow water model （ESWM） in evaluation of the flow regime of turbidity currents entering the Dez Reservoir was investigated. The continuity equations for fluid and particles and the Navier-Stokes equations govern the entire flow of turbidity currents. The shallow water equations governing the flow of the depositing phase of turbidity currents are derived from these equations. A case study was conducted on the flow regime of turbidity currents entering the Dez Reservoir in Iran from January 2002 to July 2003. Facing a serious sedimentation problem, the dead storage of the Dez Reservoir will be full in the coming 10 years, and the inflowing water in the hydropower conduit system is now becoming turbid. Based on the values of the dimensionless friction number （ Nf ≤1 ） and dimensionless entrainment number （ NE≤ 1 ） of turbidity currents, and the coefficient of determination between the observed and predicted deposit depths （R2 = 0.86） for the flow regime of negligible friction and negligible entrainment （NFNE）, the flow regime of turbidity currents coming into the Dez Reservoir is considered to be NFNE. The results suggest that the ESWM is an appropriate approach for evaluation of the flow regime of turbidity currents in dam reservoirs where the characteristics of turbidity currents, such as the deposit depth, must be evaluated.