Evaluation of the Impact of Refined Quality Control Management Model on the Qualified Rate of Disinfection and Sterilization of Surgical Instruments in the Sterilization Supply Center

Objective:To evaluate the application value of a refined quality control management model for a sterilization supply center.Methods:A retrospective analysis was conducted on the work situation of the sterilization supply center from January 2021 to January 2023.The work situation before January 31,2022,was classified as the control group;a routine quality control management model was implemented,and the work situation after January 31,2022,was classified as the observation group.The quality of medical device management and department satisfaction between the two groups were compared.Results:The timely recovery and supply rate,classification and cleaning pass rate,disinfection pass rate,packaging pass rate,sterilization pass rate,and department satisfaction score in the observation group were all higher than those of the control group(P<0.05).Conclusion:Implementing a refined quality control management model in the sterilization supply center can improve the quality management level of medical devices and department satisfaction and is worthy of promotion.

Spatio-temporal evolution analysis of landscape pattern and habitat quality in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 based on InVEST model

Habitat quality is an important indicator for evaluating the quality of ecosystem.The Qinghai Province section of the Yellow River Basin plays an important role in the ecological protection of the upper reaches of the Yellow River Basin.To comprehensively analysis the alterations of habitat quality in the Qinghai Province section of the Yellow River Basin,this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to calculate the habitat quality index and analyze the spatio-temporal variation characteristics of habitat quality in the study area from 2000 to 2022,and calculated seven landscape pattern indices(number of patches,patch density,largest patch index(LPI),landscape shape index(LSI),contagion index(CONTAG),Shannon diversity index,and Shannon evenness index)to research the variation of landscape pattern in the study area.The results showed that the number of patches,patch density,LPI,LSI,Shannon diversity index,and Shannon evenness index increased from 2000 to 2022,while the CONTAG decreased,indicating that the landscape pattern in the Qinghai Province section of the Yellow River Basin changed in the direction of distribution fragmentation,shape complexity,and heterogeneity.The average value of the habitat quality index in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 was 0.90.Based on the value of habitat quality index,we divided the level of habitat quality into five categories:lower(0.00-0.20),low(0.20-0.40),moderate(0.40-0.60),high(0.60-0.80),and higher(0.80-1.00).Most areas were at the higher habitat quality level.The lower habitat quality patches were mainly distributed in Longyang Gorge and Yellow River-Huangshui River Valley.From 2000 to 2022,the habitat quality in most areas was stable;the increase areas were mainly distributed in Guinan County,while the decrease areas were mainly distributed in Xining City,Maqen County,Xinghai County,Qumarleb County,and Darlag County.To show the extent of habitat quality variation,we calculated Sen index.The results showed that the higher habitat quality area had a decrease trending,while other categories had an increasing tendency,and the decreasing was faster than increasing.The research results provide scientific guidance for promoting ecological protection and high-quality development in the Qinghai Province section of the Yellow River Basin.

Effect analysis of applying high-quality service model to surgical nursing

BACKGROUND Surgical care of the hand plays a crucial role in the medical field,as problems with the hand can profoundly affect a patient's quality of life and function.In order to meet the needs of patients,improve patient satisfaction and improve treatment outcomes,high-quality service models have been introduced in the field of nursing.AIM To explore the effect analysis of applying high-quality service model to surgical nursing.METHODS We conducted a retrospective study of patients who underwent hand surgery at our hospital between 2019 and 2022,using a quality service model that included improved patient education,pain management,care team collaboration,and effective communication.Another group of patients received traditional care as a control group.We compared postoperative recovery,satisfaction,complication rate,and length of hospital stay between the two groups.Inferential statistics were used to compare the difference between the two groups by independent sample t test,Chi-square test and other methods to evaluate the effect of intervention measures.RESULTS Postoperative recovery time decreased from 17.8±2.3 d to 14.5±2.1 d,pain score decreased from 4.7±1.9 to 3.2±1.4,and hand function score increased from 78.4±7.1 to 88.5±6.2.In terms of patient satisfaction,the quality service model group scored 87.3±5.6 points,which was significantly higher than that of the traditional care group(74.6±6.3 points).At the same time,patients'understanding of medical information also improved from 6.9±1.4 to 8.6±1.2.In terms of postoperative complications,the application of the quality service model reduced the incidence of postoperative complications from 26%to 10%,the incidence of infection from 12%to 5%,and the incidence of bleeding from 10%to 3%.The reduction in these data indicates that the quality service model plays a positive role in reducing the risk of complications.In addition,the average hospital stay of patients in the quality service model group was shortened from 6.8±1.5 d to 5.2±1.3 d,and the hospitalization cost was also reduced from 2800±600 yuan to 2500±500 yuan.CONCLUSION Applying a quality service model to hand surgery care can significantly improve patient clinical outcomes,including faster recovery,less pain,greater satisfaction,and reduced complication rates.

An Approach to Detect Structural Development Defects in Object-Oriented Programs

Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.

Research on the Construction and Application of Service Quality Evaluation Models for Scenic Spots:Taking Chongqing Ciqikou as an Example

In the current environment of increasingly fierce competition in the tourism industry,service quality has become crucial for enhancing the competitiveness of scenic spots.This paper uses the SERVQUAL model to design a service quality evaluation questionnaire that captures the gap between tourists’expectations and perceptions,using the Ciqikou Scenic Spot as a case study.Data collected from field surveys are used to comprehensively and meticulously evaluate the service quality of the Ciqikou Scenic Spot.The analysis results show that the scenic spot,with its unique folk culture experience and beautiful ecological environment,has certain advantages in terms of service quality.However,significant deficiencies exist in infrastructure and environmental hygiene.Accordingly,targeted improvement suggestions are proposed to further enhance the service quality of the Ciqikou Scenic Spot and meet the increasingly diverse and personalized needs of tourists.This study provides not only a specific service quality improvement strategy for the Ciqikou Scenic Spot but also a valuable reference for other tourist attractions.

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.

Object-Oriented Modeling of the Variation of Acceleration and Deceleration Characteristics in Relation to Speed Bands for Railway Vehicles

Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.

Modeling Method of Automotive Body CAN/LIN Nets Application Protocol Based on Object-oriented Colored Petri Net

Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.

The impact of Internet access on household dietary quality:Evidence from rural China

Over the past few decades,the Internet has rapidly diffused across China.The spread of the Internet has had a profound economic and social impact on Chinese rural areas.Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’income.Beyond these,the Internet can affect other dimensions of social welfare.However,research about the impact of Internet access on dietary quality in rural China remains scarce.This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis.Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity.The estimates show that Internet access has significantly increased rural household dietary quality(measured by the Chinese Diet Balance Index).Further research finds that Internet access has increased the consumption of animal products,such as aquatic and dairy products.We also examine the underlying mechanisms.Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure.These results encourage the promotion of Internet access as a valuable tool for nutritional improvements,especially in rural areas.

Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

The complex sand-casting process combined with the interactions between process parameters makes it difficult to control the casting quality,resulting in a high scrap rate.A strategy based on a data-driven model was proposed to reduce casting defects and improve production efficiency,which includes the random forest(RF)classification model,the feature importance analysis,and the process parameters optimization with Monte Carlo simulation.The collected data includes four types of defects and corresponding process parameters were used to construct the RF model.Classification results show a recall rate above 90% for all categories.The Gini Index was used to assess the importance of the process parameters in the formation of various defects in the RF model.Finally,the classification model was applied to different production conditions for quality prediction.In the case of process parameters optimization for gas porosity defects,this model serves as an experimental process in the Monte Carlo method to estimate a better temperature distribution.The prediction model,when applied to the factory,greatly improved the efficiency of defect detection.Results show that the scrap rate decreased from 10.16% to 6.68%.

Software Coupling and Cohesion Model for Measuring the Quality of Software Components

Measuring software quality requires software engineers to understand the system’s quality attributes and their measurements.The quality attribute is a qualitative property;however,the quantitative feature is needed for software measurement,which is not considered during the development of most software systems.Many research studies have investigated different approaches for measuring software quality,but with no practical approaches to quantify and measure quality attributes.This paper proposes a software quality measurement model,based on a software interconnection model,to measure the quality of software components and the overall quality of the software system.Unlike most of the existing approaches,the proposed approach can be applied at the early stages of software development,to different architectural design models,and at different levels of system decomposition.This article introduces a software measurement model that uses a heuristic normalization of the software’s internal quality attributes,i.e.,coupling and cohesion,for software quality measurement.In this model,the quality of a software component is measured based on its internal strength and the coupling it exhibits with other component(s).The proposed model has been experimented with nine software engineering teams that have agreed to participate in the experiment during the development of their different software systems.The experiments have shown that coupling reduces the internal strength of the coupled components by the amount of coupling they exhibit,which degrades their quality and the overall quality of the software system.The introduced model can help in understanding the quality of software design.In addition,it identifies the locations in software design that exhibit unnecessary couplings that degrade the quality of the software systems,which can be eliminated.

Research on Welding Quality Traceability Model of Offshore Platform Block Construction Process

Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry.Currently,qualitymanagement remains in the era of primary information,and there is a lack of effective tracking and recording of welding quality data.When welding defects are encountered,it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data.In this paper,a composite welding quality traceability model for offshore platform block construction process is proposed,it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm.By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm,the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems.Furthermore,the model and the quality traceability algorithm are checked by cases in actual working conditions.Verification analyses suggest that the proposed early-warningmodel for welding quality and the algorithmfor optimizing backtracking requests are effective and can be applied to the actual construction process.

STOCHASTIC OBJECT-ORIENTED PETRI NETS (SOPNS) AND ITS APPLICATION IN MODELING OF MANUFACTURING SYSTEM RELIABILITY

Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.

Effect of health education based on information-motivationbehavioral skills model on patients with unilateral vestibular dysfunction

BACKGROUND Vestibular dysfunction(VH)is a common concomitant symptom of late peri-pheral vestibular lesions,which can be trauma,poisoning,infection,heredity,and neurodegeneration,but about 50%of the causes are unknown.The study uses the information-motivation-behavioral skills(IMB)model for health education,effectively improve the quality of life,increase their self-confidence,reduce anxiety and depression,and effectively improve the psychological state of patients.AIM To explore the effect of health education based on the IMB model on the degree of vertigo,disability,anxiety and depression in patients with unilateral vestibular hypofunction.METHODS The clinical data of 80 patients with unilateral vestibular hypofunction from January 2019 to December 2021 were selected as the retrospective research objects,and they were divided into the control group and the observation group with 40 cases in each group according to different nursing methods.Among them,the control group was given routine nursing health education and guidance,and the observation group was given health education and guidance based on the IMB model.The changes in self-efficacy,anxiety and depression,and quality of life of patients with unilateral VH were compared between the two groups.RESULTS There was no significant difference in General Self-Efficacy Scale(GSES)scale scores between the two groups of patients before nursing(P>0.05),which was comparable;after nursing,the GSES scale scores of the two groups were higher than those before nursing.The nursing group was higher than the control group,and the difference was statistically significant(P<0.05).There was no significant difference in the scores of Hospital Anxiety and Depression Scale(HADS)and anxiety and depression subscales between the two groups before nursing(P>0.05).After nursing,the HADS score,anxiety,and depression subscale scores of the two groups of patients were lower than those before nursing,and the nursing group was lower than the control group,and the difference was statistically significant(P<0.05).After nursing,the Dizziness Handicap Inventory(DHI)scale and DHI-P,DHI-E and DHI-F scores in the two groups were decreased,and the scores in the nursing group were lower than those in the control group,and the difference was statistically significant(P<0.05).CONCLUSION Health education based on the IMB model can effectively improve patients'quality of life,increase self-efficacy of patients with unilateral vestibular hypofunction,enhance patients'confidence,enable patients to resume normal work and life as soon as possible,reduce patients'anxiety and depression,and effectively improve patients'psychological status.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

A Rice Growth Models (RGM) System by Object-Oriented Programming with Visual C++

Object-oriented programming divides the crop production into subsystems and simulates their behaviors. Many classes were designed to simulate the behaviors of different parts or different physiological processes in crop production system. At the same time, many classes have to be employed for bettering user's interface. But how to manage these classes on a higher level to cooperate them into a perfect system is another problem to study. The Rice Growth Models (RGM) system represents an effort to define and implement a framework to manage these classes. In RGM system, the classes were organized into the model-document-view architecture to separate the domain models, data management and user interface. A single document with multiple views interface frame window was adopted in RGM. In the architectures, the simulation models only exchange data with documents while documents act as intermediacies between simulation models and interfaces. Views get data from documents and show the results to users. The classes for the different functions can be grouped into different architectures. Different architectures communicate with each other through documents. The classes for the different functions can be grouped into different architectures. By using the architecture, communication between classes is more efficient. Modeler can add classes in architectures or other architectures to extend the system without having to change system structure, which is useful for construction and maintenance of agricultural system models.

Influence of Human Activity Intensity on Habitat Quality in Hainan Tropical Rainforest National Park,China

Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.

Effects of health concept model-based detailed behavioral care on mood and quality of life in elderly patients with chronic heart failure

BACKGROUND With the intensification of social aging,the susceptibility of the elderly population to diseases has attracted increasing attention,especially chronic heart failure(CHF)that accounts for a large proportion of the elderly.AIM To evaluate the application value of health concept model-based detailed behavioral care in elderly patients with CHF.METHODS This study recruited 116 elderly CHF patients admitted from October 2018 to October 2020 and grouped them according to the nursing care that they received.The elderly patients who underwent health concept model-based detailed behavioral care were included in a study group(SG;n=62),and those who underwent routine detailed behavioral nursing intervention were included as a control group(CG;n=54).Patients’negative emotions(NEs),quality of life(QoL),and nutritional status were assessed using the self-rating anxiety/depression scale(SAS/SDS),the Minnesota Living with Heart Failure Questionnaire(MLHFQ),and the Modified Quantitative Subjective Global Assessment(MQSGA)of nutrition,respectively.Differences in rehabilitation efficiency,NEs,cardiac function(CF)indexes,nutritional status,QoL,and nursing satisfaction were comparatively analyzed.RESULTS A higher response rate was recorded in the SG vs the CG after intervention(P<0.05).After care,the left ventricular ejection fraction was higher while the left ventricular end-diastolic dimension and left ventricular end systolic diameter were lower in the SG compared with the CG(P<0.05).The post-intervention SAS and SDS scores,as well as MQSGA and MLHFQ scores,were also lower in the SG(P<0.05).The SG was also superior to the CG in the overall nursing satisfaction rate(P<0.05).CONCLUSION Health concept model-based detailed behavioral care has high application value in the nursing care of elderly CHF patients,and it can not only effectively enhance rehabilitation efficiency,but also mitigate patients’NEs and improve their CF and QoL.

Simulation and evaluation of tomato growth by AquaCrop model under different agricultural waste materials

This study aimed to enhance the utilization of agricultural waste and identify the most suitable agricultural waste materials for tomato cultivation. It utilized a locally modified substrate labeled as CK, along with five different groups of agricultural waste materials, designated as T1 (organic fertilizer: loessial soil: straw in a ratio of 4:5:1), T2 (organic fertilizer: loessial soil: straw: grains in a ratio of 3:5:1:1), T3 (organic fertilizer: loessial soil: straw: grains in a ratio of 2:5:1:2), T4 (organic fertilizer:loessial soil:straw:grains in a ratio of 1:5:1:3), and T5 ( loessial soil:straw:grains in a ratio of 5:1:4), the AquaCrop model was employed to validate soil water content and tomato growth and yield under these treatments. Furthermore, a multi-objective genetic algorithm was employed to determine the optimal agricultural waste materials that would ensure maximum tomato yield, water use efficiency (WUE), partial factor productivity of fertilizer (PFP) and sugar-acid ratio. The results indicated that the AquaCrop model reasonably simulated volumetric soil water content, tomato canopy cover, and biomass, with root mean square error (RMSE) ranges of 20.0-69.4 mm, 15.2%-25.1%, and 1.093-3.469 t/hm2, respectively. The CK group exhibited an R-squared (R2) value of 0.63 for volumetric soil water contents, while the ratio scenarios showed R2 values exceeding 0.80. The multi-objective genetic optimization algorithm identified T5 as the optimal ratio scenario, resulting in maximum tomato yield, WUE, PFP, and quality. This study offers a theoretical foundation for the efficient utilization of agricultural wastes and the production of high-quality fruits and vegetables.

Study Progress Analysis of Effluent Quality Prediction in Activated Sludge Process Based on CiteSpace

In this paper, CiteSpace, a bibliometrics software, was adopted to collect research papers published on the Web of Science, which are relevant to biological model and effluent quality prediction in activated sludge process in the wastewater treatment. By the way of trend map, keyword knowledge map, and co-cited knowledge map, specific visualization analysis and identification of the authors, institutions and regions were concluded. Furthermore, the topics and hotspots of water quality prediction in activated sludge process through the literature-co-citation-based cluster analysis and literature citation burst analysis were also determined, which not only reflected the historical evolution progress to a certain extent, but also provided the direction and insight of the knowledge structure of water quality prediction and activated sludge process for future research.