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.

A Web-Based Approach for the Efficient Management of Massive Multi-source 3D Models

Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.

Factors affecting farmers'choice to adopt risk management strategies:The application of multivariate and multinomial probit models

This study investigates the factors that impact farmers'adoption of risk management strategies(RMS)in Pakistan during times of uncertainty.The study examines farmers'adoption of RMS using both multinomial probit(MNP)and multivariate probit(MVP).Data were collected from 382 farmers sampled from four districts in KhyberPakhtunkhwa(KP)province of Pakistan via a multistage sampling technique.This study utilizes the MNP model,considering the assumption of Independence of Irrelevant Alternatives(IIA)and incorporating correlated error terms.The objective is to understand farmers'behavior in risky situations and determine if there is heterogeneity.Results are compared with the MVP model to assess robustness and gain deeper understanding of farmers'decisionmaking processes.The research findings reveal that our results are robust,and farmers behave homogeneously in various RMS scenarios.Farmers adopt RMS individually or in combination to mitigate the adverse effects of natural calamities on their livelihood.The risk-averse farmers,who perceive weather-related risks as a threat,access credits and information,and have farms close to a river are more likely to adopt RMS,irrespective of the format of the strategies available.Moreover,the predicted probabilities and correlation of the RMS and RM categories have strengthened our model estimation.These findings provide insights into the behavior of farmers in adopting RMS which are helpful for policymakers and stakeholders in developing strategies to mitigate the impacts of natural calamities on farmers.

Ecosystem service multifunctionality of mixed conifer-broad-leaved forests under climate change and forest management based on matrix growth modelling

Climate change and forest management are recognized as pivotal factors influencing forest ecosystem services and thus multifunctionality.However,the magnitude and the relative importance of climate change and forest management effects on the multifunctionality remain unclear,especially for natural mixed forests.In this study,our objective is to address this gap by utilizing simulations of climate-sensitive transition matrix growth models based on national forest inventory plot data.We evaluated the effects of seven management scenarios(combinations of various cutting methods and intensities)on the future provision of ecosystem services and multifunctionality in mixed conifer-broad-leaved forests in northeastern China,under four climate scenarios(SSP1-2.6,SSP2-4.5,SSP5-8.5,and constant climate).Provisioning,regulating,cultural,and supporting services were described by timber production,carbon storage,carbon sequestration,tree species diversity,deadwood volume,and the number of large living trees.Our findings indicated that timber production was significantly influenced by management scenarios,while tree species diversity,deadwood volume,and large living trees were impacted by both climate and management separately.Carbon storage and sequestration were notably influenced by both management and the interaction of climate and management.These findings emphasized the profound impact of forest management on ecosystem services,outweighing that of climate scenarios alone.We found no single management scenario maximized all six ecosystem service indicators.The upper story thinning by 5%intensity with 5-year interval(UST5)management strategy emerged with the highest multifunctionality,surpassing the lowest values by more than 20%across all climate scenarios.In conclusion,our results underlined the potential of climate-sensitive transition matrix growth models as a decision support tool and provided recommendations for long-term strategies for multifunctional forest management under future climate change context.Ecosystem services and multifunctionality of forests could be enhanced by implementing appropriate management measures amidst a changing climate.

Impact of stage-specific limb function exercises guided by a selfmanagement education model on arteriovenous fistula maturation status

BACKGROUND The exercise of limb function is the most economical and safe method to promote the maturation of arteriovenous fistula(AVF).However,due to the lack of a uni-fied exercise standard in China,many patients have insufficient awareness of the importance of AVF,leading to poor effectiveness of limb function exercise.The self-management education model can effectively promote patients to take pro-active health-related actions.This study focuses on the characteristics of patients during the peri-AVF period and conducts a phased limb function exercise under the guidance of the self-management education model to observe changes in fac-tors such as the maturity of AVF.AIM To assess the impact of stage-specific limb function exercises,directed by a self-management education model,on the maturation status of AVFs.METHODS This study is a randomized controlled trial involving 74 patients with forearm AVFs from the Nephrology Department of a tertiary hospital in Sichuan Province,China.Patients were randomly divided into an observation group and a control group using a random number table method.The observation group underwent tailored stage-specific limb func-tion exercises,informed by a self-management education model which took into account the unique features of AVF at various stages,in conjunction with routine care.Conversely,the control group was given standard limb function exercises along with routine care.The assessment involves the maturity of AVFs post-intervention,post-operative complications,and the self-management level of the fistula in both groups patients.Analyses were conducted using SPSS version 23.0.Count data were represented by frequency and percentage and subjected to chi-square test comparisons.Measurement data adhering to a normal distribution were presented as mean±SD.The independent samples t-test was utilized for inter-group comparisons,while the paired t-test was used for intra-group comparisons.For measurement data not fitting a normal distribution,the median and interquartile range were presented and analyzed using the Wilcoxon rank sum test.RESULTS At the 8-wk postoperative mark,the observation group demonstrated significantly higher scores in AVF symptom recognition,symptom prevention,and self-management compared to the control group(P<0.05).However,the variance in symptom management scores between the observation and control groups lacked statistical signi-ficance(P>0.05).At 4 wk after the operation,the observation group displayed a superior vessel diameter and depth from the skin of the drainage vessels in comparison to the control group(P<0.05).While the observation group did manifest elevated blood flow rates in the drainage vessels relative to the control group,this distinction was not statistically significant(P>0.05).By the 8-wk postoperative interval,the observation group outperformed the control group with notable enhancements in blood flow rates,vessel diameter,and depth from the skin of drainage vessels(P<0.01).Seven days following the procedure,the observation group manifested significantly diminished limb swelling and an overall reduced complication rate in contrast to the control group(P<0.05).The evaluation of infection,thrombosis,embolism,arterial aneurysm stenosis,and incision bleeding showed no notable differences between the two groups(P>0.05).By the 4-wk postoperative juncture,complications between the observation and control groups were statistically indistinguishable(P>0.05).CONCLUSION Stage-specific limb function exercises,under the guidance of a self-management education model,amplify the capacity of AVF patients to discern and prevent symptoms.Additionally,they expedite AVF maturation and miti-gate postoperative limb edema,underscoring their efficacy as a valuable method for the care and upkeep of AVF in hemodialysis patients.

Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

This article focuses on the challenges ofmodeling energy supply systems for buildings,encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings.Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material,such as for thermal upgrades,which consequently incurs additional economic costs.It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions,considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in buildings.In addition,it explores the methods and mechanisms for modeling the operating modes of electric boilers used to collectively improve energy efficiency and indoor climatic conditions.Using the developed mathematical models,the study examines the dynamic states of building energy supply systems and provides recommendations for improving their efficiency.These dynamic models are executed in software environments such as MATLAB/Simscape and Python,where the component detailing schemes for various types of controllers are demonstrated.Additionally,controllers based on reinforcement learning(RL)displayed more adaptive load level management.These RL-based controllers can lower instantaneous power usage by up to 35%,reduce absolute deviations from a comfortable temperature nearly by half,and cut down energy consumption by approximately 1%while maintaining comfort.When the energy source produces a constant energy amount,the RL-based heat controllermore effectively maintains the temperature within the set range,preventing overheating.In conclusion,the introduced energydynamic building model and its software implementation offer a versatile tool for researchers,enabling the simulation of various energy supply systems to achieve optimal energy efficiency and indoor climate control in buildings.

The Role of Grid-Style Nursing Management Model in Critically Ill Patients

Objective:This study aims to gain insight into the effects and potential advantages of the grid-style nursing management model in the care of critically ill patients.Methods:Eighty critically ill patients admitted to our hospital between May 2020 and May 2021 were selected and randomly divided into the control group and the grid group,each with 40 patients.The control group implemented traditional nursing management,while the grid group adopted a grid-style nursing management model.The quality of care,quality of life,nursing satisfaction,and treatment adherence of the two groups were compared.Results:Compared with the control group,the grid group had significantly higher quality of care and quality of life(P<0.001);in terms of nursing satisfaction,the score of the grid group was 8.26±0.85,which was significantly higher than that of the control group(6.65±0.77)(P<0.001);90.00%(36 patients)of the grid group showed good treatment adherence,significantly higher than 70.00%(28 patients)of the control group(P<0.001).Conclusion:The implementation of the grid-style nursing management model in critically ill patients can significantly improve the quality of care,quality of life,and satisfaction of patients,and effectively promote patients’treatment adherence.These positive results provide strong support for the promotion and application of this model in clinical care.

A theoretical framework for improved fire suppression by linking management models with smart early fire detection and suppression technologies

Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.However,to date,all these technologies have been applied in isola-tion.This paper introduces the latest fire detection and sup-pression technologies from ground to space.An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppres-sion.The framework harnesses the advantages of satellite-based,drone,sensor,and human reporting technologies as well as image processing and artificial intelligence machine learning.The study concludes that,if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements,a fire detection and resource suppression system can achieve the ultimate aim:to reduce the risk of fire hazards and the dam-age they may cause.

Research on the Application and Effectiveness of the DRG Model on Perioperative Medical Management of Cholecystectomy

Objective:This study aimed to explore the application and effectiveness of the DRG model in the perioperative management of cholecystectomy.By comparing the DRG model with traditional management methods,this study focused on evaluating the potential impact of the DRG model in improving surgical efficiency and reducing complication rates and medical costs.Methods:The random envelope method was used to divide patients scheduled for cholecystectomy from January 2021 to October 2023 into two groups:one group underwent surgery under the DRG model(experimental group),and the other group underwent the traditional management model(control group).Data including basic information,surgery-related data,length of stay,complication records,and medical expenses were collected.Data analysis was carried out using a t-test and chi-square(χ2)test.Results:Results showed that the DRG model shortened the average length of stay,decreased the incidence of complications,reduced medical expenses,and increased patient satisfaction.These results demonstrate the effectiveness of the DRG model in the perioperative management of cholecystectomy,especially in improving surgical efficiency,reducing medical costs,and improving patient satisfaction.Conclusion:The DRG model in the perioperative management of cholecystectomy can significantly improve medical service quality and efficiency and enhance patient satisfaction as compared to traditional treatment methods.

Analysis of the“Trinity”Model of Corporate Compliance Management

In today’s fast-changing business environment,enterprises are facing unprecedented challenges.In today’s fast-changing business environment,enterprises are facing unprecedented challenges.Compliance management has become a key element to ensure the sustainable development of enterprises,not only because it assists enterprises to comply with laws and regulations,but also because it is the cornerstone of corporate reputation and culture.A compliance management model called“Trinity”has emerged.Based on this,this paper analyzes in detail the“Trinity”model of compliance management from the value of its application in enterprises,to provide new ideas and directions for the compliance management work of enterprises,and promote enterprises to achieve a more robust and stable business environment in the complex and changing market environment.In order to provide new ideas and directions for enterprise compliance management,and to promote enterprises to realize more stable and sustainable development in the complex and changing market environment.

Whole-Process Project Cost Management Based on Building Information Modeling (BIM)

The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.

Application of Hazard Vulnerability Analysis Based on Kaiser Model in Neonatal Breast Milk Management

Objective:To analyze the existing risks in breast milk management at the neonatal department and provide corresponding countermeasures.Methods:22 risk events were identified in 7 risk links in the process of bottle-feeding of breast milk.Hazard Vulnerability Analysis based on the Kaiser model was applied to investigate and evaluate the risk events.Results:High-risk events include breast milk quality inspection,hand hygiene during collection,disinfection of collectors,cold chain management,hand hygiene during the reception,breast milk closed-loop management,and post-collection disposal.Root cause analysis of high-risk events was conducted and breast milk management strategies outside the hospital and within the neonatal department were proposed.Conclusion:Hazard Vulnerability Analysis based on the Kaiser model can identify and assess neonatal breast milk management risks effectively,which helps improve the management of neonatal breast milk.It is conducive to the safe development and promotion of bottle feeding of breast milk for neonates,ensuring the quality of medical services and the safety of children.

Research on the Optimization of Enterprise Financial Management under the Financial Sharing Model

With the advancement of globalization and information technology,the financial sharing mode has gradually emerged as a crucial means for enterprises to optimize their financial management.Particularly within the context of economic globalization,informatization,and digital transformation,enterprises find themselves navigating a rapidly evolving market environment by intensifying competition.To enhance efficiency and competitiveness,many enterprises have embraced the financial sharing model to streamline financial management processes,curtail costs,and bolster the execution of corporate strategies.This article aims to dissect the definition and essence of the financial sharing model and its significance in the realm of enterprise financial management.Drawing upon this analysis and aligning with the needs of enterprise financial management,the article proposes ideas for optimizing management practices,aspiring to foster reform and innovation in enterprise financial management while enhancing its level of financial management and ability to respond to financial risks.This contribution seeks to provide valuable insights for practitioners in the field.

Construction of the“Micro-Ideological and Political”Model for Ideological and Political Teaching Reform in Bidding and Contract Management Courses

In the context of deepening educational reforms,the significance of ideological and political education has become increasingly prominent,emerging as a crucial aspect of enhancing students’comprehensive qualities.To ensure the orderly progress of ideological and political education in courses,it is essential to actively promote the integration of ideological and political elements within coursework.This integration aims to align professional course education with ideological and political education,fostering a collaborative educational model.Therefore,in the teaching of bidding and contract management courses,constructing a“micro-ideological and political”teaching model has emerged as a critical component.The implementation of this model facilitates the seamless integration of bidding and contract management coursework with ideological and political education,thereby elevating the teaching quality of these courses.Additionally,it leverages the synergistic role of coursework and ideology in educating students,ultimately enhancing the quality and level of talent cultivation.Hence,this paper proposes strategies for constructing a“microideological and political”model within the context of ideological and political teaching reforms in bidding and contract management courses,inviting discussion and exchange on this topic.

Endoscopic diagnosis and management of gallbladder carcinoma in minimally invasive era:New needs,new models

Gallbladder cancer(GBC)is a rare and lethal malignancy;however,it represents the most common type of biliary tract cancer.Patients with GBC are often diagnosed at an advanced stage,thus,unfortunately,losing the opportunity for curative surgical intervention.This situation leads to lower quality of life and higher mortality rates.In recent years,the rapid development of endoscopic equipment and techniques has provided new avenues and possibilities for the early and minimally invasive diagnosis and treatment of GBC.This editorial comments on the article by Pavlidis et al.Building upon their work,we explore the new needs and corresponding models for managing GBC from the endoscopic diagnosis and treatment perspective.

Key Issues for Modelling, Operation, Management and Diagnosis of Lithium Batteries: Current States and Prospects

1 Introduction.With the continuous growth of the global population,the energy demand continues to increase.However,due to the dominance of fossil fuels in global energy and fossil fuels are non-renewable,it has led to the global energy crisis[1].Besides,the use of fossil fuels will generate a mass of air pollutants(e.g.,carbon dioxide,sulfur dioxide,etc.),which will cause serious environmental pollution,climate change[2],etc.To resolve the aforementioned issues,countries around the world have implemented a variety of measures hoping to fundamentally adjust the global energy structure and achieve sustainable development.Thereinto,“Paris Agreement”reached in 2015 under the framework of“United Nations Framework Convention on Climate Change”aims to control the increase in the average temperature of the globe to within 2°C below preindustrial levels,and thereafter to peak global greenhouse gas emissions as soon as possible,continuously decreasing thereafter[3].United Kingdom plans to reduce the average exhaust emissions of“new cars”to approximately 50–70 g/km by 20230,which is roughly half of what it is now[4].In addition,China proposed a plan at“United Nations General Assembly”in 2020 to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by 2060.It is a fact that the whole world is committed to changing the current energy structure,protecting the Earth’s ecology,and achieving global sustainable development[5].

User-friendly prognostic model for rectal neuroendocrine tumours: In the era of precision management

In this letter,we explore into the potential role of the recent study by Zeng et al.Rectal neuroendocrine tumours(rNETs)are rare,originate from peptidergic neurons and neuroendocrine cells,and express corresponding markers.Although most rNETs patients have a favourable prognosis,the median survival period significantly decreases when high-risk factors,such as larger tumours,poorer differentiation,and lymph node metastasis exist,are present.Clinical prediction models play a vital role in guiding diagnosis and prognosis in health care,but their complex calculation formulae limit clinical use.Moreover,the prognostic models that have been developed for rNETs to date still have several limitations,such as insufficient sample sizes and the lack of external validation.A high-quality prognostic model for rNETs would guide treatment and follow-up,enabling the precise formulation of individual patient treatment and follow-up plans.The future development of models for rNETs should involve closer collab-oration with statistical experts,which would allow the construction of clinical prediction models to be standardized and robust,accurate,and highly general-izable prediction models to be created,ultimately achieving the goal of precision medicine.

Application and Promotion of Whole-Process Capacity Management Model for CHF Patients Led by Specialist Nurses in “Heart Failure Center Alliance Unit”

Objective: To implement the whole-process capacity management model led by specialist nurses, improve the capacity management behavior of medical staff, and build a standardized, standardized and operable CHF capacity management system. Methods: According to the evidence pyramid principle and search strategy, 2 evidence-based nursing backbone completed literature search in both Chinese and English, and finally included 7 literatures. Results: Around the three key links of capacity assessment, monitoring and management, stakeholders were invited to evaluate each evidence according to the FAME principle, that is, the feasibility, suitability, effectiveness and clinical significance of evidence. Finally, 11 best evidences were obtained and 5 clinical review indicators of the cost project were transformed. This study formulated the competence management plan for CHF patients based on the current situation, established competence load evaluation criteria for CHF patients, and determined the target “dry weight” value for CHF patients. Conclusion: The whole-course volume management model of CHF patients guided by specialist nurses should be established and applied and promoted in the “heart failure Center Alliance unit”, so as to improve the capacity management ability of medical staff for CHF patients, enhance the self-management ability of CHF patients, improve the capacity management behavior and health outcomes, and effectively reduce the hospitalization rate and mortality rate of CHF patients in the region.

An Integrated Building Information Modeling (BIM) and Circular Economy (CE) Model for the Management of Construction and Deconstruction Waste Based on Construction Methods

As the climate change signs become more noticeable, the concern to prioritize sustainability within the AEC industry intensifies. This particularly pertained to issues related to the demand of resources, the excessive consumption of raw materials, and the associated generated waste. Presently, the construction industry is ranked among the industries that are accountable for the global generation of solid waste and energy consumption, leading to detrimental environmental effects. Nonetheless, over the years, construction methods, technological innovations, and building practices have made considerable progress, influenced by a growing emphasis on sustainability, especially in energy conservation and in adopting the Industrialized Production layer of Construction 4.0 (i.e., modular prefabrication, 3D concrete printing, and BIM). The concept of Circular Economy (CE) has been identified as a potential solution to achieve sustainability in building construction through the design, construction, and end-of-life deconstruction processes that enhance the management of waste based on the framework that is related to reducing, reusing, and recycling. Moreover, information and data related to geolocation complement advanced digital technologies by providing a collaborative platform that supports the application of CE as a practical approach to sustainability. Thus, this study will provide a straightforward methodology for developing a model that integrates BIM and sustainable design with Circular Economy’s concept to enhance the sustainability of construction projects to minimize their waste based on various construction methods (i.e., conventional, modular, and 3D concrete printing). The proposed model interrelates tools and data for the evaluation and planning strategies for the construction and deconstruction waste (CDW) management at the design stage, including estimating the quantities of the wasted materials, quantifying the production rates of selected equipment for the waste handling (loading and hauling) at the various stages of a project as well their associated cost. The proposed model will help users to calculate the quantity of construction and deconstruction waste (CDW) during the design of buildings based on their different construction methods at the early stage by using the concept of Design for Deconstruction (DfD);sustainable construction methods;and deconstruction process for waste management, which will lead to the suitable construction method.

PhishGuard: Integrating Fine-Tuned Large Language Models (LLMs) into Password Management

In the digital age, phishing attacks have been a persistent security threat leveraged by traditional password management systems that are not able to verify the authenticity of websites. This paper presents an approach to embedding sophisticated phishing detection within a password manager’s framework, called PhishGuard. PhishGuard uses a Large Language Model (LLM), specifically a fine-tuned BERT algorithm that works in real time, where URLs fed by the user in the credentials are analyzed and authenticated. This approach enhances user security with its provision of real-time protection from phishing attempts. Through rigorous testing, this paper illustrates how PhishGuard has scored well in tests that measure accuracy, precision, recall, and false positive rates.