Carreau-Extended非牛顿流体圆管层流流动的摄动解

非牛顿流体在工业生产中应用广泛。文中基于同时包含屈服应力、时间常数和幂律指数的Carreau-Extended(简称Carreau-E)复杂流变方程及剪切应力与压降平衡关系,建立了圆管内充分发展的稳定Carreau-E流体层流管流的运动方程,并采用摄动方法推导出相应运动方程的一阶渐近解,获得了不同类型流体管流的速度分布以及压力梯度、流核宽度、屈服应力和时间常数对Carreau-E流体管流流场分布的影响规律,该研究对Carreau-E流体及其他复杂非牛顿流体管流特性研究具有参考价值。

The Extended Hybrid Carrier-Based Multiple Access Technology for High Mobility Scenarios

The hybrid carrier(HC)system rooted in the carrier fusion concept is gradually garnering attention.In this paper,we study the extended hybrid carrier(EHC)multiple access scheme to ensure reliable wireless communication.By employing the EHC modulation,a power layered multiplexing framework is realized,which exhibits enhanced interference suppression capability owing to the more uniform energy distribution design.The implementation method and advantage mechanism are explicated respectively for the uplink and downlink,and the performance analysis under varying channel conditions is provided.In addition,considering the connectivity demand,we explore the non-orthogonal multiple access(NOMA)method of the EHC system and develop the EHC sparse code multiple access scheme.The proposed scheme melds the energy spread superiority of EHC with the access capacity of NOMA,facilitating superior support for massive connectivity in high mobility environments.Simulation results have verified the feasibility and advantages of the proposed scheme.Compared with existing HC multiple access schemes,the proposed scheme exhibits robust bit error rate performance and can better guarantee multiple access performance in complex scenarios of nextgeneration communications.

Extended context-based semantic communication system for text transmission

Context information is significant for semantic extraction and recovery of messages in semantic communication.However,context information is not fully utilized in the existing semantic communication systems since re-lationships between sentences are often ignored.In this paper,we propose an Extended Context-based Semantic Communication(ECSC)system for text transmission,in which context information within and between sentences is explored for semantic representation and recovery.At the encoder,self-attention and segment-level relative attention are used to extract context information within and between sentences,respectively.In addition,a gate mechanism is adopted at the encoder to incorporate the context information from different ranges.At the decoder,Transformer-XL is introduced to obtain more semantic information from the historical communication processes for semantic recovery.Simulation results show the effectiveness of our proposed model in improving the semantic accuracy between transmitted and recovered messages under various channel conditions.

Multiple Matching Attenuation Based on Curvelet Domain Extended Filtering

The paper develops a multiple matching attenuation method based on extended filtering in the curvelet domain,which combines the traditional Wiener filtering method with the matching attenuation method in curvelet domain.Firstly,the method uses the predicted multiple data to generate the Hilbert transform records,time derivative records and time derivative records of Hilbert transform.Then,the above records are transformed into the curvelet domain and multiple matching attenuation based on least squares extended filtering is performed.Finally,the attenuation results are transformed back into the time-space domain.Tests on the model data and field data show that the method proposed in the paper effectively suppress the multiples while preserving the primaries well.Furthermore,it has higher accuracy in eliminating multiple reflections,which is more suitable for the multiple attenuation tasks in the areas with complex structures compared to the time-space domain extended filtering method and the conventional curvelet transform method.

Occurrence of K1 and K2 serotypes and genotypic characteristics of extended spectrumβ-lactamases-producing Klebsiella pneumoniae isolated from selected hospitals in Malaysia

Objective:To determine the distribution,phenotypic and genetic background of extended spectrumβ-lactamases(ESBL)-producing Klebsiella(K.)pneumoniae clinical isolates associated with K1 and K2 serotypes in two selected hospitals in Malaysia.Methods:A total of 192 K.pneumoniae isolates were collected and subjected to antibiotic susceptibility,hypermucoviscosity test and multiplex PCR to detect the presence of K1-and K2-serotype associated genes.Multilocus sequence typing(MLST)was performed on ESBL-producing K.pneumoniae isolates presented with K1 and K2 serotypes,followed by phylogenetic analysis.Results:A total of 87 out of 192(45.3%)of the K.pneumoniae isolates collected were ESBL producers.However,only 8.3%(16/192)and 10.9%(21/192)of the total isolates were detected to carry K1-and K2-serotype associated genes,respectively.Statistical analysis showed that K1 and K2 capsular serotypes were not significantly associated with ESBL phenotype(P=0.196).However,they were significantly associated with hypervirulent,as demonstrated by the positive string test(P<0.001).MLST analysis revealed that ST23 as the predominant sequence type(ST)in the K1 serotype,while the ST in the K2 serotype is more diverse.Conclusions:Although the occurrence of ESBL-producing isolates among the hypervirulent strains was low,their coexistence warrants the need for continuous surveillance.MLST showed that these isolates were genetically heterogeneous.

Analysis of Extended Fisher-Kolmogorov Equation in 2D Utilizing the Generalized Finite Difference Method with Supplementary Nodes

In this study,we propose an efficient numerical framework to attain the solution of the extended Fisher-Kolmogorov(EFK)problem.The temporal derivative in the EFK equation is approximated by utilizing the Crank-Nicolson scheme.Following temporal discretization,the generalized finite difference method(GFDM)with supplementary nodes is utilized to address the nonlinear boundary value problems at each time node.These supplementary nodes are distributed along the boundary to match the number of boundary nodes.By incorporating supplementary nodes,the resulting nonlinear algebraic equations can effectively satisfy the governing equation and boundary conditions of the EFK equation.To demonstrate the efficacy of our approach,we present three numerical examples showcasing its performance in solving this nonlinear problem.

Extended reading板块教学设计

根据《普通高中英语课程标准(2017年版2020修订)》(以下简称“新课标”),教师应引导学生广泛阅读,提升阅读能力,丰富语言、人文和科学知识,并拓展思维,增强审美、鉴赏和评价能力。广义的拓展阅读可在课堂内外开展;狭义的拓展阅读指基于单元主题,在课堂内进行的主题式拓展阅读,是对教材主阅读板块内容的延伸和内涵的拓展。[1]作为拓展阅读的素材,非故事类文本有助于学生拓宽知识面、增进对世界的认识。

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Performance of branched-chain extended surfactant mixed with zwitterionic or cationic surfactant

2-Hexyl-1-decanol was used as the main material to prepare a block-polyether sulfonate extended surfactant(IC_(16)P_(6)E_(6)S).The solubility and surface active properties of IC_(16)P_(6)E_(6)S were evaluated,and then the IC_(16)P_(6)E_(6)S was mixed with a cationic surfactant hexadecyl trimethyl ammonium bromide(CTAB)and a zwitterionic betaine surfactant(HAB),respectively.The effects of mixing ratios of IC_(16)P_(6)E_(6)S∶HAB and IC_(16)P_(6)E_(6)S∶CTAB on the hydrodynamic diameter and interfacial properties were discussed.The emulsification,adsorption and laboratory core displacement experiments of the binary system were tested.The results showed that the critical micelle concentration(cmc)of IC_(16)P_(6)E_(6)S in distilled water was 0.1 mmol/L and the surface tension at cmc(γcmc)was 28.53 mN/m.IC_(16)P_(6)E_(6)S showed strong synergistic effects with HAB and CTAB,and the mixed systems could effectively reduce the interfacial tension compared with single surfactants.The mixed systems with n(IC_(16)P_(6)E_(6)S)∶n(HAB)of 1∶1 and n(IC_(16)P_(6)E_(6)S)∶n(CTAB)of 1∶3 could maintain ultra-low interfacial tension(in the order of magnitude of 10^(-3)mN/m)in the salinity range of 1%-7%NaCl and low interfacial tension(in the order of magnitude of 10^(-2)mN/m)in the salinity range of 3%-7%NaCl,respectively.With the increase of salinity,the emulsion formed by the mixed surfactant system underwent the phase transition process from WinsorⅠto WinsorⅢand then to WinsorⅡ.The emulsion of mixed IC_(16)P_(6)E_(6)S/HAB system had more middle-phase emulsion volume than that of the mixed IC_(16)P_(6)E_(6)S/CTAB system,and the former emulsion system was more stable.The mixed IC_(16)P_(6)E_(6)S/HAB system also had good solubilization effect,and the amount of oil solubilization was up to 43 mL/g.Meanwhile,it had good adsorption resistance.Compared with water flooding,the depressurization rate could reach 25.00%and the recovery could be enhanced by 11.75%,indicating that the IC_(16)P_(6)E_(6)S/HAB system was more conducive to the depressurization and injection enhancement for low-permeability reservoirs.

Abundant invariant solutions of extended(3+1)-dimensional KP-Boussinesq equation

Lie group analysis method is applied to the extended(3+1)-dimensional Kadomtsev–Petviashvili–Boussinesq equation and the corresponding similarity reduction equations are obtained with various infinitesimal generators.By selecting suitable arbitrary functions in the similarity reduction solutions,we obtain abundant invariant solutions,including the trigonometric solution,the kink-lump interaction solution,the interaction solution between lump wave and triangular periodic wave,the two-kink solution,the lump solution,the interaction between a lump and two-kink and the periodic lump solution in different planes.These exact solutions are also given graphically to show the detailed structures of this high dimensional integrable system.

WSN Mobile Target Tracking Based on Improved Snake-Extended Kalman Filtering Algorithm

A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.

Dynamics of Nonlinear Waves in(2+1)-Dimensional Extended Boiti-Leon-Manna-Pempinelli Equation

Based on the Hirota bilinear method,this study derived N-soliton solutions,breather solutions,lump solutions and interaction solutions for the(2+1)-dimensional extended Boiti-Leon-Manna-Pempinelli equation.The dynamical characteristics of these solutions were displayed through graphical,particularly revealing fusion and ssion phenomena in the interaction of lump and the one-stripe soliton.

Extended finite element-based cohesive zone method for modeling simultaneous hydraulic fracture height growth in layered reservoirs

In this study,a fully coupled hydromechanical model within the extended finite element method(XFEM)-based cohesive zone method(CZM)is employed to investigate the simultaneous height growth behavior of multi-cluster hydraulic fractures in layered porous reservoirs with modulus contrast.The coupled hydromechanical model is first verified against an analytical solution and a laboratory experiment.Then,the fracture geometry(e.g.height,aperture,and area)and fluid pressure evolutions of multiple hydraulic fractures placed in a porous reservoir interbedded with alternating stiff and soft layers are investigated using the model.The stress and pore pressure distributions within the layered reservoir during fluid injection are also presented.The simulation results reveal that stress umbrellas are easily to form among multiple hydraulic fractures’tips when propagating in soft layers,which impedes the simultaneous height growth.It is also observed that the impediment effect of soft layer is much more significant in the fractures suppressed by the preferential growth of adjoining fractures.After that,the combined effect of in situ stress ratio and fracturing spacing on the multi-fracture height growth is presented,and the results elucidate the influence of in situ stress ratio on the height growth behavior depending on the fracture spacing.Finally,it is found that the inclusion of soft layers changes the aperture distribution of outmost and interior hydraulic fractures.The results obtained from this study may provide some insights on the understanding of hydraulic fracture height containment observed in filed.

Extended Deep Learning Algorithm for Improved Brain Tumor Diagnosis System

At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)algorithms.Although various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system symmetrically.Therefore,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative rates.In addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were shown.The results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten iterations.Whereas in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved parameters.Thus EDLA algorithm introduces novelty concerning its performance and particular activation function.This proposed method will be utilized effectively in brain tumor detection in a precise and accurate manner.This algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses aftermodification.If the quantity of dataset records is enormous,then themethod’s computation power has to be updated.

Design of Medical Rehabilitation Experience System Based on Extended Reality

This project integrates Extended Reality technology with medical rehabilitation,integrating cloud rendering.interactive experience systems,adaptation platforms,and digital scene resources.It is a innovative application research in the era of metaverset medical rehabilitation.The project uses the Maya engine for the creation of digital assets,with Unity as the main functional development platform and PICO4 as the core device,to achieve interactive and fun experience effects for various rehabilitation training devices.It solves the problems of patients being dull,low participation,lack of confidence in traditional rehabilitation training.as well as the inability of medical staff to monitor patient progress in real time and adjust rehabilitation plans better.

Analysis of the Nursing Effect of Hierarchical Extended Nursing Based on The Guidance of Orem’s Theory in Patients with PICC Catheterization

Objective:To analyze the nursing effect of hierarchical extended nursing based on the guidance of Orem’s theory in patients with peripherally inserted central(PICC)catheterization.Methods:Ninety-one patients with PICC catheterization admitted to the hospital from May 2021 to May 2023 were selected and divided into a control group and an observation group,with 45 and 46 cases,respectively.The control group received routine nursing care,while the observation group received routine nursing care combined with hierarchical extended nursing based on the guidance of Orem’s theory for 3 months.Relevant indicators between the two groups were compared.Results:The improvement degree of various indicators in the observation group after nursing was better than that of the control group(P<0.05).Conclusion:Graded extended nursing based on the guidance of Orem’s theory improved the knowledge,belief,behavior,and self-efficacy of patients with PICC catheterization,and relieved their anxiety,depression,and other negative emotions.The nursing effect was deemed to be significant.

Effectiveness of Extended Care in Preventing Falls in Disabled Elderly and Its Impact on Quality of Life

Objective:To analyze the value of extended care interventions for disabled elderly in preventing falls and optimizing quality of life.Methods:A sample of 60 cases of disabled elderly in a tertiary hospital from May 2022 to May 2023 was selected and grouped by the random number table method.The observation group received extended care,while the control group adopted routine care.The differences in complication rate,fall rate,36-Item Short Form Health Survey(SF-36)score,health knowledge awareness score,and nursing satisfaction were compared.Results:The complication rate and fall rate of the disabled elderly in the observation group were lower than those in the control group,P<0.05;the SF-36 score,health knowledge score,and nursing satisfaction of the observation group were higher than those of the control group,P<0.05.Conclusion:Extended care for the disabled elderly can reduce the risk of falls and complications related to disability,as well as optimize their cognition and improve their quality of life,which is efficient and feasible.

Enhancing economic sustainability in mature oil fields:Insights from the clustering approach to select candidate wells for extended shut-in

Fluctuations in oil prices adversely affect decision making situations in which performance forecasting must be combined with realistic price forecasts.In periods of significant price drops,companies may consider extended duration of well shut-ins(i.e.temporarily stopping oil production)for economic reasons.For example,prices during the early days of the Covid-19 pandemic forced operators to consider shutting in all or some of their active wells.In the case of partial shut-in,selection of candidate wells may evolve as a challenging decision problem considering the uncertainties involved.In this study,a mature oil field with a long(50+years)production history with 170+wells is considered.Reservoirs with similar conditions face many challenges related to economic sustainability such as frequent maintenance requirements and low production rates.We aimed to solve this decision-making problem through unsupervised machine learning.Average reservoir characteristics at well locations,well production performance statistics and well locations are used as potential features that could characterize similarities and differences among wells.While reservoir characteristics are measured at well locations for the purpose of describing the subsurface reservoir,well performance consists of volumetric rates and pressures,which are frequently measured during oil production.After a multivariate data analysis that explored correlations among parameters,clustering algorithms were used to identify groups of wells that are similar with respect to aforementioned features.Using the field’s reservoir simulation model,scenarios of shutting in different groups of wells were simulated.Forecasted reservoir performance for three years was used for economic evaluation that assumed an oil price drop to$30/bbl for 6,12 or 18 months.Results of economic analysis were analyzed to identify which group(s)of wells should have been shut-in by also considering the sensitivity to different price levels.It was observed that wells can be characterized in the 3-cluster case as low,medium and high performance wells.Analyzing the forecasting scenarios showed that shutting in all or high-and medium-performance wells altogether results in better economic outcomes.The results were most sensitive to the number of active wells and the oil price during the high-price period.This study demonstrated the effectiveness of unsupervised machine learning in well classification for operational decision making purposes.Operating companies may use this approach for improved decision making to select wells for extended shut-in during low oil-price periods.This approach would lead to cost savings especially in mature fields with low-profit margins.

Nucleon effective mass in symmetric nuclear matter from the extended Brueckner-Hartree-Fock approach

We have calculated the nucleon effective mass in symmetric nuclear matter within the framework of the Brueckner-Bethe-Goldstone （BBG） theory, which has been extended to include both the contributions from the ground-state correlation effect and the three-body force （TBF） rearrangement effect. The effective mass is predicted by including the ground-state correlation effect and the TBF rearrangement effect, and we discuss the momentum dependence and the density dependence of the effective mass. It is shown that the effect of ground state correlations plays an important role at low densities, while the TBF-induced rearrangement effect becomes predominant at high densities.