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The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.

The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.

The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.

The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.

The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.

The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.

The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.

This study aims to conduct the aircraft electrical wiring interconnection system (EWIS) safety risk assessment process abundantly and hierarchically and establish the assessment index system considering the weights and interrelationships of different levels of indices.

Due to the failure of EWIS being multifactorial, hidden and diverse, this paper divides the factors influencing the failure of EWIS into 3 primary indices, 13 secondary indices and 38 tertiary indices. Taking open circuit failure (OCF) and short circuit failure (SCF) as examples, calculate the weights of assessment indices based on the triangular fuzzy number analytic hierarchy process (TFNAHP) and triangular fuzzy number decision-making trial and evaluation laboratory (TFNDEMATEL). The cloud model (CM) divides the risk levels and obtains the safety risk assessment results. The comparative analyses of different weight calculation methods, different failure modes and different aircraft EWIS zones verify the effectiveness and practicability of the proposed method.

The results show that the proposed method aligns more with the actual situation than other methods. Also, the results identify key focus objects in EWIS safety risk assessment, such as the surrounding environmental factors among the primary indices having the most significant influence on OCF and SCF, the risk level of SCF being higher than that of OCF, etc.

This paper proposes a safety risk assessment index system for aircraft EWIS based on the cable parameters, surrounding environmental factors, installation and protection methods. The weight assignment is added to the assessment index system, and the safety risk assessment model is constructed by combining TFNAHP, TFNDEMATEL and CM.

By analyzing tourist choices in Side and Alanya, well-known destinations for tourists in Türkiye’s thriving urban tourism sector, this study aims to fill a crucial vacuum in the body of knowledge about urban tourism. The study examines the changing dynamics of consumer preferences for advertisements and closely examines the underlying factors that influence these preferences, both pre and post-influential COVID-19 period.

This study clarifies the complex interplay between tourism marketing and prospective tourists’ decision-making processes through a thorough examination. This research greatly improves our understanding of urban tourism marketing strategies by examining the varying effects of advertising channels and comparing the persuasive power of emotional versus numerical advertising messages.

This study’s findings significantly advance our understanding of urban tourism. Examining how visitors react to advertisements in the various urban environments of Side and Alanya offers insightful information on how marketing strategies and visitor preferences correlate. This research also reveals the subtleties of efficient communication techniques, providing a practical basis for improving urban tourism experiences.

Being the first study of its sort, to the best of the authors’ knowledge, this research’s originality is supported by its insights into how advertising, consumer preferences and the urban tourism environment interact. The significant contribution to knowledge highlights the implications for those involved in urban tourism and provides practical advice for improving advertising tactics in the post-COVID-19 age.

This study examines how carbon tools, including carbon accounting and management tools, can be created, used, modified and linked with other traditional management controls to materialise and effectuate organisations’ response strategies to multiple interacting logics in carbon management and the role of sustainability managers in these processes.

This study utilises the construct of accounting toolmaking, which refers to practices of adopting, adjusting and reconfiguring accounting tools to unfold how carbon tools are used as means to materialise responses to multiple interacting carbon management logics. It embraces a field study approach, whereby 38 sustainability managers and staff from 30 organisations in New Zealand were interviewed.

This study finds that carbon toolmaking is an important means to materialise and effectuate organisations’ response strategies to multiple interacting carbon management logics. Four response strategies are identified: separation, selective coupling, combination and hybridisation. Adopting activity involves considering the additionality, detailing, localising and cascading of carbon measures and targets and their linkage to the broader carbon management programme. In adjusting carbon tools, organisations adapt the frequency and orientation of carbon reporting, intensity of carbon monitoring and breadth of carbon information sharing. Through focusing on either procedural sequencing, assimilating, equating or integrating, toolmaking reconfigures the relationship between carbon tools and traditional management control systems. Together, these three toolmaking activities can be configured differently to construct carbon tools that are fit for purpose for each response strategy. These activities also enact certain roles on sustainability managers in the process of representing, communicating and/or transferring carbon information knowledge, which also facilitate different response strategies.

The study demonstrates the various carbon toolmaking practices that allow organisations to handle the multiple interacting logics in carbon management. The findings provide suggestions for organisations on how to adopt, adjust and reconfigure carbon tools to better embed the ecological logic in organisations’ strategies and operations.

The authors identify how carbon toolmaking materialises and effectuates organisations’ responses to multiple interacting logics in carbon management.

The purpose of this study was to investigate the impact of Corona virus disease on the perceived values of urban green landscapes in a developing country setting. To achieve this objective, the author investigated changes in the preferences for urban green space services among city residents who use nature areas for recreation.

This study applied the best–worst scaling technique to elicit changes in the preferences for ecosystem services from urban recreational sites in Malawi. The study also used a fractional logit model to examine factors that motivate visitors’ willingness to donate/contribute to improve the quality of nature’s recreational services.

This study finds that the COVID-19 pandemic changed visitors’ perceptions of urban woodlands, but leisure/recreation remained the most important service with or without the Corona virus outbreak. However, the perceived value of air pollution control and cultural/religious functions gained more prominence (+3%), whereas biodiversity conservation became less prominent (−2%) during the pandemic period. The mean willingness to pay (WTP) was estimated to be US$28.73, and WTP is positively influenced by education, income status and the user’s satisfaction with the recreation site.

The study substantiated the impact of Corona virus disease on the perceived values of urban green landscapes, using Malawi as a case study. This was demonstrated through the changes in preferences for urban green space services among city residents who use nature areas for recreation.

The authors examine whether or not applicants and recipients of federal disability insurance (DI) inflate their self-assessed health (SAH) problems relative to others. To do this, the authors employ a technique which uses anchoring vignettes. This approach allows them to examine how various cohorts of the population interpret survey questions associated with subjective self-assessments of health. The results of the analysis suggest that DI participants do inflate the severity of a given health problem, but by a small but significant degree. This tendency to exaggerate the severity of disability problems is much more apparent among those with more education (especially those with a college degree). In contrast, racial minorities tend to underestimate severity ratings for a given disability vignette when compared to their white peers.

The purpose of this study is to experimentally determine whether mechanical properties of concrete can be improved by using olive pomace aggregates (OPA) as a substitute for natural sand. Two types of OPA were tested by replacing an equivalent amount of natural sand. The first type was OPA mixed with olive mill wastewater (OMW), and the second type was OPA not mixed with OMW. For each type, two series of concrete were produced using OPA in both dry and saturated states. The percentage of partial substitution of natural sand by OPA varied from 0% to 15%.

The addition of OPA leads to a reduction in the dry density of hardened concrete, causing a 5.69% decrease in density when compared to the reference concrete. After 28 days, ultrasonic pulse velocity tests indicated that the resulting material is of good quality, with a velocity of 4.45 km/s. To understand the mechanism of resistance development, microstructural analysis was conducted to observe the arrangement of OPA and calcium silicate hydrates within the cementitious matrix. The analysis revealed that there is a low level of adhesion between the cement matrix and OPA at interfacial transition zone level, which was subsequently validated by further microstructural analysis.

The laboratory mechanical tests indicated that the OPCD_OPW (5) sample, containing 5% of OPA, in a dry state and mixed with OMW, demonstrated the best mechanical performance compared to the reference concrete. After 28 days of curing, this sample exhibited a compressive strength (R_c) of 25 MPa. Furthermore, it demonstrated a tensile strength of 4.61 MPa and a dynamic modulus of elasticity of 44.39 GPa, with rebound values of 27 MPa. The slump of the specimens ranged from 5 cm to 9 cm, falling within the acceptable range of consistency (Class S2). Based on these findings, the OPCD_OPW (5) formulation is considered optimal for use in concrete production.

This research paper provides a valuable contribution to the management of OPA and OMW (OPA_OMW) generated from the olive processing industry, which is known to have significant negative environmental impacts. The paper presents an intriguing approach to recycling these materials for use in civil engineering applications.

Because container terminals (CTs) are broker organizations, their interest has complex, various internal and external factors, the purpose of this study is to scrutiny and structure the factors affecting the interests of the CT.

In terms of purpose, this study is a developmental study that, are identified the factors related to the interests of the CT through studying the library and interviewing experts and then the degree of influence of each factor on each other by using the interview with experts of CT in Bushehr province are determined. Then, the fuzzy DEMATEL method is used to calculate the feedback loop of the indicators, and then the matrix obtained Fcmapper software and the fuzzy cognitive map (FCM) is drawn.

According to the FCM analysis, three important factors are centrality identified in terms of attracting capital, quality of service and efficiency. In addition, there are three factors, attracting capital, operator performance and law have high outdegree.

This research has identified 34 effective indicators of CT interests and evaluated their relationship with FCM. In the available researches, all these indicators measurement has not been evaluated together. Furthermore, fuzzy DEMATEL has been used to evaluate self-loops. Another contribution of this research is the introduction of a strategic route as a roadmap for CT managers in Bushehr province to decide on the interests of a CT.

This study assesses the probability of an OECD member country exhibiting high persistence in unemployment duration, considering income inequality, productivity, accumulation of human capital and labor income share in Gross Domestic Product (GDP) between the years 2013–2019.

To achieve the purpose of the study, a probabilistic analysis with panel data is employed, focusing on 20 OECD countries segmented into two groups: those with high persistence and low persistence in unemployment duration. Probit and Logit models are estimated, marginal changes are analyzed and the models are evaluated in terms of their classification accuracy. Finally, trends in probabilities over time are examined.

This paper exhibits that countries with higher human capital index, greater labor income share in GDP, and more relevant productivity for well-being reduce their probabilities of experiencing high persistence in unemployment duration. It is observed that Mexico (MEX), Greece (GRC), Italy (ITA), and Turkey (TUR) have elevated probabilities of experiencing high persistence in unemployment duration in the future, while Costa Rica (CRI), Estonia (EST), Slovakia (SVK), Czech Republic (CZE), Lithuania (LTU), Poland (POL), and Israel (ISR) show a marked downward trend in these probabilities. Lastly, countries like the United Kingdom (GBR), Denmark (DNK), Sweden (SWE), Norway (NOR), Netherlands (NLD), Germany (DEU), United States (USA), and Canada (CAN) present minimal risk of experiencing high persistence in unemployment duration in the future.

The measurement of the relationship between development outcomes and persistence in unemployment duration has been scarce. Generally, the literature has focused on the analysis of development and unemployment without delving into the duration of unemployment, let alone persistence in duration.

This paper provides a solid foundation for the formulation of policies aimed at promoting sustainable employment and inclusive economic growth.

Based on the findings of the study, two key development policies are proposed. Firstly, the implementation of investment programs in Human Capital to increase productivity is recommended. Resources should be directed towards initiatives that improve the necessary skills and competencies in the labor markets of OECD countries, especially in strategic economic sectors with higher production linkages. Additionally, incentivizing the application of active labor policies is proposed. This entails prioritizing policies aimed at increasing the labor income share in GDP through progressive fiscal reforms that strengthen social safety nets and ensure fair labor standards. Implementing employment programs targeted at vulnerable groups, such as long-term unemployed individuals, youth, female heads of households and marginalized communities, is also recommended to eliminate structural barriers to labor market participation and reduce disparities in unemployment persistence. Adopting these policies can help mitigate the risk of high unemployment duration persistence and foster sustainable and inclusive long-term economic growth.

This is the first study to analyze the probabilities of both developing and developed countries experiencing high persistence in unemployment duration. It specifically evaluates these probabilities over a period of time and also estimates potential outcomes if real investments were made to enhance their human capital, productivity and employability.

The conflict in Russian Ukraine is a problem for the world economy because it hinders growth and drives up inflation when it is already high. The trade route between India and Russia is also impacted by the Russia-Ukraine crisis. This study aims to compile the most recent data on how the present global economic crisis is affecting it, with particular emphasis on the Indian economy.

This research develops a mathematical forecasting model to evaluate how the Russia-Ukraine crisis would affect the Indian economy when perturbations are applied to the major transport sectors. Input-output modeling (I-O model) and interval programing (IP) are the two precise methods used in the model. The inoperability I-O model developed by Wassily Leontief examines how disruption in one sector of the economy spreads to the other. To capture data uncertainties, IP has been added to IIM.

This study uses the forecasted inoperability value to analyze how the sectors are interconnected. Economic loss is used to determine the lowest and highest priority sectors due to the Russia-Ukraine crisis on the Indian economy. Furthermore, this study provides a decision-support conclusion for studying the sectors under various scenarios.

In future studies, other sectors could be added to study the Russian-Ukrainian crises’ effects on the Indian economy. Perturbation is only applied to transport sectors and could be applied to other sectors for studying the effects of the crisis. The availability of incomplete data is a significant concern in this study.

Russia-Ukraine conflict is a significant blow to the global economy and affects the global transportation network. This study discusses the application of the IIM-IP model to the Russia-Ukraine conflict. It also forecasts the values to examine how the crisis affected the Indian economy. This study uses a variety of scenarios to create a decision-support conclusion table that aids decision-makers in analyzing the Indian economy’s lowest and most affected sectors as a result of the crisis.