Current situation and influencing factors of classroom situationdeviant behavior of undergraduate nursing students in colleges oftraditional Chinese medicine

Objective: To investigate the current situation and influencing factors of classroom situation deviant behavior ofundergraduate nursing students in colleges of traditional Chinese medicine. Methods: Three hundred andeighty-two undergraduate nursing students in Tianjin University of Traditional Chinese Medicine were investigatedby general situation questionnaire, Classroom Situation Deviation Behavior questionnaire, Utrecht WorkEngagement Scale-Student and Mobile phone addiction index scale. Results: The scores of the ClassroomSituation Deviation Behavior questionnaire of nursing students were (46.04 ± 14.94). The results of multiple linearregression analysis showed that gender, academic ranking, family income (RMB/month), learning involvement andmobile phone dependence were the influencing factors, accounting for 32.9% of the total variation. Conclusion:The classroom situation deviant behavior of undergraduate nursing students in colleges of traditional Chinesemedicine is moderately upper-level. It is suggested that the management departments of colleges should strictlyenforce the classroom management system, improve the teaching level of teachers, guide students to develop goodlearning habits, and constantly stimulate students' learning enthusiasm in order to reduce the occurrence ofclassroom situation deviation behavior.

Efficacy and safety of perioperative therapy for locally resectable gastric cancer:A network meta-analysis of randomized clinical trials

BACKGROUND Gastric cancer(GC)is the fifth most commonly diagnosed malignancy worldwide,with over 1 million new cases per year,and the third leading cause of cancer-related death.AIM To determine the optimal perioperative treatment regimen for patients with locally resectable GC.METHODS A comprehensive literature search was conducted,focusing on phase II/III randomized controlled trials(RCTs)assessing perioperative chemotherapy and chemoradiotherapy in treating locally resectable GC.The R0 resection rate,overall survival(OS),disease-free survival(DFS),and incidence of grade 3 or higher nonsurgical severe adverse events(SAEs)associated with various perioperative regimens were analyzed.A Bayesian network meta-analysis was performed to compare treatment regimens and rank their efficacy.RESULTS Thirty RCTs involving 8346 patients were included in this study.Neoadjuvant XELOX plus neoadjuvant radiotherapy and neoadjuvant CF were found to significantly improve the R0 resection rate compared with surgery alone,and the former had the highest probability of being the most effective option in this context.Neoadjuvant plus adjuvant FLOT was associated with the highest probability of being the best regimen for improving OS.Owing to limited data,no definitive ranking could be determined for DFS.Considering nonsurgical SAEs,FLO has emerged as the safest treatment regimen.CONCLUSION This study provides valuable insights for clinicians when selecting perioperative treatment regimens for patients with locally resectable GC.Further studies are required to validate these findings.

Multifaceted role of microRNAs in gastric cancer stem cells: Mechanisms and potential biomarkers

MicroRNAs(miRNAs)have received much attention in the past decade as potential key epigenomic regulators of tumors and cancer stem cells(CSCs).The abnormal expression of miRNAs is responsible for different phenotypes of gastric cancer stem cells(GCSCs).Some specific miRNAs could be used as promising biomarkers and therapeutic targets for the identification of GCSCs.This review summarizes the coding process and biological functions of miRNAs and demon-strates their role and efficacy in gastric cancer(GC)metastasis,drug resistance,and apoptosis,especially in the regulatory mechanism of GCSCs.It shows that the overexpression of onco-miRNAs and silencing of tumor-suppressor miRNAs can play a role in promoting or inhibiting tumor metastasis,apart from the initial formation of GC.It also discusses the epigenetic regulation and potential clinical applications of miRNAs as well as the role of CSCs in the pathogenesis of GC.We believe that this review may help in designing novel therapeutic approaches for GC.

Evolutionary Safe Padé Approximation Scheme for Dynamical Study of Nonlinear Cervical Human Papilloma Virus Infection Model

This study proposes a structure-preserving evolutionary framework to find a semi-analytical approximate solution for a nonlinear cervical cancer epidemic(CCE)model.The underlying CCE model lacks a closed-form exact solution.Numerical solutions obtained through traditional finite difference schemes do not ensure the preservation of the model’s necessary properties,such as positivity,boundedness,and feasibility.Therefore,the development of structure-preserving semi-analytical approaches is always necessary.This research introduces an intelligently supervised computational paradigm to solve the underlying CCE model’s physical properties by formulating an equivalent unconstrained optimization problem.Singularity-free safe Padérational functions approximate the mathematical shape of state variables,while the model’s physical requirements are treated as problem constraints.The primary model of the governing differential equations is imposed to minimize the error between approximate solutions.An evolutionary algorithm,the Genetic Algorithm with Multi-Parent Crossover(GA-MPC),executes the optimization task.The resulting method is the Evolutionary Safe PadéApproximation(ESPA)scheme.The proof of unconditional convergence of the ESPA scheme on the CCE model is supported by numerical simulations.The performance of the ESPA scheme on the CCE model is thoroughly investigated by considering various orders of non-singular Padéapproximants.

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.

Reform and Practice of an Engineering Postgraduate Training Pattern in an Open-Ended Base:Taking Foshan Base as an Example

The flawed engineering practice is considered the main factor that is affecting to the development quality of engineering postgraduates.Taking Foshan Base as an example,this paper has analyzed the operational pattern,practice teaching model,and internal governance system of the open-ended base as a new system for engineering practice and proposed several suggestions for the reformation of engineering postgraduates based on the construction effect.

Effectiveness and safety of traditional Chinese medicine decoction for diabetic gastroparesis:A network meta-analysis

BACKGROUND Diabetic gastroparesis(DGP)is a prevalent complication of diabetes that impairs people's quality of life and places a significant financial burden on them.The gastrointestinal symptoms of DGP patients can be improved by several Traditional Chinese Medicine(TCM)decoctions that have been shown to be effective in treating the disease.There are still many unanswered questions regarding the identification of appropriate therapeutic agents for the treatment of DGP in clinical practice.AIM To analyze the efficacy of several TCM decoctions in the treatment of DGP using Bayesian network meta-analysis for reference.METHODS PubMed,EMBASE,Cochrane Library,Web of Science,China National Knowledge Infrastructure,The China Biology Medicine DVD,Wanfang,and CQVIP were searched from inception to September 17,2022,to collect randomized controlled trials(RCTs)about TCM decoctions for DGP.Clinical effects and symptom scores were the primary outcomes.Additionally,we assessed motilin(MOT),somatostatin(SS),gastrin(GAS),gastric emptying rate,gastric emptying time,and adverse drug events as secondary outcomes.RESULTS A total of 67 eligible RCTs involving 4790 DGP patients and 7 TCM decoctions were included.The results of network meta-analysis(NMA)and surface under the cumulative ranking curve showed that with western medicine(WM)as a common control,the Banxia Xiexin Decoction(BXXD)+WM was most effective in clinical effects and enhancing early satiety scores;the Simo decoction(SMD)+WM was most effective in improving nausea and vomiting scores and anorexia scores,bloating scores;the Chaishao Liujunzi Decoction(CSLJD)was most effective in MOT,the Zhishi Xiaopi Decoction(ZSXPD)was most effective in SS and upgrading emptying rate;the Jianpi Xiaozhi Decoction was most effective in GAS;the CSLJD+WM was most effective in improving gastric emptying time.CONCLUSION These NMA results suggest that the BXXD+WM and SMD+WM may be one of the potential optimal treatments.Due to various limitations,further large-sample,double-blind,multi-center randomized RCTs are needed.

Eosinophilic fasciitis difficult to differentiate from scleroderma:A case report

BACKGROUND Eosinophilic fasciitis(EF)is a rare connective tissue disease that can cause swelling and sclerosis of the extremities,and special attention is needed to differentiate EF from systemic sclerosis.Misdiagnosis or omission markedly delays treatment of EF,and severe skin sclerosis in advanced stages can cause joint contracture and tendon retraction,worsening the patient's prognosis and quality of life.CASE SUMMARY We report a case of EF in a young woman diagnosed by tissue biopsy,confirming the difficulty of differential diagnosis with scleroderma.CONCLUSION Focusing on skin manifestations,completing tissue biopsy and radiography can help diagnose EF effectively.Clinicians should enhance their understanding of the differences between EF and scleroderma,and early diagnosis and standardized treatment can improve the prognosis of patients with EF.

Stochastic Analysis for the Dynamics of a Poliovirus Epidemic Model

Most developing countries such as Afghanistan,Pakistan,India,Bangladesh,and many more are still fighting against poliovirus.According to the World Health Organization,approximately eighteen million people have been infected with poliovirus in the last two decades.In Asia,still,some countries are suffering from the virus.The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied.Some basic properties of the deterministic model are studied,equilibria,local stability around the stead states,and reproduction number.Euler Maruyama,stochastic Euler,and stochastic Runge-Kutta study the behavior of complex stochastic differential equations.The main target of this study is to develop a nonstandard computational method that restores dynamical features like positivity,boundedness,and dynamical consistency.Unfortunately,the existing methods failed to fix the actual behavior of the disease.The comparison of the proposed approach with existing methods is investigated.

Alphabet-Level Indian Sign Language Translation to Text Using Hybrid-AO Thresholding with CNN

Sign language is used as a communication medium in the field of trade,defence,and in deaf-mute communities worldwide.Over the last few decades,research in the domain of translation of sign language has grown and become more challenging.This necessitates the development of a Sign Language Translation System(SLTS)to provide effective communication in different research domains.In this paper,novel Hybrid Adaptive Gaussian Thresholding with Otsu Algorithm(Hybrid-AO)for image segmentation is proposed for the translation of alphabet-level Indian Sign Language(ISLTS)with a 5-layer Convolution Neural Network(CNN).The focus of this paper is to analyze various image segmentation(Canny Edge Detection,Simple Thresholding,and Hybrid-AO),pooling approaches(Max,Average,and Global Average Pooling),and activation functions(ReLU,Leaky ReLU,and ELU).5-layer CNN with Max pooling,Leaky ReLU activation function,and Hybrid-AO(5MXLR-HAO)have outperformed other frameworks.An open-access dataset of ISL alphabets with approx.31 K images of 26 classes have been used to train and test the model.The proposed framework has been developed for translating alphabet-level Indian Sign Language into text.The proposed framework attains 98.95%training accuracy,98.05%validation accuracy,and 0.0721 training loss and 0.1021 validation loss and the perfor-mance of the proposed system outperforms other existing systems.

Effect of Measurement Error on the Multivariate CUSUM Control Chart for Compositional Data

Control charts(CCs)are one of the main tools in Statistical Process Control that have been widely adopted in manufacturing sectors as an effective strategy for malfunction detection throughout the previous decades.Measurement errors(M.E’s)are involved in the quality characteristic of interest,which can effect the CC’s performance.The authors explored the impact of a linearmodel with additive covariate M.E on the multivariate cumulative sum(CUSUM)CC for a specific kind of data known as compositional data(CoDa).The average run length(ARL)is used to assess the performance of the proposed chart.The results indicate that M.E’s significantly affects themultivariate CUSUM-CoDaCCs.The authors haveused theMarkov chainmethod to study the impact of different involved parameters using six different cases for the variance-covariance matrix(VCM)(i.e.,uncorrelated with equal variances,uncorrelated with unequal variances,positively correlated with equal variances,positively correlated with unequal variances,negatively correlatedwith equal variances and negatively correlated with unequal variances).The authors concluded that the error VCM has a negative impact on the performance of themultivariate CUSUM-CoDa CC,as the ARL increases with an increase in the value of the error VCM.The subgroup size m and powering operator b positively impact the proposed CC,as the ARL decreases with an increase in m or b.The number of variables p also has a negative impact on the performance of the proposed CC,as the values of ARL increase with an increase in p.For the implementation of the proposal,two illustrated examples have been reported formultivariate CUSUM-CoDaCCs inthe presence ofM.E’s.Onedealswith themanufacturingprocessof uncoated aspirin tablets,and the other is based on monitoring the machines involved in the muesli manufacturing process.

Ranked-Set Sampling Based Distribution Free Control Chart with Application in CSTR Process

Nonparametric(distribution-free)control charts have been introduced in recent years when quality characteristics do not follow a specific distribution.When the sample selection is prohibitively expensive,we prefer ranked-set sampling over simple random sampling because ranked set sampling-based control charts outperform simple random sampling-based control charts.In this study,we proposed a nonparametric homogeneously weighted moving average based on theWilcoxon signed-rank test with ranked set sampling(NPHWMARSS)control chart for detecting shifts in the process location of a continuous and symmetric distribution.Monte Carlo simulations are used to obtain the run length characteristics to evaluate the performance of the proposed NPHWMARSS control chart.The proposed NPHWMARSS control chart’s performance is compared to that of parametric and nonparametric control charts.These control charts include the exponentially weighted moving average(EWMA)control chart,Wilcoxon signed-rank with simple random sampling based the nonparametric EWMA control chart,the nonparametric EWMA sign control chart,Wilcoxon signed-rank with ranked set sampling-based the nonparametric EWMA control chart,and the homogeneously weighted moving average control charts.The findings show that the proposed NPHWMARSS control chart performs better than its competitors,particularly for the small shifts.Finally,an example is presented to demonstrate how the proposed scheme can be implemented practically.

Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

The application of fuzzy theory is vital in all scientific disciplines.The construction of mathematical models with fuzziness is little studied in the literature.With this in mind and for a better understanding of the disease,an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classicalmodel ofmalaria transmission.The parametersβandδ,being function of the malaria virus load,are considered fuzzy numbers.Three steady states and the reproduction number of the model are analyzed in fuzzy senses.A numerical technique is developed in a fuzzy environment to solve the studied model,which retains essential properties such as positivity and dynamic consistency.Moreover,numerical simulations are carried out to illustrate the analytical results of the developed technique.Unlike most of the classical methods in the literature,the proposed approach converges unconditionally and can be considered a reliable tool for studying malaria disease dynamics.

Computational Investigation of Hand Foot Mouth Disease Dynamics with Fuzziness

The first major outbreak of the severely complicated hand,foot and mouth disease(HFMD),primarily caused by enterovirus 71,was reported in Taiwan in 1998.HFMD surveillance is needed to assess the spread of HFMD.The parameters we use in mathematical models are usually classical mathematical parameters,called crisp parameters,which are taken for granted.But any biological or physical phenomenon is best explained by uncertainty.To represent a realistic situation in any mathematical model,fuzzy parameters can be very useful.Many articles have been published on how to control and prevent HFMD from the perspective of public health and statistical modeling.However,few works use fuzzy theory in building models to simulateHFMDdynamics.In this context,we examined anHFMD model with fuzzy parameters.A Non Standard Finite Difference(NSFD)scheme is developed to solve the model.The developed technique retains essential properties such as positivity and dynamic consistency.Numerical simulations are presented to support the analytical results.The convergence and consistency of the proposed method are also discussed.The proposed method converges unconditionally while the many classical methods in the literature do not possess this property.In this regard,our proposed method can be considered as a reliable tool for studying the dynamics of HFMD.

New Trends in Fuzzy Modeling Through Numerical Techniques

Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica.It is spread through person-toperson contact or by eating or drinking food or water contaminated with feces.Its transmission rate depends on the number of cysts present in the environment.The traditional models assumed a homogeneous and contradictory transmission with reality.The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics.The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory.In this context,a fuzzy SEIR Amoebiasis disease model is considered in this study.The equilibrium analysis and reproductive number are studied with fuzziness.Two numerical schemes forward Euler method and a nonstandard finite difference(NSFD)approach,are developed for the learned model,and the results of numerical simulations are presented.The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease despite the uncertainty and heterogeneity.Moreover,the obtained method generates plausible predictions that regulators can use to support decision-making to design and develop control strategies.

Numerical Analysis for the Effect of Irresponsible Immigrants on HIV/AIDS Dynamics

The human immunodeficiency viruses are two species of Lentivirus that infect humans.Over time,they cause acquired immunodeficiency syndrome,a condition in which progressive immune system failure allows life-threatening opportunistic infections and cancers to thrive.Human immunodeficiency virus infection came from a type of chimpanzee in Central Africa.Studies show that immunodeficiency viruses may have jumped from chimpanzees to humans as far back as the late 1800s.Over decades,human immunodeficiency viruses slowly spread across Africa and later into other parts of the world.The Susceptible-Infected-Recovered(SIR)models are significant in studying disease dynamics.In this paper,we have studied the effect of irresponsible immigrants on HIV/AIDS dynamics by formulating and considering different methods.Euler,Runge Kutta,and a Non-standardfinite difference(NSFD)method are developed for the same problem.Numerical experiments are performed at disease-free and endemic equilibria points at different time step sizes‘ℎ’.The results reveal that,unlike Euler and Runge Kutta,which fail for large time step sizes,the proposed Non-standardfinite difference(NSFD)method gives a convergence solution for any time step size.Our proposed numerical method is bounded,dynamically con-sistent,and preserves the positivity of the continuous solution,which are essential requirements when modeling a prevalent disease.

New Trends in the Modeling of Diseases Through Computational Techniques

The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent performance.The handling strategies of real-world problems are artificial neural networks(ANN),evolutionary computing(EC),and many more.An estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually,with only 25%to 45%reported to the World Health Organization(WHO).It remains one of the top parasitic diseases with outbreak and mortality potential.In 2020,more than ninety percent of new cases reported to World Health Organization(WHO)occurred in ten countries:Brazil,China,Ethiopia,Eritrea,India,Kenya,Somalia,South Sudan,Sudan,and Yemen.The transmission of visceral leishmaniasis is studied dynamically and numerically.The study included positivity,boundedness,equilibria,reproduction number,and local stability of the model in the dynamical analysis.Some detailed methods like Runge Kutta and Euler depend on time steps and violate the physical relevance of the disease.They produce negative and unbounded results,so in disease dynamics,such developments have no biological significance;in other words,these results are meaningless.But the implicit nonstandard finite difference method does not depend on time step,positive,bounded,dynamic and consistent.All the computational techniques and their results were compared using computer simulations.

Modeling of Computer Virus Propagation with Fuzzy Parameters

Typically,a computer has infectivity as soon as it is infected.It is a reality that no antivirus programming can identify and eliminate all kinds of viruses,suggesting that infections would persevere on the Internet.To understand the dynamics of the virus propagation in a better way,a computer virus spread model with fuzzy parameters is presented in this work.It is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity,which depends on the quantity of virus.Considering this,the parametersβandγbeing functions of the computer virus load,are considered fuzzy numbers.Using fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical models.The essential features of the model,like reproduction number and equilibrium analysis,are discussed in fuzzy senses.Moreover,with fuzziness,two numerical methods,the forward Euler technique,and a nonstandard finite difference(NSFD)scheme,respectively,are developed and analyzed.In the evidence of the numerical simulations,the proposed NSFD method preserves the main features of the dynamic system.It can be considered a reliable tool to predict such types of solutions.

Computational Analysis for Computer Network Model with Fuzziness

A susceptible,exposed,infectious,quarantined and recovered(SEIQR)model with fuzzy parameters is studied in this work.Fuzziness in the model arises due to the different degrees of susceptibility,exposure,infectivity,quarantine and recovery among the computers under consideration due to the different sizes,models,spare parts,the surrounding environments of these PCs and many other factors like the resistance capacity of the individual PC against the virus,etc.Each individual PC has a different degree of infectivity and resis-tance against infection.In this scenario,the fuzzy model has richer dynamics than its classical counterpart in epidemiology.The reproduction number of the developed model is studied and the equilibrium analysis is performed.Two different techniques are employed to solve the model numerically.Numerical simulations are performed and the obtained results are compared.Positivity and convergence are maintained by the suggested technique which are the main features of the epidemic models.

Optimization of Coronavirus Pandemic Model Through Artificial Intelligence

Artificial intelligence is demonstrated by machines,unlike the natural intelligence displayed by animals,including humans.Artificial intelligence research has been defined as the field of study of intelligent agents,which refers to any system that perceives its environment and takes actions that maximize its chance of achieving its goals.The techniques of intelligent computing solve many applications of mathematical modeling.The researchworkwas designed via a particularmethod of artificial neural networks to solve the mathematical model of coronavirus.The representation of the mathematical model is made via systems of nonlinear ordinary differential equations.These differential equations are established by collecting the susceptible,the exposed,the symptomatic,super spreaders,infection with asymptomatic,hospitalized,recovery,and fatality classes.The generation of the coronavirus model’s dataset is exploited by the strength of the explicit Runge Kutta method for different countries like India,Pakistan,Italy,and many more.The generated dataset is approximately used for training,validation,and testing processes for each cyclic update in Bayesian Regularization Backpropagation for the numerical treatment of the dynamics of the desired model.The performance and effectiveness of the designed methodology are checked through mean squared error,error histograms,numerical solutions,absolute error,and regression analysis.