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Fabric quality and performance is assessed subjectively by the customer using an important and complex phenomenon of fabric hand. Objectively, it is evaluated with complicated and expensive instruments, such as Kawabata Evaluation System for Fabrics (KES-F) and Fabric Assurance with Simple Testing (FAST). The present research explores a non-touch objective approach, i.e., three-dimensional (3D) drape model to estimate fabric hand. Fabric hand prediction was testified on different commercial fabrics spanning a wide range of areal weight, thickness, yarn count, and fabric density. Fabric objective ranks based on drape indicators using principal component analysis (PCA) were compared with subjective ranks of fabric hand. Additionally, fabric drape is evaluated three dimensionally and a new drape indicator drape height (DH) is proposed. The cosine similarity results have proved fabric drape as an objective alternate to fabric hand.

In the apparel manufacturing, fabric utilization always remains the significant apprehensions in controlling the production expenditure. Alteration in pattern shapes and marker preparation leads to the enormous utilization of fabric. The purpose of this research is to study fabric efficiency in correspondence with four different human body shapes in both genders. Two clothing styles, fitted trousers and fitted shirts, were processed conventionally in the garment manufacturing company. The comparative study of auto-marker and manual-marker making through Garment Gerber Technology (GGT) software were also accomplished. The evaluation of fabric consumptions, marker efficiency, marker loss, fabric loss, and fabric cost relevant to four different body shapes was analyzed for both women and men. The investigation carried out in this article concludes that there are differences in fabric consumptions, efficiencies, and cost-effectiveness relative to body shapes. The result revealed that the manualmarker of trousers for triangular body shape in women’s wears has the least fabric consumption (most cost-effective), whereas the shirt’s auto-marker for an oval body shape in men’s wears has the most fabric utilization (least costeffective). The manual-virtual-marker making is efficient (significant p-value) than auto-generated-markers. Also, fabric utilization for women’s garments is cost-effective than that for men. Trousers are cost-effective compared to the shirts.

Cotton fibre maturity is the measure of cotton’s secondary cell wall thickness. Both immature and over-mature fibres are undesirable in textile industry due to the various problems caused during different manufacturing processes. The determination of cotton fibre maturity is of vital importance and various methods and techniques have been devised to measure or calculate it. Artificial neural networks have the power to model the complex relationships between the input and output variables. Therefore, a model was developed for the prediction of cotton fibre maturity using the fibre characteristics. The results of predictive modelling showed that mean absolute error of 0.0491 was observed between the actual and predicted values, which show a high degree of accuracy for neural network modelling. Moreover, the importance of input variables was also defined.

In this research work, thermal properties of plain woven fabrics generated from regenerated bamboo and cotton fiber blended yarns were investigated. Seven mixtures of fiber (100% bamboo, 100% cotton, 10:90 bamboo: cotton, 20:80 bamboo: cotton, 30:70 bamboo: cotton, 40:60 bamboo: cotton and 50:50 bamboo: cotton) were developed to create 60 Tex ring spun yarn. The warp yarns were used as 100% regenerated bamboo and the bamboo: cotton blends were used alternatively in weft to produce plain woven fabrics. The plain structured woven fabrics show eminent thermal comfort properties with the blending of regenerated bamboo fibers. The air permeability of 100% regenerated bamboo fiber was recorded higher than the compared blends; the increased key factor contents of bamboo changed the air properties of the fabric. Furthermore, plain woven fabric of bamboo/cotton (50/50) has shown greater thermal conductivity and heat retention properties. The work reported in this paper is ensuring highpoints of thermal comfort properties of regenerated bamboo (100%) and cotton (100%) with plain woven structured fabrics, and potentially, the fabrics can be used for winter suiting apparel products.

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Weed management has become a highly labor-intensive activity, which is the reason for decreased yields and high costs. Moreover, the lack of skilled labor and weed-resistant herbicides severely impact the agriculture sector and food production, hence increasing the need for automation in agriculture. The use of agricultural robots will help in the assurance of higher yields and proactive control of the crops. This study proposes a laser-based weeding vehicle with a unique mechanical body that is adjustable relative to the field structure, called the Robot Operating System (ROS) based robust control system, and is customizable, cost-effective and easily replicable. Hence, an autonomous-mobile-agricultural robot with a 20 watt laser has been developed for the precise removal of weed plants. The assembled robot's testing was conducted in the agro living lab. The field trials have demonstrated that the robot takes approximately 23.7 h at the linear velocity of 0.07 m/s for the weeding of one acre plot. It includes 5 s of laser to kill one weed plant. Comparatively, the primitive weeding technique is highly labor intensive and takes several days to complete an acre plot area. The data presented herein reflects that implementing this technology could become an excellent approach to removing unwanted plants from agricultural fields. This solution is relatively cost-efficient and provides an alternative to expensive human labor initiatives to deal with the increased labor wages. [ABSTRACT FROM AUTHOR]

Recently, some improvement has been made in the dominant notion of fuzzy set that is Yager investigated the generalized concept of fuzzy set, Intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS) and called it q-rung orthopair fuzzy (q-ROF) set (q-ROFS). The aim of this manuscript is to present the concept of q-ROF soft (q-ROFSt) set (q-ROFStS) based on the Dombi operations. Since Dombi operational parameter possess natural flexibility with the resilience of variability. Some new operational laws are defined based on hybrid study of soft sets and q-ROFS. The advantage of Dombi operational parameter is very important to express the experts' attitude in decision making. In this paper, we present q-ROFSt Dombi average (q-ROFSt DA) aggregation operators including q-ROFSt Dombi weighted average (q-ROFSt DWA), q-ROFSt Dombi ordered weighted average (q-ROFSt DOWA) and q-ROFSt Dombi hybrid average (q-ROFSt DHA) operators. Moreover, we investigate q-ROFSt Dombi geometric (q-ROFSt DG) aggregation operators including q-ROFSt Dombi weighted geometric (q-ROFSt DWG), q-ROFSt Dombi ordered weighted geometric (q-ROFSt DOWG), and q-ROFSt Dombi hybrid geometric (q-ROFSt DHG) operators. The basic properties of these operators are presented with detail such us Idempotency, Boundedness, Monotonicity, Shift invariance, and Homogeneity. Thus from the analysis and advantages of proposed model, it is clear that the investigated q-ROFSt DWA operator is the generalized form of IF St DWA, PFSt DWA and q-ROFDWA operators. Similarly, the investigated q-ROFSt DWG operator is the generalized form of IF St DWG, PFSt DWG and q-ROFDWG operators. By applying the develop approach, this manuscript contains the technique and algorithm for multicriteria decision making (MCDM). Further a numerical example is developed to illustrate the flexibility and applicability of the developed operators. [ABSTRACT FROM AUTHOR]

The management of the abundant amount of used plastic bottle waste is a major concern nowadays, because it is a major contributor to landfills and overburdens waste processing facilities. Once disposed of, plastic can take centuries to break down, hence, recycling not only manages the waste efficiently, but it reduces the environmental impact and creates economic opportunities, as well. An incentive-based Reverse Vending machine (RVM) is an effective way to involve the general public in the management of plastic waste. The existing solutions are either very expensive, from a computation and cost perspective, or they lack the robustness and durability necessary for deployment. In this research, we have developed an incentive-based low-cost RVM for the collection, identification, classification, and sorting of used plastic bottles with the addition of a reward-based user application. The developed RVM includes a low-cost computing device running a lightweight image processing algorithm, sensors, camera, and a self-designed mechanical arm. To support the low computing device in the RVM, a lightweight MobileNet model has been trained using transfer learning. A dataset of 10,983 pet bottle images was collected using a camera installed inside the machine for the classification model. The results of the study show that MobileNet achieved 99.2% testing accuracy, which is better than the existing bottle-classification approaches. Moreover, the weight of the developed model was only 12 Mb, which is fourteen and six times less than inceptionV3 and Res-Net (Residual Neural Networks), respectively. Furthermore, the developed RVM costs a fraction of the price, compared to the existing solutions. Two versions of the machine have been deployed at a University for more than 6 months, collecting over 650 kg of plastic waste. [ABSTRACT FROM AUTHOR]

In order to generate the three-dimensional (3D) mesh of draped fabric based on a two-dimensional (2D) fabric projection, the 3D point cloud of draped fabric was scanned via a self-built 3D scanning device followed by triangulation. The 3D boundary of fabric drape model and the two-dimensional contour of the projection of the fabric drape model were extracted respectively. Two neural networks were constructed to bridge the 2D fabric drape projection and the 3D boundary of draped fabric. With the trained neural networks, the 3D boundary of draped fabric could be inferred by merely referring a 2D projection of draped fabric. Six reference triangular meshes with different triangle density were generated. Driven by two mesh deformation methods, Laplacian deformation and Poisson deformation, the reference mesh was deformed into 3D mesh similar to scanned fabric drape models (meshes). The result shows that the generated models have a high agreement with the scanned meshes. In addition, the Laplacian deformation outperforms Poisson deformation in generating 3D fabric drape models. [ABSTRACT FROM AUTHOR]

Automatic 3D human body measurement is a crucial issue for tailoring and made-to-measure. This paper presents a novel framework for 3D human landmarks extraction and measurement. The proposed approach first segments the 3D human body into 13 parts by utilizing an improved Mean Curvature Skeleton (MCS) algorithm, in which we modify the Laplacian operator used in the original MCS with mesh saliency to enable the segmentation boundaries to be closer to the human joints. Based on the human segmentation, K-Nearest Neighbors, linear modeling, and geometric methods are employed to extract at least 21 landmarks. Many essential landmarks, such as acromion, elbow, crotch, etc., are extracted in new ways. To our best knowledge, this is the first paper to propose a generalized solution to approximate the elbow point for arbitrary arm poses in the automatic 3D human measurement systems. Subsequently, various anthropometric measurements can be calculated according to the landmarks extracted automatically. The proposed method is validated on the public datasets and our real scans, and the experimental results have verified that the proposed approach is efficient and effective in processing various 3D human bodies. [ABSTRACT FROM AUTHOR]

Modernization and the global fashion market demand continuous improvements in upland cotton cultivars (Gossypium hirustum L.) to meet these improved fiber characteristics (fiber length, fiber strength, micronaire) requirements. Researchers have centered their efforts on improved fiber quality; however, the efforts are not immediately supporting the textile sector. The daily mean and temperature amplitude fluctuation affect cotton yield and fiber characteristics. This study analyzed four newly developed cotton varieties in two cotton regions for fiber characteristics' variations. It was observed that cotton fiber quality characteristics (fiber length, uniformity, strength, and micronaire) are impacted in diverse ways. Fiber quality is mainly affected by the genotype and environmental conditions, e.g., weather conditions, irrigation management, fertilization, and cultural practices. The Khanewal region had shown better fiber characteristics than the Multan region, whereas cotton variety CIM-785 had better fiber characteristics in both regions. [ABSTRACT FROM AUTHOR]

Industrial control system (ICS) attacks are usually targeted attacks that use the ICS entry approach to get a foothold within a system and move laterally throughout the organization. In recent decades, powerful attacks such as Stuxnet, Duqu, Flame, and Havex have served as wake-up calls for industrial units. All organizations are faced with the rise of security challenges in technological innovations. This paper aims to develop aggregation operators that can be used to address the decision-making problems based on a spherical fuzzy rough environment. Meanwhile, some interesting properties of idempotence, boundedness, and monotonicity for the proposed operators are analyzed. Moreover, we use this newly constructed framework to select ICS security suppliers and validate its acceptability. Furthermore, a different test has been performed based on a new operator to strengthen the suggested approach. Additionally, comparative analysis based on the novel extended TOPSIS method is presented to demonstrate the superiority of the proposed technique. The results show that the conventional approach has a larger area for information representation, better adaptability to the evaluation environment, and higher reliability of the evaluation results. [ABSTRACT FROM AUTHOR]

The main purpose of this manuscript is to present a novel idea on the q-rung orthopair fuzzy rough set (q-ROFRS) by the hybridized notion of q-ROFRSs and rough sets (RSs) and discuss its basic operations. Furthermore, by utilizing the developed concept, a list of q-ROFR Einstein weighted averaging and geometric aggregation operators are presented which are based on algebraic and Einstein norms. Similarly, some interesting characteristics of these operators are initiated. Moreover, the concept of the entropy and distance measures is presented to utilize the decision makers' unknown weights as well as attributes' weight information. The EDAS (evaluation based on distance from average solution) methodology plays a crucial role in decision-making challenges, especially when the problems of multicriteria group decision-making (MCGDM) include more competing criteria. The core of this study is to develop a decision-making algorithm based on the entropy measure, aggregation information, and EDAS methodology to handle the uncertainty in real-word decision-making problems (DMPs) under q-rung orthopair fuzzy rough information. To show the superiority and applicability of the developed technique, a numerical case study of a real-life DMP in agriculture farming is considered. Findings indicate that the suggested decision-making model is much more efficient and reliable to tackle uncertain information based on q-ROFR information. [ABSTRACT FROM AUTHOR]

Recently, Yager presented the new concept of q-rung orthopair fuzzy (q-ROF) set (q-ROFS) which emerged as the most significant generalization of Pythagorean fuzzy set (PFS). From the analysis of q-ROFS, it is clear that the rung q is the most significant feature of this notion. When the rung q increases, the orthopair adjusts in the boundary range which is needed. Thus, the input range of q-ROFS is more flexible, resilient, and suitable than the intuitionistic fuzzy set (IFS) and PFS. The aim of this manuscript is to investigate the hybrid concept of soft set ( S t S) and rough set with the notion of q-ROFS to obtain the new notion of q-ROF soft rough (q-ROF S t R) set (q-ROF S t RS). In addition, some averaging aggregation operators such as q-ROF S t R weighted averaging (q-ROF S t RWA), q-ROF S t R ordered weighted averaging (q-ROF S t ROWA), and q-ROF S t R hybrid averaging (q-ROF S t RHA) operators are presented. Then, the basic desirable properties of these investigated averaging operators are discussed in detail. Moreover, we investigated the geometric aggregation operators, such as q-ROF S t R weighted geometric (q-ROF S t RWG), q-ROF S t R ordered weighted geometric (q-ROF S t ROWG), and q-ROF S t R hybrid geometric (q-ROF S t RHG) operators, and proposed the basic desirable characteristics of the investigated geometric operators. The technique for multicriteria decision-making (MCDM) and the stepwise algorithm for decision-making by utilizing the proposed approaches are demonstrated clearly. Finally, a numerical example for the developed approach is presented and a comparative study of the investigated models with some existing methods is brought to light in detail which shows that the initiated models are more effective and useful than the existing methodologies. [ABSTRACT FROM AUTHOR]

Molodtsov investigated the pioneer notion of soft set (SfS) which provides a general framework for mathematical problems by affix parameterization tools during the analysis as compared to fuzzy set and q‐rung orthopair fuzzy set (q‐ROFS). The aim of this manuscript is to investigate the notion of q‐rung orthopair fuzzy soft set (q‐ROFSfS), which provide a lay of foundation for those difficulties and complexities which the contemporary theories face during the study of uncertainty. Therefore, our main contribution in this manuscript is to investigate the q‐rung orthopair fuzzy soft weighted averaging, q‐rung orthopair fuzzy soft ordered weighted averaging and q‐rung orthopair fuzzy soft hybrid averaging operators in q‐ROF soft (q‐ROFSf) environment. Further, the fundamental properties of these aggregation operators are studied. On the base of developed approach an algorithm for multicriteria decision making method is being presented. An application of medical diagnosis problems is solved on the proposed algorithm under the q‐ROFSf environment. Finally, comparison between the developed operators with some existing operators are being presented showing the superiority and efficiency of the developed approach than the existing literature. [ABSTRACT FROM AUTHOR]

This paper aims to originate two new notions that are soft rough Pythagorean fuzzy set and Pythagorean fuzzy soft rough set, and investigate some important properties of soft rough Pythagorean fuzzy set and Pythagorean fuzzy soft rough set in detail. Furthermore, classical representations of Pythagorean fuzzy soft rough approximation operators are presented. Then the proposed operators are applied on decision-making problem in which the experts provide their preferences in Pythagorean fuzzy soft rough environment. Finally through an illustrative example, it is shown that how the proposed operators work in decision-making problems. [ABSTRACT FROM AUTHOR]

In this manuscript we develop a comprehensive model to tackle decision making problems where strong points of view are in the favor and against some projects, entities or plans. Therefore a new approach is adopted to hybrid q-rung orthopair fuzzy sets with notions of covering rough set and TOPSIS. This model has stronger capability than intuitionistic fuzzy set and Pythagorean fuzzy set to manage the uncertainty. Furthermore an example is given to demonstrate how the proposed method helps us in decision making problems. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In apparel manufacturing, more than 50% of the total cost is consumed by the fabric in comparison to the rest of the materials. The efficient use of fabric may result in the reduction of considerable expenditure and efforts. Therefore, the purpose of this study is to propose an image projected virtual marker (IPVM) onto the surface of fabric layers/plies to improve fabric utilization and visual quality control. 20 garment production orders are scheduled for experimental work to investigate the utilization of fabrics with imperfections. The statistical analysis indicates a 3.5%–4% improvement in the fabric utilization, a 22% improvement in throughput time of visual inspection, and a 25% reduction of labor intensity during visual inspection in the cutting room. The result implies that the proposed method is an efficient approach to improve fabric utilization and cost reduction. [ABSTRACT FROM AUTHOR]

Concept of generalized rough approximations for fuzzy filters in ordered semigroups is introduced. Then this idea is extended to rough approximations of fuzzy bi-filters and fuzzy quasi-filters in ordered semigroups. -fuzzy filters are a generalization of fuzzy filters and these can be further generalized by -fuzzy filters. Generalized roughness has been studied for both and -fuzzy filters of ordered semigroups. [ABSTRACT FROM AUTHOR]

In this article, we consider a portfolio optimization problem of the Merton’s type with complete memory over a finite time horizon. The problem is formulated as a stochastic control problem on a finite time horizon and the state evolves according to a process governed by a stochastic process with memory. The goal is to choose investment and consumption controls such that the total expected discounted utility is maximized. Under certain conditions, we derive the explicit solutions for the associated Hamilton–Jacobi–Bellman (HJB) equations in a finite-dimensional space for exponential, logarithmic, and power utility functions. For those utility functions, verification results are established to ensure that the solutions are equal to the value functions, and the optimal controls are also derived. [ABSTRACT FROM AUTHOR]

In this paper we consider a portfolio optimization problem of the Merton's type over an infinite time horizon. Unlike the classical Markov model, we consider a system with delays. The problem is formulated as a stochastic control problem on an infinite time horizon and the state evolves according to a process governed by a stochastic process with delay. The goal is to choose investment and consumption controls such that the total expected discounted utility is maximized. Under certain conditions, we derive the explicit solutions for the associated Hamilton-Jacobi-Bellman (HJB) equations in a finite dimensional space for logarithmic and power utility functions. For those utility functions, verification results are established to ensure that the solutions are equal to the value functions, and the optimal controls are derived, too. [ABSTRACT FROM AUTHOR]

Recently, nanosized cellulose materials preparation has been extensively increased from the sources of sustainable materials and utilization in various functional applications as nanofillers. Cellulose nanofibrils (CNF) extraction through green bio-based materials featured as promising interest in the field of science. In this research, cellulose nanofibrils were extracted from a cellulose rich biomass Ficus natalensis barkcloth. Furthermore, extracted cellulose nanofibrils and Zinc oxide nanoparticles (ZnONPs) were mixed and casted to posterior analysis of formed sodium carboxymethyl cellulose (CMC) film at various concentrations of CNF (1 wt%, 5 wt%, 8 wt%, and 12 wt%) and fixed amount of ZnONPs (0.5wt%) based on CMC weight. Results revealed that CNF was smoothly distributed in the polymer matrix to form even and flexible films indicating the cellulose nanofibrils and zinc oxide are highly compatible with the CMC. Similarly, the water solubility percentage (WVP) of CMC film was low at lower content of CNF, and increased with the increase of CNF percentage. Addition of CNF and ZnONPs in nanocomposite films improved the thermal stability values and antibacterial activities of CMC films. Thus on the basis of various tremendous performance, this study showed that F.natalensis barkcloth could be considered as an alternative source of cellulose nanofibrils. Similarly, the prepared nanocomposite films can have potential application in packaging films for the extension of shelf life of fresh and minimally processed fruits and vegetables. [ABSTRACT FROM AUTHOR]

We present Justice, a set of extensions to the Liberty simulation infrastructure that model chip area, wire length, and power consumption. Based on an architectural specification of a processor, Justice estimates the area and per-access power consumption of each module in the architecture. It then constructs a floorplan for the processor and computes the length and delay of critical communication paths. Finally, Justice modifies the architectural specification to account for wire delay and generates an executable simulator for the processor. To illustrate its capabilities, we simulate a number of very long instruction word (VLIW) architectures. Our results illustrate how Justice makes it possible for designers to compare the costs and benefits of different changes to an architecture and demonstrate the importance of considering wire delay early in the design process. [ABSTRACT FROM AUTHOR]

\nResearch highlightsThe study examines the impact of zinc ions on energy storage in solvothermal-synthesised graphene-zinc oxide nanocomposites. In recent years, there has been extensive research focus on graphene and metal oxides, particularly in heterostructures and composites. These materials have a broad range of applications, like energy storage. Faradaic processes were shown by the observation of redox peaks in the CV analysis of a three-electrode system. The estimated specific capacitances of graphene at scan rates of (1, 50, and 100) mVS−1 were (1250, 562.5, and 390.6) Fg−1. The G-ZnO (2 w%) and G-ZnO (3 w%) gave the specific capacitance of (1354, 750, and 520) Fg−1 and (1422, 818, and 568) Fg−1 at the same scan rates of 1, 50, and 100 mV/s. Applying a potential to the material reveals its pseudo-capacitive properties. The XRD results for G-ZnO (2 w%) and G-ZnO (3 w%) show diffraction peaks at 2θ = 20.56°, 32.95°, 40.69°, 47.41°, 59.02°, and 69.04°, which correspond to the diffraction planes 011, 100, 101, 102, 110, and 200, respectively. The study examines the impact of zinc ions on energy storage in solvothermal-synthesised graphene-zinc oxide nanocomposites.Faradaic processes were confirmed by the observation of redox peaks in the CV analysis of a three-electrode system.The estimation of specific capacitances of graphene was carried out at scan rates of (1, 50, and 100) mVS−1, and it yielded values of (1250, 562.5, and 390.6) Fg−1.The study examines the impact of zinc ions on energy storage in solvothermal-synthesised graphene-zinc oxide nanocomposites.Faradaic processes were confirmed by the observation of redox peaks in the CV analysis of a three-electrode system.The estimation of specific capacitances of graphene was carried out at scan rates of (1, 50, and 100) mVS−1, and it yielded values of (1250, 562.5, and 390.6) Fg−1. [ABSTRACT FROM AUTHOR]

Prolonged drying times of terry fabrics is a problem as they can not be re-used until completely dry. To resolve this issue, we have designed a sandwich polyester in the mid-layer with low moisture content that could reduce the drying time with excellent wicking properties. These fabrics are widely used as activewear and sportswear. The effect of different softeners on the moisture management properties of weft-knitted terry fabrics' for various applications has also been studied. Terry knitted fabrics were prepared using a circular knitting machine. Six different softeners were applied with three different concentrations, i.e., 10 g/L, 15 g/L, and 20 g/L, on the fabric using the pad-dry-cure method. Moisture management tests and rubbing fastness tests were performed to analyze the applied softener's effect on the fabric comfort and moisture management performance. Results revealed that softener type (i.e., cationic, anionic, and non-ionic) and concentration levels considerably affect the moisture management capability of terry knitted fabrics. [ABSTRACT FROM AUTHOR]

The objective of this paper is to present new interactive averaging aggregation operators by assigning associate probabilities for T-spherical fuzzy sets (T-SFSs). T-SFS is a generalization of several existing theories such as intuitionistic fuzzy sets and picture fuzzy sets to handle imprecise information. Under such an environment, we developed a series of averaging interactive aggregation operators under the features that each element is represented with T-spherical fuzzy numbers. Various properties of the proposed operators are also investigated. Further, to rank the different T-SFSs, we exhibit the new score functions and state their some properties. To demonstrate the presented algorithm, a decision-making process algorithm is presented with T-SFS features. To save non-renewable resources and to the protect environment, the use of renewable resources is important. Solar energy is one of the best renewable energy resources and is also environment-friendly and thus the selection of solar cells is typically a multi-attribute decision-making problem. Therefore, the applicability of the developed algorithm is demonstrated with a numerical example in the selection of the solar cells and comparison of their performance with the several existing approaches. [ABSTRACT FROM AUTHOR]

In real life, human opinion cannot be limited to yes or no situations as shown in an ordinary fuzzy sets and intuitionistic fuzzy sets but it may be yes, abstain, no, and refusal as treated in Picture fuzzy sets or in Spherical fuzzy (SF) sets. In this article, we developed a comprehensive model to tackle decision-making problems, where strong points of view are in the favour; neutral; and against some projects, entities, or plans. Therefore, a new approach of covering-based spherical fuzzy rough set (CSFRS) models by means of spherical fuzzy β -neighborhoods (SF β -neighborhoods) is adopted to hybrid spherical fuzzy sets with notions of covering the rough set. Then, by using the principle of TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) to present the spherical fuzzy, the TOPSIS approach is presented through CSFRS models by means of SF β -neighborhoods. Via the SF-TOPSIS methodology, a multi-attribute decision-making problem is developed in an SF environment. This model has stronger capabilities than intuitionistic fuzzy sets and picture fuzzy sets to manage the vague and uncertainty. Finally, the proposed method is demonstrated through an example of how the proposed method helps us in decision-making problems. [ABSTRACT FROM AUTHOR]

Objective: To investigate the frequency and distribution of DRB1 and DQB1 alleles in Patients with rheumatoid arthritis (RA) and analyze the relationship between clinical response to methotrexate (MTX) and the HLA-DR and HLA-DQ genotypes in these patients., Methods: In this case-control study, the HLA-DRB1 and HLA-DQB1 polymorphism in 91 RA patients and 91 healthy controls was done using polymerase chain reaction and sequence specific primers., Results: There was no statistical difference in frequencies of HLA-DRB1*03, DRB1*04, DRB1*07, DRB1*10, DRB1*11, DRB1*12, DRB1*13, DRB1*14, DRB1*15 and DRB1*16 genotypes between patients and controls. However, DRB1*01 was found to be significantly more common (p=0.015) in RA patients compared to controls. HLA-DRB1*15 was more common in patients (43.5%) compared to controls (30.8%) but results were not significant. HLA-DRB1*08 and DRB1*09 were present in negligible number in patients as well as controls while HLA-DRB1*12 was conspicuously absent in controls. Similarly, DQB1*06 was also significantly more common (p = 0.01) among the patients compared to healthy control subjects, while there was no statistical difference in the frequencies of DQB1*02, DQB1*03, DQB1*04 and DQB1*05 among the cases and the controls. RA susceptibility in most patients appeared to be associated with the HLA-DRB1*01/DQB1 *06 genotype. Regarding association between HLA-DR or HLA-DQ genotype and clinical response to methotrexate (MTX), the data showed that with the exception of HLA-DRB1*03, there appears to be no association between the particular subtypes of HLA-DR and HLA-DQ. HLA-DRB1*03 was significantly-more common among non-responders to MTX alluding to the possibility that another genes responsible for MTX metabolism, might be in linkage disequilibrium with HLA-DRB1*03 in the Pakistani population, thereby making such individuals non-responsive to MTX-therapy., Conclusion: RA susceptibility in most Pakistani patients is associated with the HLA-DRB1*01/DQB1*06 genotype. HLA-DRB1*03 was found to be significantly more common among non-responders to MTX treatment suggesting that Pakistani patients with this genotype are less likely to benefit from MTX.