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.

Fuzzy multiple attribute decision-making model for synergic knowledge innovation in supply chain

The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then the characteristics of synergic knowledge innovation in the supply chain are analyzed,including complexity,accumulating and evolving process,and the cooperation of members and network integration.Due to the characteristics of multi-factors and uncertainties of the supply chain system,the fuzzy multi-attribution group decision-making model is introduced to solve the involved problem of synergic knowledge innovation in the supply chain.After elaborating on steps of using the fuzzy multiple attribute decision-making(MADM)model,the procedure of decision making for synergic knowledge innovation in the supply chain is explained from an example in the application of a fuzzy MADM model.The fuzzy MADM model,which amalgamates intuition and resolution decision-making can effectively improve the rationality of decision-making for synergic knowledge innovation in the supply chain.

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.

Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

Infiltration by monocytes of the central nervous system and its role in multiple sclerosis: reflections on therapeutic strategies

Mononuclear macrophage infiltration in the central nervous system is a prominent feature of neuroinflammation. Recent studies on the pathogenesis and progression of multiple sclerosis have highlighted the multiple roles of mononuclear macrophages in the neuroinflammatory process. Monocytes play a significant role in neuroinflammation, and managing neuroinflammation by manipulating peripheral monocytes stands out as an effective strategy for the treatment of multiple sclerosis, leading to improved patient outcomes. This review outlines the steps involved in the entry of myeloid monocytes into the central nervous system that are targets for effective intervention: the activation of bone marrow hematopoiesis, migration of monocytes in the blood, and penetration of the blood–brain barrier by monocytes. Finally, we summarize the different monocyte subpopulations and their effects on the central nervous system based on phenotypic differences. As activated microglia resemble monocyte-derived macrophages, it is important to accurately identify the role of monocyte-derived macrophages in disease. Depending on the roles played by monocyte-derived macrophages at different stages of the disease, several of these processes can be interrupted to limit neuroinflammation and improve patient prognosis. Here, we discuss possible strategies to target monocytes in neurological diseases, focusing on three key aspects of monocyte infiltration into the central nervous system, to provide new ideas for the treatment of neurodegenerative diseases.

Healthcare providers’perspectives on factors influencing their critical care decision-making during the COVID-19 pandemic:An international pilot survey

BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpful in uncertain situations is clinical judgment.Clinicians must deal with contradictory information,lack of time to make decisions,and long-term factors when emergencies occur.AIM To examine the ethical issues healthcare professionals faced during the coronavirus disease 2019(COVID-19)pandemic and the factors affecting clinical decision-making.METHODS This pilot study,which means it was a preliminary investigation to gather information and test the feasibility of a larger investigation was conducted over 6 months and we invited responses from clinicians worldwide who managed patients with COVID-19.The survey focused on topics related to their professional roles and personal relationships.We examined five core areas influencing critical care decision-making:Patients'personal factors,family-related factors,informed consent,communication and media,and hospital administrative policies on clinical decision-making.The collected data were analyzed using theχ2 test for categorical variables.RESULTS A total of 102 clinicians from 23 specialties and 17 countries responded to the survey.Age was a significant factor in treatment planning(n=88)and ventilator access(n=78).Sex had no bearing on how decisions were made.Most doctors reported maintaining patient confidentiality regarding privacy and informed consent.Approximately 50%of clinicians reported a moderate influence of clinical work,with many citing it as one of the most important factors affecting their health and relationships.Clinicians from developing countries had a significantly higher score for considering a patient's financial status when creating a treatment plan than their counterparts from developed countries.Regarding personal experiences,some respondents noted that treatment plans and preferences changed from wave to wave,and that there was a rapid turnover of studies and evidence.Hospital and government policies also played a role in critical decision-making.Rather than assessing the appropriateness of treatment,some doctors observed that hospital policies regarding medications were driven by patient demand.CONCLUSION Factors other than medical considerations frequently affect management choices.The disparity in treatment choices,became more apparent during the pandemic.We highlight the difficulties and contradictions between moral standards and the realities physicians encountered during this medical emergency.False information,large patient populations,and limited resources caused problems for clinicians.These factors impacted decision-making,which,in turn,affected patient care and healthcare staff well-being.

Voices that matter:The impact of patient-reported outcome measures on clinical decision-making

The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.

Air combat decision-making of multiple UCAVs based on constraint strategy games

Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.

DNA extraction method selection for agricultural soil using TOPSIS multiple criteria decision-making model

There is an increased interest in the extraction of nucleic acids from various environmental samples since culture-independent molecular techniques contribute to deepen and broaden the understanding of a greater portion of uncultivable microorganisms. Due to difficulties to select the optimum DNA extraction method in view of downstream molecular analyses, this article presents a straightforward mathematical framework for comparing some of the most commonly used methods. Four commercial DNA extraction kits and two physical-chemical methods (bead-beating and freeze-thaw) were compared for the extraction of DNA under several quantitative DNA analysis criteria: yield of extraction, purity of extracted DNA (A260/280 and A260/230 ratios), degradation degree of DNA, easiness of PCR amplification, duration of extraction, and cost per extraction. From a practical point of view, it is unlikely that a single DNA extraction strategy can be optimum for all selected criteria. Hence, a systematic Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to compare the methods. The PowerSoil? DNA Isolation Kit was systematically defined as the best performing method for extracting DNA from soil samples. More specifically, for soil:manure and soil:manure:biochar mixtures, the PowerSoil?DNA Isolation Kit method performed best, while for neat soil samples its alternative version gained the first rank.

Cotangent Similarity Measure of Consistent Neutrosophic Sets and Application to Multiple Attribute Decision-Making Problems in Neutrosophic Multi-Valued Setting

A neutrosophic multi-valued set(NMVS)is a crucial representation for true,false,and indeterminate multivalued information.Then,a consistent single-valued neutrosophic set(CSVNS)can effectively reflect the mean and consistency degree of true,false,and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS.However,there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature.This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting.The cosine similarity measures showthe cosine of the angle between two vectors projected into amultidimensional space,rather than their distance.The cotangent similaritymeasures in this study can alleviate several shortcomings of cosine similarity measures in vector space to a certain extent.Then,a decisionmaking approach is presented in viewof the established cotangent similarity measures in the case of NMVSs.Finally,the developed decision-making approach is applied to selection problems of potential cars.The proposed approach has obtained two different results,which have the same sort sequence as the compared literature.The decision results prove its validity and effectiveness.Meantime,it also provides a new manner for neutrosophic multi-valued decision-making issues.

Intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization

The decision-making method of tunnel boring machine(TBM)operating parameters has a significant guiding significance for TBM safe and efficient construction,and it has been one of the TBM tunneling research hotspots.For this purpose,this paper introduces an intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization.First,linear cutting tests and numerical simulations are used to investigate the physical rules between different cutting parameters(penetration,cutter spacing,etc.)and rock compressive strength.Second,a dual-driven mapping of rock parameters and TBM operating parameters based on data mining and physical rules of rock breaking is established with high accuracy by combining rock-breaking rules and deep neural networks(DNNs).The decision-making method is established by dual-driven mapping,using the effective rock-breaking capacity and the rated value of mechanical parameters as constraints and the total excavation cost as the optimization objective.The best operational parameters can be obtained by searching for the revolutions per minute and penetration that correspond to the extremum of the constrained objective function.The practicability and effectiveness of the developed decision-making model is verified in the SecondWater Source Channel of Hangzhou,China,resulting in the average penetration rate increasing by 11.3%and the total cost decreasing by 10%.

Decision-Making of a Single Supplier and Multiple Loss-Averse Retailers under Partial Trade Credit

Under partial trade credit,suppliers usually require retailers to pay a fraction of the purchase cost immediately when ordering and the remaining payment is deferred at the end of the sales period.Considering a supply chain consisting of a risk-neutral supplier and multiple loss-averse retailers,we develop models under partial trade credit.We analyze the optimal decisions of a supplier and retailers under decentralized decision-making.The study shows that there is a unique Nash equilibrium among the retailers,and the optimal total order quantity of retailers increases as the delayed payment ratio increases and as the degree of retailers'competition increases,but decreases with an increase in the loss aversion.Numerical studies are conducted to demonstrate the solution procedures and the effects of the parameters on decisions and profits.

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.

Gut flora in multiple sclerosis:implications for pathogenesis and treatment

Multiple sclerosis is an inflammatory disorder chara cterized by inflammation,demyelination,and neurodegeneration in the central nervous system.Although current first-line therapies can help manage symptoms and slow down disease progression,there is no cure for multiple sclerosis.The gut-brain axis refers to complex communications between the gut flo ra and the immune,nervous,and endocrine systems,which bridges the functions of the gut and the brain.Disruptions in the gut flora,termed dys biosis,can lead to systemic inflammation,leaky gut syndrome,and increased susceptibility to infections.The pathogenesis of multiple sclerosis involves a combination of genetic and environmental factors,and gut flora may play a pivotal role in regulating immune responses related to multiple scle rosis.To develop more effective therapies for multiple scle rosis,we should further uncover the disease processes involved in multiple sclerosis and gain a better understanding of the gut-brain axis.This review provides an overview of the role of the gut flora in multiple scle rosis.

A Review on Vibration Control of Multiple Cylinders Subjected to FlowInduced Vibrations

The fatigue damage caused by flow-induced vibration(FIV)is one of the major concerns for multiple cylindrical structures in many engineering applications.The FIV suppression is of great importance for the security of many cylindrical structures.Many active and passive control methods have been employed for the vibration suppression of an isolated cylinder undergoing vortex-induced vibrations(VIV).The FIV suppression methods are mainly extended to the multiple cylinders from the vibration control of the isolated cylinder.Due to the mutual interference between the multiple cylinders,the FIV mechanism is more complex than the VIV mechanism,which makes a great challenge for the FIV suppression.Some efforts have been devoted to vibration suppression of multiple cylinder systems undergoing FIV over the past two decades.The control methods,such as helical strakes,splitter plates,control rods and flexible sheets,are not always effective,depending on many influence factors,such as the spacing ratio,the arrangement geometrical shape,the flow velocity and the parameters of the vibration control devices.The FIV response,hydrodynamic features and wake patterns of the multiple cylinders equipped with vibration control devices are reviewed and summarized.The FIV suppression efficiency of the vibration control methods are analyzed and compared considering different influence factors.Further research on the FIV suppression of multiple cylinders is suggested to provide insight for the development of FIV control methods and promote engineering applications of FIV control methods.

Linear paired electrolysis of furfural to furoic acid at both anode and cathode in a multiple redox mediated system

Implementing a new energy-saving electrochemical synthesis system with high commercial value is a strategy of the sustainable development for upgrading the bulk chemicals preparation technology in the future.Here,we report a multiple redox-mediated linear paired electrolysis system,combining the hydrogen peroxide mediated cathode process with the I2 mediated anode process,and realize the conversion of furfural to furoic acid in both side of the dividedflow cell simultaneously.By reasonably controlling the cathode potential,the undesired water splitting reaction and furfural reduction side reactions are avoided.Under the galvanostatic electrolysis,the two-mediated electrode processes have good compatibility,which reduce the energy consumption by about 22%while improving the electronic efficiency by about 125%.This system provides a green electrochemical synthesis route with commercial prospects.

Early detection of multiple endocrine neoplasia type 1: A case report

BACKGROUND Multiple endocrine neoplasias(MENs)are a group of hereditary diseases invol-ving multiple endocrine glands,and their prevalence is low.MEN type 1(MEN1)has diverse clinical manifestations,mainly involving the parathyroid glands,gastrointestinal tract,pancreas and pituitary gland,making it easy to miss the clinical diagnosis.CASE SUMMARY We present the case of a patient in whom MEN1 was detected early.A middle-aged male with recurrent abdominal pain and diarrhea was admitted to the hos-pital.Blood tests at admission revealed hypercalcemia and hypophosphatemia,and emission computed tomography of the parathyroid glands revealed a hy-perfunctioning parathyroid lesion.Gastroscopy findings suggested a duodenal bulge and ulceration.Ultrasound endoscopy revealed a hypoechoic lesion in the duodenal bulb.Further blood tests revealed elevated levels of serum gastrin.Surgery was performed,and pathological analysis of the surgical specimens revealed a parathyroid adenoma after parathyroidectomy and a neuroendocrine tumor after duodenal bulbectomy.The time from onset to the definitive diagnosis of MEN1 was only approximately 1 year.CONCLUSION For patients who present with gastrointestinal symptoms accompanied by hyper-calcemia and hypophosphatemia,clinicians need to be alert to the possibility of MEN1.

C634Y mutation in RET-induced multiple endocrine neoplasia type 2A:A case report

BACKGROUND Multiple endocrine neoplasia type 2(MEN2)is a rare,autosomal dominant endocrine disease.Currently,the RET proto-oncogene is the only gene implicated in MEN2A pathogenesis.Once an RET carrier is detected,family members should be screened to enable early detection of medullary thyroid carcinoma,pheochromocytoma,and hyperparatitity.Among these,medullary thyroid carcinoma is the main factor responsible for patient mortality.Accordingly,delineating strategies to inform clinical follow-up and treatment plans based on genes is paramount for clinical practitioners.CASE SUMMARY Herein,we present RET proto-oncogene mutations,clinical characteristics,and treatment strategies in a family with MEN2A.A family study was conducted on patients diagnosed with MEN2A.DNA was extracted from the peripheral blood of family members,and first-generation exon sequencing of the RET protooncogene was conducted.The C634Y mutation was identified in three family members spanning three generations.Two patients were sequentially diagnosed with pheochromocytomas and bilateral medullary thyroid carcinomas.A 9-yearold child harboring the gene mutation was diagnosed with medullary thyroid carcinoma.Surgical resection of the tumors was performed.All family members were advised to undergo complete genetic testing related to the C634Y mutation,and the corresponding treatments administered based on test results and associated clinical guidelines.CONCLUSION Advancements in MEN2A research are important for familial management,assessment of medullary thyroid cancer invasive risk,and deciding surgical timing.

In situ formation of multiple catalysts for enhancing the hydrogen storage of MgH_(2) by adding porous Ni_(3)ZnC_(0.7)/Ni loaded carbon nanotubes microspheres

MgH_(2) is considered one of the most promising hydrogen storage materials because of its safety,high efficiency,high hydrogen storage quantity and low cost characteristics.But some shortcomings are still existed:high operating temperature and poor hydrogen absorption dynamics,which limit its application.Porous Ni_(3)ZnC_(0.7)/Ni loaded carbon nanotubes microspheres(NZC/Ni@CNT)is prepared by facile filtration and calcination method.Then the different amount of NZC/Ni@CNT(2.5,5.0 and 7.5 wt%)is added to the MgH_(2) by ball milling.Among the three samples with different amount of NZC/Ni@CNT(2.5,5.0 and 7.5 wt%),the MgH_(2)-5 wt%NZC/Ni@CNT composite exhibits the best hydrogen storage performances.After testing,the MgH_(2)-5 wt%NZC/Ni@CNT begins to release hydrogen at around 110℃ and hydrogen absorption capacity reaches 2.34 wt%H_(2) at 80℃ within 60 min.Moreover,the composite can release about 5.36 wt%H_(2) at 300℃.In addition,hydrogen absorption and desorption activation energies of the MgH_(2)-5 wt%NZC/Ni@CNT composite are reduced to 37.28 and 84.22 KJ/mol H_(2),respectively.The in situ generated Mg_(2)NiH_(4)/Mg_(2)Ni can serve as a"hydrogen pump"that plays the main role in providing more activation sites and hydrogen diffusion channels which promotes H_(2) dissociation during hydrogen absorption process.In addition,the evenly dispersed Zn and MgZn2 in Mg and MgH_(2) could provide sites for Mg/MgH_(2) nucleation and hydrogen diffusion channel.This attempt clearly proved that the bimetallic carbide Ni_(3)ZnC_(0.7) is a effective additive for the hydrogen storage performances modification of MgH_(2),and the facile synthesis of the Ni_(3)ZnC_(0.7)/Ni@CNT can provide directions of better designing high performance carbide catalysts for improving MgH_(2).