Integrated Model Research Articles

О двух подходах к проблеме понимания текста: концепции А.А. Залевской и А.И. Новикова

The article is devoted to the theoretical review of two concepts of text comprehension within the framework of psycholinguistic research, namely, the theories of A.A. Zalevskaya and A.I. Novikov. The comparative analysis of the scientists’ works on the stated problematic allowed to define and briefly describe the main regularities of the comprehension process highlighted by both scientists. The fundamental principles, according to both authors, are the active role of the recipient in the process of text perception, the multidimensional and implicit nature of the understanding process itself, the mechanism of which, due to its dual nature, can be compared to projection. When analysing the process of text comprehension, researchers emphasize the important role of key words as dominant units of the text, as material ‘carriers of meaning’ providing the coagulation and unfolding of information contained in the text. The detailed analysis allowed us to show that both A.A. Zalevskaya and A.I. Novikov emphasise the relevance and significance of using an interdisciplinary approach to investigate the problem of understanding and to develop an integrative model to describe it. The article gives a brief description of the models of understanding developed by the scientists within the framework of their experimental research: A.A. Zalevskaya’s spiral model and A.I. Novikov’s interactive model, which were developed in the works of their pupils. As a general conclusion, the authors of the article suggest considering the prospect of integrating these two areas of research within the framework of text psycholinguistics, which hypothetically could provide a comprehensive systematic approach to solving the ‘eternal’ problem of understanding.

The Vertical Integration Model of Peacebuilding as Applied to the Bangsamoro Peace Process

The Vertical Integration Model of Peacebuilding as Applied to the Bangsamoro Peace Process

Software data objects application integrity modeling in medication dispensing errors predictions using machine learning algorithms in workflow-based pharmacy software systems

The study focuses on using the software objects created at each stage of the workflow-based systems (and in our article we can focus on the pharmacy-based medication dispensing software systems) to predict the anomalies or potential issues in that software object constructed at each stage of the workflow using the historical issues recorded in that specific workflow stage using linear regression, decision trees, and neural network algorithms. By utilizing historical data and integrity metrics, the research aims to forecast potential failures and maintain the reliability of software applications. The focus is on employing algorithms such as linear regression, decision trees, and neural networks to enhance predictive accuracy and facilitate informed decisions or recommendations to the workflow users (pharmacists) about the potential medication dispensing error the software objects constructed at that state or workflow could cause and advise to take necessary corrections.

English

English

Integrating AHP and GTMA for Enhanced Multi-Criteria Decision Making in Logistics Provider Selection

The selection of logistics providers is a critical task for organizations aiming to enhance their supply chain performance and maintain a competitive edge. This paper proposes an integrated approach that combines the Analytic Hierarchy Process (AHP) and Graph-Theoretic Matrix Approach (GTMA) for effective multi-criteria decision-making (MCDM) in the selection of logistics providers. AHP is widely used for evaluating criteria and alternatives based on pairwise comparisons, while GTMA enhances decision-making by incorporating complex interdependencies among criteria. The integrated AHPGTMA approach is demonstrated through a case study involving the selection of a third-party logistics provider (3PLP). The proposed method improves the decision-making process by simplifying complex relationships among criteria while ensuring an efficient and robust selection. This integrated model presents a more comprehensive and reliable framework for logistics provider selection, overcoming limitations observed in stand-alone AHP and ANP approaches. Future research may focus on the application of fuzzy logic to further enhance decision accuracy in uncertain environments.

A Study on the Key Factors for the Sustainable Development of Shared Mobility Based on TDM Theory: The Case Study from China

This study is based on an investigation of shared mobility in Chinese cities, which identifies the factors affecting the sustainable development of shared mobility based on the theoretical framework of TDM (travel demand management). Through a literature review and expert interviews, the FUZZY-DEMATEL-ISM-MICMAC integration model was used to screen 21 influencing factors from aspects that fit the research theme. Triangular fuzzy numbers are used to quantify the subjective scores of nine expert groups and weaken the subjective influence of expert scores. The logical relationships among DEMATEL technology-building factors and ISM technology-based factors are divided into levels. The MICMAC technique is used to divide the types of factors according to the driving power and dependency. The results show that (1) the influence factors of the “soft strategy” and “hard strategy” in the framework of TDM are determined. In the soft strategy, we should focus on “shared mobility education” (shared mobility education, shared mobility publicity and shared mobility “environment” information) and “community organization” (community organization and advocacy and organizational interaction). In the hard strategy, we should focus on “traffic planning and measures”, “dedicated lanes”, “parking facilities”, and “financial subsidies”. (2) The ISM recursive structure model is divided into five layers. Among them, shared mobility education, shared mobility operating technology, and organizational interaction are at the deep root level, which can continuously influence other factors in the long run. (3) In MICMAC, the number of related factors is large. When making decisions on these factors, managers should comprehensively consider the correlation of factors and adjust the use of factors from an overall perspective. This study can help managers identify the key factors affecting the sustainability of shared mobility and make targeted recommendations.

An Integrated Circular Supply Chain Framework to Enhance Malaysian Business Performance

Businesses rely on supply chain management to suit the needs of global and multigenerational consumers. However, the current linear manufacturing and distribution supply chain strategy has been regarded as the source of dangerous waste generation, environmental deterioration, and the global warming phenomenon. In mitigating this issue, circular supply chain management, a practical integration model, is seen as the solution as it helps to reduce material flows and supply chain waste. Unfortunately, the fundamental mechanisms that can support its effective execution have not been comprehensively examined, hindering its complete incorporation into company strategy. Thus, to overcome this knowledge gap and improve organizational understanding, this study uses the systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) procedure to investigate the characteristics, enablers, and barriers of circular supply chain management. The study found five interconnected key structures: government, industry stakeholders, corporate management, end users, and financial institutions, all of which play important roles in the successful implementation of a circular supply chain strategy. As a result, close collaboration across the five identified stakeholders is essential to enable successful implementation. This study's objective is to the United Nations Sustainable Development Goals (SDGs) 8, 9, and 12, which aim to promote peace and prosperity for people and the planet both now and in the future.

Effectiveness of Community-Based Multidisciplinary Integrated Care for Older Adults with General Practitioner Involvement: A Systematic Review and Meta-Analysis

Abstract Background Changing demographics has led to healthcare systems reorientating healthcare delivery towards the community setting and implementing integrated models of care worldwide. A knowledge gap exists with regards to what elements of integrated care facilitate effective age-attuned healthcare delivery. This systematic review examines the effectiveness of community-based multidisciplinary integrated care strategies with General Practitioner (GP) participation for community-dwelling older adults and describes the level of care integration in each study. Methods PUBMED, EMBASE, CINAHL, Central Register of Controlled Trials in the Cochrane Library and MEDLINE were systematically searched in April 2023. Randomised controlled trials (RCTs) or cluster RCTs that focused on interventions for community-dwelling older adults delivered by health and social care professionals with GPs were included. Two reviewers independently conducted the risk of bias assessment, applied the GRADE tool to quantify the certainty of evidence and used the Rainbow Model of Integrated Care taxonomy to describe the elements of integrated care used within studies. The primary outcome was functional status. Meta-analyses were performed using Review Manager 5.4. Results Twelve trials (14 reports) recruiting 8069 participants across 8 countries were included. Community-based multidisciplinary team (MDT) integrated care demonstrated significant improvements in functional status (standardised mean difference (SMD) 0.21, 95% confidence interval (CI) 0.05-0.37; low certainty evidence), hospitalisation (risk ratio (RR) 0.77, 95% CI 0.63-0.95; very low certainty evidence) and participant satisfaction with care (SMD 0.46, 95%c CI 0.15-0.76; low certainty evidence) from 12-36 months. No statistically significant effects favouring community-based MDT interventions for functional status at 6-month follow-up, Emergency Department presentation, mortality, health-related quality of life, or nursing home admission were established. Conclusion Community-based MDT integrated care with GP participation improves clinical and process outcomes for community-dwelling older adults. Future research should focus on models of integrated care that respond to the needs and preferences of older adults.

Study protocol for Early Tracking of Childhood Health determinants (ETCHED): A longitudinal observational life course study

BackgroundThe prevalence of childhood obesity and diabetes continues to rise in the United States (US), especially among minority populations. The objective of the Early Tracking of Childhood Health Determinants (ETCHED) study is to investigate the role of adverse fetal and early-life risk exposures that contribute to the development of childhood obesity and metabolic risk.MethodsETCHED is a longitudinal observational study of American Indian/Alaska Native (AI/AN) and Hispanic pregnant woman and their offspring. Pregnant mothers ≥ 18 years old are enrolled at a large public hospital system in the southwestern US. Enrolled mothers are followed through pregnancy, delivery, and the maternal/offspring dyad will be followed until the child’s 18th birthday. At each maternal visit, questionnaires assessing medical history, diet, physical activity, sleep, perceived stress, and socioeconomic and sociocultural information are obtained. Standard laboratory tests during maternal visits include glycemic measures, lipids, and renal function. Additional bio samples obtained include venous blood samples and cord blood for obesity/metabolic biomarkers and genetic/epigenetic testing, urinalysis, placental tissue for examining functional pathways, breast milk for metabolomics, and stool for metabolites and microbiome analysis. The offspring will have 6 infant/toddler visits at 6–12 weeks, 4 months, 6 months, 18 months, 2 and 3 years respectively. Thereafter, they will undergo comprehensive research visits (major visits) at 4–5 years, 6–9 years, 10–13 years, and 14–17 years. The major visits in children include detailed medical history, anthropometry, developmental assessment, socioeconomic and environmental assessments (food insecurity, family structure, and childcare), feeding and activity, biochemical tests, genetics/epigenetic testing, and ultrasound elastography. Electronic health records will be reviewed for additional clinical information. The primary analysis will constitute estimation of correlation coefficients between continuous variables. The planned study duration in this ongoing study is 23-years.DiscussionThis is a life course study that that will examine biological and environmental risk factors for obesity and cardiometabolic risk from the intrauterine period to early childhood and adolescence in a population with high-risk of obesity and type 2 diabetes in the United States. The ETCHED study would also provide a unique opportunity to combine multi-omics and clinical data to create novel integrative models to predict the cardiometabolic risk associated with childhood obesity and possibly identify etiopathogenetic mechanisms and future targets of intervention.Trial registration numberClinicalTrials.gov identifier: NCT03481829. Updated July 19, 2024, https://clinicaltrials.gov/study/NCT03481829?cond=ETCHED&rank=1.

Stress-induced overeating behaviors explained from a (transitory) relief-learning perspective

People use various behaviors to cope with stressful events. These behaviors are mostly adaptive, as they allow a successful release of stress without impacting other aspects of life: How nice is it to have a break with a few spoons of that favorite ice cream during a hectic working day? However, when excessive consumption of high-sugar/salt ultra-processed food becomes the gateway to find relief from stress, eating loses this adaptive function and may escalate to binge eating, lead to obesity, and other medical conditions linked to overweight.Several etiological models attempt to explain stress-induced eating and excessive overeating behaviors characterizing these clinical conditions. The popular Emotional Eating Theory proposes that stress-related (over-)eating, a major predictor of obesity and diagnosed binge eating disorders, develops based on negative reinforcement learning since food consumption regulates the negative affective state associated with stressful circumstances. Differently, the prominent Incentive Sensitization Theory explains overeating, binge eating disorders (including bulimia), and obesity in terms of excessive amplification of reward ‘wanting’, which is thought to emerge from overexposure to obesogenic (food)cues. The several studies oriented by these theories have paved the way to better understand stress-related (over-)eating and its clinical excesses. However, a deep mechanistic understanding of how and why stress-induced (over-)eating can escalate till clinical forms of overeating remain elusive. A well-funded connection of the mechanisms proposed by the Emotional Eating Theory and the Incentive Sensitization Theory might address this etiological open question. To avoid erroneous arguments, it is however essential to first address the internal theoretical and methodological shortcomings of each theory and connected studies. These shortcomings stem from conceptual fallacies and poorly implemented designs, which might partially explain the ‘high variability and low replicability’ problem of empirical findings. Next, the formulation of a new integrative model could provide fresh insight into the deep learning and biological mechanisms of this escalation. A successful formalization of this model could then create the much-needed impact in clinical and preventive research since excessive overeating is a behavior hard to change once established.In this opinion paper, I propose to apply recent insights we gathered on the role of relief from the field of safety learning to stress (over-)eating. I will present a new relief-based model that, as a starting point, has the potential to connect the Emotional Eating Theory with the Incentive Sensitization Theory, setting the base for more integrative science.

An integrated approach toward digital design and simulation of the automated overbraiding process for composite manufacturing

The study presents a new integrated hybrid modeling framework that combines kinematic models with Finite Element Analysis (FEA) to simulate the overbraiding process on non-circular and variable cross-section mandrels in composite manufacturing. By combining the computational efficiencies of kinematic models with the detailed physical insights from FEA simulations, this hybrid method provides a holistic solution for designing and prototyping overbraided structures. Specifically applied to a complex rectangular-to-square mandrel, the approach accurately predicts braid angles, validated against physical braiding experiments covering a range of target angles. The achieved results highlight the model's accuracy and emphasize its potential to boost the efficiency and precision of overbraiding in industrial settings, thereby reducing the need for costly and time-consuming physical braiding iterations.

When sexual distress shares the bed: the role of sexual self-esteem in the relationship between dispositional mindfulness and sexual distress in sex therapy patients.

Sexual distress (eg, feeling distressed, unhappy, frustrated, stressed, dissatisfied, or bothered about their sexuality) is a central concern reported by patients seeking sex therapy, and might be related to sexual self-esteem and mindfulness disposition, yet research is needed to examine the links among those variables within the specific population of patients seeking therapy. This study aimed to examine the indirect role of sexual self-esteem in the relationship between dispositional mindfulness and sexual distress. The study was conducted among 696 patients undergoing sexual therapy (mean age 34.19 ± 11.21 years, age range 18-78years). Participants identified as women (57.3%), men (38.5%), or nonbinary (4.2%). They completed self-report questionnaires assessing dispositional mindfulness (Five Facet Mindfulness Questionnaire), sexual self-esteem (Multidimensional Sexuality Questionnaire), and sexual distress (Sexual Distress Scale-Revised), during their first few sessions (ie, first to third sessions [the assessment phase]). Sexual distress was the main outcome, as measured with the Sexual Distress Scale-Revised. Results indicated that 54% (n = 376) of patients reported elevated sexual distress based on the questionnaire threshold score. Path analyses indicated an indirect effect in which higher dispositional mindfulness was associated with higher levels of sexual self-esteem, which in turn was associated with lower sexual distress. Results also highlighted that specific facets of mindfulness were related to higher sexual self-esteem (ie, describing, and nonreacting) and lower sexual distress (ie, nonjudgment and acting with awareness). The integrative model explained 23% of the variance of sexual distress scores. Findings suggest that addressing specifically sexual self-esteem and mindfulness may represent relevant clinical avenues to reduce sexual distress among sex therapy patients. Strengths of this study include the novel examination of the role of sexual self-esteem in the link between mindfulness disposition and sexual distress in a large clinical sample of patients seeking sex therapy. Limitations includes reliance on patient self-report and a cross-sectional design that limit conclusion regarding causality. This study makes a valuable contribution to the existing body of research highlighting the pivotal roles of sexual self-esteem in the link between dispositional mindfulness and reduced sexual distress among adults undergoing sex therapy, allowing us to identify potential targets of intervention.

CRISPR-mediated megabase-scale transgene de-duplication to generate a functional single-copy full-length humanized DMD mouse model

BackgroundThe development of sequence-specific precision treatments like CRISPR gene editing therapies for Duchenne muscular dystrophy (DMD) requires sequence humanized animal models to enable the direct clinical translation of tested strategies. The current available integrated transgenic mouse model containing the full-length human DMD gene, Tg(DMD)72Thoen/J (hDMDTg), has been found to have two copies of the transgene per locus in a tail-to-tail orientation, which does not accurately simulate the true (single) copy number of the DMD gene. This duplication also complicates analysis when testing CRISPR therapy editing outcomes, as large genetic alterations and rearrangements can occur between the cut sites on the two transgenes.ResultsTo address this, we performed long read nanopore sequencing on hDMDTg mice to better understand the structure of the duplicated transgenes. Following that, we performed a megabase-scale deletion of one of the transgenes by CRISPR zygotic microinjection to generate a single-copy, full-length, humanized DMD transgenic mouse model (hDMDTgSc). Functional, molecular, and histological characterisation shows that the single remaining human transgene retains its function and rescues the dystrophic phenotype caused by endogenous murine Dmd knockout.ConclusionsOur unique hDMDTgSc mouse model simulates the true copy number of the DMD gene, and can potentially be used for the further generation of DMD disease models that would be better suited for the pre-clinical assessment and development of sequence specific CRISPR therapies.

Clinical Health Psychology Perspectives in Diabetes Care: A Retrospective Cohort Study Examining the Role of Depression in Adherence to Visits and Examinations in Type 2 Diabetes Management

Background: Depression in type 2 diabetes mellitus (T2DM) impacts glycemic control and complications. This study examines the influence of depression on compliance with recommended annual diabetes assessments in patients within the Local Healthcare Authority of Romagna. From a clinical health psychology perspective, understanding how depression influences patients’ engagement in managing their conditions is crucial. This insight can help improve healthcare services by ensuring they address mental health needs and thereby enhance treatment effectiveness and overall patient outcomes. Methods: This retrospective cohort study included residents of Romagna with incident T2DM from 2015 to 2017, followed from 1 January 2018 to 31 December 2022. Depression was identified via hospital discharge records or antidepressant prescriptions. Adherence to diabetes care guidelines was measured using the Guideline Composite Indicator (GCI). Results: The study included 13,285 patients, with a mean age of 61.1 years. Prevalence of post-diabetes depression increased from 3.0% in 2018 to 8.9% in 2022. Initial analyses showed higher GCI rates among patients with depression. However, propensity-score adjustment revealed that by 2021–2022, patients with pre-diabetes depression had 5% lower compliance rates (p-value ≤ 0.05). Older adults with depression had reduced adherence, while younger adults with post-diabetes depression had higher adherence rates. Conclusions: Depression significantly affects adherence to diabetes care guidelines in T2DM patients, particularly among older adults. Integrated care models addressing both diabetes and depression are crucial for improving health outcomes.

Numerical investigation of arc characteristics and metal properties in ELAMF-assisted WAAM with wire retraction

In this study, a multi-physics integrated model of wire arc additive manufacturing (WAAM) with wire retraction and external longitudinal alternating magnetic field (ELAMF) assistance is proposed and validated, and the effect of ELAMF on the arc plasma characteristics and metal properties are systematically and quantitatively investigated. The model comprehensively takes the arc plasma heating, wire dynamic retraction, droplet transfer, the formation and diffusion of metal vapor, the melting and solidification of molten metal, and the stirring effect of ELAMF into account. The simulated results show that ELAMF has compressed the arc morphology, and decreased the temperature, potential, current density and static pressure, which are most pronounced when the wire is at an elevated position and the transient current is at its peak phase. Meanwhile, the formation of low-temperature and low-velocity cavities in the center of arc column are promoted by ELAMF, consequently diminishing the energy transferred from the arc plasma to molten pool through thermal conduction and mitigating the squeezing of the arc plasma on the surface of molten pool. The results also demonstrate that the ELAMF has reduced the temperature gradient of liquid metal inside the molten pool, and intensified the forced convection for the occurrence of multiple circulations.

A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodules

Accurate, non-invasive, and cost-effective tools are needed to assist pulmonary nodule diagnosis and management due to increasing detection by low-dose computed tomography (LDCT). We perform genome-wide methylation sequencing on malignant and non-malignant lung tissues and designed a panel of 263 differential DNA methylation regions, which is used for targeted methylation sequencing on blood cell-free DNA (cfDNA) in two prospectively collected and retrospectively analyzed multicenter cohorts. We develop and optimize an integrative model for risk stratification of pulmonary nodules based on 40 cfDNA methylation biomarkers, age, and five simple computed tomography (CT) imaging features using machine learning approaches and validate its good performance in two cohorts. Using the two-threshold strategy can effectively reduce unnecessary invasive surgeries, overtreatment costs, and injury for patients with benign nodules while advising immediate treatment for patients with lung cancer, which can potentially improve the overall diagnosis of lung cancer following LDCT/CT screening.

Groups and Subgroups in Autism Spectrum Disorder (ASD) Considering an Advanced Integrative Model (AIM).

Autism spectrum disorder (ASD) is related to social communication difficulties, repetitive behaviors, and highly restricted interests beginning early in life. Currently, ASD is more diagnosed than in the past, and new models are needed. The Advanced Integrative Model (AIM) is a new model in which genes and concomitant medical problems to diagnosis (CMPD) and the impact of their rigorous and adequate treatment are considered. The role of a dynamic encephalopathy from which the individual response, susceptibilities in the brain and outside the brain, gut barrier and brain-blood-barrier permeabilities, and the plastic nature of the brain is proposed as a tool for diagnosis. The concomitant medical problems (CMP) are those at and outside the brain. The individual response to treatments of CMP is analyzed. The AIM allows for classification into 3 main groups and 24 subgroups. The groups and subgroups in ASD are obtained taking into account CMPD treatments and individual response.

An in vitro study of a combined patient-specific device for safe and accurate insertion of infrazygomatic crest miniscrews.

To develop and assess the efficacy of a novel combined patient-specific device (CPSD) for the accurate and safe insertion of infrazygomatic crest miniscrews in orthodontic procedures. Twenty-eight miniscrews were placed in the infrazygomatic crest region of 28 cadaver maxillae using the direct manual method (n = 14) or the CPSD (n = 14) based on preset trajectories. The CPSD, designed based on the integration model, included a positioning guide, an insertion guide, and a depth-limiting groove. Deviations in the insertion site, tip location, insertion angle, and biting depth between the preset and real insertion trajectories were calculated to evaluate the accuracy of miniscrew insertion. Classification frequencies of root proximity, sinus penetration depth, and biting depth of the miniscrew after insertion were also calculated to evaluate the safety of miniscrew insertion. Regarding evaluation of accuracy, significant differences were observed in the deviation values of the insertion site, tip location, insertion angle, and biting depth between the CPSD and freehand groups (P = .001, P < .001, P < .001, P = .039, respectively). Regarding evaluation of safety, a significant difference was observed in the classification frequencies of root proximity between the two groups (P = .016). Compared with manual insertion, CPSD could be a preferred method for safe and accurate insertion of infrazygomatic crest miniscrews for orthodontists.

Health service utilization, substance use treatment response, and death in patients with opioid use disorder and comorbid hepatitis C findings from prospective cohort study with administrative database linkage

BackgroundAmong patients with opioid use disorder (OUD), high rates of overdose and death have been reported in subgroups with Hepatitis C Virus (HCV). Evidence on the comorbid effect of HCV on clinical and substance use trajectories has been limited by small sample sizes, short follow-up, and heavy reliance on administrative data which lacks granularity on important prognostic factors. Additionally, few studies include populations on substance use treatment. AimTo establish the impact of HCV exposure (antibody positivity) on health care utilization patterns, substance use treatment response, and death in a cohort of patients with OUD on opioid agonist therapy (OAT). MethodsThis multi-center prospective cohort study recruited adult patients with OUD on OAT from 57 substance use treatment centers in Ontario, Canada. The study collected substance use outcomes, and classified patients with ≥50 % positive opioid urine screens over one year of follow-up as having poor treatment response. Additional data obtained via linkage with ICES administrative databases evaluated the relationship between HCV status, healthcare service utilization, and death over 3 years of follow-up. Multiple logistic regression models established the adjusted impact of HCV on various outcomes. ResultsAmong recruited participants (n = 3430), 44.10 % were female with a mean age of 38.64 years (Standard deviation: 10.96). HCV was prevalent in 10.6 % of the cohort (n = 365). Methadone was used most often (83.9 %, n = 2876), followed by sublingual buprenorphine (16.2 %, n = 554). Over the three-year follow-up, 5.3 % of patients died (n = 181). Unadjusted results reveal rates of hospitalization (all-cause, mental-health related, critical care) and emergency department visits (mental health-related), were significantly higher among HCV patients. Associations diminished in adjusted models. Active injection drug use exhibited the highest predictive risk for all outcomes. ConclusionA high degree of acute physical and mental illness and its resulting health service utilization burden is concentrated among patients with OUD and comorbid HCV. Future research should explore the role for targeted interventions and how best to implement integrated healthcare models to better address the complex health needs of HCV populations who inject drugs.

Optimization analysis of vibration reduction for aeroengine multistage blade-disk system

In order to reduce the vibration localization of multistage blade-disk system of aeroengine compressor, the integral model and substructure model of multistage blade-disk system are established by using substructure modal synthesis method, and the dynamic characteristics of two models are analyzed and the accuracy of the substructure model is verified by comparison. Based on the substructure model, two optimization algorithms of the random wear mass and the snake optimization are proposed. The results show that the vibration amplitudes of the two models are in good agreement in the first 200 modes, and the substructure model meets the requirement of analysis accuracy. Both optimization algorithms can effectively reduce the degree of the vibration localization of the mistuned blade-disk system. The random wear mass algorithm can quickly reduce the amplitude of the blade. The snake optimization algorithm can find the global optimal solution with enough iterations. The results show that the maximum vibration amplitude and the vibration localization factor after optimization are reduced by 5.72 % and 12.0 % respectively by using the random wear mass algorithm, and that of 9.13 % and 16.7 % respectively by using the snake optimization algorithm. The analysis method presented in this paper takes into account the analysis efficiency and analysis precision, it can be used for dynamic analysis and vibration reduction optimization of large power machinery such as aeroengine and gas turbine, and provides a basis for further improving the reliability and service life of aircraft.