Cervical cancer prevention in China: where are we now, and what's next?

Cervical cancer(CC) epidemiology CC, the fourth most frequently diagnosed malignancy in women worldwide, is a major global health challenge, particularly in low-resource regions. Approximately 88.1% of the 604,000 CC new cases occurred in low-and middle-income countries in 2020, and more than 90% of the 342,000 CC deaths occurred in low-and middle-income countries in 2020~1.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Recent advances in promising drugs for primary prevention of gastroesophageal variceal bleeding with cirrhotic portal hypertension

Background:Gastroesophageal variceal bleeding is one of the most severe complications of patients with cirrhosis.Although primary prevention drugs,including non-selectiveβ-blockers,have effectively reduced the incidence of bleeding,their efficacy is limited due to side effects and related contraindications.With recent advances in precision medicine,precise drug treatment provides better treatment efficacy.Data sources:Literature search was conducted in PubMed,MEDLINE and Web of Science for relevant articles published up to May 2022.Information on clinical trials was obtained from https://clinicaltrials.gov/and http://www.chictr.org.cn/.Results:The in-depth understanding of the pathogenesis and advances of portal hypertension has enabled the discovery of multiple molecular targets for promising drugs.According to the site of action,these drugs could be classified into four classes:intrahepatic,extrahepatic,both intrahepatic and extrahepatic targets and others.All these classes of drugs offer advantages over traditional treatments in prevention of gastroesophageal variceal bleeding in patients with cirrhotic portal hypertension.Conclusions:This review classified and summarized the promising drugs,which prevent gastroesophageal variceal bleeding by targeting specific markers of pathogenesis of portal hypertension,demonstrating the significance of using the precision medicine strategy to discover and develop promising drugs for the primary prevention of gastroesophageal variceal bleeding in patients with cirrhotic portal hypertension.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.

Unlocking the potential-vitamin D in prostate cancer prevention

Prostate cancer poses a significant health challenge globally,demanding proactive prevention strategies.This editorial explores the emerging role of vitamin D in prostate cancer prevention.While traditionally associated with bone health,vitamin D is increasingly recognized for its broader impact on immune function,cellular signaling,and cancer prevention.Epidemiological studies suggest an intriguing link between vitamin D deficiency and elevated prostate cancer risk,particularly in regions with limited sunlight exposure.Mechanistically,vitamin D regulates cellular processes,inhibiting unchecked cancer cell growth and bols-tering immune surveillance.Personalized prevention strategies,considering individual factors,are deemed essential for harnessing the full potential of vitamin D.To unlock this potential,the future calls for robust research,public awareness campaigns,dietary improvements,and vigilant medical guidance.Collaborative efforts are poised to pave the way toward a future where vitamin D stands as a sentinel in prostate cancer prevention,ushering in hope and improved health for men worldwide.

Navigating nephrotoxic waters:A comprehensive overview of contrast-induced acute kidney injury prevention

Contrast-induced acute kidney injury(CI-AKI)is the third leading cause of acute kidney injury deriving from the intravascular administration of contrast media in diagnostic and therapeutic procedures and leading to longer in-hospital stay and increased short and long-term mortality.Its pathophysiology,although not well-established,revolves around medullary hypoxia paired with the direct toxicity of the substance to the kidney.Critically ill patients,as well as those with pre-existing renal disease and cardiovascular comorbidities,are more susceptible to CI-AKI.Despite the continuous research in the field of CI-AKI prevention,clinical practice is based mostly on periprocedural hydration.In this review,all the investigated methods of prevention are presented,with an emphasis on the latest evidence regarding the potential of RenalGuard and contrast removal systems for CI-AKI prevention in high-risk individuals.

Effectiveness of serological markers of gastric mucosal atrophy in the gastric precancer screening and in cancer prevention

BACKGROUND New markers are needed to improve the effectiveness of serological screening for atrophic gastritis.AIM To develop a cost-effective method for serological screening of atrophic gastritis with a high level of sensitivity.METHODS Of the 169 patients with atrophic gastritis,selected by the visual endoscopic Kimura-Takemoto method,165 showed histological mucosal atrophy using the updated Kimura-Takemoto method.All 169 patients were examined for postprandial levels of gastrin-17(G17)and pepsinogen-1(PG1)using Gastro-Panel®(Biohit Plc,Helsinki,Finland).RESULTS We used the histological standard of five biopsies of the gastric mucosa,in accordance with the Kimura-Takemoto classification system to assess the sensitivity of G17 in detecting gastric mucosal atrophy.We also compared the morphofunctional relationships between the detected histological degree of gastric mucosal atrophy and the serological levels of G17 and PG1,as the markers of atrophic gastritis.The sensitivity of postprandial G17 was 62.2%for serological levels of G17(range:0-4 pmol/L)and 100%for serological G17(range:0-10 pmol/L)for the detection of monofocal severe atrophic gastritis.No strong correlation was found between the levels of PG1 and degree of histological atrophy determined by the Kimura-Takemoto classification system to identify the severity of mucosal atrophy of the gastric corpus.In the presented clinical case of a 63-year-old man with multifocal atrophic gastritis,there is a pronounced positive long-term dynamics of the serological marker of atrophy-postprandial G17,after five months of rennet replacement therapy.CONCLUSION Serological screening of multifocal atrophic gastritis by assessment of postprandial G17 is a cost-effective method with high sensitivity.Postprandial G17 is an earlier marker of regression of atrophic gastritis than a morphological examination of a gastric biopsy in accordance with the Sydney system.Therefore,postprandial G17 is recommended for dynamic monitoring of atrophic gastritis after treatment.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

Beyond dentistry:could prevention and screening for neurodegenerative diseases start in the dental office?

The differential diagnosis of neurodegenerative diseases is complex and relies on clinical assessment,biomarker levels in cerebrospinal fluid,neuroimaging and neuropsychological assessment.The efforts of the scientific community are focused on two aspects:a)the discovery of minimally invasive biomarkers;b)the discovery of early biomarkers that can predict the progression to clinical disease in the presymptomatic stage of a disease.Considering the impact of the number of patients affected by chronic neurodegenerative diseases on public health expenditures,early diagnosis seems to be a primary need of our society.

Physical activity with or without dietary intervention for the prevention of cardiovascular diseases

We and others have published extensively on the benefits of physical activity(PA),exercise training,and cardiorespiratory fitness(CRF)to decrease the prevalence of cardiovascular diseases(CVDs)and CVD and all-cause morbidity and mortality.^(1-5)Both PA and CRF are important;however,CRF,which is mostly obtained through PA,although there is a genetic component,seems to be even more important than PA for predicting prognosis.^(1,4-6)Certainly,the wealth of data from across the world has indicated that increasing PA to enhance CRF while mitigating sedentary behavior would go a long way to lessen the world-wide obesity epidemic and reduce CVD and all-cause mortality.

Community-based prevention and treatment of cardiovascular diseases

The Annual Report on Cardiovascular Health and Diseases in China(2022)intricate landscape of cardiovascular health in China.This is the third section of the report with a specific focus on community-based prevention and treatment of cardiovascular diseases(CVD).This section of the report underscores the importance of initiatives outlined in the"Healthy China 2030 Plan,"emphasizing the comprehensive prevention and control strategy for chronic diseases.A key aspect of this plan involves the establishment of national demonstration areas aimed at comprehensive prevention and control of chronic diseases.By 2020,488 such areas had been set up across China,surpassing the initial target and covering a significant proportion of counties and districts.The report highlights the successful implementation of these strategies in Lishan district,Anshan city,where demonstration areas for comprehensive prevention and control of chronic diseases were launched in 2013.Over the course of seven years,the number of healthy units increased substantially,leading to improvements in managing risk factors for CVD among residents.Significant reductions in prevalence rates of overweight,obesity,smoking,passive smoking,and drinking were observed,along with the development of healthier behaviors among residents.Similarly,Qiaokou district in Wuhan City,designated as a national demonstration area in 2014,implemented comprehensive public health promotion initiatives.Notably,special clinics for hypertension intervention were established,contributing to an increase in self-reported rates of hypertension,a slight decrease in prevalence,and a remarkable improvement in the control rate among treated patients.Overall,these efforts underscore the effectiveness of community-based approaches in driving positive health outcomes and advancing the comprehensive prevention and control of chronic diseases,particularly cardiovascular diseases,in China.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

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.

Helicobacter pylori eradication for primary prevention of gastric cancer:progresses and challenges

Gastric cancer remains a significant global health challenge,causing a substantial number of cancer-related deaths,particularly in China.While the exact causes of gastric cancer are still being investigated,Helicobac-ter pylori(H.pylori)infection has been identified as the primary risk factor,which triggers chronic inflammation and a multistage progression of gastric lesions that may lead to carcinogenesis over a long latency time.Since the 1990s,numerous efforts have focused on assessing the effectiveness of H.pylori eradication in preventing new cases of gastric cancer among both the general population and patients who have undergone early-stage cancer treatment.This body of work,including several community-based interventions and meta-analyses,has shown a reduction in both the incidence of and mortality from gastric cancer following H.pylori treatment,alongside a decreased risk of metachronous gastric cancer.In this review,we seek to consolidate current knowledge on the effects of H.pylori treatment on gastric cancer prevention,its systemic consequences,cost-effectiveness,and the influence of antibiotic resistance and host characteristics on treatment outcomes.We further discuss the potential for precision primary prevention of H.pylori treatment and comment on the efficient implementation of test-and-treat policies and allocation of health resources towards minimizing the burden of gastric cancer globally.

Practice of Infection Prevention and Control Strategies in Risk Departments during the COVID-19 Epidemic

Objective: To explore the practice and application of infection prevention and control strategies in risk departments during the COVID-19 epidemic, and to formulate the infection prevention and control measures to provide advice and guidance in risk departments. Methods: According to the latest plan of diagnosis and treatment, prevention and control issued by the National Health Commission, expert advice and consensus, combined with the actual situation in our hospital, a series of infection prevention and control measures of COVID-19 in risk department was formulated. Results: During the epidemic period, the prevention and control measures of nine risk departments including emergency operation, anesthesiology, endoscopy center, blood purification center, otolaryngology, stomatology, medical imaging department, medical cosmetology department and pulmonary function room were established from six aspects, including pre-examination and screening, medical technology control, personnel management, personal protection, environmental disinfection, medical waste disposal, etc. Conclusion: During the epidemic period, the infection prevention and control strategy of risk departments is one of the key links to control the spread of the epidemic, and risk departments must pay attention to and strictly implement various infection prevention and control measures.

Comprehensive approach to esophageal variceal bleeding:From prevention to treatment

Esophageal variceal bleeding is a severe complication often associated with portal hypertension,commonly due to liver cirrhosis.Prevention and treatment of this condition are critical for patient outcomes.Preventive strategies focus on reducing portal hypertension to prevent varices from developing or enlarging.Primary prophylaxis involves the use of non-selective beta-blockers,such as propranolol or nadolol,which lower portal pressure by decreasing cardiac output and thereby reducing blood flow to the varices.Endoscopic variceal ligation(EVL)may also be employed as primary prophylaxis to prevent initial bleeding episodes.Once bleeding occurs,immediate treatment is essential.Initial management includes hemodynamic stabilization followed by pharmacological therapy with vasoactive drugs such as octreotide or terlipressin to control bleeding.Endoscopic intervention is the cornerstone of treatment,with techniques such as EVL or sclerotherapy applied to directly manage the bleeding varices.In cases where bleeding is refractory to endoscopic treatment,transjugular intrahepatic portosystemic shunt may be considered to effectively reduce portal pressure.Long-term management after an acute bleeding episode involves secondary prophylaxis using betablockers and repeated EVL sessions to prevent rebleeding,complemented by monitoring and managing liver function to address the underlying disease.In light of new scientific evidence,including the findings of the study by Peng et al,this editorial aims to review available strategies for the prevention and treatment of esophageal varices.

Determination of the best materials for development and designing product using a multi-criteria decision-making

Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

Assessment of Breast Cancer Prevention Practices among Women Attending Primary Health Care in Abha City, Aseer Region, Saudi Arabia

Cancer is a leading cause of death worldwide, with breast cancer being the most common (2.26 million new cases and 685,000 deaths). In Saudi Arabia, breast cancer ranked the first among females in 2014, accounting for 15.9% of all cancers reported among Saudi nationals and 28.7% of all cancers reported among females of all ages. Early detection of breast cancer could decrease the risks, have a better prognosis, and have better outcomes/more successful treatments. Prevalence of breast cancer reached more than 25% of all diagnosed cancer in the kingdom among women. Aim: This study aims to assess the knowledge and performance of women attending primary care centers about breast self-examination and mammogram screening for prevention and early detection of breast cancer in Abha city primary healthcare centers, Kingdom of Saudi Arabia. Research Method: cross sectional design was conducted by using questionnaire, which was distributed to primary care center nurses. The collected data was statistically analyzed using the Statistical Package for Social Sciences, version 25. Results: The study found that participants had poor awareness and knowledge about breast self-examination, risk factors for breast cancer, and trends and practices in early diagnosis of breast cancer. Conclusion and Recommendations: It recommends increasing awareness campaigns and providing educational programs to improve knowledge and practices.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.