Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Trends and hotspots in gastrointestinal neoplasms risk assessment: A bibliometric analysis from 1984 to 2022

BACKGROUND Gastrointestinal neoplasm(GN)significantly impact the global cancer burden and mortality,necessitating early detection and treatment.Understanding the evolution and current state of research in this field is vital.AIM To conducts a comprehensive bibliometric analysis of publications from 1984 to 2022 to elucidate the trends and hotspots in the GN risk assessment research,focusing on key contributors,institutions,and thematic evolution.METHODS This study conducted a bibliometric analysis of data from the Web of Science Core Collection database using the"bibliometrix"R package,VOSviewer,and CiteSpace.The analysis focused on the distribution of publications,contributions by institutions and countries,and trends in keywords.The methods included data synthesis,network analysis,and visualization of international collaboration networks.RESULTS This analysis of 1371 articles on GN risk assessment revealed a notable evolution in terms of research focus and collaboration.It highlights the United States'critical role in advancing this field,with significant contributions from institutions such as Brigham and Women's Hospital and the National Cancer Institute.The last five years,substantial advancements have been made,representing nearly 45%of the examined literature.Publication rates have dramatically increased,from 20 articles in 2002 to 112 in 2022,reflecting intensified research efforts.This study underscores a growing trend toward interdisciplinary and international collaboration,with the Journal of Clinical Oncology standing out as a key publication outlet.This shift toward more comprehensive and collaborative research methods marks a significant step in addressing GN risks.CONCLUSION This study underscores advancements in GN risk assessment through genetic analyses and machine learning and reveals significant geographical disparities in research emphasis.This calls for enhanced global collaboration and integration of artificial intelligence to improve cancer prevention and treatment accuracy,ultimately enhancing worldwide patient care.

Safety assessment of a novel marine multi-stress-tolerant yeast Meyerozyma guilliermondii GXDK6 according to phenotype and whole genome-sequencing analysis

The application of microorganisms as probiotics is limited due to lack of safety evaluation.Here,a novel multi-stress-tolerant yeast Meyerozyma guilliermondii GXDK6 with aroma-producing properties was identified from marine mangrove microorganisms.Its safety and probiotic properties were assessed in accordance with phenotype and whole-genome sequencing analysis.Results showed that the genes and phenotypic expression of related virulence,antibiotic resistance and retroelement were rarely found.Hyphal morphogenesis genes(SIT4,HOG1,SPA2,ERK1,ICL1,CST20,HSP104,TPS1,and RHO1)and phospholipase secretion gene(VPS4)were annotated.True hyphae and phospholipase were absent.Only one retroelement(Tad1-65_BG)was found.Major biogenic amines(BAs)encoding genes were absent,except for spermidine synthase(JA9_002594),spermine synthase(JA9_004690),and tyrosine decarboxylase(inx).The production of single BAs and total BAs was far below the food-defined thresholds.GXDK6 had no resistance to common antifungal drugs.Virulence enzymes,such as gelatinase,DNase,hemolytic,lecithinase,and thrombin were absent.Acute toxicity test with mice demonstrated that GXDK6 is safe.GXDK6 has a good reproduction ability in the simulation gastrointestinal tract.GXDK6 also has a strong antioxidant ability,β-glucosidase,and inulinase activity.To sum up,GXDK6 is considered as a safe probiotic for human consumption and food fermentation.

Aspect based sentiment analysis using multi-criteria decision-making and deep learning under COVID-19 pandemic in India

The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to stay within walls and become more addicted towards social networks.They express their emotions and sympathy via these online platforms.Thus,popular social media(Twitter and Facebook)have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues.We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases.The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus.India-specific COVID-19 tweets have been annotated,for analysing the sentiment of common public.To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35%for Lockdown and 83.33%for Unlock data set.The suggested method outperforms many of the contemporary approaches(long shortterm memory,Bi-directional long short-term memory,Gated Recurrent Unit etc.).This study highlights the public sentiment on lockdown and stepwise unlocks,imposed by the Indian Government on various aspects during the Corona outburst.

Multi-Criteria Group Decision-Making Method Based on an Improved Single-Valued Neutrosophic Hamacher Weighted Average Operator and Grey Relational Analysis

This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.

Three-dimensional pseudo-dynamic reliability analysis of seismic shield tunnel faces combined with sparse polynomial chaos expansion

To address the seismic face stability challenges encountered in urban and subsea tunnel construction,an efficient probabilistic analysis framework for shield tunnel faces under seismic conditions is proposed.Based on the upper-bound theory of limit analysis,an improved three-dimensional discrete deterministic mechanism,accounting for the heterogeneous nature of soil media,is formulated to evaluate seismic face stability.The metamodel of failure probabilistic assessments for seismic tunnel faces is constructed by integrating the sparse polynomial chaos expansion method(SPCE)with the modified pseudo-dynamic approach(MPD).The improved deterministic model is validated by comparing with published literature and numerical simulations results,and the SPCE-MPD metamodel is examined with the traditional MCS method.Based on the SPCE-MPD metamodels,the seismic effects on face failure probability and reliability index are presented and the global sensitivity analysis(GSA)is involved to reflect the influence order of seismic action parameters.Finally,the proposed approach is tested to be effective by a engineering case of the Chengdu outer ring tunnel.The results show that higher uncertainty of seismic response on face stability should be noticed in areas with intense earthquakes and variation of seismic wave velocity has the most profound influence on tunnel face stability.

Design & Test of an Advanced Web Security Analysis Tool (AWSAT)

Considering the escalating frequency and sophistication of cyber threats targeting web applications, this paper proposes the development of an automated web security analysis tool to address the accessibility gap for non-security professionals. This paper presents the design and implementation of an automated web security analysis tool, AWSAT, aimed at enabling individuals with limited security expertise to effectively assess and mitigate vulnerabilities in web applications. Leveraging advanced scanning techniques, the tool identifies common threats such as Cross-Site Scripting (XSS), SQL Injection, and Cross-Site Request Forgery (CSRF), providing detailed reports with actionable insights. By integrating sample payloads and reference study links, the tool facilitates informed decision-making in enhancing the security posture of web applications. Through its user-friendly interface and robust functionality, the tool aims to democratize web security practices, empowering a wider audience to proactively safeguard against cyber threats.

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

Item-Level Analysis of the Revised Occupational Therapy Fieldwork Performance Evaluation Applied in Practice

Competency-based assessments for healthcare professionals are critical for safe and effective client outcomes. Rehabilitation clinical skill competency assessments must be validated and revised to produce safe and skilled practitioners. The revised American Occupational Therapy Association (AOTA) Fieldwork Performance Evaluation (FWPE) instrument measures occupational therapy student performance to determine readiness for practice. The assessment includes thirty-seven competencies that address both profession specific clinical skills and general professional behavior skills. The objective of this study was to use Rasch methods to explore the use of the revised FWPE in actual fieldwork practice and to determine the instrument’s psychometric properties when separating the item components into two distinct subdomains: General Health Professions Competences and Occupational Therapy-Specific Competencies. Internal construct validity and test reliability were analyzed using data from 149 occupational therapy students after completing their initial Level II A fieldwork clinical internship. This study examined the item difficulty hierarchy, item fit, person-fit to model, person separation index, person separation reliability coefficient, strata, ceiling and floor effect, and unidimensionality of the FWPE instrument as a whole and as two separate domains. With the exception of not meeting the criteria for unidimensionality, the full FWPE instrument and the Occupational Therapy-Specific Competencies subdomain showed acceptable item-level psychometrics for reliability and precision. While the General Health Professions Competencies subdomain showed good item-level psychometrics, it was below the criterion for reliability and only separated the sample into two strata. Results support the validity, reliability, and clinical use of the revised FWPE full instrument and the Occupational Therapy-Specific Competencies subdomain to measure entry-level clinical skill competencies in practice.

Assessment of hindlimb motor recovery affer severe thoracic spinal cord injury in rats: classification of CatWalk XT■ gait analysis parameters

Assessment of locomotion recovery in preclinical studies of experimental spinal cord injury remains challenging. We studied the CatWalk XT■gait analysis for evaluating hindlimb functional recovery in a widely used and clinically relevant thoracic contusion/compression spinal cord injury model in rats. Rats were randomly assigned to either a T9 spinal cord injury or sham laminectomy. Locomotion recovery was assessed using the Basso, Beattie, and Bresnahan open field rating scale and the CatWalk XT■gait analysis. To determine the potential bias from weight changes, corrected hindlimb(H) values(divided by the unaffected forelimb(F) values) were calculated. Six weeks after injury, cyst formation, astrogliosis, and the deposition of chondroitin sulfate glycosaminoglycans were assessed by immunohistochemistry staining. Compared with the baseline, a significant spontaneous recovery could be observed in the CatWalk XT■parameters max intensity, mean intensity, max intensity at%, and max contact mean intensity from 4 weeks after injury onwards. Of note, corrected values(H/F) of CatWalk XT■parameters showed a significantly less vulnerability to the weight changes than absolute values, specifically in static parameters. The corrected CatWalk XT■parameters were positively correlated with the Basso, Beattie, and Bresnahan rating scale scores, cyst formation, the immunointensity of astrogliosis and chondroitin sulfate glycosaminoglycan deposition. The CatWalk XT■gait analysis and especially its static parameters, therefore, seem to be highly useful in assessing spontaneous recovery of hindlimb function after severe thoracic spinal cord injury. Because many CatWalk XT■parameters of the hindlimbs seem to be affected by body weight changes, using their corrected values might be a valuable option to improve this dependency.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

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.

Histological Assessment and Transcriptome Analysis Provide Insights into the Toxic Effects of Perfluorooctanoic Acid to Juvenile Half Smooth Tongue Sole Cynoglossus semilaevis

Perfluorooctanoic acid(PFOA)is a widespread synthetic persistent organic pollutant that may enrich along the food chain and affect the growth,development,reproduction,and lipid metabolism of aquatic organisms,particularly the benthic organisms.How-ever,the toxic effects of PFOA on the half-smooth tongue sole Cynoglossus semilaevis,a commercial benthic fish in China,have rarely been reported.Because juvenile fish are sensitive to environmental pollutants,in the present study,histological assessment and tran-scriptome sequencing were performed to determine the short-term impact of PFOA on juvenile half-smooth tongue soles.Histologi-cal analysis showed that PFOA exposure caused hepatocyte rupture,intestinal villi breakage,increased goblet cell count,and brain ab-normal.Transcriptome results showed that some interesting signaling pathways,such as glycolysis/gluconeogenesis,PPAR signaling pathway and GABAergic synapse signaling pathway,were enriched after PFOA exposure.In addition,some metabolic,immune and neural genes were differentially expressed,which including ependymin,hbb1-like and gad 1,and they were up-regulated after 14 days of exposure.Transcriptome results also indicated that half-smooth tongue sole might improve energy metabolism in response to PFOA toxicity after 7 days of exposure.These findings provide a basis for studying the ecological effects of PFOA on marine benthic fishes.

Retrospective Analysis of External Quality Assessment Data of Humoral (Except Feces) Morphology in Guangxi from 2010 to 2022

[Objectives] The study aims to improve the ability of inspectors to recognize humoral morphology and provide data reference for the improvement of EQA work of humoral morphology by Guangxi Clinical Laboratory Center. [Methods] A retrospective analysis was made on the EQA of humoral morphology by Guangxi Clinical Laboratory Center from 2010 to 2022, and the number of participating laboratories, the rate of return, sample types and maps of EQA of humoral morphology such as urine sediment, vaginal secretions and so on(except feces), and the reasons for the high error rate of the results of the participating laboratories were analyzed. [Results] The number of laboratories participating in the assessment of humoral morphology increased from 98 in 2010 to 371 in 2022. Except for 2011(90.98%), the rate of return was more than 94%, and the highest rate of return was up to 100%. A total of 119 pictures of EQA of humoral morphology were studied, including 101 urine sediment smears, 13 vaginal secretions smears and 5 other smears. The types of specimens were relatively comprehensive. The distribution of the maps was basically reasonable. The urinary sediment was mainly composed of crystalline salts, followed by tubes, and cells and fungi ranked third. The coverage was relatively complete. The error rate of return results from high to low were bacteria(error rate was equal to 40%), tubes and crystalline salts(error rate was close to 29%), and cells and fungi(error rate was about 14%). The main cases with high error rate of return results are as follows: the difference between different tubes was not clear, and the diversity of crystal morphology was not understood enough;the phase division of cells in the same system was wrong. [Conclusions] The analysis and summary of the reasons for the high error rate of the data and results of Guangxi's EQA of humoral morphology is helpful for laboratory physicians to improve their awareness of morphological examination and identify clearly the error type and blurred concept, and lays a foundation for Guangxi Clinical Laboratory Center to carry out EQA of humoral morphology more specifically.

Behavior analysis and formative assessments in online oral medicine education during the COVID-19 pandemic

BACKGROUND During the coronavirus disease 2019(COVID-19)pandemic,traditional teaching methods were disrupted and online teaching became a new topic in education reform and informatization.In this context,it is important to investigate the necessity and effectiveness of online teaching methods for medical students.This study explored stomatology education in China to evaluate the development and challenges facing the field using massive open online courses(MOOCs)for oral medicine education during the pandemic.AIM To investigate the current situation and challenges facing stomatology education in China,and to assess the necessity and effectiveness of online teaching methods among medical students.METHODS Online courses were developed and offered on personal computers and mobile terminals.Behavioral analysis and formative assessments were conducted to evaluate the learning status of students.RESULTS The results showed that most learners had already completed MOOCs and achieved better results.Course behavior analysis and student surveys indicated that students enjoyed the learning experience.However,the development of oral MOOCs during the COVID-19 pandemic faced significant challenges.CONCLUSION This study provides insights into the potential of using MOOCs to support online professional learning and future teaching innovation,but emphasizes the need for careful design and positive feedback to ensure their success.

Group decision-making method based on entropy and experts cluster analysis

According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

Approach of technical decision-making by element flow analysis and Monte-Carlo simulation of municipal solid waste stream

This paper deals with the procedure and methodology which can be used to select the optimal treatment and disposal technology of municipal solid waste （MSW）, and to provide practical and effective technical support to policy-making, on the basis of study on solid waste management status and development trend in China and abroad. Focusing on various treatment and disposal technologies and processes of MSW, this study established a Monte-Carlo mathematical model of cost minimization for MSW handling subjected to environmental constraints. A new method of element stream （such as C, H, O, N, S） analysis in combination with economic stream analysis of MSW was developed. By following the streams of different treatment processes consisting of various techniques from generation, separation, transfer, transport, treatment, recycling and disposal of the wastes, the element constitution as well as its economic distribution in terms of possibility functions was identified. Every technique step was evaluated economically. The Mont-Carlo method was then conducted for model calibration. Sensitivity analysis was also carried out to identify the most sensitive factors. Model calibration indicated that landfill with power generation of landfill gas was economically the optimal technology at the present stage under the condition of more than 58% of C, H, O, N, S going to landfill. Whether or not to generate electricity was the most sensitive factor. If landfilling cost increases, MSW separation treatment was recommended by screening first followed with incinerating partially and composting partially with residue landfilling. The possibility of incineration model selection as the optimal technology was affected by the city scale. For big cities and metropolitans with large MSW generation, possibility for constructing large-scale incineration facilities increases, whereas, for middle and small cities, the effectiveness of incinerating waste decreases.

Frequency Analysis on the Data of Field Fertilizer Efficiency Test and Fertilization Decision-making

To solve the problems of abnormal larger, abnormal lower or even negative of target yield and fertilizing amount recommended by part of non-typical fertilizer effect equations using agricultural experiments and statistical analysis software,Yangzhou analyzer（2.2）, regression analysis of Excel, which objected to local actual production, the study adopted the principle and method of basic knowledge and the frequency of using probability theory, and carried out statistical analysis on the rape field fertilizer experiment data by frequency analysis method, the rape yield after optimizing fertilizing amount was 1 732.4 kg/hm^2, the ranges of N, P and K optimal combinations were： N=210.36-149.64 kg/hm^2,P2O5=81.89-58.11 kg/hm^2, K2O=81.89-58.11 kg/hm^2,which was consistent with local actual production. This study was based on frequency analysis, using weighted average method to determine the production combinations of different yield objectives, hereinto, the combinations with high yield, high frequency of occurrence（dependable crop） and fertilizer-saving were viewed as the optimizing production measures, and they had the merits of increasing fertilization decision-making information, reducing or avoiding the risk of small probability event. The results of this study can solve the problem of abnormal values fertilizing amount and target yield recommended by non-typical fertilizer effect function, which did not accord with local actual production, caused by Yangzhou analyzer（2.2）, regression analysis of Excel, and DPS statistical analysis software. For the fertilizer effect function equation established by regression analysis which did not reach significance level using variance analysis, whether the method can be adapted to for carrying out fertilization decision-making, recommending optimization combinations of N, P and K fertilizers and yield under optimized fertilizing amount should be further researched in future working practice.

Decision-making approach by employing grey incidence analysis and group negotiation

For the problems of the consistency ranking of the group decision-making scheme,from the view of group negotiation and system coordination,the grey incidence analysis and Nash bargaining model are used to establish a consistency group decision-making method.First,the concepts of the consensus partial decision-making program and the consensus overall ideal decision-making program are defined,and then a multi-object optimization model is constructed based on the satisfaction maximization of group negotiation and deviation minimization of system coordination to determine the consensus partial decision-making program and the consensus overall ideal decision-making program.Moreover,the grey incidence analysis is exploited to measure the close degrees between them.Finally,a real case of the online product evaluation verifies the validity and rationality of the proposed model.