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The manufacture of polymer composites with a lower environmental footprint requires incorporation of sustainably sourced components. In addition, the incorporation of novel components should not compromise the material properties. The purpose of this paper is to demonstrate the use of a synthetic amine functional toluidine acetaldehyde condensate (AFTAC) as a modifier for fiber-reinforced epoxy composites. One of the fiber components was sourced from agricultural byproducts, and glass fiber was used as the fiber component for comparison.

The AFTAC condensate was synthesized via an acid-catalyzed reaction between o-toluidine and acetaldehyde. To demonstrate its efficacy as a toughening agent for diglycidyl ether bisphenol A resin composites and for the comparison of reinforcing materials of interest, composites were fabricated using a natural fiber (mat stick) and a synthetic glass fiber as the reinforcing material. A matched metal die technique was used to fabricate the composites. Composites were prepared and their mechanical and thermal properties were evaluated.

The inclusion of AFTAC led to an improvement in the mechanical strengths of these composites without any significant deterioration of the thermal stability. It was also observed that the fracture strengths for mat stick fiber-reinforced composites were lower than that of glass fiber-reinforced composites.

To the best of the authors’ knowledge, the use of the AFTAC modifier as well as incorporation of mat stick fibers in epoxy composites has not been demonstrated previously.

In the denim industry, enzyme washing and its combination with stone washing are generally used to get the desired worn-out look. However, these conventional methods include high water, energy and time consumption. Nowadays, laser fading, which is a computer-controlled, dry, ecological finishing method, is preferred in the denim fading process. The purpose of this study is to observe the effects of chemical pretreatment applications on laser-faded denim fabric in terms of color and mechanical properties. To eliminate the enzyme washing process in denim fading and to minimize the disadvantages of laser fading, such as decreased mechanical properties and increased fabric yellowness, various chemical pretreatment applications were applied to the denim fabric before laser fading, followed by simple rinsing instead of enzyme washing.

Two different indigo-dyed, organic cotton denim fabrics with different unit weights were exposed to pretreatment processes and then laser treatment, followed by simple rinsing. Polysilicic acid, boric acid, borax and bicarbonate were used for pretreatment processes, and laser treatment was carried out under optimized laser parameters (40 dpi resolution and 300 µs pixel time). Tensile strength was tested, and color values (CIE L*, a*, b*, ΔE*, C* and h), color yield (K/S), yellowness and whiteness indexes were measured to identify the color differences.

Before laser fading, 30 g/L and 40 g/L polysilicic acid pretreatments for sulfur-indigo-dyed fabric and a mixture of 10 g/L boric acid and 10 g/L borax pretreatments for the fabric only indigo-dyed were recommended for the laser fading with sufficient mechanical properties and good color values.

With the chemical pretreatments defined in this study, it was possible to reduce yellowness and maintain the mechanical properties after laser fading, thus minimizing the disadvantages of laser treatment and also eliminating enzyme washing.

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.

First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.

The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.

The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

This study aims to dye silk with natural pigments extract of Coreopsis tinctoria, by treating the fabrics with appropriate mordant under suitable dyeing conditions, to achieve good dyeing depth, fastness and ultraviolet (UV) protection.

Firstly, single factor experiments were used to determine the basic dyeing conditions of Coreopsis tinctoria. The optimal process conditions for direct dyeing were determined through orthogonal experiments. After that, the dyeing with mordant was used. Based on the previously determined optimal process conditions, silk fabrics were dyed with different mordanting methods, with different mordants and mordant dosages. The dyeing results were compared, in terms of the K/S values of the dyed fabrics, to determine the most appropriate dyeing conditions with mordant.

The extract of Coreopsis tinctoria can dye silk fabrics satisfactorily. Good dyeing depth and fastness can be obtained by using suitable dyeing methods and dyeing conditions, especially when using the natural mordant pomegranate rind and the rare earth mordant neodymium oxide. The silk fabrics dyed with Coreopsis tinctoria have good UV resistance, which allows a desirable finishing effect to be achieved while dyeing, using a safe and environmentally friendly method.

The composition of Coreopsis tinctoria is complex, and the specific composition of colouring the silk fibre has not been determined. There are many factors that affect the dyeing experiment, which have an impact on the experimental results.

The results of this study may help expand the application of Coreopsis tinctoria beyond medicine.

To the best of the authors’ knowledge, this paper is the first report on dyeing silk with the extract of Coreopsis tinctoria achieving good dyeing results. Its depth of staining and staining fastness were satisfactory. Optimum dyeing method and dyeing conditions have been identified. The fabric dyed with Coreopsis tinctoria has good UV protection effect, which is conducive to improving the application value of the dyeing fabric. The findings help offer a new direction for the application of medicinal plants in the eco-friendly dyeing of silk.

Today, the sustainability and outreach of microfinance institutions (MFIs) are crucial to the success of microfinance and the sector’s potential to make a lasting impact. The ability of MFIs to operate financially well without sacrificing their social goals has come under scrutiny. This study aims to identify the kind of relationships between the two objectives of MFIs in Ethiopia.

This study investigated the association between the outreach and financial sustainability of Ethiopian MFIs from the years 2012 to 2021 using a balanced set of panel data. The study used secondary data and employed a descriptive research design and a quantitative research approach. To this end, random and fixed effects estimation models, as well as three-stage least squares, with the model of seemingly unrelated regression (SUR) are used.

According to the study, outreach performance enables MFIs to achieve sustainability/financial performance. On the other side, MFI that are financially sound improve social performance. There was therefore no trade-off between the two objectives.

As Ethiopia’s microfinance sector shifts away from government and non-government backing and toward commercialization, such research is crucial. This aspect of the Ethiopian microfinance industry has gotten little consideration in research. The SUR model was used in the study together with random and fixed effect estimators, and the most reliable estimation result was chosen based on the necessary tests.

Peanut skins are an agro-waste product with no commercial value. The purpose of this paper is to evaluate peanut skin as a natural dyestuff and to determine if this natural dye could be used in the dyeing of some Egyptian cotton cultivars.

The methodology consists of several steps; dye extraction procedure from peanut skin through aqueous extraction, then dyeing optimized using simultaneous mordanting using alum. Finally, dyed cotton has been subjected to different textile laboratory tests, for example, color measurements and mechanical properties. Color-fastness was determined on Egyptian cotton fabric. The peanut skin as a source of natural dye and the dyed cotton sample were characterized by fourier transform infrared spectroscopy (FTIR) analysis.

It was found that the natural dye extracted from peanut skin has an affinity for cotton samples and showed high dyeability with a unique color shade, good color strength and very good fastness.

The novelty of this paper is the extraction of color from the peanut's outer skin which is discarded as waste such as agro-waste of the agricultural process which can be used as a natural dye in the textile industry and applied to dyeing some Egyptian cotton fibers from different genotypes.

Many healthcare institutions, such as hospitals, have recently implemented quality improvement initiatives such as Lean Six Sigma (LSS). However, only a few have sustained the initiatives and remained successful. One of the main reasons for the failure of LSS implementation is that managers tend to view LSS as individual projects. Managers lack a Change Management (CM) focus during the implementation. The primary purpose of this study is to document the implementation of LSS through a CM approach to improve sustainability.

Define-Measure-Analyse-Improve-Control (DMAIC) and the Awareness-Desire-Knowledge-Ability-Reinforcement (ADKAR), a popular CM approach, are combined to propose a new framework. The usefulness of the proposed framework is demonstrated using a case study in a multispeciality hospital located in southern India.

The study found that several factors are responsible for the high Length of Stay (LOS) for patients in the Emergency Department (ED). By implementing this proposed model to implement LSS and taking corrective actions, the average LOS was reduced from 267 to 158 min (a 40% reduction approximately).

The complete step-by-step approach is explained, and the LOS was considerably reduced during the pilot project. The findings will provide valuable insights for healthcare practitioners to understand the steps involved in the combined DMAIC-ADKAR model. The findings would also give healthcare practitioners the confidence to identify suitable tools and implement LSS in organisations where the practitioners work.

According to the authors' knowledge, this is the first study that synergises two models (DMAIC and ADKAR) into a single framework to implement in a hospital.

The purpose of this study was to review the information on the scientific efforts and achievements in sustainable industrial textile applications of natural colourants. Then the paper suggests the ways of improving the industrial textile applications of plant-based colourants.

The literature on the chemistry, sources and extraction of plant-based natural colourants was reviewed. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested. Lastly, the current situation of industrial application of natural dyes in textiles is presented.

Despite the scientific achievement to overcome the challenges of natural colourants for textiles, the global industrial application of natural colourants is still low. Inadequate knowledge of the dyers results into poor performance of the natural dyed textile. The natural dyed textiles are expensive due to the scarcity of raw materials for manufacturing of natural colourants. The selection of suitable extraction, application methods and type of substrate should consider the chemistry of the particular colourant. The society should be educated about the benefits of natural dyed textiles. Cultivation of colourant-bearing plants should be promoted to meet the industrial material demand.

The paper provides a synthesized collection of information about the source, chemistry, extraction, textile application and challenges of plant-based natural colourants. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

This study aims to determine the most similar set of recommendation books to the user selections in LibraryThing.

For this purpose, 30,000 tags related to History on the LibraryThing have been selected. Their tags and the tags of the related recommended books were extracted from three different recommendations sections on LibraryThing. Then, four similarity criteria of Jaccard coefficient, Cosine similarity, Dice coefficient and Pearson correlation coefficient were used to calculate the similarity between the tags. To determine the most similar recommended section, the best similarity criterion had to be determined first. So, a researcher-made questionnaire was provided to History experts.

The results showed that the Jaccard coefficient, with a frequency of 32.81, is the best similarity criterion from the point of view of History experts. Besides, the degree of similarity in LibraryThing recommendations section according to this criterion is equal to 0.256, in the section of books with similar library subjects and classifications is 0.163 and in the Member recommendations section is 0.152. Based on the findings of this study, the LibraryThing recommendations section has succeeded in introducing the most similar books to the selected book compared to the other two sections.

To the best of the authors’ knowledge, itis for the first time, three sections of LibraryThing recommendations are compared by four different similarity criteria to show which sections would be more beneficial for the user browsing. The results showed that machine recommendations work better than humans.