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Local rough sets are an efficient model to analyze large-scale datasets with finite labels because they are an essential development in classical rough sets. The objective of this paper, we put forth the idea of a local soft rough approximation measure (LSRAM), which preserves rough approximation measure associated characteristics from the context of traditional rough set theory. In order to account for the uncertainty brought on by the difference between the given lower and upper approximations based on soft equivalence relation, we propose the notion of local soft knowledge distance (LSKD). Moreover, some associated proposition's, theorems, corollaries, and a novel GM built on the LSKD model are given. Subsequently, LSRAM is combined with the suggested GM to create the enhanced LSRAM. This illustrates that the upgraded LSRAM maintains monotonicity with granularity subdivision. Further, to examine the conflict situation in the Middle East, we create a new conflict analysis model that is based on local soft rough sets in a framework of soft equivalence relations and soft indiscernible relations. Finally, we provided positive responses to a number of queries that different authors had raised. Our recently constructed model is much more effective than the existing strategies, according to an analysis of a general algorithm for conflict problems. [ABSTRACT FROM AUTHOR]

The core contribution of this study is to develop a novel generalized idea of q-rung orthopair probabilistic hesitant fuzzy rough set (q-ROPHFRS) which is hybrid structure of the q-rung orthopair fuzzy set, probabilistic hesitant fuzzy set, and rough set. The q-ROPHFRS covers the positive and negative membership grades in the form of probabilistic hesitant fuzzy rough information to address the uncertainties in real-world decision-making problems. This paper proposes a list of novel q-rung orthopair probabilistic hesitant fuzzy rough averaging/geometric aggregation operators to handle the uncertainty effectively and reliably to aggregate the uncertain information under q-ROPHFRSs. Several interesting elementary properties have been investigated. Furthermore, a novel multi-attribute decision-making approach based on the proposed aggregation information is presented. Finally, a numerical application regarding selecting a medical oxygen supplier to the hospital is presented to illustrate the consistency of the developed decision-making technique. The comparison of the proposed technique with q-rung orthopair probabilistic hesitant fuzzy rough TOPSIS shows that the proposed multi-criteria decision-making methodology is reliable and effective in addressing the uncertainty in real-world decision-making problems. [ABSTRACT FROM AUTHOR]

The precise selection of suppliers to fulfill production requirements is a fundamental component of all manufacturing and process industries. Due to the increasing consumption levels, green supplier selection (GSS) has been one of the most important issues for environmental preservation and sustainable growth. The present work aims to develop a technique based on Fermatean hesitant fuzzy rough set (FHFRS), a robust fusion of Fermatean fuzzy set, hesitant fuzzy set, and rough set for GSS in the process industry. On the basis of the operational rules of FHFRS, a list of innovative Fermatean hesitant fuzzy rough weighted averaging operators has been established. Further, several intriguing features of the proposed operators are highlighted. To cope with the ambiguity and incompleteness of real-world decision-making (DM) challenges, a DM algorithm has been developed. To illustrate the applicability of the methodology, a numerical example for the chemical processing industry is presented to determine the optimum supplier. The empirical findings suggest that the model has a significant application of scalability for GSS in the process industry. Finally, the improved FHFR-VIKOR and TOPSIS approaches are employed to validate the proposed technique. The results demonstrate that the suggested DM approach is practicable, accessible, and beneficial for addressing uncertainty in DM problems. [ABSTRACT FROM AUTHOR]

In literature the researchers employ the idea of fuzzy similarity relation to find the fuzzy rough approximations. To our knowledge, nowadays, there does not exist any research methodology for fuzzy rough set model based on β , δ -fuzzy similarity relations where β ∈ 0 , 0.5 , and δ ∈ 0.5 , 1. So, in order to accommodate this research space, this paper aims to extend the notion of Pawlak's rough sets to the so-called α -fuzzified rough sets based on β , δ -fuzzy similarity relations. Moreover, the approximation defined based on α -fuzzified rough sets using β , δ -fuzzy similarity relations play a key role between β , δ -fuzzy similarity relation and crisp set. Furthermore, the approximation defined based on α -similarity rough sets using β , δ -fuzzy similarity relations are useful in different uncertainties. Then we put forward the notion of generalized fuzzy rough set by the combination of fuzzy implication I and t-norm T called I , T -fuzzy rough sets based on β , δ -fuzzy similarity relation and investigate their various properties for the development of this study. Presently a characterization is available for R -implications obtained from left continuous quasi-overlap functions denoted by I O . We establish the I O , O -fuzzy rough set model obtained from quasi-overlap functions, especially for the connections between β , δ -fuzzy similarity relations and the new fuzzy rough approximation operators. We further described two algorithms to manipulate the unpredictability problems based on I O , O -fuzzy rough set using β , δ -fuzzy similarity relation. Finally, we discuss the applications of the proposed techniques for finding the most suitable conditional attribute for emergency plans among the given ones and present the comparison analysis of the proposed techniques with other existing models. [ABSTRACT FROM AUTHOR]

The classical theory of rough set was established by Pawlak, which mainly focusses on the approximation of sets characterized by a single equivalence relation over the universe. However, most of the current single granulation structure models cannot meet the user demand or the target of solving problems. Multigranulation rough sets approach can better deal with the problems, where data might be spread over various locations. In this article, we present the idea of soft preference and soft dominance relation for the development of soft dominance rough set in an incomplete information system. Subsequently, several important structural properties and results of the proposed model are carefully analyzed. After employing soft dominance based rough set approach to it for any times, we can only get six different sets at most in an incomplete information system. That is to say, every rough set in a universe can be approximated by only six sets, where the lower and upper approximations of each set in the six sets are still lying among these six sets. The relationships among these six sets are established. Based on soft dominance relation, we introduce logical disjunction/conjunction soft dominance optimistic/pessimistic multigranulation decision theoretic rough approximations in an incomplete information. Meanwhile, to measure the uncertainty of soft dominance optimistic/pessimistic multigranulation decision theoretic rough approximation and some of their interesting properties are examined. Thereafter, a novel multi attribute with multi decision making problem approach based on logical disjunction/conjunction soft dominance optimistic/pessimistic multigranulation decision theoretic rough sets approach are developed to solve the selection of medicine to treat the coronavirus disease (COVID-19). The basic principle and the detailed steps of the decision making model (algorithms) are presented in detail. To demonstrate the applicability and potentiality of the proposed model, we present a practical example of a medical diagnosis is given to validate the practicality of the technique. [ABSTRACT FROM AUTHOR]

Wind power is often recognized as one of the best clean energy solutions due to its widespread availability, low environmental impact, and great cost-effectiveness. The successful design of optimal wind power sites to create power is one of the most vital concerns in the exploitation of wind farms. Wind energy site selection is determined by the rules and standards of environmentally sustainable development, leading to a low, renewable energy source that is cost effective and contributes to global advancement. The major contribution of this research is a comprehensive analysis of information for the multi-attribute decision-making (MADM) approach and evaluation of ideal site selection for wind power plants employing q-rung orthopair hesitant fuzzy rough Einstein aggregation operators. A MADM technique is then developed using q-rung orthopair hesitant fuzzy rough aggregation operators. For further validation of the potential of the suggested method, a real case study on wind power plant site has been given. A comparison analysis based on the unique extended TOPSIS approach is presented to illustrate the offered method's capability. The results show that this method has a larger space for presenting information, is more flexible in its use, and produces more consistent evaluation results. This research is a comprehensive collection of information that should be considered when choosing the optimum site for wind projects. [ABSTRACT FROM AUTHOR]

In this paper, we point out that the transfer function for computing the fuzzy preference degree of Pan et al. (Fuzzy Sets Syst 312:87–108, 2017) for the construction of upward/downward fuzzy relations is not additive consistent. Appropriate counterexample is given. Further their modified versions are presented. Meanwhile, we construct upward consistency matrices of experts which satisfy the upward additive consistency and the upward order consistency simultaneously. After that, by introducing some new fuzzy upward β -coverings, fuzzy upward β -neighborhoods and fuzzy upward complement β -neighborhoods are proposed and related properties are studied. Furthermore, we propose multigranulation optimistic/pessimistic I , T -fuzzy upward rough set based on fuzzy upward β -covering and investigate some of their properties. Finally we construct a new approach to multiple attribute decision making problem based on multigranulation optimistic/pessimistic I , T -fuzzy upward rough set. The decision making procedure, methodology and the algorithm of the proposed technique are given. The detailed comparison of the present work with other methods to multiple attribute decision making problem illustrates the advantages of the this work and limitations of other studies. [ABSTRACT FROM AUTHOR]

The extension of rough set model is a crucial and vast research direction in rough set theory. Meanwhile decision making can be considered as a mental process in which human beings make a choice among several alternatives. However, with the increasing complexity of real decision making problems, the decision makers frequently face the challenge of characterizing their preferences in an uncertain context. In the present paper, we initiate a multi attribute group decision making problem in the presence of multi attribute and multi decision in decision making with preferences. We further present the concept of soft preference relation and soft dominance relation corresponding to decision attribute in the multi criteria and multi decision information system. Further we put forward the idea of two types of optimistic/pessimistic multigranulation (soft dominance based optimistic/pessimistic multigranulation decision theoretic) approximations and their applications in solving a multi agent conflict analysis decision problem. The proposed method addresses the limitations of the Pawlak model and Sun's conflict analysis model and thus improve these models. Finally, the results on labor management negotiation problems show that the proposed algorithms are more effective and efficient for feasible consensus strategy when compared with other techniques. [ABSTRACT FROM AUTHOR]

The current study describes the production of maize starch–fatty acid complexes through high speed homogenization, a novel field of research, without heat or any chemical treatment. The starch–fatty acid complexes were produced with three different fatty acids, i.e. stearic acid (T1), palmitic acid (T2) and lauric acid (T3). The complexes were analyzed through various techniques. The results reveal that the complexing index (CI), swelling power (SP) and solubility (S) for T1 were significantly higher compared to T2 and T3. In X-ray diffraction (XRD) studies, relatively lower crystalline (V-type pattern) structures were obtained for the samples T1–T3, where T2 showed the highest crystallinity amongst all. Fourier transformed infrared (FTIR) spectra showed characteristic bands i.e., OH, C=O, C–O and long-chain CH2 functionalities thus confirming the overall incorporation of acids into glycoside moieties. The Scanning electron microscopy (SEM) analysis showed sub-crystalline matrix structures with fewer or no spherulites indicating the overall incorporation of acids in starch. The samples showed relatively low thermal stability in the thermal gravimetric analysis (TGA) in the range of 180 to 280 °C. These results suggest that high speed homogenization had the potential for the development of green and biocompatible maize starch–fatty acid complexes. [ABSTRACT FROM AUTHOR]

Multi-attribute group decision making (MAGDM ) can be considered as the process of ranking alternatives or selecting an optimal alternative by many decision makers based on multiple criteria. By comparing any two alternatives pairwise, preference relations provide efficient ways to represent the preference degrees of decision makers. The aim of this paper is to introduce the notions of upward intuitionistic fuzzy preference relations from fuzzy information system and to study some properties of these relations. Further the series of upward intuitionistic fuzzy preference aggregation operators including the upward intuitionistic fuzzy preference weighted averaging UIFPWA operator, upward intuitionistic fuzzy preference ordered weighted averaging UIFPOWA operator and upward intuitionistic fuzzy preference hybrid averaging UIFPHA operator and their related results are also investigated. We developed a MAGDM method based on the proposed operators under the fuzzy environment and illustrated with a numerical example to study the applicability of the new approach on a candidate selection decision-making problem. [ABSTRACT FROM AUTHOR]

In this note, we point out that the transfer function for computing the fuzzy preference degree in Mandal and Ranadive (Soft Comput, 2018. https://doi.org/10.1007/s00500-018-3411-7) for the construction of upward/downward fuzzy relations is not additive consistent. Appropriate counterexample is given. Further, their modified versions are presented. [ABSTRACT FROM AUTHOR]

Multi-attribute group decision-making is the process of evaluating alternatives or choosing the best alternative based on a number of different factors. Preference relations offer effective techniques to depict the degree of preferences of decision-makers via a comparison of any two alternatives pairwise. By presenting the rough set based on the λ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\lambda $$\end{document}-dominance degree, this research presents a generic framework for the analysis of multi-attribute and multi-decision information systems. There are only a maximum of six sets that can be obtained after applying a rough set technique based on the λ\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\lambda $$\end{document}-dominance degree to it for any times. This means that only six sets can adequately approximate all of the universe’s rough sets, with the lower and upper approximations of each set still lying among these six sets. The present study also focuses on the development of the two kinds of approximate precision, rough degree, approximate quality, approximate accuracy, and the relationship between them. Finally, a comparison between our suggested algorithms and Sun’s method is conducted, and the results show that the developed algorithms outperform the other models. [ABSTRACT FROM AUTHOR]

In this study, the Maillard reaction (MR) of glucose was applied to improve the physicochemical and functional properties of walnut protein isolate (WNPI). The MR products (MRPs) were prepared with glucose at 0 h (MRP0), 1 h (MRP1), 2 h (MRP2) and 3 h (MRP3) heating at 95 °C. The Infra-Red spectrum showed reduction of amide and S–H functionalities in MRPs with complete intermixing of glucose in MRP3. Scanning electron microscopy indicated changes in the morphology of MRP3 which also exhibited promising antioxidant effect. Significant decrease (P < 0.05) in hydrophobicity values (Ho) and increase (P < 0.05) in emulsifying activity/emulsifying stability indexes values were observed for MRPs. Uniform droplet distribution was observed in microscopy of emulsions while an increase in the interfacial protein concentration (Г) was obtained for MRPs. These results suggest that MR is useful in improving the utilization of this protein in food product development. [ABSTRACT FROM AUTHOR]

Using more general form of quasi-coincident fuzzy points, the notion of (α~,β~)-fuzzy ternary subsemigroups is introduced. Several properties are discussed. Characterizations of (∈,∈∨q0δ)-fuzzy ternary subsemigroups are considered. Relations between(∈,∈)-fuzzy ternary subsemigroups and (∈,∈∨q0δ)-fuzzy ternary subsemigroups are provided. [ABSTRACT FROM AUTHOR]

A dynamic light scattering (DLS) study was performed to investigate the interactions of maize straw cellulose nanocrystals (CNC) with the cationic surfactant hexadecyltrimethylammonium bromide (CTAB). Phase analysis light scattering (which gives access to zeta potential ( ζ) and electrical conductance) technique was used with the aim to obtain additional information. Zeta potential behavior demonstrated the colloidal systems are stable. By electrical conductance data, it was verified that the process of formation of micelles is thermodynamically spontaneous. Dynamic light scattering was shown to be very useful to find the optimum hydrolysis time so as to obtain well dispersed and more isolated nanocrystals. In the presence of the cationic surfactant CTAB, the formation of micelles and aggregates CNC/CTAB were well identified by DLS showing that the dynamics of cellulose nanocrystals in aqueous suspensions is strongly affected by the surfactant. [ABSTRACT FROM AUTHOR]

Hydroxypropylcellulose (HPC) films were prepared by casting with cellulose nanocrystals in the presence of anionic surfactant sodium dodecylsulphate (SDS) and cationic surfactant hexadecyltrimethyl ammonium bromide (CTAB). The cellulose nanocrystals were isolated from maize straw, a biomass source produced in huge quantities as an agrowaste in Brazil. These bionanocomposite films had good transparency and their surface hydrophilic character was evidenced by static contact angle measurements. Thermogravimetry (TGA) measurement revealed that nanocrystals and surfactants changed the thermal stability of the HPC films. Dynamic mechanical analysis (DMA) showed that the tensile storage and loss moduli of the HPC films increased by increasing the contents of cellulose nanocrystals and surfactants, especially in the case of CTAB. This good reinforcing effect of HPC matrix can be explained as due to electrostatic attractive interactions brought about by the presence of CTAB and the nanocrystals. [ABSTRACT FROM AUTHOR]

In this work cellulose was extracted from corn/maize straw (Zea mays) by means of an environmental-friendly multistep procedure involving alkaline treatment and a totally chlorine-free bleaching. This multistep procedure efficiently removed lignin and hemicelluloses. The pulp resulting from each step was characterized by attenuated total reflectance fourier transform infrared spectroscopy (ATR-FTIR). The optimum pulping time (time of alkaline treatment) was determined by means of thermogravimetric analysis. The extracted cellulose is highly crystalline as verified by X-ray diffraction. The partial acid hydrolysis with sulfuric acid led to the isolation of cellulose whiskers in aqueous suspension as confirmed by light scattering and transmission electron microscopy. The depolarization ratio value of these nanocrystals is the same as that determined for cotton whiskers, showing that this ratio does not depend on the cellulose source. The maize whiskers are arranged laterally in bundles with average thickness around five times that of the crystallite. [ABSTRACT FROM AUTHOR]

Department of Mathematics, Khawaja Farid University of Engineering and Information Technology, Rahim Yar Khan, Pakistan In the Acknowledgements section, "Muhammad Naeem would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4310396DSR02)." now reads: "Muhammad Naeem would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4310396DSR06)." Shahzaib Ashraf was incorrectly affiliated with 'Department of Mathematics and Statistics, Bacha Khan University, Charsadda, KPK, Pakistan'. [Extracted from the article]

The interactions of non-ionic amphiphilic diblock copolymer poly(oxyethylene/oxybutylene) (EB) with anionic surfactant sodium dodecyl sulphate (SDS) and cationic surfactant hexadecyltrimethylammonium bromide (CTAB) were studied by using various techniques such as surface tension, conductivity, steady-state fluorescence and dynamic light scattering. Surface tension measurements were used to determine the critical micelle concentration (CMC) and thereby the free energy of micellization (Δ G), free energy of adsorption (Δ G), surface excess concentration ( Γ) and minimum area per molecule ( A). Conductivity measurements were used to determine the critical micelle concentration (CMC), critical aggregation concentration (CAC), polymer saturation point (PSP), degree of ionization ( α) and counter ion binding ( β). Dynamic light scattering experiments were performed to check the changes in physiochemical properties of the block copolymer micelles taken place due to the interactions of diblock copolymers with ionic surfactants. The ratio of the first and third vibronic peaks ( I/ I) indicated the polarity of the pyrene micro environment and was used for the detection of micelle as well as polymer-surfactant interactions. Aggregation number ( N), number of binding sites ( n) and free energy of binding (Δ G) for pure surfactants as well as for polymer-surfactant mixed micellar systems were determined by the fluorescence quenching method. [ABSTRACT FROM AUTHOR]