Hybrid response surface method for system reliability analysis of pilereinforced slopes

To consider the complex soil-structure interaction in a pile-slope system,it is necessary to analyze the performance of pile-slope systems based on a three-dimensional(3D)numerical model.Reliability analysis of a pile-slope system based on 3D numerical modeling is very challenging because it is computationally expensive and the performance function of the pile failure mode is only defined in the safe domain of soil stability.In this paper,an efficient hybrid response surface method is suggested to study the system reliability of pile-reinforced slopes,where the support vector machine and the Kriging model are used to approximate performance functions of soil failure and pile failure,respectively.The versatility of the suggested method is illustrated in detail with an example.For the example examined in this paper,it is found that the pile failure can significantly contribute to system failure,and the reinforcement ratio can effectively reduce the probability of pile failure.There exists a critical reinforcement ratio beyond which the system failure probability is not sensitive to the reinforcement ratio.The pile spacing affects both the probabilities of soil failure and pile failure of the pile-reinforced slope.There exists an optimal location and an optimal length for the stabilizing piles.

Development of multi-functional anchorage support dynamic-static coupling performance test system and its application

In underground engineering with complex conditions,the bolt(cable)anchorage support system is in an environment where static and dynamic stresses coexist,under the action of geological conditions such as high stresses and strong disturbances and construction conditions such as the application of high prestress.It is essential to study the support components performance under dynamic-static coupling conditions.Based on this,a multi-functional anchorage support dynamic-static coupling performance test system(MAC system)is developed,which can achieve 7 types of testing functions,including single component performance,anchored net performance,anchored rock performance and so on.The bolt and cable mechanical tests are conducted by MAC system under different prestress levels.The results showed that compared to the non-prestress condition,the impact resistance performance of prestressed bolts(cables)is significantly reduced.In the prestress range of 50–160 k N,the maximum reduction rate of impact energy resisted by different types of bolts is 53.9%–61.5%compared to non-prestress condition.In the prestress range of 150–300 k N,the impact energy resisted by high-strength cable is reduced by76.8%–84.6%compared to non-prestress condition.The MAC system achieves dynamic-static coupling performance test,which provide an effective means for the design of anchorage support system.

Active Fault Tolerant Nonsingular Terminal Sliding Mode Control for Electromechanical System Based on Support Vector Machine

Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this paper.By borrowing the advantages of model-driven and data-driven methods,a fault tolerant nonsingular terminal sliding mode control method based on support vector machine(SVM)is proposed.A SVM is designed to estimate the fault by off-line learning from small sample data with solving convex quadratic programming method and is introduced into a high-gain observer,so as to improve the state estimation and fault detection accuracy when the fault occurs.The state estimation value of the observer is used for state reconfiguration.A novel nonsingular terminal sliding mode surface is designed,and Lyapunov theorem is used to derive a parameter adaptation law and a control law.It is guaranteed that the proposed controller can achieve asymptotical stability which is superior to many advanced fault-tolerant controllers.In addition,the parameter estimation also can help to diagnose the system faults because the faults can be reflected by the parameters variation.Extensive comparative simulation and experimental results illustrate the effectiveness and advancement of the proposed controller compared with several other main-stream controllers.

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

A Temporary Frequency Response Strategy Using a Voltage Source-Based PermanentMagnet Synchronous Generator and Energy Storage Systems

Energy storage systems(ESS)and permanent magnet synchronous generators(PMSG)are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives.The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted.To improve the inertia response and frequency control capability,we propose a short-term frequency support strategy for the ESS and PMSG.To this end,the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion.The effectiveness of the proposed control strategy was verified using PSCAD/EMTDC.The simulations revealed that the proposed strategy could improve the maximum rate of change of the frequency nadir and maximum frequency excursion.Therefore,it provides a promising solution of ancillary services for frequency regulation of PMSG and ESS.

Improvement of the nutritional support management system for patients in intensive care units

BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.

Evaluation of G3BP1 in the prognosis of acute and acute-on-chronic liver failure after the treatment of artificial liver support system

BACKGROUND The increased expression of G3BP1 was positively correlated with the prognosis of liver failure.AIM To investigate the effect of G3BP1 on the prognosis of acute liver failure(ALF)and acute-on-chronic liver failure(ACLF)after the treatment of artificial liver support system(ALSS).METHODS A total of 244 patients with ALF and ACLF were enrolled in this study.The levels of G3BP1 on admission and at discharge were detected.The validation set of 514 patients was collected to verify the predicted effect of G3BP1 and the viability of prognosis.RESULTS This study was shown that lactate dehydrogenase(LDH),alpha-fetoprotein(AFP)and prothrombin time were closely related to the prognosis of patients.After the ALSS treatment,the patient’amount of decreased G3BP1 index in difference of G3BP1 between the value of discharge and admission(difG3BP1)<0 group had a nearly 10-fold increased risk of progression compared with the amount of increased G3BP1 index.The subgroup analysis showed that the difG3BP1<0 group had a higher risk of progression,regardless of model for end-stage liver disease high-risk or low-risk group.At the same time,compared with the inflam matory marks[tumor necrosis factor-α,interleukin(IL)-1βand IL-18],G3BP1 had higher discrimination and was more stable in the model analysis and validation set.When combined with AFP and LDH,concordance index was respectively 0.84 and 0.8 in training and validation cohorts.CONCLUSION This study indicated that G3BP1 could predict the prognosis of ALF or ACLF patients treated with ALSS.The combination of G3BP1,AFP and LDH could accurately evaluate the disease condition and predict the clinical endpoint of patients.

High standards facilitate energy transition and high-quality development of new power system

Guided by SAMR, China's standardization has achieved remarkable results. The State Grid Corporation of China steadily operates the power grid with the highest voltage level, the strongest energy resource allocation capacity, and the largest scale of new energy grid connection. The State Grid thoroughly implements the National Standardization Development Outline, and strengthens the top-level design to build a new pattern of the coordinated development of domestic and international standardization work, which demonstrates the role of standards in supporting the high-quality development of power grid.

Machine learning algorithm partially reconfigured on FPGA for an image edge detection system

Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.

Supportive care in transplantation: A patient-centered care model to better support kidney transplant candidates and recipients

Kidney transplantation(KT),although the best treatment option for eligible patients,entails maintaining and adhering to a life-long treatment regimen of medications,lifestyle changes,self-care,and appointments.Many patients experience uncertain outcome trajectories increasing their vulnerability and symptom burden and generating complex care needs.Even when transplants are successful,for some patients the adjustment to life post-transplant can be challenging and psychological difficulties,economic challenges and social isola-tion have been reported.About 50%of patients lose their transplant within 10 years and must return to dialysis or pursue another transplant or conservative care.This paper documents the complicated journey patients undertake before and after KT and outlines some initiatives aimed at improving patient-centered care in transplantation.A more cohesive approach to care that borrows its philosophical approach from the established field of supportive oncology may improve patient experiences and outcomes.We propose the"supportive care in transplantation"care model to operationalize a patient-centered approach in transplantation.This model can build on other ongoing initiatives of other scholars and researchers and can help advance patient-centered care through the entire care continuum of kidney transplant recipients and candidates.Multi-dimensionality,multi-disciplinarity and evidence-based approaches are proposed as other key tenets of this care model.We conclude by proposing the potential advantages of this approach to patients and healthcare systems.Core Tip:Kidney transplant recipients and candidates face several uncertainties in their care journey and have several expressed unmet healthcare needs.We recommend a structured and comprehensive approach to transplant care across the entire continuum of a transplant patient’s journey similar to what has been developed in the field of oncology.The supportive care in transplantation model can operationalize patient-centered care and build on the efforts of other researchers in the field.We postulate that such a model would significantly improve care delivery and patients’experiences and outcomes and potentially decrease healthcare utilization and cost.INTRODUCTION Patients with kidney failure benefit from(KT)[1,2],and experience improved survival rates when compared with dialysis[3-6].KT studies,using validated instruments,have also consistently demonstrated that kidney transplant recipients(KTRs)experience better health-related quality of life and several improvements in other disease-specific domains when compared with dialysis[7].In countries where dialysis is out of reach for many,the diagnosis of kidney failure would be futile without KT[8].Thus,increasing KT has been a priority for the nephrology and transplant communities.This priority has been reflected in recent global trends:Of the 79 countries where data were available,the International Society of Nephrology’s Global Kidney Atlas reported that the prevalence of KTRs in 2023 was 279 per million population which represented an increase of 9.4%from the data published four years prior[8].Despite this growth,KT can be a challenging journey for many patients and it is sometimes regarded as a‘cure’,which does not conform with the reality that many patients experience[9-13].KTRs must maintain a life-long treatment regimen of medications,lifestyle changes,self-care and medical appointments[14-17].As poignantly stated by a young female transplant recipient,“I thought everything would change once I got my kidney.I thought I would be healthy again”but after experiencing multiple side effects of immunosuppressive medications and graft loss,she stated,“I am just a different kind of patient now”[18].Indeed,a significant proportion of patients experience graft failure and return to dialysis;it is estimated that over 50%return to dialysis within 10 years of KT[19-23].Patients are often not prepared for this outcome and report several psychosocial and physical ramifications of graft failure[24,25].Overall,high symptom burden,adverse effects of immunosuppressants,risk of graft rejection or failure and mortality,contribute to complex needs,vulnerability and uncertainties for patients,increasing their care needs and treatment burden[26-30].In this paper,we highlight the complex journey that KTRs and candidates undertake that can generate varied outcome trajectories and complex healthcare needs.We highlight the need for a comprehensive patient-centered approach to care and conclude with a proposal for a“supportive care in transplantation”care model.

The Support Systems and Coping Strategies of Infertile Women Attending the Out-Patient Consultation Unit of CHRACERH Yaoundé, Cameroon: A Cross-Sectional Study

Background: Infertility is a complex disorder with significant psycho-social and economic consequences. It globally affects 10% - 15% of couples. In Cameroon, little is known about what women do to overcome the psychosocial aspects of the disease. Objectives: This study aimed to identify the support systems and coping strategies of infertile women attending the outpatient consultation unit of the Gynaecological Endoscopic Surgery and Reproductive Teaching Hospital (CHRACERH), Yaoundé, Cameroon. Methods: A hospital-based cross-sectional study was conducted from the 14th of March to the 6th of April 2023 at CHRACERH Yaoundé. A total of 190 participants were recruited using a convenience sampling method. Data regarding socio-demographic characteristics, support systems and coping strategies were collected using a pretested questionnaire. Descriptive and analytic statistics were conducted using SPSS version 25. Results: The mean age of participants was 39.52 ± 7.64 years. The majority 78.9% of participants were workers (public, private sector, or traders) and were Christians 95.8%. The most common source of psychological support was from family 76.8 and husbands 72.63%. Most of the participants 89.5% resorted to prayer and getting busy 48.4% as a coping strategy. There was no statistically significant relationship between coping strategies and psychological disorders p > 0.05. Conclusion: The main support system of participants was family, husband, and friends. Prayer, getting busy and adoption were the most common coping strategies. There is a need for the Ministry of Public Health and other stakeholders to put in place other support systems and coping strategies (FELICIA) used elsewhere and provide adequate health education and infection control to prevent infertility in Cameroon.

Nutritional Support under the Neuman Systems Model for Stroke Patients

Objective: To explore nutritional support under the Neuman systems model in treating dysphagia in stroke patients. Methods: In this retrospective study, we enrolled 97 patients with dysphagia after stroke admitted to our hospital, and randomly divided them into the Neuman group (n = 51) given nursing intervention based on Neuman systems model and a control group (n = 46) given routine nursing intervention. Both groups received nutritional support for 3 months. Nutritional indexes (serum total protein, plasma albumin, serum albumin, hemoglobin and transferrin levels) and immune indexes (immunoglobulin (Ig) A, IgG, IgM and total lymphocyte count (TLC) in both groups were recorded and compared. Pulmonary function recovery, video fluoroscopic swallowing study score, water swallowing test score, complication rate, and health knowledge mastery level were also compared between the two groups. Results: After the intervention, the Neuman group showed less decrease in the nutritional and immune index scores (serum total protein, plasma albumin, hemoglobin, serum albumin;IgA, IgG, IgM, and TLC;all P Conclusion: For patients with stroke and dysphagia, comprehensive nursing intervention (e.g., nutritional support) under theNeuman systems model can promote the recovery of immune, swallowing, and pulmonary function, reduce complication incidence and facilitate comprehensive rehabilitation, ensuring adequate nutritional intake.

Nursing Care of 10 Patients with Vasovagal Reflex Caused by Artificial Liver Support System Treatment

This study outlines the essential nursing strategies employed in the care of 10 patients experiencing vascular vagal reflex, managed with artificial liver support systems. It highlights a holistic nursing approach tailored to the distinct clinical manifestations of these patients. Key interventions included early detection of psychological issues prior to initiating treatment, the implementation of comprehensive health education, meticulous monitoring of vital signs throughout the therapy, prompt emergency interventions when needed, adherence to prescribed medication protocols, and careful post-treatment observations including venous catheter management. Following rigorous treatment and dedicated nursing care, 7 patients demonstrated significant improvement and were subsequently discharged.

Supportive care needs of women with gynecologic cancer and factors affecting in Turkiye: a cross sectional study

Background:Identifying and managing patients'supportive care needs is an essential component of health care.The cancer patients'needs are multidimensional and it is important to identify these needs.This study was conducted to assess supportive care needs of women with gynecologic cancer and affecting factors.Methods:This cross-sectional study consisted of 98 women with gynecologic cancer.The data of the study was gathered using“Personal Information Form”and the“James Supportive Care Screening”.Results:The most frequently reported unmet needs of gynecologic cancer patients were emotional issues,including uncertainty(87.6%),fears(85.7%),feeling down(86.7%),worry(87.6%),loss of interest in usual activities(73.3%)and physical symptoms including fatigue/lack of energy(81.9%),weakness(81.9%),lack of appetite(76.2%).The most frequently reported social/practical problems was transportation problems(50%).The mean scores for JSCS was 29.72±15.57.There were a statistically significant difference was found only between family type,stage of the disease,and time of diagnosis,and the total mean scores of the JSCS(p<0.05).Conclusion:It has been determined that patients with gynecological cancer mostly experience emotional and physical problems.Health professionals working in the oncology unit should be aware of unmet needs.Certain programs and services to address the identified unmet needs should be provided.

Design and Implementation of the Employment Management Decision Support System based on Machine Learning

To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system collects and analyzes multidimensional data,uses machine learning algorithms for prediction and matching,provides personalized employment guidance for students,and provides decision support for universities and enterprises.The research results indicate that the system can effectively improve the efficiency and accuracy of employment guidance,promote school-enterprise cooperation,and achieve a win-win situation for all parties.

Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System

With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use.

A multi-purpose prototype test system for mechanical behavior of tunnel supporting structure: Development and application

A multi-purpose prototype test system is developed to study the mechanical behavior of tunnel sup-porting structure,including a modular counterforce device,a powerful loading equipment,an advanced intelligent management system and an efficient noncontact deformation measurement system.The functions of the prototype test system are adjustable size and shape of the modular counterforce structure,sufficient load reserve and accurate loading,multi-connection linkage intelligent management,and high-precision and continuously positioned noncontact deformation measurement.The modular counterforce structure is currently the largest in the world,with an outer diameter of 20.5 m,an inner diameter of 16.5 m and a height of 6 m.The case application proves that the prototype test system can reproduce the mechanical behavior of the tunnel lining during load-bearing,deformation and failure processes in detail.

Research on the Voltage Supporting Capability of Multi-VSC-HVDC Subsystems Operation Strategy to Receiving-end LCC-HVDC Network in Weak AC Grid

For the hybrid multi-infeed HVDC system in which the receiving-end grid is a strong AC grid including LCC-HVDC subsystems and multiple VSC-HVDC subsystems,it has higher voltage support capability.However,for weak AC grid,the voltage support capability of the multi-VSC-HVDC subsystems to the LCC-HVDC subsystem(voltage support capability-mVSCs-LCC)can resist the risk of commutation failure.Based on this consideration,this paper proposes an evaluation index called Dynamic Voltage Support Strength Factor(DVSF)for the hybrid multi-infeed system,and uses this index to qualitatively judge the voltage support capability-mVSCs-LCC in weak AC grid.In addition,the proposed evaluation index can also indirectly judge the ability of the LCC-HVDC subsystem to suppress commutation failure.Firstly,the mathematical model of the power flow of the LCC and VSC networks in the steady-state is analyzed,and the concept of DVSF applied to hybrid multi-infeed system is proposed.Furthermore,the DVSF index is also used to qualitatively judge the voltage support capability-mVSCs-LCC.Secondly,the influence of multiple VSC-HVDC subsystems with different operation strategies on the DVSF is analyzed with reference to the concept of DVSF.Finally,the indicators proposed in this paper are compared with other evaluation indicators through MATLAB simulation software to verify its effectiveness.More importantly,the effects of multi-VSC-HVDC subsystems using different coordinated control strategies on the voltage support capability of the receiving-end LCC-HVDC subsystem are also verified.

Support vector regression-based operational effectiveness evaluation approach to reconnaissance satellite system

As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and application.Aiming at the problem of nonlinear effectiveness evaluation under small sample conditions,we propose an evaluation method based on support vector regression(SVR)to effectively address the defects of traditional methods.Considering the performance of SVR is influenced by the penalty factor,kernel type,and other parameters deeply,the improved grey wolf optimizer(IGWO)is employed for parameter optimization.In the proposed IGWO algorithm,the opposition-based learning strategy is adopted to increase the probability of avoiding the local optima,the mutation operator is used to escape from premature convergence and differential convergence factors are applied to increase the rate of convergence.Numerical experiments of 14 test functions validate the applicability of IGWO algorithm dealing with global optimization.The index system and evaluation method are constructed based on the characteristics of RSS.To validate the proposed IGWO-SVR evaluation method,eight benchmark data sets and combat simulation are employed to estimate the evaluation accuracy,convergence performance and computational complexity.According to the experimental results,the proposed method outperforms several prediction based evaluation methods,verifies the superiority and effectiveness in RSS operational effectiveness evaluation.

Preparation and evaluation of controllable drug delivery system:A light responsive nanosphere based on β-cyclodextrin/mesoporous silica

A novel light responsive nanosphere was constructed,and it was used as a drug carrier to investigate the loading and release properties of the Quercetin(QU).In this paper,mesoporous silica nanoparticles(MSN)were used as a substrate,and 3-aminopropyl triethyoxysilane was used as a surface modification agent to introduce—NH_(2),and the azobenzene-4,4’-dicarboxylic acid(AZO)was used as light responsive agent to introduce the group of—N=N—,and thenβ-cyclodextrin(β-CD)was combined with AZO through host-guest interaction to construct light responsive nanoparticles(MSN@β-CD).The structure and properties of the carrier were analyzed by FTIR,BET,XPS,TGA,XRD,SEM and TEM.In vitro drug release studies showed the release rate of QU@MSN@β-CD(dark)was 12.19%within 72 h,but the release rate of QU@MSN@β-CD(light 10 min)was 26.09%,exhibiting a light-responsive property.The CCK8 tests demonstrated that MSN@β-CD could significantly decrease the toxicity of QU.Therefore,the controllable light-responsive drug delivery system has great application prospects.