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.

Scenario analysis of water pollution control in the typical peri-urban river using a coupled hydrodynamic-water quality model

The water quality pollution and ecological deterioration in peri-urban rivers are usually serious under rapid urbanization and economic growth.In the study,a typical peri-urban river,Nansha River,was selected as a case study to discuss the scheme of peri-urban river rehabilitation.Located in the north part of the Beijing central region,the Nansha River watershed has been designated as an ecologically friendly garden-style area with high-tech industry parks and upscale residential zones.However,the Nansha River is currently seriously contaminated by urban and rural pollutants from both nonpoint sources(NPS)and point sources(PS).In this study,the pollutant loads from point sources and nonpoint sources in the Nansha River watershed were first assessed.A coupled model,derived from the Environmental Fluid Dynamics Code and Water Quality Analysis Simulation Program,was developed to simulate the hydrodynamics and water quality in the Nansha River.According to the characteristics of the typical peri-urban river,three different PS and NPS control scenarios were designed and examined by modeling analyses.Based on the results of the scenario analysis,a river rehabilitation scheme was recommended for implementation.

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.

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.

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.

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.

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%.

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.

Yield Characteristics of a New High-quality Disease-resistant Wheat Variety Chuanmai 618

[Objectives]The paper was to analyze the yield characteristics of a new high-quality disease-resistant wheat variety Chuanmai 618.[Methods]The yield characteristics of Chuanmai 618 were analyzed using the AMMI model and GGE biplot based on data from a 2-year regional test and a 1-year production test.[Results]The analysis of the AMMI model for the 2-year regional test indicated that Chuanmai 618 had a moderate yield and good stability.During the production test,Chuanmai 618 had an average yield of 450.52 kg/666.7 m^(2),an effective spike of 235700 spike/666.7 m^(2),a 1000-seed weight of 47.93 g,and a kernel number per spike of 47.28.The AMMI analysis sequencing graph showed that the varieties were ranked in the following order:Zhongkemai 1816>Chuanmai 618>Shumai 1958>Chuanyu 42>Mianmai 367>Xikemai 5518.According to the GE analysis,Chuanmai 618 had comparative advantages.[Conclusions]The new wheat variety Chuanmai 618 is a high-quality disease-resistant variety with good yield and stability.

The Construction of Integrated Nursing Model Prevention of Oxaliplatin Chemotherapy-Induced Peripheral Nerve Injury

Objective: To investigate the effect of the integrated nursing model in the prevention of chemotherapy-induced peripheral injury. Methods: A total of 60 tumor patients receiving oxaliplatin for 1 - 6 cycles of chemotherapy from January to September 2023 were selected. 30 patients were selected from January to March and divided into the control group, and 30 patients were selected from July to 9 as the experimental group. The control group received conventional chemotherapy nursing, while the experimental group received integrated nursing. Anxiety, peripheral nerve toxicity stage and quality of life score were compared between the two groups before and after intervention. Results: After intervention, the scores of the self-rating Anxiety Scale (SAS) and the total scores of the oxaliplatin Levi specific sensory neurotoxicity scale in the experimental group were significantly lower than those in the control group, and the differences were statistically significant (P< 0.05);The Quality of Life Scale (FACT-G) score of cancer patients was higher than that of control group, and the difference was statistically significant (P< 0.05). Conclusion: The integrated nursing model can effectively reduce the anxiety of patients, reduce the incidence of peripheral nerve injury and improve the quality of life of patients.

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.

Modeling of Total Dissolved Solids (TDS) and Sodium Absorption Ratio (SAR) in the Edwards-Trinity Plateau and Ogallala Aquifers in the Midland-Odessa Region Using Random Forest Regression and eXtreme Gradient Boosting

Efficient water quality monitoring and ensuring the safety of drinking water by government agencies in areas where the resource is constantly depleted due to anthropogenic or natural factors cannot be overemphasized. The above statement holds for West Texas, Midland, and Odessa Precisely. Two machine learning regression algorithms (Random Forest and XGBoost) were employed to develop models for the prediction of total dissolved solids (TDS) and sodium absorption ratio (SAR) for efficient water quality monitoring of two vital aquifers: Edward-Trinity (plateau), and Ogallala aquifers. These two aquifers have contributed immensely to providing water for different uses ranging from domestic, agricultural, industrial, etc. The data was obtained from the Texas Water Development Board (TWDB). The XGBoost and Random Forest models used in this study gave an accurate prediction of observed data (TDS and SAR) for both the Edward-Trinity (plateau) and Ogallala aquifers with the R2 values consistently greater than 0.83. The Random Forest model gave a better prediction of TDS and SAR concentration with an average R, MAE, RMSE and MSE of 0.977, 0.015, 0.029 and 0.00, respectively. For the XGBoost, an average R, MAE, RMSE, and MSE of 0.953, 0.016, 0.037 and 0.00, respectively, were achieved. The overall performance of the models produced was impressive. From this study, we can clearly understand that Random Forest and XGBoost are appropriate for water quality prediction and monitoring in an area of high hydrocarbon activities like Midland and Odessa and West Texas at large.

Projection pursuit cluster model and its application in water quality assessment

One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.

High-resolution modeling and evaluation of ozone air quality of Osaka using MM5-CMAQ system

High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality （CMAQ） model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model （GPV-MSM） data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.

Development and application of a two-dimensional water quality model for the Daqinghe River Mouth of the Dianchi Lake

Water quality models are important tools to support the optimization of aquatic ecosystem rehabilitation programs and assess their efficiency. Basing on the flow conditions of the Daqinghe River Mouth of the Dianchi Lake, China, a two-dimensional water quality model was developed in the research. The hydrodynamics module was numerically solved by the alternating direction iteration （ADI） method. The parameters of the water quality module were obtained through the in situ experiments and the laboratory analyses that were conducted from 2006 to 2007. The model was calibrated and verified by the observation data in 2007. Among the four modelled key variables, i.e., water level, COD （in CODcr）, NH4＋-N and PO43-P the minimum value of the coefficient of determination （COD） was 0.69, indicating the model performed reasonably well. The developed model was then applied to simulate the water quality changes at a downstream cross-section assuming that the designed restoration programs were implemented. According to the simulated results, the restoration programs could cut down the loads of COD and PO43-P about 15%. Such a load reduction, unfortunately, would have very little effect on the NH4^＋-N removal. Moreover, the water quality at the outlet cross-section would be still in class V （3838-02）, indicating more measures should be taken to further reduce the loads. The study demonstrated the capability of water quality models to support aquatic ecosystem restorations.

A genetic algorithm based stochastic programming model for air quality management

This paper presents a model that can aid planners in defining the total allowable pollutant discharge in the planning region, accounting for the dynamic and stochastic character of meteorological conditions. This is accomplished by integrating Monte Carlo simulation and using genetic algorithm to solve the model. The model is demonstrated by using a realistic air urban scale SO 2 control problem in the Yuxi City of China. To evaluate effectiveness of the model, results of the approach are shown to compare with those of the linear deterministic procedures. This paper also provides a valuable insight into how air quality targets should be made when the air pollutant will not threat the residents' health. Finally, a discussion of the areas for further research are briefly delineated.

Three-Dimensional Tidal Model and Its Application to Numerical Simulation of Water Quality in Coastal Waters

The turbulence mechanism plays an important part in the mixing process and momentum transfer of turbulence. A three-dimensional Prandtl mixing length tidal model has been developed to simulate tidal flows and water quality. The eddy viscosities and diffusivities are computed from the Prandtl mixing length model. In order to model the water quality of an estuary or coastal area many interdependent processes need to be simulated. These may be conveniently separated into three main groups: transport and mixing processes, biochemical interaction of water quality variables and the utilization and re-cycling of nutrients by living matter. The model simulates full oxygen and nutrient balance, primary productivity and the transport, reaction mechanism and fate of pollutants over tidal time-scales. The model is applied to numerical simulation of tidal flows and water quality in Dalian Bay. The model has been calibrated against a limited data set of historical water quality observations and in general demonstrates excellent agreement with all available data.

Characteristics analyzing and parametric modeling of the arc sound in CO_2 GMAW for on-line quality monitoring

For on-line monitoring of welding quality, the characteristics of the arc sound signals in short circuit CO2 GMAW were analyzed in the time and frequency domains. The arc sound presents a series of ringing-like oscillations that occur at the end of short circuit i. e. the moment of arc re-ignition, and distributes mainly in the frequency band below 10 kHz. A concept of the arc tone channel and its equivalent electrical model were suggested, which is considered a time-dependent distributed parametric system of which the transmission properties depend upon the geometric and physical characteristics of the arc and surroundings, and is excited by the sound source results from the change of arc energy so that results in arc sound. The linear prediction coding （ LPC ） model is an estimation of the tone channel. The radial basis function （ RBF ） neural networks were built for on-line pattern recognition of the gas-lack in welding, in which the input vectors were formed with the LPC coefficients. The test results proved that the LPC model of arc sound and the RBF networks are feasible in on-line quality monitoring.

Using ADMS models for Air Quality Assessment and Management in China

ADMS-Urban is the most widely used advanced dispersion model for urban areas, being used extensively in China and worldwide, providing a practical tool for assessing and managing urban air quality. In this paper we briefly describe the ADMS dispersion models and give an overview of their use in China. And it describes in more detail the use of ADMS-Urban in Fushun in Liaoning province and in Jinan in Shangdong province respectively, for studies of urban air quality. Finally the conclusions are presented.