Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets

This socialized environment among educated and developed people causes themto focusmore on their appearance and health,which turns them towards medical-related treatments,leading us to discuss anti-aging treatment methods for each age group,particularly for urban people who are interested in this.Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects.Five anti-aging therapies such as microdermabrasion or dermabrasion,laser resurfacing anti-aging skin treatments,chemical peels,dermal fillers for aged skin,and botox injections are considered in this study.Based on the criteria of safety risk,investment cost,customer happiness,and side effects,the optimal alternative is picked.As a result,a NormalWiggly Hesitant Pythagorean Fuzzy Set(NWHPFS)is constructed and used in Multi-Criteria Decision-Making(MCDM)using traditional wavy mathematical approaches.The entropy approach is utilized to determine weight values,and the Normal Wiggly Hesitant Pythagorean-VlseKriterijumska Optimizacija I Kompromisno Resenje(NWHPF-VIKOR)method is utilized to rank alternatives using MCDM methodologies.Sensitivity analysis and comparative analysis were performed to ensure the robustness and reliability of the proposed method.The smart final choice will undoubtedly assist Decision Makers(DM)in making the right judgments,and the MCDM approach will undoubtedly assist individuals in understanding the medicine.

Heterogeneous information fusion recognition method based on belief rule structure

To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Acceptance of COVID-19 vaccine and its related determinants in Nigeria:An online survey

BACKGROUND Vaccine hesitancy is a major challenge in the fight against the coronavirus disease 2019(COVID-19)pandemic.Identifying the sociodemographic factors associated with vaccine acceptance among Nigerians is crucial for improving vaccine uptake.AIM To assess the acceptance rate of COVID-19 vaccine and its related determinants among Nigerians.METHODS An online cross-sectional survey(observational study)was conducted between February 2021 and May 2021,using a questionnaire hosted on SurveyMonkey.The invitation to take part in the poll was sent out to participants through social networking platforms.A logistic regression was used to determine which sociodemographic factors were associated with vaccine acceptance constructs.RESULTS A total of 1800 persons responded to the survey,a larger proportion of whom were males(53.9%)and within the age group of 21-30 years(29.4%)and earned an average income of less than$500 per month(43.3%).Only 0.56%of participants had a high perceived risk of COVID-19 infection,while only 1.11%had a perceived risk of dying from COVID-19.The perception rate of the COVID-19 vaccine among participants was 51.1%,while the acceptance rate was 63.9%.There was no significant association between the COVID-19 vaccine acceptance rate and related determinants assessed,particularly age(χ²=3.049,P=0.550),sex(χ²=0.102,P=0.749),average income(χ²=3.802,P=0.875),and religion(χ²=2.819,P=0.420).Participants with chronic conditions demonstrated a higher acceptance rate compared to the general population.CONCLUSION Despite the positive perception observed and substantial vaccine acceptance rate among the study participants,more public health interventions are still needed to enhance vaccine acceptability in Nigeria.

COVID-19 Vaccine Acceptance and Hesitancy among Pregnant Women: A Knowledge, Attitude, and Perceived Risks Survey in Lusaka, Zambia

Introduction: The coronavirus disease 2019 (COVID-19) is an infectious disease of the respiratory tract caused by SARS-CoV-2. Since its emergence, there have been increased rates of transmission and spread, morbidity and mortality which led to the development of COVID-19 vaccines to address the pandemic. This study assessed acceptance, knowledge, attitude, and perceived risks regarding COVID-19 vaccines among pregnant women attending antenatal care at two First-Level Hospitals in Lusaka, Zambia. Materials and Methods: This was a cross-sectional study that was conducted among 241 pregnant women using a questionnaire from August 2023 to October 2023 in two First-Level Hospitals in Lusaka district, Zambia. The collected data were analyzed using IBM Statistical Package for Social Sciences (SPSS) version 22.0. Statistical analysis was performed using a Chi-square test. The statistical significance was set at a 95% confidence level. Results: Of the 241 participants, 107 (42.7%) were aged between 24 and 34 years. Overall, 64.3% accepted the COVID-19 vaccines, of which 122 (50.6%) were already vaccinated. Further, 203 (84.6%) of the pregnant women had good knowledge, and 199 (82.6%) had positive attitudes towards COVID-19 vaccines. However, 58.5% thought COVID-19 vaccines were not safe and could cause infertility. Alongside this, 70.1% thought that COVID-19 vaccines were harmful during pregnancy. Having good knowledge of COVID-19 vaccines was associated with age (p = 0.049), education status (p = 0.001), and employment status (p = 0.001). Having a positive attitude towards COVID-19 vaccines was associated with education status (p = 0.001) and employment status (p = 0.001). Conclusion: This study found that most pregnant women had good knowledge, and positive attitudes, and the majority accepted the COVID-19 vaccine. Encouragingly, most of the pregnant women who accepted the COVID-19 vaccines were already vaccinated. Most pregnant women thought that COVID-19 vaccines had side effects, were not safe, and could be harmful during pregnancy. Consequently, this could have contributed to the hesitancy to receive a vaccine among some participants. The findings of this study demonstrate the need to provide pregnant women with continuous educational programs on the benefits of vaccinations for themselves and their children.

Color Thresholding, Detection and Recognition of the Road Signs Using the Information Set Theory

In this paper, approaches are presented for the thresholding, detection, tracking and recognition of the road signs as part of an Advanced Driver Assistance System (ADAS). In all these approaches, feature extraction is the backbone, whereas detection and recognition require the use of detectors and classifiers, respectively. In this, two issues are dominant: 1) Tackling the variability involved in the lighting conditions, sizes, and shapes of the road signs after segregating them from a world scene, and 2) Focusing on inaccurate fuzzy modeling arising due to the improper distribution of pixel intensities. The variability is overcome with the uncertainty representation using the information sets, an extension of fuzzy sets, whereas the incorrect fuzzy modeling is rectified using the pervasive information sets, an extension of intuitionistic fuzzy sets. The development of the intuitionistic fuzzy transform paralleling the fuzzy entropy function paves the way for the formulation of different hesitancy features by cashing in on the non-membership function. Next, promulgation of the Hanman law prescribes the fuzzy gradient/divergent values for different tasks. The notable landmarks of this work are the creation of a Color-Based Detector (CBD), derivation of the incremental hesitancy features accrued from the color histograms and the formulation of a variant of the Hanman Transform Classifier using Convolutional Neural Network (CNN) features. We have used the Belgium dataset to vindicate the efficacy of the proposed methods.

Three-Way Behavioral Decision Making With Hesitant Fuzzy Information Systems:Survey and Challenges

Three-way decision(T-WD)theory is about thinking,problem solving,and computing in threes.Behavioral decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal object,of which prospect theory and regret theory are two widely used tools.The hesitant fuzzy set(HFS)captures a series of uncertainties when it is difficult to specify precise fuzzy membership grades.Guided by the principles of three-way decisions as thinking in threes and integrating these three topics together,this paper reviews and examines advances in three-way behavioral decision making(TW-BDM)with hesitant fuzzy information systems(HFIS)from the perspective of the past,present,and future.First,we provide a brief historical account of the three topics and present basic formulations.Second,we summarize the latest development trends and examine a number of basic issues,such as one-sidedness of reference points and subjective randomness for result values,and then report the results of a comparative analysis of existing methods.Finally,we point out key challenges and future research directions.

Pythagorean probabilistic hesitant triangular fuzzy aggregation operators with applications in multiple attribute decision making

As a generalization of fuzzy set,hesitant probabilistic fuzzy set and pythagorean triangular fuzzy set have their own unique advantages in describing decision information.As modern socioeconomic decision-making problems are becoming more and more complex,it also becomes more and more difficult to appropriately depict decision makers’cognitive information in decision-making process.In order to describe the decision information more comprehensively,we define a pythagorean probabilistic hesitant triangular fuzzy set(PPHTFS)by combining the pythagorean triangular fuzzy set and the probabilistic hesitant fuzzy set.Firstly,the basic operation and scoring function of the pythagorean probabilistic hesitant triangular fuzzy element(PPHTFE)are proposed,and the comparison rule of two PPHTFEs is given.Then,some pythagorean probabilistic hesitant triangular fuzzy aggregation operators are developed,and their properties are also studied.Finally,a multi-attribute decision-making(MADM)model is constructed based on the proposed operators under the pythagorean probabilistic hesitant triangular fuzzy information,and an illustration example is given to demonstrate the practicability and validity of the proposed decision-making method.

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE preference matrix is transformed into the normalized HFE preference matrix.On this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated.Then,the normalized HFEs are transformed into agent satisfactions.Considering the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed.Based on the agent satisfaction matrix,the matching intention matrix of two-sided agents is built.According to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set up.Furthermore,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions.Using the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is obtained.Finally,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

Effect of patient COVID-19 vaccine hesitancy on hospital care team perceptions

BACKGROUND The coronavirus disease 2019(COVID-19)pandemic posed new challenges in patient care worldwide.Vaccinations,which have proven efficacious in lowering the COVID-19 hospital burden,are still avoided by large populations.We,therefore,hypothesized that hospital care teams would have worse perceptions regarding the characteristics and care of patients with vaccine hesitancy.AIM To evaluate whether patient vaccine hesitancy affected the hospital care team(HCT)perceptions.METHODS We performed a prospective clinical study using structured questionnaires.We approached physicians and nurses with previous experience caring for COVID-19patients from 11 medical centers across Israel during the fourth COVID-19 surge(September and October 2021).The participants completed a questionnaire with the following parts:(1)Sociodemographic characteristics;(2)Assessment of anger(STAXI instrument)and chronic workplace stress(Shirom-Melamed burnout measure);and(3)Three tools to assess the effect of patient vaccine hesitancy on the HCT perceptions(the difficult doctor-patient relation questionnaire,the medical staff perception of patient’s responsibility questionnaire and the characterological derogation questionnaire).Results were evaluated according to each part of the questionnaire and the questionnaire as a whole.Associations between HCT perceptions and their baseline characteristics,anger or chronic workplace stress were assessed.RESULTS The HCT experienced their relationship with unvaccinated patients as more difficult(P<0.001,Cohen’s d=0.85),perceived unvaccinated patients as responsible for their medical condition(P<0.001,d=1.39)and perceived vaccinated patients as having a higher character value(P<0.001,d=1.03).Unvaccinated patients were considered selfish(P<0.001),less mature(P<0.001)and less satisfying to care for(P<0.001).The relationship with unvaccinated patients was more difficult among HCT with higher burnout(r=0.37,n=66,P=0.002).No correlations with baseline characteristics were found.All three study tools showed high internal consistency(αbetween 0.72 and 0.845).CONCLUSION Our results should raise awareness of the possible effects of vaccine hesitancy on HCT perceptions regarding unvaccinated patients.In order to minimize the potential negative impact on patient care,designated departments should promote specific patient-centered preparations.Further investigations should assess whether vaccine hesitancy directly affects patient quality of care.

The Correlation Coefficient of Hesitancy Fuzzy Graphs in Decision Making

The hesitancy fuzzy graphs(HFGs),an extension of fuzzy graphs,are useful tools for dealing with ambiguity and uncertainty in issues involving decision-making(DM).This research implements a correlation coefficient measure(CCM)to assess the strength of the association between HFGs in this article since CCMs have a high capacity to process and interpret data.The CCM that is proposed between the HFGs has better qualities than the existing ones.It lowers restrictions on the hesitant fuzzy elements’length and may be used to establish whether the HFGs are connected negatively or favorably.Additionally,a CCMbased attribute DM approach is built into a hesitant fuzzy environment.This article suggests the use of weighted correlation coefficient measures(WCCMs)using the CCM concept to quantify the correlation between two HFGs.The decisionmaking problems of hesitancy fuzzy preference relations(HFPRs)are considered.This research proposes a new technique for assessing the relative weights of experts based on the uncertainty of HFPRs and the correlation coefficient degree of each HFPR.This paper determines the ranking order of all alternatives and the best one by using the CCMs between each option and the ideal choice.In the meantime,the appropriate example is given to demonstrate the viability of the new strategies.

Novel Distance Measures on Hesitant Fuzzy Sets Based on Equal-Probability Transformation and Their Application in Decision Making on Intersection Traffic Control

The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special way.Firstly,a probability density function is assigned for any given HFE.Thereafter,equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function.The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs,the higher the credibility of the mentioned membership degrees is,then,the bigger the probability density values for them are.According to this transformation technique,a set of novel distance measures on HFSs is provided.Finally,an illustrative example of intersection traffic control is introduced to show the usefulness of the given distance measures.The example also shows that this study is a good complement to operation theories on HFSs.

Intention and hesitancy to receive a booster dose of COVID-19 vaccine among pregnant women using a health belief model: A cross-sectional study

Objective:To examine the pattern of COVID-19 infection and vaccination,and to explore pregnant women’s willingness and reluctance to accept a booster dose of the COVID-19 vaccine.Methods:This was a cross-sectional,descriptive study with a convenient sample size using a structured questionnaire among pregnant women attending the gynecology and obstetrics department at Acıbadem Mehmet Ali Aydinlar Hospital,Istanbul,Türkiye.The Health Belief Model scale was used to assess the intention and reluctance to accept a booster dose of the COVID-19 vaccine.Results:A total of 145 participants,with a mean age of(33.5±4.8)years,and a gestational age of(30.9±7.3)weeks,were enrolled in this study.88.8%Received full doses of the Pfizer-BioNTech vaccination.47.8%Participants suffered from vaccine adverse effects.Health Belief Model demonstrated a significant finding of perceived susceptibility(P<0.001),perceived severity of COVID-19 complications(P<0.001),and perceived benefits regarding a booster COVID-19 vaccination(P<0.001).Conclusions:Most pregnant women who received the COVID-19 immunization express a significant intention to receive a booster dose,regardless of the adverse effects experienced from the previous doses.However,a small percentage of the study sample express hesitancy about receiving the booster dose.

Fermatean Hesitant Fuzzy Prioritized Heronian Mean Operator and Its Application in Multi-Attribute Decision Making

In real life,incomplete information,inaccurate data,and the preferences of decision-makers during qualitative judgment would impact the process of decision-making.As a technical instrument that can successfully handle uncertain information,Fermatean fuzzy sets have recently been used to solve the multi-attribute decision-making(MADM)problems.This paper proposes a Fermatean hesitant fuzzy information aggregation method to address the problem of fusion where the membership,non-membership,and priority are considered simultaneously.Combining the Fermatean hesitant fuzzy sets with Heronian Mean operators,this paper proposes the Fermatean hesitant fuzzy Heronian mean(FHFHM)operator and the Fermatean hesitant fuzzyweighted Heronian mean(FHFWHM)operator.Then,considering the priority relationship between attributes is often easier to obtain than the weight of attributes,this paper defines a new Fermatean hesitant fuzzy prioritized Heronian mean operator(FHFPHM),and discusses its elegant properties such as idempotency,boundedness and monotonicity in detail.Later,for problems with unknown weights and the Fermatean hesitant fuzzy information,aMADM approach based on prioritized attributes is proposed,which can effectively depict the correlation between attributes and avoid the influence of subjective factors on the results.Finally,a numerical example of multi-sensor electronic surveillance is applied to verify the feasibility and validity of the method proposed in this paper.

Novel Decision Making Methodology under Pythagorean Probabilistic Hesitant Fuzzy Einstein Aggregation Information

This research proposes multicriteria decision-making(MCDM)-based real-time Mesenchymal stem cells(MSC)transfusion framework.The testing phase of the methodology denotes the ability to stick to plastic surfaces,the upregulation and downregulation of certain surface protein markers,and lastly,the ability to differentiate into various cell types.First,two scenarios of an enhanced dataset based on a medical perspective were created in the development phase to produce varying levels of emergency.Second,for real-timemonitoring ofCOVID-19 patients with different emergency levels(i.e.,mild,moderate,severe,and critical),an automated triage algorithmbased on a formal medical guideline is proposed,taking into account the improvement and deterioration procedures fromone level to the next.For this strategy,Einstein aggregation information under the Pythagorean probabilistic hesitant fuzzy environment(PyPHFE)is developed.Einstein operations on PyPHFE such as Einstein sum,product,scalar multiplication,and their properties are investigated.Then,several Pythagorean probabilistic hesitant fuzzy Einstein aggregation operators,namely the Pythagorean probabilistic hesitant fuzzy weighted average(PyPHFWA)operator,Pythagorean probabilistic hesitant fuzzy Einstein weighted geometric(PyPHFEWG)operator,Pythagorean probabilistic hesitant fuzzy Einstein ordered weighted average(PyPHFEOWA)operator,Pythagorean probabilistic hesitant fuzzy Einstein ordered weighted geometric(PyPHFEOWG)operator,Pythagorean probabilistic hesitant fuzzy Einstein hybrid average(PyPHFEHA)operator and Pythagorean probabilistic hesitant fuzzy Einstein hybrid geometric(PyPHFEHG)operator are investigated.All the above-mentioned operators are helpful in design the algorithm to tackle uncertainty in decision making problems.In last,a numerical case study of decision making is presented to demonstrate the applicability and validity of the proposed technique.Besides,the comparison of the existing and the proposed technique is established to show the effectiveness and validity of the established technique.

The Laplacian Energy of Hesitancy Fuzzy Graphs in Decision-Making Problems

Decision-making(DM)is a process in which several persons concur-rently engage,examine the problems,evaluate potential alternatives,and select an appropriate option to the problem.Technique for determining order preference by similarity to the ideal solution(TOPSIS)is an established DM process.The objective of this report happens to broaden the approach of TOPSIS to solve the DM issues designed with Hesitancy fuzzy data,in which evaluation evidence given by the experts on possible solutions is presents as Hesitancy fuzzy decision matrices,each of which is defined by Hesitancy fuzzy numbers.Findings:we represent analytical results,such as designing a satellite communication network and assessing reservoir operation methods,to demonstrate that our suggested thoughts may be used in DM.Aim:We studied a new testing method for the arti-ficial communication system to give proof of the future construction of satellite earth stations.We aim to identify the best one from the different testing places.We are alsofinding the best operation schemes in the reservoir.In this article,we present the concepts of Laplacian energy(LE)in Hesitancy fuzzy graphs(HFGs),the weight function of LE of HFGs,and the TOPSIS method technique is used to produce the hesitancy fuzzy weighted-average(HFWA).Also,consider practical examples to illustrate the applicability of thefinest design of satellite communication systems and also evaluation of reservoir schemes.

Vaccine Hesitancy—A Persistant Pandemic and Continued Threat to Global Health

Last time the world faced a deadly pandemic was the H1N1 Spanish flu in 1918, which affected almost one third of the world’s population (500 million people). Since then, almost 100 years later, we are now facing another pandemic of the SARS-CoV2 virus (Covid-19), which is still endemic to this day. As technology evolved during those 100 years, an effective vaccine for Covid-19 was produced within only a year, a huge feat. But, unfortunately, due to its fast development, another force would arise limiting the impact of the vaccine: Vacccine hesitancy and anti-vaxxers, which John Hopkins and the World Health Organization call the biggest current threat to global health. From politics to social media, it is clear that there has been a rapid spread of misinformation, resulting in hesitancy, especially from sociopolitically motivated people popularly referred to as antivaccers. However, a second group of vaccine-hesitant people have also emerged, who are uneducated and remain undecided about vaccination mostly due to safety concerns. They come under the massive influence of anti-vaxxers and anti-vaccine propaganda through social media and politicians, which often make bold claims and huge headlines. To combat vaccine hesitancy, it is crucial that we debunk these conspiracy theories and misinformation that so many believe in, with factual, data-based information. Actively spreading correct information about the vaccines, such as disclosing the rigorous developmental processes and validation of safety data by the FDA, assurance for unlikeliness of getting a lethal side effect along with tremendous health benefits, will encourage people to safe vaccination against Covid-19 and other potentially infectious diseases in future. This article discusses the role of anti-vaxxers and vaccine hesitancy groups, electronic social media, and politics in vaccine hesitancy among people. It describes the strategies to combat the roadblocks in the vaccination programs and health benefits, offered by recent advances in scientific and technological developments.

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Fuzzy sets have undergone several expansions and generalisations in the literature,including Atanasov’s intuitionistic fuzzy sets,type 2 fuzzy sets,and fuzzy multisets,to name a few.They can be regarded as fuzzy multisets from a formal standpoint;nevertheless,their interpretation differs from the two other approaches to fuzzy multisets that are currently available.Hesitating fuzzy sets(HFS)are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships.However,these possible memberships can be not only crisp values in[0,1],but also interval values during a practical evaluation process.Hesitant bipolar valued fuzzy set(HBVFS)is a generalization of HFS.This paper aims to introduce a general framework of multi-attribute group decision-making using social network.We propose two types of decision-making processes:Type-1 decision-making process and Type-2 decision-making process.In the Type-1 decision-making process,the experts’original opinion is proces for thefinal ranking of alternatives.In Type-2 decision making processs,there are two major aspects we consider.First,consistency tests and checking of consensus models are given for detecting that the judgments are logically rational.Otherwise,the framework demands(partial)decision-makers to review their assessments.Second,the coherence and consensus of several HBVFSs are established forfinal ranking of alternatives.The proposed framework is clarified by an example of software packages selection of a university.

Inequity in the global distribution of monkeypox vaccines

Monkeypox(mpox)has been a public health emergency of international concern that emerged in mid-2022 and has spread to 110 countries.The clinical findings of the disease vary according to the seriousness of the cases.Although its case fatality risk has not been high,a significant percentage of patients require hospitalization.In this context,local initiatives were taken to extend the limited supply of vaccines against the disease;however,such measures have not been sufficient to contain the spread of cases and ensure an equitable distribution of health resources.As a result,endemic regions of low-income countries continue to have insufficient access to mpox vaccination.Despite this and considering the global scope of the disease,there is still little discussion in the literature about the difficulties in achieving adequate vaccination coverage rates for the target population of interest.In this article,we briefly discussed general aspects of the disease,including its surveillance,the current global context of challenges for mpox vaccination,and issues on global allocation of health resources as well as proposed related recommendations.